<div class="medium-feed-item"><a href="https://python.plainenglish.io/step-by-step-download-stock-data-market-for-free-in-2024-with-python-5acdabc5ccc1?source=rss----78073def27b8---4"><img src="https://cdn-images-1.medium.com/max/2600/1*KQ7Coa4O7AoOTfiRFducAA.jpeg" width="7831"></a>Let&#x2019;s learn step-by-step download the stock data market for free with Python in 2024 for your Portofolio<a href="https://python.plainenglish.io/step-by-step-download-stock-data-market-for-free-in-2024-with-python-5acdabc5ccc1?source=rss----78073def27b8---4">Continue reading on Python in Plain English »</a></div>

Let’s learn step-by-step download the stock data market for free with Python in 2024 for your Portofolio
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Step-by-Step Download Stock Data Market For Free in 2024 with Python

<div class="medium-feed-item"><a href="https://python.plainenglish.io/pythonic-way-to-merge-dictionaries-92ba86278543?source=rss----78073def27b8---4"><img src="https://cdn-images-1.medium.com/max/2600/0*X2BQ5BQmYG_DI7Vb" width="4160"></a>Merge Dictionaries Like a Pro with the Union Operator (|)<a href="https://python.plainenglish.io/pythonic-way-to-merge-dictionaries-92ba86278543?source=rss----78073def27b8---4">Continue reading on Python in Plain English »</a></div>

Merge Dictionaries Like a Pro with the Union Operator (|)
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Pythonic Way To Merge Dictionaries

<div class="medium-feed-item"><a href="https://python.plainenglish.io/key-python-libraries-for-automation-every-beginner-should-know-43cb850c0f1b?source=rss----78073def27b8---4"><img src="https://cdn-images-1.medium.com/max/2600/0*okMW-JSkgwR7shks" width="7680"></a>Simplify your tasks with these Python libraries that feel like magic<a href="https://python.plainenglish.io/key-python-libraries-for-automation-every-beginner-should-know-43cb850c0f1b?source=rss----78073def27b8---4">Continue reading on Python in Plain English »</a></div>

Simplify your tasks with these Python libraries that feel like magic
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Key Python Libraries for Automation Every Beginner Should Know

<figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*A9e_0wEvPoTVuzed-qPdDg.jpeg" /></figure>Python is easy to start with, but mastering its full potential is a different story. Even experienced developers sometimes overlook its many features and best practices. In this article, I’ll share 12 practical tips to help you write cleaner, more efficient, and more professional Python code.<h4>1. Use enumerate Instead of a Manual Counter</h4>When iterating through a list and needing an index, avoid manually maintaining a counter. Use enumerate for cleaner and more Pythonic code.Before:<pre>i = 0 for item in my_list: print(i, item) i += 1</pre>After:<pre>for i, item in enumerate(my_list): print(i, item)</pre><h4>2. Compare with None the Right Way</h4>When checking for None, always use is instead of ==. It’s more readable and follows PEP 8 recommendations.<pre>if value is None: print(&quot;Value is None&quot;)</pre><h4>3. Avoid Mutable Default Arguments</h4>Using mutable objects (like lists) as default arguments can lead to unexpected bugs.Problematic:<pre>def append_to_list(value, my_list=[]): my_list.append(value) return my_list</pre>Better:<pre>def append_to_list(value, my_list=None): if my_list is None: my_list = [] my_list.append(value) return my_list</pre><h4>4. Use f-strings for Formatting</h4>F-strings make your code more readable and concise compared to older string formatting methods.<pre>name = &quot;Alice&quot; print(f&quot;Hello, {name}!&quot;)</pre><h4>5. Explore the collections Library</h4>The collections module offers powerful alternatives for common tasks. For example, Counter makes counting elements in a list straightforward.<pre>from collections import Counter data = [&#39;apple&#39;, &#39;banana&#39;, &#39;apple&#39;] counter = Counter(data) print(counter) # Output: Counter({&#39;apple&#39;: 2, &#39;banana&#39;: 1})pyt</pre><h4>6. Favor Generators Over Lists</h4>If you don’t need to use all elements of a list at once, use generators to save memory.<pre>squared_numbers = (x**2 for x in range(10)) for num in squared_numbers: print(num)</pre><h4>7. Optimize Membership Checks</h4>For large datasets, checking membership in a list can be slow. Convert the list to a set for faster lookups.Inefficient:<pre>if value in my_list: # O(n) print(&quot;Found!&quot;)</pre>Efficient:<pre>my_set = set(my_list) if value in my_set: # O(1) print(&quot;Found!&quot;)</pre><h4>8. **Master *args and kwargs</h4>These features simplify handling dynamic numbers of arguments in functions.<pre>def print_all(*args, **kwargs): print(&quot;Positional:&quot;, args) print(&quot;Keyword:&quot;, kwargs) print_all(1, 2, 3, name=&quot;Alice&quot;, age=30)</pre><h4>9. Use Decorators for Repeated Logic</h4>If the same logic repeats across functions, decorators can help reduce redundancy.<pre>def log_execution(func): def wrapper(*args, **kwargs): print(f&quot;Executing {func.__name__}&quot;) return func(*args, **kwargs) return wrapper @log_execution def say_hello(): print(&quot;Hello!&quot;) say_hello()</pre><h4>10. Write Tests with pytest</h4>pytest makes testing your code simple and enjoyable. It’s a favorite among Python developers.Example:<pre>def add(a, b): return a + b def test_add(): assert add(2, 3) == 5</pre><h4>11. Leverage Context Managers</h4>The with statement isn’t just for files—it can manage other resources like database connections or threading locks.<pre>with open(&quot;file.txt&quot;, &quot;r&quot;) as file: content = file.read()</pre><h4>12. **Control Imports with **all</h4>If you’re creating a package, use __all__ to explicitly control what gets imported with from module import *.<pre>__all__ = [&#39;function1&#39;, &#39;ClassA&#39;]</pre><h3>Conclusion</h3>Python’s true power reveals itself when you use the language the right way. By following these tips, you can write code that’s cleaner, more efficient, and easier to maintain. Which of these tips are you already using, and which ones surprised you? Share your thoughts in the comments below!<h3>In Plain English 🚀</h3>Thank you for being a part of the <a href="https://plainenglish.io/">In Plain English</a> community! Before you go:<ul><li>Be sure to clap and follow the writer ️👏️️</li><li>Follow us: <a href="https://x.com/inPlainEngHQ">X</a> | <a href="https://www.linkedin.com/company/inplainenglish/">LinkedIn</a> | <a href="https://www.youtube.com/channel/UCtipWUghju290NWcn8jhyAw">YouTube</a> | <a href="https://discord.gg/in-plain-english-709094664682340443">Discord</a> | <a href="https://newsletter.plainenglish.io/">Newsletter</a> | <a href="https://open.spotify.com/show/7qxylRWKhvZwMz2WuEoua0">Podcast</a></li><li><a href="https://differ.blog/">Create a free AI-powered blog on Differ.</a></li><li>More content at <a href="https://plainenglish.io/">PlainEnglish.io</a></li></ul><img src="https://medium.com/_/stat?event=post.clientViewed&referrerSource=full_rss&postId=fe3214c22a14" width="1" height="1" alt=""><hr><a href="https://python.plainenglish.io/12-python-tips-every-developer-should-know-and-use-fe3214c22a14">12 Python Tips Every Developer Should Know and Use</a> was originally published in <a href="https://python.plainenglish.io">Python in Plain English</a> on Medium, where people are continuing the conversation by highlighting and responding to this story.

Python is easy to start with, but mastering its full potential is a different story. Even experienced developers sometimes overlook its many features and best practices. In this article, I’ll share 12 practical tips to help you write cleaner, more efficient, and more professional Python code.
1. Use enumerate Instead of a Manual Counter
When iterating through a list and needing an index, avoid manually maintaining a counter. Use enumerate for cleaner and more Pythonic code.
Before:
i = 0
for item in my_list:
    print(i, item)
    i += 1
After:
for i, item in enumerate(my_list):
    print(i, item)
2. Compare with None the Right Way
When checking for None, always use is instead of ==. It’s more readable and follows PEP 8 recommendations.
if value is None:
    print("Value is None")
3. Avoid Mutable Default Arguments
Using mutable objects (like lists) as default arguments can lead to unexpected bugs.
Problematic:
def append_to_list(value, my_list=[]):
    my_list.append(value)
    return my_list
Better:
def append_to_list(value, my_list=None):
    if my_list is None:
        my_list = []
    my_list.append(value)
    return my_list
4. Use f-strings for Formatting
F-strings make your code more readable and concise compared to older string formatting methods.
name = "Alice"
print(f"Hello, {name}!")
5. Explore the collections Library
The collections module offers powerful alternatives for common tasks. For example, Counter makes counting elements in a list straightforward.
from collections import Counter
data = ['apple', 'banana', 'apple']
counter = Counter(data)
print(counter)
# Output: Counter({'apple': 2, 'banana': 1})pyt
6. Favor Generators Over Lists
If you don’t need to use all elements of a list at once, use generators to save memory.
squared_numbers = (x**2 for x in range(10))
for num in squared_numbers:
    print(num)
7. Optimize Membership Checks
For large datasets, checking membership in a list can be slow. Convert the list to a set for faster lookups.
Inefficient:
if value in my_list:  # O(n)
    print("Found!")
Efficient:
my_set = set(my_list)
if value in my_set:  # O(1)
    print("Found!")
8. **Master *args and kwargs
These features simplify handling dynamic numbers of arguments in functions.
def print_all(*args, **kwargs):
    print("Positional:", args)
    print("Keyword:", kwargs)
print_all(1, 2, 3, name="Alice", age=30)
9. Use Decorators for Repeated Logic
If the same logic repeats across functions, decorators can help reduce redundancy.
def log_execution(func):
    def wrapper(*args, **kwargs):
        print(f"Executing {func.__name__}")
        return func(*args, **kwargs)
    return wrapper
@log_execution
def say_hello():
    print("Hello!")
say_hello()
10. Write Tests with pytest
pytest makes testing your code simple and enjoyable. It’s a favorite among Python developers.
Example:
def add(a, b):
    return a + b
def test_add():
    assert add(2, 3) == 5
11. Leverage Context Managers
The with statement isn’t just for files—it can manage other resources like database connections or threading locks.
with open("file.txt", "r") as file:
    content = file.read()
12. **Control Imports with **all
If you’re creating a package, use __all__ to explicitly control what gets imported with from module import *.
__all__ = ['function1', 'ClassA']
Conclusion
Python’s true power reveals itself when you use the language the right way. By following these tips, you can write code that’s cleaner, more efficient, and easier to maintain. Which of these tips are you already using, and which ones surprised you? Share your thoughts in the comments below!
In Plain English 🚀
Thank you for being a part of the In Plain English community! Before you go:

Be sure to clap and follow the writer ️👏️️
Follow us: X | LinkedIn | YouTube | Discord | Newsletter | Podcast
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12 Python Tips Every Developer Should Know and Use was originally published in Python in Plain English on Medium, where people are continuing the conversation by highlighting and responding to this story.

12 Python Tips Every Developer Should Know and Use

<div class="medium-feed-item"><a href="https://python.plainenglish.io/mastering-risk-and-reward-in-cryptocurrency-backtesting-a-complete-python-guide-with-real-world-efba5ccc08a0?source=rss----78073def27b8---4"><img src="https://cdn-images-1.medium.com/max/2600/1*VdDZTsQYUJpPpQScHwzVMQ.jpeg" width="5913"></a>Cryptocurrency trading has the potential to be very profitable, however, the risks are also very high.<a href="https://python.plainenglish.io/mastering-risk-and-reward-in-cryptocurrency-backtesting-a-complete-python-guide-with-real-world-efba5ccc08a0?source=rss----78073def27b8---4">Continue reading on Python in Plain English »</a></div>

Cryptocurrency trading has the potential to be very profitable, however, the risks are also very high.
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Mastering Risk and Reward in Cryptocurrency Backtesting: A Complete Python Guide with…

Essential tips for data analysts to improve Python skills, from effective learning methods to practical resources.<figure><img alt="" src="https://cdn-images-1.medium.com/max/750/1*IuXt34djeXpJMO2CQrdhag.jpeg" /></figure>Python has become the go-to programming language for data analysts due to its simplicity, versatility, and extensive libraries for data manipulation, visualization, and machine learning. But mastering Python requires more than just writing code — it’s about understanding how to leverage its powerful tools efficiently.If you’re a data analyst looking to upskill, here are 10 tips to help you master Python and elevate your data game.<h3>1. Start with the Basics of Python</h3>Before diving into advanced libraries like Pandas or NumPy, ensure you have a solid foundation in Python basics. Focus on understanding variables, data types, loops, functions, and file handling.<h3>What to Practice:</h3><ul><li>Writing and running Python scripts.</li><li>Using loops (for, while) to iterate over data.</li><li>Writing reusable functions using def.</li></ul><h3>Example: Basic Python Script</h3><pre># Calculate average sales sales = [1200, 900, 1500, 1100] average_sales = sum(sales) / len(sales) print(f&quot;Average Sales: {average_sales}&quot;)</pre><blockquote>Pro Tip: Use interactive platforms like <a href="https://jupyter.org/">Jupyter Notebook</a> to test and practice Python basics in an intuitive environment.</blockquote><h3>2. Get Comfortable with Pandas for Data Manipulation</h3>Pandas is the backbone of Python-based data analysis. It allows you to manipulate, clean, and organize data efficiently using DataFrames and Series.<h3>What to Focus On:</h3><ul><li>Reading and writing data from CSVs, Excel, or SQL databases.</li><li>Filtering, grouping, and sorting data in DataFrames.</li><li>Handling missing values and duplicates.</li></ul><h3>Example: Data Manipulation with Pandas</h3><pre>import pandas as pd # Load data df = pd.read_csv(&quot;sales_data.csv&quot;) # Filter rows where sales &gt; 1000 filtered_data = df[df[&#39;sales&#39;] &gt; 1000] # Group by region and calculate total sales grouped_data = df.groupby(&#39;region&#39;)[&#39;sales&#39;].sum() print(grouped_data)</pre><blockquote>Pro Tip: Explore Pandas’ built-in methods like df.describe() and df.info() to quickly understand your dataset.</blockquote><h3>3. Learn NumPy for Numerical Operations</h3>NumPy is essential for handling numerical data in Python. Its array-based operations are faster and more memory-efficient than Python lists.<h3>What to Practice:</h3><ul><li>Creating and manipulating NumPy arrays.</li><li>Performing mathematical operations on arrays.</li><li>Using NumPy for statistical calculations.</li></ul><h3>Example: NumPy Array Operations</h3><pre>import numpy as np # Create a NumPy array sales = np.array([1200, 900, 1500, 1100]) # Calculate total and average sales total_sales = np.sum(sales) average_sales = np.mean(sales) print(f&quot;Total: {total_sales}, Average: {average_sales}&quot;)</pre><blockquote>Pro Tip: Use NumPy’s random module to generate sample data for practice.</blockquote><h3>4. Master Data Visualization with Matplotlib and Seaborn</h3>Data visualization is crucial for communicating insights, and Python’s Matplotlib and Seaborn libraries offer powerful tools to create impactful charts and graphs.<h3>What to Focus On:</h3><ul><li>Creating line, bar, scatter, and pie charts with Matplotlib.</li><li>Customizing visualizations with titles, labels, and legends.</li><li>Using Seaborn for advanced visualizations like heatmaps and pair plots.</li></ul><h3>Example: Sales Visualization</h3><pre>import matplotlib.pyplot as plt import seaborn as sns # Plot sales trend plt.plot(df[&#39;month&#39;], df[&#39;sales&#39;], marker=&#39;o&#39;) plt.title(&quot;Monthly Sales Trend&quot;) plt.xlabel(&quot;Month&quot;) plt.ylabel(&quot;Sales&quot;) plt.show() # Create a heatmap for correlation sns.heatmap(df.corr(), annot=True) plt.show()</pre><blockquote>Pro Tip: Save your plots as images with plt.savefig() for use in reports or presentations.</blockquote><h3>5. Practice Data Cleaning Techniques</h3>Real-world data is messy, and cleaning it is a critical skill. Use Python to handle missing values, incorrect formats, duplicates, and outliers.<h3>Key Techniques:</h3><ul><li>Handling null values with fillna() or dropna().</li><li>Removing duplicates using drop_duplicates().</li><li>Standardizing data formats (e.g., converting strings to dates).</li></ul><h3>Example: Cleaning Data with Pandas</h3><pre># Fill missing values in sales with the median df[&#39;sales&#39;].fillna(df[&#39;sales&#39;].median(), inplace=True) # Drop duplicate rows df.drop_duplicates(inplace=True) # Convert date column to datetime df[&#39;date&#39;] = pd.to_datetime(df[&#39;date&#39;])</pre><blockquote>Pro Tip: Automate repetitive cleaning tasks by creating reusable cleaning functions.</blockquote><h3>6. Automate Repetitive Tasks</h3>Automation is one of Python’s greatest strengths. From data cleaning to generating reports, Python can save you hours by automating repetitive workflows.<h3>Example: Automating a Daily Sales Report</h3><pre># Generate a summary report def generate_report(data): total_sales = data[&#39;sales&#39;].sum() print(f&quot;Total Sales: {total_sales}&quot;) # Automate for new files for file in [&quot;sales_data_jan.csv&quot;, &quot;sales_data_feb.csv&quot;]: df = pd.read_csv(file) generate_report(df)</pre><blockquote>Pro Tip: Use Python scripts to schedule regular tasks with tools like cron jobs or Task Scheduler.</blockquote><h3>7. Use SQL with Python for Database Queries</h3>Combine Python with SQL for seamless interaction with relational databases. Libraries like <a href="https://www.youtube.com/watch?v=byHcYRpMgI4">SQLite3 </a>or <a href="https://www.youtube.com/watch?v=aAy-B6KPld8">SQLAlchemy</a> allow you to query, analyze, and manipulate data directly from a database.<h3>Example: Querying Data with SQL in Python</h3><pre>import sqlite3 # Connect to database conn = sqlite3.connect(&quot;sales.db&quot;) # Query data query = &quot;SELECT region, SUM(sales) FROM sales GROUP BY region;&quot; df = pd.read_sql_query(query, conn) print(df)</pre><blockquote>Pro Tip: Use Python to automate repetitive SQL queries and transform results into Pandas DataFrames for analysis.</blockquote><h3>8. Learn Python for Exploratory Data Analysis (EDA)</h3>Exploratory Data Analysis (EDA) is the process of summarizing and understanding data. Python makes EDA efficient with its ability to handle large datasets and produce quick insights.<h3>What to Practice:</h3><ul><li>Calculating summary statistics with Pandas (mean, median, std).</li><li>Identifying trends and outliers using visualization tools.</li><li>Using groupby to explore aggregated metrics.</li></ul><h3>Example: Quick EDA</h3><pre># Summarize data print(df.describe()) # Group data by region print(df.groupby(&#39;region&#39;)[&#39;sales&#39;].mean()) # Visualize outliers with boxplots sns.boxplot(x=&#39;region&#39;, y=&#39;sales&#39;, data=df) plt.show()</pre><blockquote>Pro Tip: Combine EDA techniques in a Jupyter Notebook to document your findings as you explore.</blockquote><h3>9. Explore Advanced Python Libraries</h3>Once you’re comfortable with the basics, dive into advanced Python libraries like Scikit-learn for machine learning, Statsmodels for statistical analysis, and Dash for interactive dashboards.<h3>Example: Predictive Analysis with Scikit-learn</h3><pre>from sklearn.linear_model import LinearRegression # Train a linear regression model X = df[[&#39;marketing_spend&#39;, &#39;sales_team_size&#39;]] y = df[&#39;sales&#39;] model = LinearRegression().fit(X, y) # Predict sales predictions = model.predict(X) print(predictions)</pre><blockquote>Pro Tip: Use these libraries to expand your skillset into predictive analytics and beyond.</blockquote><h3>10. Work on Real-World Projects</h3>The best way to master Python is by applying it to real-world problems. Practice with publicly available datasets from platforms like <a href="https://www.kaggle.com/">Kaggle</a> or <a href="https://datasetsearch.research.google.com/">Google Dataset Search</a>.<h3>Ideas for Practice Projects:</h3><ul><li>Build a sales dashboard showing monthly and regional performance.</li><li>Analyze customer behavior and churn using transactional data.</li><li>Create a forecasting model for revenue or demand.</li></ul><blockquote>Pro Tip: Document your projects in Jupyter Notebooks and include them in your portfolio to showcase your skills.</blockquote><h3>Conclusion</h3>Mastering Python as a data analyst is a journey, but with these tips, you can build a strong foundation and quickly scale your skills. Start with the basics, dive into essential libraries like Pandas and NumPy, and practice on real-world projects to gain confidence.Python isn’t just a tool — it’s the key to unlocking faster, more effective data analysis. Start applying these tips today, and you’ll soon see the difference in your workflows and insights.<h3>In Plain English 🚀</h3>Thank you for being a part of the <a href="https://plainenglish.io/">In Plain English</a> community! Before you go:<ul><li>Be sure to clap and follow the writer ️👏️️</li><li>Follow us: <a href="https://x.com/inPlainEngHQ">X</a> | <a href="https://www.linkedin.com/company/inplainenglish/">LinkedIn</a> | <a href="https://www.youtube.com/channel/UCtipWUghju290NWcn8jhyAw">YouTube</a> | <a href="https://discord.gg/in-plain-english-709094664682340443">Discord</a> | <a href="https://newsletter.plainenglish.io/">Newsletter</a> | <a href="https://open.spotify.com/show/7qxylRWKhvZwMz2WuEoua0">Podcast</a></li><li><a href="https://differ.blog/">Create a free AI-powered blog on Differ.</a></li><li>More content at <a href="https://plainenglish.io/">PlainEnglish.io</a></li></ul><img src="https://medium.com/_/stat?event=post.clientViewed&referrerSource=full_rss&postId=43a7b2de0c54" width="1" height="1" alt=""><hr><a href="https://python.plainenglish.io/top-10-tips-for-data-analysts-to-master-python-43a7b2de0c54">Top 10 Tips for Data Analysts to Master Python</a> was originally published in <a href="https://python.plainenglish.io">Python in Plain English</a> on Medium, where people are continuing the conversation by highlighting and responding to this story.

Essential tips for data analysts to improve Python skills, from effective learning methods to practical resources.

Python has become the go-to programming language for data analysts due to its simplicity, versatility, and extensive libraries for data manipulation, visualization, and machine learning. But mastering Python requires more than just writing code — it’s about understanding how to leverage its powerful tools efficiently.
If you’re a data analyst looking to upskill, here are 10 tips to help you master Python and elevate your data game.
1. Start with the Basics of Python
Before diving into advanced libraries like Pandas or NumPy, ensure you have a solid foundation in Python basics. Focus on understanding variables, data types, loops, functions, and file handling.
What to Practice:

Writing and running Python scripts.
Using loops (for, while) to iterate over data.
Writing reusable functions using def.

Example: Basic Python Script
# Calculate average sales
sales = [1200, 900, 1500, 1100]
average_sales = sum(sales) / len(sales)
print(f"Average Sales: {average_sales}")
Pro Tip: Use interactive platforms like Jupyter Notebook to test and practice Python basics in an intuitive environment.
2. Get Comfortable with Pandas for Data Manipulation
Pandas is the backbone of Python-based data analysis. It allows you to manipulate, clean, and organize data efficiently using DataFrames and Series.
What to Focus On:

Reading and writing data from CSVs, Excel, or SQL databases.
Filtering, grouping, and sorting data in DataFrames.
Handling missing values and duplicates.

Example: Data Manipulation with Pandas
import pandas as pd
# Load data
df = pd.read_csv("sales_data.csv")
# Filter rows where sales > 1000
filtered_data = df[df['sales'] > 1000]
# Group by region and calculate total sales
grouped_data = df.groupby('region')['sales'].sum()
print(grouped_data)
Pro Tip: Explore Pandas’ built-in methods like df.describe() and df.info() to quickly understand your dataset.
3. Learn NumPy for Numerical Operations
NumPy is essential for handling numerical data in Python. Its array-based operations are faster and more memory-efficient than Python lists.
What to Practice:

Creating and manipulating NumPy arrays.
Performing mathematical operations on arrays.
Using NumPy for statistical calculations.

Example: NumPy Array Operations
import numpy as np
# Create a NumPy array
sales = np.array([1200, 900, 1500, 1100])
# Calculate total and average sales
total_sales = np.sum(sales)
average_sales = np.mean(sales)
print(f"Total: {total_sales}, Average: {average_sales}")
Pro Tip: Use NumPy’s random module to generate sample data for practice.
4. Master Data Visualization with Matplotlib and Seaborn
Data visualization is crucial for communicating insights, and Python’s Matplotlib and Seaborn libraries offer powerful tools to create impactful charts and graphs.
What to Focus On:

Creating line, bar, scatter, and pie charts with Matplotlib.
Customizing visualizations with titles, labels, and legends.
Using Seaborn for advanced visualizations like heatmaps and pair plots.

Example: Sales Visualization
import matplotlib.pyplot as plt
import seaborn as sns
# Plot sales trend
plt.plot(df['month'], df['sales'], marker='o')
plt.title("Monthly Sales Trend")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.show()
# Create a heatmap for correlation
sns.heatmap(df.corr(), annot=True)
plt.show()
Pro Tip: Save your plots as images with plt.savefig() for use in reports or presentations.
5. Practice Data Cleaning Techniques
Real-world data is messy, and cleaning it is a critical skill. Use Python to handle missing values, incorrect formats, duplicates, and outliers.
Key Techniques:

Handling null values with fillna() or dropna().
Removing duplicates using drop_duplicates().
Standardizing data formats (e.g., converting strings to dates).

Example: Cleaning Data with Pandas
# Fill missing values in sales with the median
df['sales'].fillna(df['sales'].median(), inplace=True)
# Drop duplicate rows
df.drop_duplicates(inplace=True)
# Convert date column to datetime
df['date'] = pd.to_datetime(df['date'])
Pro Tip: Automate repetitive cleaning tasks by creating reusable cleaning functions.
6. Automate Repetitive Tasks
Automation is one of Python’s greatest strengths. From data cleaning to generating reports, Python can save you hours by automating repetitive workflows.
Example: Automating a Daily Sales Report
# Generate a summary report
def generate_report(data):
    total_sales = data['sales'].sum()
    print(f"Total Sales: {total_sales}")
# Automate for new files
for file in ["sales_data_jan.csv", "sales_data_feb.csv"]:
    df = pd.read_csv(file)
    generate_report(df)
Pro Tip: Use Python scripts to schedule regular tasks with tools like cron jobs or Task Scheduler.
7. Use SQL with Python for Database Queries
Combine Python with SQL for seamless interaction with relational databases. Libraries like SQLite3 or SQLAlchemy allow you to query, analyze, and manipulate data directly from a database.
Example: Querying Data with SQL in Python
import sqlite3
# Connect to database
conn = sqlite3.connect("sales.db")
# Query data
query = "SELECT region, SUM(sales) FROM sales GROUP BY region;"
df = pd.read_sql_query(query, conn)
print(df)
Pro Tip: Use Python to automate repetitive SQL queries and transform results into Pandas DataFrames for analysis.
8. Learn Python for Exploratory Data Analysis (EDA)
Exploratory Data Analysis (EDA) is the process of summarizing and understanding data. Python makes EDA efficient with its ability to handle large datasets and produce quick insights.
What to Practice:

Calculating summary statistics with Pandas (mean, median, std).
Identifying trends and outliers using visualization tools.
Using groupby to explore aggregated metrics.

Example: Quick EDA
# Summarize data
print(df.describe())
# Group data by region
print(df.groupby('region')['sales'].mean())
# Visualize outliers with boxplots
sns.boxplot(x='region', y='sales', data=df)
plt.show()
Pro Tip: Combine EDA techniques in a Jupyter Notebook to document your findings as you explore.
9. Explore Advanced Python Libraries
Once you’re comfortable with the basics, dive into advanced Python libraries like Scikit-learn for machine learning, Statsmodels for statistical analysis, and Dash for interactive dashboards.
Example: Predictive Analysis with Scikit-learn
from sklearn.linear_model import LinearRegression
# Train a linear regression model
X = df[['marketing_spend', 'sales_team_size']]
y = df['sales']
model = LinearRegression().fit(X, y)
# Predict sales
predictions = model.predict(X)
print(predictions)
Pro Tip: Use these libraries to expand your skillset into predictive analytics and beyond.
10. Work on Real-World Projects
The best way to master Python is by applying it to real-world problems. Practice with publicly available datasets from platforms like Kaggle or Google Dataset Search.
Ideas for Practice Projects:

Build a sales dashboard showing monthly and regional performance.
Analyze customer behavior and churn using transactional data.
Create a forecasting model for revenue or demand.

Pro Tip: Document your projects in Jupyter Notebooks and include them in your portfolio to showcase your skills.
Conclusion
Mastering Python as a data analyst is a journey, but with these tips, you can build a strong foundation and quickly scale your skills. Start with the basics, dive into essential libraries like Pandas and NumPy, and practice on real-world projects to gain confidence.
Python isn’t just a tool — it’s the key to unlocking faster, more effective data analysis. Start applying these tips today, and you’ll soon see the difference in your workflows and insights.
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Python Lists Cheat Sheet - Developer Resources

<![CDATA[Hey, there!This is Kenn, Your Daily Advocate from CodeWithKenn!Welcome to the Blog! Make yourself at home! In this article, we won't talk much. For a couple of days, I've been thinking about a way of making my content easier and shorter so that Developers won't have to spend so much time scrolling; I want this Blog a Place of Resources and Discovery, not a Boring Blog.<img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644857915236/HNJherNb5.jpeg" alt="save-your-time-2a7fb4.jpg" /><h1 id="heading-what-are-python-lists">What are Python Lists?</h1>Today, we're gonna get one of the first resources, Python Lists Easy Cheatsheet.Python Lists are used to store an ordered collection of items, which might be of different types but usually they aren't.<h1 id="heading-cheatsheet-content">Cheatsheet Content</h1><h2 id="heading-step-1">Step 1</h2><h3 id="heading-snippet-image">Snippet - Image</h3><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644858459662/CGjzyuSpc.png" alt="carbon (1).png" /><h3 id="heading-snippet-code">Snippet - Code</h3><pre><code># Create an empty list using square brackets.numbers = []print(numbers) # Output: []# Create an empty list using list().numbers = list()print(numbers) # Output: []# Create a list of numbers.numbers = [1, 2, 3]print(numbers) # Output: [1, 2, 3]# Create a list of numbers in a range.numbers = list(range(1, 4))print(numbers) # Output: [1, 2, 3]# Create a list of tuples.tuples_list = [(1, 2), (2, 4), (3, 6)]print(tuples_list) # Output: [(1, 2), (2, 4), (3, 6)]</code></pre><h2 id="heading-step-2">Step 2</h2><h3 id="heading-snippet-image">Snippet - Image</h3><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644858667007/4gPld_KaY.png" alt="carbon (2).png" /><h3 id="heading-snippet-code">Snippet - Code</h3><pre><code># Create a list of lists.list_of_lists = [[1, 2], [2, 4], [3, 6]]print(list_of_lists) # Output: [[1, 2], [2, 4], [3, 6]]# Create a list with items of different data types.random_list = [1, "hey", [1, 2]]print(random_list) # Output: [1, "hey", [1, 2]]# Get length of list by using len() method.numbers = [5, 8, 8]print(len(numbers)) # Output: 3# Access elements of a list by indexing.str_list = ["hey", "there!", "how", "are", "you?"]print(str_list[0]) # Output: "hey"print(str_list[len(str_list) - 1]) # Output: "you?"print(str_list[-1]) # Output: "you?"</code></pre><h2 id="heading-step-3">Step 3</h2><h3 id="heading-snippet-image">Snippet - Image</h3><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644858847484/c0ND1W-Sd.png" alt="carbon (3).png" /><h3 id="heading-snippet-code">Snippet - Code</h3><pre><code># Slicing a list.str_list = ["hey", "there!", "how", "are", "you?"]print(str_list[2:]) # Output: ["how", "are", "you?"]print(str_list[:2]) # Output: ["hey", "there!"]print(str_list[-3:]) # Output: ["how", "are", "you?"]print(str_list[:-3]) # Output: ["hey", "there!"]print(str_list[1:4]) # Output: ["there!", "how", "are"]# Get a copy of list by slicing.print(str_list[:]) # Output: ["hey", "there!", "how", "are", "you?"]</code></pre><h2 id="heading-step-4">Step 4</h2><h3 id="heading-snippet-image">Snippet - Image</h3><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644859067103/nPyMnPAEf.png" alt="carbon (4).png" /><h3 id="heading-snippet-code">Snippet - Code</h3><pre><code># Append to a list.numbers = [1, 2]print(numbers) # Output: [1, 2]numbers.append(3)print(numbers) # Output: [1, 2, 3]# Concatenate lists.numbers = [1, 2]strings = ["Hey", "there"]print(numbers + strings) # Output: [1, 2, "Hey", "there"]</code></pre><h2 id="heading-step-5">Step 5</h2><h3 id="heading-snippet-image">Snippet - Image</h3><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644859171328/c4_s-MMOg.png" alt="carbon (5).png" /><h3 id="heading-snippet-code">Snippet - Code</h3><pre><code># Mutate a list, that is, change its contents.numbers = [1, 2, 3]numbers[0] = 100print(numbers) # Output: [100, 2, 3]numbers[0:2] = [300, 400]print(numbers) # Output: [300, 400, 3]numbers[1:3] = []print(numbers) # Output: [300]numbers[:] = []print(numbers) # Output: []# Insert item to a list.greeting = ["how", "you?"]greeting.insert(1, "are")print(greeting) # Output: ["how", "are", "you?"]</code></pre><h2 id="heading-step-6">Step 6</h2><h3 id="heading-snippet-image">Snippet - Image</h3><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644859543800/asWaM8DPR.png" alt="carbon-lists-2.png" /><h3 id="heading-snippet-code">Snippet - Code</h3><pre><code># Our list of lists.matrix_1 = [[1,1,1], [2,2,2], [3,3,3]]matrix_2 = [[4,4,4], [5,5,5], [6,6,6]]# Matrix addition with for loop.# Assuming that the matrices are of the same dimensionsmatrix_sum = []for row in range(len(matrix_1)): matrix_sum.append([]) for column in range(len(matrix[0])): matrix_sum[row].append(matrix_1[row][column] + matrix_2[row][column])</code></pre><h2 id="heading-step-7">Step 7</h2><h3 id="heading-snippet-image">Snippet - Image</h3><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644859582127/JjYy8T4TYT.png" alt="carbon-lists-2-1.png" /><h3 id="heading-snippet-code">Snippet - Code</h3><pre><code># Our list of lists.matrix_1 = [[1,1,1], [2,2,2], [3,3,3]]matrix_2 = [[4,4,4], [5,5,5], [6,6,6]]# Rewrite using list comprehension only for inner lists.matrix_sum = []for row in range(len(matrix_1)): matrix_sum.append([matrix_1[row][column] + matrix_2[row][column] for column in range(len(matrix[0]))])# Rewrite using nested list comprehension.matrix_sum = [[matrix_1[row][column] + matrix_2[row][column] for column in range(len(matrix[0]))] for row in range(len(matrix_1))]print(matrix_sum) # Output: [[5, 5, 5], [7, 7, 7], [9, 9, 9]]</code></pre><h2 id="heading-credit-cheat-sheet">Credit - Cheat Sheet</h2><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1644859646012/41yYXVXuE.png" alt="carbon.png" /> All the Credit goes to <a target="_blank" href="https://gist.github.com/ShyamaSankar">@ShyamaSankar</a><h1 id="heading-before-leaving">🌎 Before Leaving</h1><ul><li> <a target="_blank" href="https://codewithkenn.hashnode.dev/discover-amazing-python-resources-for-free">Discover Amazing Python Resources FOR FREE!</a></li><li> <a target="_blank" href="https://codewithkenn.hashnode.dev/you-need-to-learn-python-in-2022-business-perspective">YOU NEED to Learn Python in 2022! (Business Perspective)</a></li></ul><ul><li><a target="_blank" href="https://twitter.com/CodeWithKenn">Twitter</a> </li><li><a target="_blank" href="https://github.com/KennStack01">Github</a> </li><li><a target="_blank" href="https://www.linkedin.com/in/kennkibadi/">LinkedIn</a> </li><li><a target="_blank" href="https://www.instagram.com/codewithkenn_/">Instagram</a> </li><li><a target="_blank" href="https://www.facebook.com/Code-With-Kenn-104376625415201">Facebook</a></li><li><a target="_blank" href="https://www.bio.link/IamKenn">See My Bio Link</a></li></ul>Want to start blogging? 🔥<a target="_blank" href="https://hashnode.com/@CodeWithKenn/joinme">Join NOW!</a> ]]>

This is Kenn, Your Daily Advocate from CodeWithKenn!Welcome to the Blog! Make yourself at home! 
In this article, we won't talk much. For a couple of days, I've been thinking about a way of making my content easier and shorter so that Developers won't have to spend so much time scrolling; I want this Blog a Place of Resources and Discovery, not a Boring Blog.

What are Python Lists?
Today, we're gonna get one of the first resources, Python Lists Easy Cheatsheet.
Python Lists are used to store an ordered collection of items, which might be of different types but usually they aren't.
Cheatsheet Content
Step 1
Snippet - Image

Snippet - Code
# Create an empty list using square brackets.numbers = []print(numbers) # Output: []# Create an empty list using list().numbers = list()print(numbers) # Output: []# Create a list of numbers.numbers = [1, 2, 3]print(numbers) # Output: [1, 2, 3]# Create a list of numbers in a range.numbers = list(range(1, 4))print(numbers) # Output: [1, 2, 3]# Create a list of tuples.tuples_list = [(1, 2), (2, 4), (3, 6)]print(tuples_list) # Output: [(1, 2), (2, 4), (3, 6)]
Step 2
Snippet - Image

Snippet - Code
# Create a list of lists.list_of_lists = [[1, 2], [2, 4], [3, 6]]print(list_of_lists) # Output: [[1, 2], [2, 4], [3, 6]]# Create a list with items of different data types.random_list = [1, "hey", [1, 2]]print(random_list) # Output: [1, "hey", [1, 2]]# Get length of list by using len() method.numbers = [5, 8, 8]print(len(numbers)) # Output: 3# Access elements of a list by indexing.str_list = ["hey", "there!", "how", "are", "you?"]print(str_list[0]) # Output: "hey"print(str_list[len(str_list) - 1]) # Output: "you?"print(str_list[-1]) # Output: "you?"
Step 3
Snippet - Image

Snippet - Code
# Slicing a list.str_list = ["hey", "there!", "how", "are", "you?"]print(str_list[2:]) # Output: ["how", "are", "you?"]print(str_list[:2]) # Output: ["hey", "there!"]print(str_list[-3:]) # Output: ["how", "are", "you?"]print(str_list[:-3]) # Output: ["hey", "there!"]print(str_list[1:4]) # Output: ["there!", "how", "are"]# Get a copy of list by slicing.print(str_list[:]) # Output: ["hey", "there!", "how", "are", "you?"]
Step 4
Snippet - Image

Snippet - Code
# Append to a list.numbers = [1, 2]print(numbers) # Output: [1, 2]numbers.append(3)print(numbers) # Output: [1, 2, 3]# Concatenate lists.numbers = [1, 2]strings = ["Hey", "there"]print(numbers + strings) # Output: [1, 2, "Hey", "there"]
Step 5
Snippet - Image

Snippet - Code
# Mutate a list, that is, change its contents.numbers = [1, 2, 3]numbers[0] = 100print(numbers) # Output: [100, 2, 3]numbers[0:2] = [300, 400]print(numbers) # Output: [300, 400, 3]numbers[1:3] = []print(numbers) # Output: [300]numbers[:] = []print(numbers) # Output: []# Insert item to a list.greeting = ["how", "you?"]greeting.insert(1, "are")print(greeting) # Output: ["how", "are", "you?"]
Step 6
Snippet - Image

Snippet - Code
# Our list of lists.matrix_1 = [[1,1,1], [2,2,2], [3,3,3]]matrix_2 = [[4,4,4], [5,5,5], [6,6,6]]# Matrix addition with for loop.# Assuming that the matrices are of the same dimensionsmatrix_sum = []for row in range(len(matrix_1)):  matrix_sum.append([])  for column in range(len(matrix[0])):      matrix_sum[row].append(matrix_1[row][column] + matrix_2[row][column])
Step 7
Snippet - Image

Snippet - Code
# Our list of lists.matrix_1 = [[1,1,1], [2,2,2], [3,3,3]]matrix_2 = [[4,4,4], [5,5,5], [6,6,6]]# Rewrite using list comprehension only for inner lists.matrix_sum = []for row in range(len(matrix_1)):  matrix_sum.append([matrix_1[row][column] + matrix_2[row][column] for column in range(len(matrix[0]))])# Rewrite using nested list comprehension.matrix_sum = [[matrix_1[row][column] + matrix_2[row][column] for column in range(len(matrix[0]))]              for row in range(len(matrix_1))]print(matrix_sum) # Output: [[5, 5, 5], [7, 7, 7], [9, 9, 9]]
Credit - Cheat Sheet

 All the Credit goes to @ShyamaSankar
🌎 Before Leaving

 Discover Amazing Python Resources FOR FREE!

 YOU NEED to Learn Python in 2022! (Business Perspective)


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]]>

Get Python Resources and Make your Learning Process easier!!!

<![CDATA[What if I told you You can learn Python in ONLY three weeks? <img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1642666266619/IWrUSxbAn.jpeg" alt="a4a7c2e1507c539f41229ca8200d3a44.jpg" />Will you trust me? haha 😅Hey, there! This is Kenn, Your Daily Advocate, and Friend from CodeWithKenn!In this Article, You gonna get one of the easiest Python Learning Roadmap and Resources for Free. Make sure to follow up for more articles coming. That's it! Let's get down to Business!Don't worry, You won't get bored with CodeWithKenn! Easy, Free, Short, but Use articles for Your Journey. Let's Gooooooo!<h1 id="heading-brief-description-of-python">Brief Description of Python</h1>If you just come from my article on <a target="_blank" href="https://codewithkenn.hashnode.dev/you-need-to-learn-python-in-2022-business-perspective">Learning Python in 2022! (Business Perspective)</a>, You've already known much on the subject.In a nutshell, Python is one of the easiest programming languages to get started with. For this reason, the community keeps growing every month, with a market value of over $10 Billion.So, why not get the Resources you really need for the Journey???<img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1642666622218/c1IFjXUpB.jpeg" alt="4752b206e5dc2c3713d57f536d527d06.jpg" /><h1 id="heading-get-what-you-really-need">Get what You really need</h1>As they are plenty of them, here are the two main resources you can use as references to go and check according to what you need:<h2 id="heading-refresh-the-memory-with-the-fundamentals">Refresh the memory with the Fundamentals</h2>Without the fundamentals, there is no way to bring innovation, meaning there is a necessity of getting a foundation. Here are the main resources:<h4 id="heading-videos-resources">Videos Resources</h4> <a target="_blank" href="https://www.youtube.com/watch?v=rfscVS0vtbw">FreeCodeCamp Beginners Course</a> <a target="_blank" href="https://www.youtube.com/playlist?list=PL-osiE80TeTskrapNbzXhwoFUiLCjGgY7">Corey Schafer Beginners Python Videos Series</a> <a target="_blank" href="https://www.youtube.com/watch?v=8ext9G7xspg">Start Building Projects</a> <h4 id="heading-community-resources">Community Resources</h4> <a target="_blank" href="https://forum.freecodecamp.org/c/python/424">FreeCodeCamp Python Community</a> <a target="_blank" href="https://www.reddit.com/r/Python/">Python Sub-reddit to ask for help</a> <h4 id="heading-docs-resources">Docs Resources</h4> <a target="_blank" href="https://docs.python.org/3/tutorial/index.html">Python Official Docs</a> <a target="_blank" href="https://devdocs.io/python~3.10-tutorial/">DevDocs Python</a> <h2 id="heading-python-for-web-development">Python for Web Development</h2>Here you have all You need for your Backend Journey. Don't overthink, use this and start building stuff:<h3 id="heading-interested-in-flask-app-development">Interested in Flask App Development?</h3><h4 id="heading-videos-resources">Videos Resources</h4> <a target="_blank" href="https://www.youtube.com/playlist?list=PL-osiE80TeTs4UjLw5MM6OjgkjFeUxCYH">Corey Schafer Beginners Flask Videos Series</a> <a target="_blank" href="https://www.youtube.com/watch?v=yKHJsLUENl0">Build a CRUD APP with Python Engineer</a> <h4 id="heading-community-resources">Community Resources</h4>Coding, but Stuck with some bugs? Here is the Solution, Go and ask the Community: <a target="_blank" href="https://www.reddit.com/r/flask/">Flask Subreddit Community</a> <a target="_blank" href="https://www.reddit.com/r/Python/">Python Subreddit Community</a><h4 id="heading-docs-resources">Docs Resources</h4> <a target="_blank" href="https://github.com/humiaozuzu/awesome-flask">Awesome Flask Links</a> <a target="_blank" href="https://github.com/realpython/discover-flask">Flask for your Project</a> <a target="_blank" href="https://flask.palletsprojects.com/en/latest/">Flask Latest Docs</a> <h3 id="heading-django-app-development">Django App Development</h3><h4 id="heading-videos-resources">Videos Resources</h4> <a target="_blank" href="https://www.youtube.com/playlist?list=PL-osiE80TeTtoQCKZ03TU5fNfx2UY6U4p">Corey Schafer Beginners Django Videos Series</a> <a target="_blank" href="https://www.youtube.com/watch?v=F5mRW0jo-U4&amp;t=64s">FreeCodeCamp Djajngo for Beginners</a> <h4 id="heading-community-resources">Community Resources</h4>Coding, but Stuck with some bugs? Here is the Solution, Go and ask the Community: <a target="_blank" href="https://www.reddit.com/r/django/">Django Subreddit Community</a> <a target="_blank" href="https://www.djangoproject.com/community/blogs/">Django Community</a><h4 id="heading-docs-resources">Docs Resources</h4> <a target="_blank" href="https://docs.djangoproject.com/en/4.0/intro/">Django Official Docs</a> <a target="_blank" href="https://django.readthedocs.io/en/stable/contents.html">Django ReadTheDocs.io</a> 🔥 This article is being updated, I'm adding Fast API Resources and AI/ML Resources on the Blog! Stay tuned! Stay tuned! More articles are coming out! Feel free to comment and share the articles to support me 🤙<h1 id="heading-lets-connect">🌎 Let's connect</h1><ul><li><a target="_blank" href="https://twitter.com/CodeWithKenn">Twitter</a> </li><li><a target="_blank" href="https://github.com/KennStack01">Github</a> </li><li><a target="_blank" href="https://www.linkedin.com/in/kennkibadi/">LinkedIn</a> </li><li><a target="_blank" href="https://www.instagram.com/codewithkenn_/">Instagram</a> </li><li><a target="_blank" href="https://www.facebook.com/Code-With-Kenn-104376625415201">Facebook</a></li></ul>Want to start blogging? 🔥<a target="_blank" href="https://hashnode.com/@CodeWithKenn/joinme">Join NOW!</a> ]]>

ONLY three weeks? 

Will you trust me? haha 😅
Hey, there! This is Kenn, Your Daily Advocate, and Friend from CodeWithKenn!
In this Article, You gonna get one of the easiest Python Learning Roadmap and Resources for Free. Make sure to follow up for more articles coming. That's it! Let's get down to Business!
Don't worry, You won't get bored with CodeWithKenn! Easy, Free, Short, but Use articles for Your Journey. Let's Gooooooo!
Brief Description of Python
If you just come from my article on Learning Python in 2022! (Business Perspective), You've already known much on the subject.
In a nutshell, Python is one of the easiest programming languages to get started with. For this reason, the community keeps growing every month, with a market value of over $10 Billion.
So, why not get the Resources you really need for the Journey???

Get what You really need
As they are plenty of them, here are the two main resources you can use as references to go and check according to what you need:
Refresh the memory with the Fundamentals
Without the fundamentals, there is no way to bring innovation, meaning there is a necessity of getting a foundation. Here are the main resources:
Videos Resources
 FreeCodeCamp Beginners Course 
 Corey Schafer Beginners Python Videos Series 
 Start Building Projects 
Community Resources
 FreeCodeCamp Python Community 
 Python Sub-reddit to ask for help 
Docs Resources
 Python Official Docs 
 DevDocs Python 
Python for Web Development
Here you have all You need for your Backend Journey. Don't overthink, use this and start building stuff:
Interested in Flask App Development?
Videos Resources
 Corey Schafer Beginners Flask Videos Series 
 Build a CRUD APP with Python Engineer 
Community Resources
Coding, but Stuck with some bugs? Here is the Solution, Go and ask the Community:
 Flask Subreddit Community
 Python Subreddit Community
Docs Resources
 Awesome Flask Links 
 Flask for your Project 
 Flask Latest Docs 
Django App Development
Videos Resources
 Corey Schafer Beginners Django Videos Series 
 FreeCodeCamp Djajngo for Beginners 
Community Resources
Coding, but Stuck with some bugs? Here is the Solution, Go and ask the Community:
 Django Subreddit Community
 Django Community
Docs Resources
 Django Official Docs 
 Django ReadTheDocs.io 
🔥 This article is being updated, I'm adding Fast API Resources and AI/ML Resources on the Blog! Stay tuned! 
Stay tuned! More articles are coming out! Feel free to comment and share the articles to support me 🤙
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Facebook

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]]>

Discover Amazing Python Resources FOR FREE!

Why You should start Learning Python Programming Right NOW!

<![CDATA[Python is one of the easiest programming languages to get started with. For this reason, the community keeps growing every month.Because of its simplicity (of the Syntax), Python has become the most popular language.Besides, Python helps Engineers build great products in many industries and professional domains.The Programmer's life gets easier when it comes to having a look at Python.<h1 id="heading-what-about-the-python-business-market-size">What about the Python Business Market size?</h1><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1642662070916/ha3UIJDHx.jpeg" alt="market-size-market-share.jpg" />Python is an open-source language, which means that anyone can use it. However, if you look to an industry such as data analytics, in which Python can be used, the market value is over $10 billion.Shared by <a target="_blank" href="https://www.futurelearn.com/info/insights/python-insights">futurelearn.com</a> <h1 id="heading-here-are-the-top-10-most-common-uses-of-python-by-industry">Here are the top 10 most common uses of Python by industry</h1><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1642662192938/xYTgi2Ycs.png" alt="pandemic-hero.png" /> Insurance: Creating business insights with machine learning. Retail Banking: Flexible data transformation and manipulation. Aerospace: Meeting software system deadlines. Finance: Data mining to identify cross-sell opportunities. Business Services: API access to financial information Hardware: Automating network administration Healthcare: Predicting disease prognosis Consulting Services: Bespoke web development InfoTech: IT modernization Software: Adding extensibility to legacy applicationsShared by <a target="_blank" href="https://appdevelopermagazine.com/ten-industries-using-python-programming/">appdevelopermagazine.com</a> <h1 id="heading-here-are-5-world-class-software-companies-that-use-python">Here are 5 World-Class Software Companies That Use Python</h1><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1642662333807/Y73E563_X.jpeg" alt="COTW-TechAcquisitions-Shareable-2.jpg" />(Photo by Visual Capitalist)Google, Meta (Facebook), Instagram, Netflix, Instagram.There are plenty of companies searching for Python Developers around the globe.<h1 id="heading-hence-i-created-this-blog-to-help-you-out">Hence, I created this Blog to help you out!</h1><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1642662424540/nnlZkUO_y.jpeg" alt="Design-Blog-Page-Python.jpg" />Hence, Learning Python helps you create Opportunities from jobs to Building Products people use.I just got into Full-stack development using Python Software Development, React + Python as Tech Stack.<h2 id="heading-make-sure-to-follow-codewithkenn-for-more-articles-about">Make sure to follow CodeWithKenn for more articles about:</h2> Learning Python in simple terms Building Side Projects and SaaS using React + Python Getting useful Resources and tips for your coding JourneyStay tuned! More articles are coming out! Feel free to comment and share the articles to support me 🤙<h1 id="heading-lets-connect">🌎 Let's connect</h1><ul><li><a target="_blank" href="https://twitter.com/CodeWithKenn">Twitter</a> </li><li><a target="_blank" href="https://github.com/KennStack01">Github</a> </li><li><a target="_blank" href="https://www.linkedin.com/in/kennkibadi/">LinkedIn</a> </li><li><a target="_blank" href="https://www.instagram.com/codewithkenn_/">Instagram</a> </li><li><a target="_blank" href="https://www.facebook.com/Code-With-Kenn-104376625415201">Facebook</a></li></ul>Want to start blogging? 🔥<a target="_blank" href="https://hashnode.com/@CodeWithKenn/joinme">Join NOW!</a> ]]>

Python is one of the easiest programming languages to get started with. For this reason, the community keeps growing every month.
Because of its simplicity (of the Syntax), Python has become the most popular language.
Besides, Python helps Engineers build great products in many industries and professional domains.The Programmer's life gets easier when it comes to having a look at Python.
What about the Python Business Market size?

Python is an open-source language, which means that anyone can use it. However, if you look to an industry such as data analytics, in which Python can be used, the market value is over $10 billion.
Shared by futurelearn.com 
Here are the top 10 most common uses of Python by industry

 Insurance: Creating business insights with machine learning.
 Retail Banking: Flexible data transformation and manipulation.
 Aerospace: Meeting software system deadlines.
 Finance: Data mining to identify cross-sell opportunities.
 Business Services: API access to financial information
 Hardware: Automating network administration
 Healthcare: Predicting disease prognosis
 Consulting Services: Bespoke web development
 InfoTech: IT modernization
 Software: Adding extensibility to legacy applications
Shared by appdevelopermagazine.com 
Here are 5 World-Class Software Companies That Use Python
(Photo by Visual Capitalist)
Google, Meta (Facebook), Instagram, Netflix, Instagram.There are plenty of companies searching for Python Developers around the globe.
Hence, I created this Blog to help you out!

Hence, Learning Python helps you create Opportunities from jobs to Building Products people use.I just got into Full-stack development using Python Software Development, React + Python as Tech Stack.
Make sure to follow CodeWithKenn for more articles about:
 Learning Python in simple terms
 Building Side Projects and SaaS using React + Python
 Getting useful Resources and tips for your coding Journey
Stay tuned! More articles are coming out! Feel free to comment and share the articles to support me 🤙
🌎 Let's connect

Twitter 
Github 
LinkedIn 
Instagram 
Facebook

Want to start blogging?  🔥Join NOW! 
]]>

YOU NEED to Learn Python in 2022! (Business Perspective)

<![CDATA[Python is one of the most popular coding languages available and is great as a starting point in your learning journey. It can be used for a range of things, such as web and internet development, software development application, network programming, and 3D graphics... (<a target="_blank" href="https://hethelinnovation.com/">hethelinnovation.com</a>)While learning, we end up getting stuck in small bugs that can take more time to solve, whereas we could have solved it quickly if we could only remember the basics. So, this is a series of Basics Python tips to remember whenever we work with numbers and strings. You can also use this article as a reference somehow while coding...Enjoy!<h1 id="heading-python-numbers">Python Numbers</h1>There are three numeric types we use in Python: <ul><li>int: or integer, is a whole number without decimals.</li></ul><pre><code>x = 1245y = -789print(type(x))print(type(y))</code></pre><ul><li>float: or Floating, a number with one or more decimals.</li></ul><pre><code>x = 12.45y = 42E5print(type(x))print(type(y))</code></pre><ul><li>complex: as studied in high school, is a number written with a "j" as the imaginary part.</li></ul><pre><code>x = 3 + 2jy = -15jprint(type(x))print(type(y))</code></pre><h2 id="heading-numbers-types-conversion">Numbers Types Conversion</h2>To convert numbers from one type (from the three) to another, we used methods.In Python, a method is a function that is available for a given object because of the object's type.So, You can convert from one type to another with the int(), float(), and complex() methods:<pre><code>x = 4 # int numbery = 0.8 # float numberz = 4j # complex number# from int to float:a = float(x)# from float to int:b = int(y)# from int to complex:c = complex(x)print(a)print(b)print(c)print(type(a))print(type(b))print(type(c))</code></pre><h2 id="heading-lets-build-a-simple-calculator">Let's Build a Simple Calculator</h2><pre><code># Python Simple calculator# Addition Functiondef add(x, y): return x + y# Substraction Functiondef subtract(x, y): return x - y# Multiplication Functiondef multiply(x, y): return x * y# Division Functiondef divide(x, y): return x / ydef calculate(first_number, second_number, operator): if operator == "+": answer = add(first_number, second_number) return answer elif operator == "-": answer = subtract(first_number, second_number) return answer elif operator == "/": answer = divide(first_number, second_number) return answer elif operator == "*" or operator == "x": answer = subtract(first_number, second_number) return answer else: return "Invalid"num1 = int(input("Enter the first number: "))num2 = int(input("Enter the second number: "))operator = input("Enter the Operator: ")print(f"{num1} {operator} {num2} = {calculate(num1, num2, operator)}")</code></pre><h1 id="heading-python-strings">Python Strings</h1>Strings in python are surrounded by: <ul><li>Single quotation marks <pre><code>'bonjour'</code></pre></li><li>Double quotation marks<pre><code>"bonjour"</code></pre></li></ul><h2 id="heading-use-a-variable-to-save-the-string">Use a Variable to save the String</h2>The assignment sign is made of = (equal sign).<pre><code>name = "Kennedy"role = "Software Engineer"print(name)print(role)</code></pre><h2 id="heading-we-can-also-use-multiline-strings">We can also use Multiline Strings</h2><pre><code>poem = """Your face is the grave of your noseyour face is the grave of your earsyour face is the grave of your faceonce again your face overflows uncontrollably."""print(poem)</code></pre><h2 id="heading-accessing-a-character-of-the-string">Accessing a Character of the String</h2>We can think of strings like an array made of characters. For example, the word "Elon Musk" is made of "E", "l", "o", "n", " ", "M", "u", "s" and "k" (Notice the space is also counted as a character).The first character is counted at index 0 (not 1). <pre><code>greeting = "Hello, World!"print(greeting[1]) #prints "e"</code></pre><h2 id="heading-working-with-strings">Working with Strings</h2><h3 id="heading-checking-the-string-length">Checking the String Length</h3>use the <code>len()</code> function<pre><code>name = "Kennedy"length_of_name = len(name)print(length_of_name)</code></pre><h3 id="heading-checking-an-existing-string-or-character-in-a-string">Checking an existing string or character in a string</h3>Use the <code>in</code> keyword.<pre><code>sentence = "Kennedy is a python programmer"if "python" in a sentence: print("Yes, 'python' is present.")</code></pre><h3 id="heading-most-common-string-methods">Most Common String Methods</h3><ul><li><code>capitalize()</code> method converts the first character of a string to an uppercase letter and lowercases all other characters.</li></ul><pre><code>name = "python"print(name.capitalize())</code></pre><ul><li><code>casefold()</code> method Converts string into lower case.</li></ul><pre><code>name = "PYTHON"print(name.casefold())</code></pre><ul><li><code>upper()</code> method converts all the characters into Uppercase.</li></ul><pre><code>name = "python"print(name.upper())</code></pre><ul><li><code>lower()</code> method converts all the characters into Lowercase.</li></ul><pre><code>name = "PYTHON"print(name.lower())</code></pre><ul><li><code>len()</code> method used to count the total number of characters in a string.</li></ul><pre><code>name = "python"print( len(name) )</code></pre><ul><li><code>find()</code> searches the string for a specified value and returns the position of where it was found.</li></ul><pre><code>sentence = "python is great"print( sentence.find('great') )</code></pre><ul><li><code>replace()</code> is used to replace a string with another.</li></ul><pre><code>sentence = "python is great"new_sentence = sentence.replace('great', 'awesome') print(new_sentence)</code></pre><ul><li><code>str()</code> is used for string conversion</li></ul><pre><code>ten = str(10)print(ten) #converts 10 to '10'</code></pre><ul><li>You can find more in the <a target="_blank" href="https://docs.python.org/2.5/lib/string-methods.html">Python.org Official Docs</a> </li></ul><h3 id="heading-lets-work-on-a-small-project">Let's work on a Small Project</h3><h4 id="heading-arrange-string-characters-such-that-lowercase-letters-should-come-first">- Arrange string characters such that lowercase letters should come first</h4>Initial Code<pre><code>noun = PrOgRamMinG# Expected Output : rgaminPORMG</code></pre>Solution<pre><code>noun = "PrOgRamMinG"# Let's create a Function to handle itdef arrange_string(my_string): print('Original String:', my_string) lower = [] upper = [] #Let's iterate and convert for char in my_string: if char.islower(): # add lowercase characters to lower list lower.append(char) else: # add uppercase characters to lower list upper.append(char) # Join both list sorted_str = ''.join(lower + upper) print('Result:', sorted_str)# Now, let's call execute the function we just created! arrange_string(noun)# Output: # Original String: PrOgRamMinG# Result: rgaminPORMG</code></pre>Resources for more Details:<ul><li><a target="_blank" href="https://www.w3schools.com/python/">www.w3schools.com</a> </li><li><a target="_blank" href="https://www.programiz.com/python-programming">www.programiz.com</a> </li><li><a target="_blank" href="https://pynative.com/python-string-exercise/#h-exercise-4-arrange-string-characters-such-that-lowercase-letters-should-come-first">www.pynative.com/</a> </li></ul>👉 <a target="_blank" href="https://codewithkenn.hashnode.dev/">DISCOVER MORE useful ARTICLES</a> Thanks for reading this article, many others are coming very soon, Feel free to subscribe 🤙.<h1 id="heading-lets-connect">🌎 Let's connect</h1><ul><li><a target="_blank" href="https://twitter.com/CodeWithKenn">Twitter</a> </li><li><a target="_blank" href="https://github.com/KennStack01">Github</a> </li><li><a target="_blank" href="https://www.linkedin.com/in/kennkibadi/">LinkedIn</a> </li><li><a target="_blank" href="https://www.instagram.com/codewithkenn_/">Instagram</a> </li></ul>Want to start blogging? 🔥<a target="_blank" href="https://hashnode.com/@CodeWithKenn/joinme">Join NOW!</a> ]]>

hethelinnovation.com)
While learning, we end up getting stuck in small bugs that can take more time to solve, whereas we could have solved it quickly if we could only remember the basics. 
So, this is a series of Basics Python tips to remember whenever we work with numbers and strings. You can also use this article as a reference somehow while coding...
Enjoy!
Python Numbers
There are three numeric types we use in Python: 

int: or integer, is a whole number without decimals.

x = 1245y = -789print(type(x))print(type(y))

float: or Floating, a number with one or more decimals.

x = 12.45y = 42E5print(type(x))print(type(y))

complex: as studied in high school, is a number written with a "j" as the imaginary part.

x = 3 + 2jy = -15jprint(type(x))print(type(y))
Numbers Types Conversion
To convert numbers from one type (from the three) to another, we used methods.
In Python, a method is a function that is available for a given object because of the object's type.So, You can convert from one type to another with the int(), float(), and complex() methods:
x = 4    # int numbery = 0.8  # float numberz = 4j   # complex number# from int to float:a = float(x)# from float to int:b = int(y)# from int to complex:c = complex(x)print(a)print(b)print(c)print(type(a))print(type(b))print(type(c))
Let's Build a Simple Calculator
# Python Simple calculator# Addition Functiondef add(x, y):    return x + y# Substraction Functiondef subtract(x, y):    return x - y# Multiplication Functiondef multiply(x, y):    return x * y# Division Functiondef divide(x, y):    return x / ydef calculate(first_number, second_number, operator):    if operator == "+":        answer = add(first_number, second_number)        return answer    elif operator == "-":        answer = subtract(first_number, second_number)        return answer    elif operator == "/":        answer = divide(first_number, second_number)        return answer    elif operator == "*" or operator == "x":        answer = subtract(first_number, second_number)        return answer    else:        return "Invalid"num1 = int(input("Enter the first number: "))num2 = int(input("Enter the second number: "))operator = input("Enter the Operator: ")print(f"{num1} {operator} {num2} = {calculate(num1, num2, operator)}")
Python Strings
Strings in python are surrounded by: 

Single quotation marks 
'bonjour'

Double quotation marks
"bonjour"

Use a Variable to save the String
The assignment sign is made of = (equal sign).
name = "Kennedy"role = "Software Engineer"print(name)print(role)
We can also use Multiline Strings
poem = """Your face is the grave of your noseyour face is the grave of your earsyour face is the grave of your faceonce again your face overflows uncontrollably."""print(poem)
Accessing a Character of the String
We can think of strings like an array made of characters. For example, the word "Elon Musk" is made of "E", "l", "o", "n", " ", "M", "u", "s" and "k" (Notice the space is also counted as a character).
The first character is counted at index 0 (not 1). 
greeting = "Hello, World!"print(greeting[1]) #prints "e"
Working with Strings
Checking the String Length
use the len() function
name = "Kennedy"length_of_name = len(name)print(length_of_name)
Checking an existing string or character in a string
Use the in keyword.
sentence = "Kennedy is a python programmer"if "python" in a sentence:  print("Yes, 'python' is present.")
Most Common String Methods

capitalize() method converts the first character of a string to an uppercase letter and lowercases all other characters.

name = "python"print(name.capitalize())

casefold() method Converts string into lower case.

name = "PYTHON"print(name.casefold())

upper() method converts all the characters into Uppercase.

name = "python"print(name.upper())

lower() method converts all the characters into Lowercase.

name = "PYTHON"print(name.lower())

len() method used to count the total number of characters in a string.

name = "python"print( len(name) )

find() searches the string for a specified value and returns the position of where it was found.

sentence = "python is great"print( sentence.find('great') )

replace() is used to replace a string with another.

sentence = "python is great"new_sentence = sentence.replace('great', 'awesome') print(new_sentence)

str() is used for string conversion

ten = str(10)print(ten) #converts 10 to '10'

You can find more in the Python.org Official Docs 

Let's work on a Small Project
- Arrange string characters such that lowercase letters should come first
Initial Code
noun = PrOgRamMinG# Expected Output : rgaminPORMG
Solution
noun = "PrOgRamMinG"# Let's create a Function to handle itdef arrange_string(my_string):    print('Original String:', my_string)    lower = []    upper = []    #Let's iterate and convert    for char in my_string:        if char.islower():            # add lowercase characters to lower list            lower.append(char)        else:            # add uppercase characters to lower list            upper.append(char)    # Join both list    sorted_str = ''.join(lower + upper)    print('Result:', sorted_str)# Now, let's call execute the function we just created! arrange_string(noun)# Output: # Original String: PrOgRamMinG# Result: rgaminPORMG
Resources for more Details:

www.w3schools.com 
www.programiz.com 
www.pynative.com/ 

👉 DISCOVER MORE useful ARTICLES 
Thanks for reading this article, many others are coming very soon, Feel free to subscribe 🤙.
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LinkedIn 
Instagram 

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]]>

Working with Numbers & Strings in Python

<![CDATA[We live in a world full of resources and data. Being a Python Developer can't escape the trend. That being said, in this article you're going to get all the resources you need to get started for the Journey.After learning Python basics, you'll find yourself being overwhelmed with a lot of information, and this can be very hard to go on. It becomes easier to get trapped in the Tutorial Hell 🔥.<h1 id="heading-brief-description-of-flask">Brief Description of Flask</h1>Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries. In other words, The Flask Framework is a Python platform that provides a foundation for developing software applications using Python Programming language. If your goal is to use Python for Web Development apps, Flask is what you need (sort of) for the Journey. Flask helps you set the Backend of your Web App. It's equivalent to Django (Another Python Backend Framework), NodeJS, Ruby on Rails, and so on.What is Special about Flask is its simplicity, there are not many things to get overwhelmed, You only get what you need, simply. 🤙That being said, using your favorite front-end technology (React, Vue, Angular, Svelte, or whatever you prefer), before jumping to read on the resources, you really have to determine what you need, exactly. Because, as we just said at the beginning, there are tons of resources and information you don't need, but still it makes you overwhelmed... <h1 id="heading-check-these-resources">Check these Resources</h1>As they are plenty of them, here are the two main resources you can use as references to go and check according to what you need:<h3 id="heading-refresh-the-memory-with-the-fundamentals">Refresh the memory with the Fundamentals</h3>Without the fundamentals, there is no way to bring innovation, meaning there is a necessity of getting a foundation. Here are the main resources: <a target="_blank" href="https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-i-hello-world">The Flask Mega-Tutorial</a> <a target="_blank" href="https://medium.com/javarevisited/5-best-python-flask-courses-for-beginners-2f262f8e23da">Five Best Python Flask Courses You need</a> <h3 id="heading-get-the-resources-you-need-to-build-real-world-projects">Get the Resources you need to Build Real-world Projects</h3>Knowing the Fundamentals isn't sufficient for real-world projects, you need to know topics like plugins (to avoid reinventing the wheel). Get the resources here: <a target="_blank" href="https://github.com/humiaozuzu/awesome-flask">Awesome Flask Links</a> <a target="_blank" href="https://github.com/realpython/discover-flask">Flask for your Project</a> <h3 id="heading-get-the-benefit-of-the-flask-community">Get the Benefit of the Flask Community</h3>Coding, but Stuck with some bugs? Here is the Solution, Go and ask the Community: <a target="_blank" href="https://www.reddit.com/r/flask/">Flask Subreddit Community</a> <a target="_blank" href="https://www.reddit.com/r/Python/">Python Subreddit Community</a>Thanks for reading this article, many others are coming very soon, Feel free to subscribe 🤙.<h1 id="heading-lets-connect">🌎 Let's connect</h1><ul><li><a target="_blank" href="https://twitter.com/CodeWithKenn">Twitter</a> </li><li><a target="_blank" href="https://github.com/KennStack01">Github</a> </li><li><a target="_blank" href="https://www.linkedin.com/in/kennkibadi/">LinkedIn</a> </li><li><a target="_blank" href="https://www.instagram.com/codewithkenn_/">Instagram</a> </li></ul>Want to start blogging? 🔥<a target="_blank" href="https://hashnode.com/@CodeWithKenn/joinme">Join NOW!</a> ]]>

After learning Python basics, you'll find yourself being overwhelmed with a lot of information, and this can be very hard to go on. It becomes easier to get trapped in the Tutorial Hell 🔥.
Brief Description of Flask
Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries. 
In other words, The Flask Framework is a Python platform that provides a foundation for developing software applications using Python Programming language. 
If your goal is to use Python for Web Development apps, Flask is what you need (sort of) for the Journey. Flask helps you set the Backend of your Web App. It's equivalent to Django (Another Python Backend Framework), NodeJS, Ruby on Rails, and so on.
What is Special about Flask is its simplicity, there are not many things to get overwhelmed, You only get what you need, simply. 🤙
That being said, using your favorite front-end technology (React, Vue, Angular, Svelte, or whatever you prefer), before jumping to read on the resources, you really have to determine what you need, exactly. Because, as we just said at the beginning, there are tons of resources and information you don't need, but still it makes you overwhelmed... 
Check these Resources
As they are plenty of them, here are the two main resources you can use as references to go and check according to what you need:
Refresh the memory with the Fundamentals
Without the fundamentals, there is no way to bring innovation, meaning there is a necessity of getting a foundation. Here are the main resources:
  The Flask Mega-Tutorial
  Five Best Python Flask Courses You need 
Get the Resources you need to Build Real-world Projects
Knowing the Fundamentals isn't sufficient for real-world projects, you need to know topics like plugins (to avoid reinventing the wheel). Get the resources here:
 Awesome Flask Links 
 Flask for your Project 
Get the Benefit of the Flask Community
Coding, but Stuck with some bugs? Here is the Solution, Go and ask the Community:
 Flask Subreddit Community
 Python Subreddit Community
Thanks for reading this article, many others are coming very soon, Feel free to subscribe 🤙.
🌎 Let's connect

Twitter 
Github 
LinkedIn 
Instagram 

Want to start blogging?  🔥Join NOW! 
]]>

Amazing Flask Resources FOR FREE!

What You Should Know About The Django User Model

How to Start a Production-Ready Django Project

Chart.js is a cool open source JavaScript library that helps you render HTML5 charts. It is responsive and counts with
8 different chart types.
In this tutorial we are going to explore a little bit of how to make Django talk with Chart.js and render some simple
charts based on data extracted from our models.
Installation
For this tutorial all you are going to do is add the Chart.js lib to your HTML page:
<script src="https://cdn.jsdelivr.net/npm/chart.js@2.9.3/dist/Chart.min.js"></script>


You can download it from Chart.js official website and use it locally, or you can use it from a CDN using the URL above.
Example Scenario
I’m going to use the same example I used for the tutorial How to Create Group By Queries With Django ORM which is a good complement to this tutorial because actually the tricky part of working with charts is to transform the data so it can fit in a bar chart / line chart / etc.
We are going to use the two models below, Country and City:
class Country(models.Model):
 name = models.CharField(max_length=30)

class City(models.Model):
 name = models.CharField(max_length=30)
 country = models.ForeignKey(Country, on_delete=models.CASCADE)
 population = models.PositiveIntegerField()


And the raw data stored in the database:
cities
 
 
id
 name
 country_id
 population
 
1Tokyo2836,923,000
2Shanghai1334,000,000
3Jakarta1930,000,000
4Seoul2125,514,000
5Guangzhou1325,000,000
6Beijing1324,900,000
7Karachi2224,300,000
8Shenzhen1323,300,000
9Delhi2521,753,486
10Mexico City2421,339,781
11Lagos921,000,000
12São Paulo120,935,204
13Mumbai2520,748,395
14New York City2020,092,883
15Osaka2819,342,000
16Wuhan1319,000,000
17Chengdu1318,100,000
18Dhaka417,151,925
19Chongqing1317,000,000
20Tianjin1315,400,000
21Kolkata2514,617,882
22Tehran1114,595,904
23Istanbul214,377,018
24London2614,031,830
25Hangzhou1313,400,000
26Los Angeles2013,262,220
27Buenos Aires813,074,000
28Xi'an1312,900,000
29Paris612,405,426
30Changzhou1312,400,000
31Shantou1312,000,000
32Rio de Janeiro111,973,505
33Manila1811,855,975
34Nanjing1311,700,000
35Rhine-Ruhr1611,470,000
36Jinan1311,000,000
37Bangalore2510,576,167
38Harbin1310,500,000
39Lima79,886,647
40Zhengzhou139,700,000
41Qingdao139,600,000
42Chicago209,554,598
43Nagoya289,107,000
44Chennai258,917,749
45Bangkok158,305,218
46Bogotá277,878,783
47Hyderabad257,749,334
48Shenyang137,700,000
49Wenzhou137,600,000
50Nanchang137,400,000
51Hong Kong137,298,600
52Taipei297,045,488
53Dallas–Fort Worth206,954,330
54Santiago146,683,852
55Luanda236,542,944
56Houston206,490,180
57Madrid176,378,297
58Ahmedabad256,352,254
59Toronto56,055,724
60Philadelphia206,051,170
61Washington, D.C.206,033,737
62Miami205,929,819
63Belo Horizonte15,767,414
64Atlanta205,614,323
65Singapore125,535,000
66Barcelona175,445,616
67Munich165,203,738
68Stuttgart165,200,000
69Ankara25,150,072
70Hamburg165,100,000
71Pune255,049,968
72Berlin165,005,216
73Guadalajara244,796,050
74Boston204,732,161
75Sydney105,000,500
76San Francisco204,594,060
77Surat254,585,367
78Phoenix204,489,109
79Monterrey244,477,614
80Inland Empire204,441,890
81Rome34,321,244
82Detroit204,296,611
83Milan34,267,946
84Melbourne104,650,000
countries
 
 
id
 name
 
1Brazil
2Turkey
3Italy
4Bangladesh
5Canada
6France
7Peru
8Argentina
9Nigeria
10Australia
11Iran
12Singapore
13China
14Chile
15Thailand
16Germany
17Spain
18Philippines
19Indonesia
20United States
21South Korea
22Pakistan
23Angola
24Mexico
25India
26United Kingdom
27Colombia
28Japan
29Taiwan
Example 1: Pie Chart
For the first example we are only going to retrieve the top 5 most populous cities and render it as a pie chart.
In this strategy we are going to return the chart data as part of the view context and inject the results in the
JavaScript code using the Django Template language.
views.py
from django.shortcuts import render
from mysite.core.models import City

def pie_chart(request):
 labels = []
 data = []

 queryset = City.objects.order_by('-population')[:5]
 for city in queryset:
 labels.append(city.name)
 data.append(city.population)

 return render(request, 'pie_chart.html', {
 'labels': labels,
 'data': data,
 })


Basically in the view above we are iterating through the City queryset and building a list of labels and a list of
data. Here in this case the data is the population count saved in the City model.
For the urls.py just a simple routing:
urls.py
from django.urls import path
from mysite.core import views

urlpatterns = [
 path('pie-chart/', views.pie_chart, name='pie-chart'),
]


Now the template. I got a basic snippet from the Chart.js Pie Chart Documentation.
pie_chart.html
{% extends 'base.html' %}

{% block content %}
 <div id="container" style="width: 75%;">
 <canvas id="pie-chart"></canvas>
 </div>

 <script src="https://cdn.jsdelivr.net/npm/chart.js@2.9.3/dist/Chart.min.js"></script>
 <script>

 var config = {
 type: 'pie',
 data: {
 datasets: [{
 data: {{ data|safe }},
 backgroundColor: [
 '#696969', '#808080', '#A9A9A9', '#C0C0C0', '#D3D3D3'
 ],
 label: 'Population'
 }],
 labels: {{ labels|safe }}
 },
 options: {
 responsive: true
 }
 };

 window.onload = function() {
 var ctx = document.getElementById('pie-chart').getContext('2d');
 window.myPie = new Chart(ctx, config);
 };

 </script>

{% endblock %}


In the example above the base.html template is not important but you can see it in the code example I shared in the
end of this post.
This strategy is not ideal but works fine. The bad thing is that we are using the Django Template Language to interfere
with the JavaScript logic. When we put {{ data|safe}} we are injecting a variable that came from
the server directly in the JavaScript code.
The code above looks like this:

Example 2: Bar Chart with Ajax
As the title says, we are now going to render a bar chart using an async call.
views.py
from django.shortcuts import render
from django.db.models import Sum
from django.http import JsonResponse
from mysite.core.models import City

def home(request):
 return render(request, 'home.html')

def population_chart(request):
 labels = []
 data = []

 queryset = City.objects.values('country__name').annotate(country_population=Sum('population')).order_by('-country_population')
 for entry in queryset:
 labels.append(entry['country__name'])
 data.append(entry['country_population'])
 
 return JsonResponse(data={
 'labels': labels,
 'data': data,
 })


So here we are using two views. The home view would be the main page where the chart would be loaded at. The other
view population_chart would be the one with the sole responsibility to aggregate the data the return a JSON response
with the labels and data.
If you are wondering about what this queryset is doing, it is grouping the cities by the country and aggregating the
total population of each country. The result is going to be a list of country + total population. To learn more about
this kind of query have a look on this post: How to Create Group By Queries With Django ORM
urls.py
from django.urls import path
from mysite.core import views

urlpatterns = [
 path('', views.home, name='home'),
 path('population-chart/', views.population_chart, name='population-chart'),
]


home.html
{% extends 'base.html' %}

{% block content %}

 <div id="container" style="width: 75%;">
 <canvas id="population-chart" data-url="{% url 'population-chart' %}"></canvas>
 </div>

 <script src="https://code.jquery.com/jquery-3.4.1.min.js"></script>
 <script src="https://cdn.jsdelivr.net/npm/chart.js@2.9.3/dist/Chart.min.js"></script>
 <script>

 $(function () {

 var $populationChart = $("#population-chart");
 $.ajax({
 url: $populationChart.data("url"),
 success: function (data) {

 var ctx = $populationChart[0].getContext("2d");

 new Chart(ctx, {
 type: 'bar',
 data: {
 labels: data.labels,
 datasets: [{
 label: 'Population',
 backgroundColor: 'blue',
 data: data.data
 }] 
 },
 options: {
 responsive: true,
 legend: {
 position: 'top',
 },
 title: {
 display: true,
 text: 'Population Bar Chart'
 }
 }
 });

 }
 });

 });

 </script>

{% endblock %}


Now we have a better separation of concerns. Looking at the chart container:
<canvas id="population-chart" data-url="{% url 'population-chart' %}"></canvas>


We added a reference to the URL that holds the chart rendering logic. Later on we are using it to execute the Ajax call.
var $populationChart = $("#population-chart");
$.ajax({
 url: $populationChart.data("url"),
 success: function (data) {
 // ...
 }
});


Inside the success callback we then finally execute the Chart.js related code using the JsonResponse data.

Conclusions
I hope this tutorial helped you to get started with working with charts using Chart.js. I published another tutorial
on the same subject a while ago but using the Highcharts library. The approach is pretty much the same: 
How to Integrate Highcharts.js with Django.
If you want to grab the code I used in this tutorial you can find it here: github.com/sibtc/django-chartjs-example.

How to Use Chart.js with Django

In this tutorial you are going to learn how to pass extra data to your serializer, before saving it to the database.

<ul>
 <li><a href="#introduction">Introduction</a></li>
 <li><a href="#example-using-apiview">Example Using APIView</a></li>
 <li><a href="#example-using-viewset">Example Using ViewSet</a></li>
</ul>

<h3 id="introduction">Introduction</h3>

When using regular Django forms, there is this common pattern where we save the form with <code class="highlighter-rouge">commit=False</code> and then pass
some extra data to the instance before saving it to the database, like this:

<figure class="highlight"><pre><code class="language-python" data-lang="python">form = InvoiceForm(request.POST)
if form.is_valid():
 invoice = form.save(commit=False)
 invoice.user = request.user
 invoice.save()</code></pre></figure>

This is very useful because we can save the required information using only one database query and it also make it 
possible to handle not nullable columns that was not defined in the form.

To simulate this pattern using a Django REST Framework serializer you can do something like this:

<figure class="highlight"><pre><code class="language-python" data-lang="python">serializer = InvoiceSerializer(data=request.data)
if serializer.is_valid():
 serializer.save(user=request.user)</code></pre></figure>

You can also pass several parameters at once:

<figure class="highlight"><pre><code class="language-python" data-lang="python">serializer = InvoiceSerializer(data=request.data)
if serializer.is_valid():
 serializer.save(user=request.user, date=timezone.now(), status='sent')</code></pre></figure>

<hr />

<h3 id="example-using-apiview">Example Using APIView</h3>

In this example I created an app named <code class="highlighter-rouge">core</code>.

models.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from django.contrib.auth.models import User
from django.db import models

class Invoice(models.Model):
 SENT = 1
 PAID = 2
 VOID = 3
 STATUS_CHOICES = (
 (SENT, 'sent'),
 (PAID, 'paid'),
 (VOID, 'void'),
 )

 user = models.ForeignKey(User, on_delete=models.CASCADE, related_name='invoices')
 number = models.CharField(max_length=30)
 date = models.DateTimeField(auto_now_add=True)
 status = models.PositiveSmallIntegerField(choices=STATUS_CHOICES)
 amount = models.DecimalField(max_digits=10, decimal_places=2)</code></pre></figure>

serializers.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from rest_framework import serializers
from core.models import Invoice

class InvoiceSerializer(serializers.ModelSerializer):
 class Meta:
 model = Invoice
 fields = ('number', 'amount')</code></pre></figure>

views.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from rest_framework import status
from rest_framework.response import Response
from rest_framework.views import APIView
from core.models import Invoice
from core.serializers import InvoiceSerializer

class InvoiceAPIView(APIView):
 def post(self, request):
 serializer = InvoiceSerializer(data=request.data)
 serializer.is_valid(raise_exception=True)
 serializer.save(user=request.user, status=Invoice.SENT)
 return Response(status=status.HTTP_201_CREATED)</code></pre></figure>

<hr />

<h3 id="example-using-viewset">Example Using ViewSet</h3>

Very similar example, using the same models.py and serializers.py as in the previous example.

views.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from rest_framework.viewsets import ModelViewSet
from core.models import Invoice
from core.serializers import InvoiceSerializer

class InvoiceViewSet(ModelViewSet):
 queryset = Invoice.objects.all()
 serializer_class = InvoiceSerializer

 def perform_create(self, serializer):
 serializer.save(user=self.request.user, status=Invoice.SENT)</code></pre></figure>

In this tutorial you are going to learn how to pass extra data to your serializer, before saving it to the database.
Introduction
Example Using APIView
Example Using ViewSet
Introduction
When using regular Django forms, there is this common pattern where we save the form with commit=False and then pass
some extra data to the instance before saving it to the database, like this:
form = InvoiceForm(request.POST)
if form.is_valid():
    invoice = form.save(commit=False)
    invoice.user = request.user
    invoice.save()


This is very useful because we can save the required information using only one database query and it also make it 
possible to handle not nullable columns that was not defined in the form.
To simulate this pattern using a Django REST Framework serializer you can do something like this:
serializer = InvoiceSerializer(data=request.data)
if serializer.is_valid():
    serializer.save(user=request.user)


You can also pass several parameters at once:
serializer = InvoiceSerializer(data=request.data)
if serializer.is_valid():
    serializer.save(user=request.user, date=timezone.now(), status='sent')




Example Using APIView
In this example I created an app named core.
models.py
from django.contrib.auth.models import User
from django.db import models

class Invoice(models.Model):
    SENT = 1
    PAID = 2
    VOID = 3
    STATUS_CHOICES = (
        (SENT, 'sent'),
        (PAID, 'paid'),
        (VOID, 'void'),
    )

    user = models.ForeignKey(User, on_delete=models.CASCADE, related_name='invoices')
    number = models.CharField(max_length=30)
    date = models.DateTimeField(auto_now_add=True)
    status = models.PositiveSmallIntegerField(choices=STATUS_CHOICES)
    amount = models.DecimalField(max_digits=10, decimal_places=2)


serializers.py
from rest_framework import serializers
from core.models import Invoice

class InvoiceSerializer(serializers.ModelSerializer):
    class Meta:
        model = Invoice
        fields = ('number', 'amount')


views.py
from rest_framework import status
from rest_framework.response import Response
from rest_framework.views import APIView
from core.models import Invoice
from core.serializers import InvoiceSerializer

class InvoiceAPIView(APIView):
    def post(self, request):
        serializer = InvoiceSerializer(data=request.data)
        serializer.is_valid(raise_exception=True)
        serializer.save(user=request.user, status=Invoice.SENT)
        return Response(status=status.HTTP_201_CREATED)




Example Using ViewSet
Very similar example, using the same models.py and serializers.py as in the previous example.
views.py
from rest_framework.viewsets import ModelViewSet
from core.models import Invoice
from core.serializers import InvoiceSerializer

class InvoiceViewSet(ModelViewSet):
    queryset = Invoice.objects.all()
    serializer_class = InvoiceSerializer

    def perform_create(self, serializer):
        serializer.save(user=self.request.user, status=Invoice.SENT)

How to Save Extra Data to a Django REST Framework Serializer

In this tutorial we are going to explore three date/datetime pickers options that you can easily use in a Django 
project. We are going to explore how to do it manually first, then how to set up a custom widget and finally how to
use a third-party Django app with support to datetime pickers.
Introduction
Tempus Dominus Bootstrap 4
 
Direct Usage
Custom Widget
XDSoft DateTimePicker
 
Direct Usage
Custom Widget
Fengyuan Chen’s Datepicker
 
Direct Usage
Custom Widget
Conclusions
Introduction
The implementation of a date picker is mostly done on the front-end.
The key part of the implementation is to assure Django will receive the date input value in the correct format, and 
also that Django will be able to reproduce the format when rendering a form with initial data.
We can also use custom widgets to provide a deeper integration between the front-end and back-end and also to promote
better reuse throughout a project.
In the next sections we are going to explore following date pickers:
Tempus Dominus Bootstrap 4
Docs 
Source 

XDSoft DateTimePicker
Docs 
Source 

Fengyuan Chen’s Datepicker
Docs 
Source 

Tempus Dominus Bootstrap 4
Docs 
Source 
This is a great JavaScript library and it integrate well with Bootstrap 4. The downside is that it requires moment.js
and sort of need Font-Awesome for the icons.
It only make sense to use this library with you are already using Bootstrap 4 + jQuery, otherwise the list of CSS and JS
may look a little bit overwhelming.
To install it you can use their CDN or download the 
latest release from their GitHub Releases page.
If you downloaded the code from the releases page, grab the processed code from the build/ folder.
Below, a static HTML example of the datepicker:
<!doctype html>
<html lang="en">
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <title>Static Example</title>

 
 <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.2.1/css/bootstrap.min.css" integrity="sha384-GJzZqFGwb1QTTN6wy59ffF1BuGJpLSa9DkKMp0DgiMDm4iYMj70gZWKYbI706tWS" crossorigin="anonymous">
 <script src="https://code.jquery.com/jquery-3.3.1.slim.min.js" integrity="sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo" crossorigin="anonymous"></script>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.14.6/umd/popper.min.js" integrity="sha384-wHAiFfRlMFy6i5SRaxvfOCifBUQy1xHdJ/yoi7FRNXMRBu5WHdZYu1hA6ZOblgut" crossorigin="anonymous"></script>
 <script src="https://stackpath.bootstrapcdn.com/bootstrap/4.2.1/js/bootstrap.min.js" integrity="sha384-B0UglyR+jN6CkvvICOB2joaf5I4l3gm9GU6Hc1og6Ls7i6U/mkkaduKaBhlAXv9k" crossorigin="anonymous"></script>

 
 <link href="https://stackpath.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css" rel="stylesheet" integrity="sha384-wvfXpqpZZVQGK6TAh5PVlGOfQNHSoD2xbE+QkPxCAFlNEevoEH3Sl0sibVcOQVnN" crossorigin="anonymous">

 
 <script src="https://cdnjs.cloudflare.com/ajax/libs/moment.js/2.23.0/moment.min.js" integrity="sha256-VBLiveTKyUZMEzJd6z2mhfxIqz3ZATCuVMawPZGzIfA=" crossorigin="anonymous"></script>

 
 <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/tempusdominus-bootstrap-4/5.1.2/css/tempusdominus-bootstrap-4.min.css" integrity="sha256-XPTBwC3SBoWHSmKasAk01c08M6sIA5gF5+sRxqak2Qs=" crossorigin="anonymous" />
 <script src="https://cdnjs.cloudflare.com/ajax/libs/tempusdominus-bootstrap-4/5.1.2/js/tempusdominus-bootstrap-4.min.js" integrity="sha256-z0oKYg6xiLq3yJGsp/LsY9XykbweQlHl42jHv2XTBz4=" crossorigin="anonymous"></script>

 </head>
 <body>

 <div class="input-group date" id="datetimepicker1" data-target-input="nearest">
 <input type="text" class="form-control datetimepicker-input" data-target="#datetimepicker1"/>
 <div class="input-group-append" data-target="#datetimepicker1" data-toggle="datetimepicker">
 <div class="input-group-text"></div>
 </div>
 </div>

 <script>
 $(function () {
 $("#datetimepicker1").datetimepicker();
 });
 </script>

 </body>
</html>



 

 
Direct Usage
The challenge now is to have this input snippet integrated with a Django form.
forms.py
from django import forms

class DateForm(forms.Form):
 date = forms.DateTimeField(
 input_formats=['%d/%m/%Y %H:%M'],
 widget=forms.DateTimeInput(attrs={
 'class': 'form-control datetimepicker-input',
 'data-target': '#datetimepicker1'
 })
 )


template
<div class="input-group date" id="datetimepicker1" data-target-input="nearest">
 {{ form.date }}
 <div class="input-group-append" data-target="#datetimepicker1" data-toggle="datetimepicker">
 <div class="input-group-text"></div>
 </div>
</div>

<script>
 $(function () {
 $("#datetimepicker1").datetimepicker({
 format: 'DD/MM/YYYY HH:mm',
 });
 });
</script>


The script tag can be placed anywhere because the snippet $(function () { ... }); will run the datetimepicker 
initialization when the page is ready. The only requirement is that this script tag is placed after the jQuery script
tag.
Custom Widget
You can create the widget in any app you want, here I’m going to consider we have a Django app named core.
core/widgets.py
from django.forms import DateTimeInput

class BootstrapDateTimePickerInput(DateTimeInput):
 template_name = 'widgets/bootstrap_datetimepicker.html'

 def get_context(self, name, value, attrs):
 datetimepicker_id = 'datetimepicker_{name}'.format(name=name)
 if attrs is None:
 attrs = dict()
 attrs['data-target'] = '#{id}'.format(id=datetimepicker_id)
 attrs['class'] = 'form-control datetimepicker-input'
 context = super().get_context(name, value, attrs)
 context['widget']['datetimepicker_id'] = datetimepicker_id
 return context


In the implementation above we generate a unique ID datetimepicker_id and also include it in the widget context.
Then the front-end implementation is done inside the widget HTML snippet.
widgets/bootstrap_datetimepicker.html
<div class="input-group date" id="{{ widget.datetimepicker_id }}" data-target-input="nearest">
 {% include "django/forms/widgets/input.html" %}
 <div class="input-group-append" data-target="#{{ widget.datetimepicker_id }}" data-toggle="datetimepicker">
 <div class="input-group-text"></div>
 </div>
</div>

<script>
 $(function () {
 $("#{{ widget.datetimepicker_id }}").datetimepicker({
 format: 'DD/MM/YYYY HH:mm',
 });
 });
</script>


Note how we make use of the built-in django/forms/widgets/input.html template.
Now the usage:
core/forms.py
from .widgets import BootstrapDateTimePickerInput

class DateForm(forms.Form):
 date = forms.DateTimeField(
 input_formats=['%d/%m/%Y %H:%M'], 
 widget=BootstrapDateTimePickerInput()
 )


Now simply render the field:
template
{{ form.date }}


The good thing about having the widget is that your form could have several date fields using the widget and you
could simply render the whole form like:
<form method="post">
 {% csrf_token %}
 {{ form.as_p }}
 <input type="submit" value="Submit">
</form>




XDSoft DateTimePicker
Docs 
Source 
The XDSoft DateTimePicker is a very versatile date picker and doesn’t rely on moment.js or Bootstrap, although it looks
good in a Bootstrap website.
It is easy to use and it is very straightforward.
You can download the source from GitHub releases page.
Below, a static example so you can see the minimum requirements and how all the pieces come together:
<!doctype html>
<html lang="en">
<head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <title>Static Example</title>

 
 <script src="https://code.jquery.com/jquery-3.3.1.slim.min.js" integrity="sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo" crossorigin="anonymous"></script>

 
 <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/jquery-datetimepicker/2.5.20/jquery.datetimepicker.min.css" integrity="sha256-DOS9W6NR+NFe1fUhEE0PGKY/fubbUCnOfTje2JMDw3Y=" crossorigin="anonymous" />
 <script src="https://cdnjs.cloudflare.com/ajax/libs/jquery-datetimepicker/2.5.20/jquery.datetimepicker.full.min.js" integrity="sha256-FEqEelWI3WouFOo2VWP/uJfs1y8KJ++FLh2Lbqc8SJk=" crossorigin="anonymous"></script>
</head>
<body>

 <input id="datetimepicker" type="text">

 <script>
 $(function () {
 $("#datetimepicker").datetimepicker();
 });
 </script>

</body>
</html>



 

 
Direct Usage
A basic integration with Django would look like this:
forms.py
from django import forms

class DateForm(forms.Form):
 date = forms.DateTimeField(input_formats=['%d/%m/%Y %H:%M'])


Simple form, default widget, nothing special.
Now using it on the template:
template
{{ form.date }}

<script>
 $(function () {
 $("#id_date").datetimepicker({
 format: 'd/m/Y H:i',
 });
 });
</script>


The id_date is the default ID Django generates for the form fields (id_ + name).
Custom Widget
core/widgets.py
from django.forms import DateTimeInput

class XDSoftDateTimePickerInput(DateTimeInput):
 template_name = 'widgets/xdsoft_datetimepicker.html'


widgets/xdsoft_datetimepicker.html
{% include "django/forms/widgets/input.html" %}

<script>
 $(function () {
 $("input[name='{{ widget.name }}']").datetimepicker({
 format: 'd/m/Y H:i',
 });
 });
</script>


To have a more generic implementation, this time we are selecting the field to initialize the component using its name
instead of its id, should the user change the id prefix.
Now the usage:
core/forms.py
from django import forms
from .widgets import XDSoftDateTimePickerInput

class DateForm(forms.Form):
 date = forms.DateTimeField(
 input_formats=['%d/%m/%Y %H:%M'], 
 widget=XDSoftDateTimePickerInput()
 )


template
{{ form.date }}




Fengyuan Chen’s Datepicker
Docs 
Source 
This is a very beautiful and minimalist date picker. Unfortunately there is no time support. But if you only need dates
this is a great choice.
To install this datepicker you can either use their CDN or download the 
sources from their GitHub releases page. Please note that they
do not provide a compiled/processed JavaScript files. But you can download those to your local machine using the CDN.
<!doctype html>
<html lang="en">
<head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <title>Static Example</title>
 <style>body {font-family: Arial, sans-serif;}</style>
 
 
 <script src="https://code.jquery.com/jquery-3.3.1.slim.min.js" integrity="sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo" crossorigin="anonymous"></script>

 
 <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/datepicker/0.6.5/datepicker.min.css" integrity="sha256-b88RdwbRJEzRx95nCuuva+hO5ExvXXnpX+78h8DjyOE=" crossorigin="anonymous" />
 <script src="https://cdnjs.cloudflare.com/ajax/libs/datepicker/0.6.5/datepicker.min.js" integrity="sha256-/7FLTdzP6CfC1VBAj/rsp3Rinuuu9leMRGd354hvk0k=" crossorigin="anonymous"></script>
</head>
<body>

 <input id="datepicker">

 <script>
 $(function () {
 $("#datepicker").datepicker();
 });
 </script>

</body>
</html>



 

 
Direct Usage
A basic integration with Django (note that we are now using DateField instead of DateTimeField):
forms.py
from django import forms

class DateForm(forms.Form):
 date = forms.DateTimeField(input_formats=['%d/%m/%Y %H:%M'])


template
{{ form.date }}

<script>
 $(function () {
 $("#id_date").datepicker({
 format:'dd/mm/yyyy',
 });
 });
</script>


Custom Widget
core/widgets.py
from django.forms import DateInput

class FengyuanChenDatePickerInput(DateInput):
 template_name = 'widgets/fengyuanchen_datepicker.html'


widgets/fengyuanchen_datepicker.html
{% include "django/forms/widgets/input.html" %}

<script>
 $(function () {
 $("input[name='{{ widget.name }}']").datepicker({
 format:'dd/mm/yyyy',
 });
 });
</script>


Usage:
core/forms.py
from django import forms
from .widgets import FengyuanChenDatePickerInput

class DateForm(forms.Form):
 date = forms.DateTimeField(
 input_formats=['%d/%m/%Y %H:%M'], 
 widget=FengyuanChenDatePickerInput()
 )


template
{{ form.date }}




Conclusions
The implementation is very similar no matter what date/datetime picker you are using. Hopefully this tutorial provided
some insights on how to integrate this kind of frontend library to a Django project.
As always, the best source of information about each of those libraries are their official documentation.
I also created an example project to show the usage and implementation of the widgets for each of the libraries 
presented in this tutorial. Grab the source code at github.com/sibtc/django-datetimepicker-example.

How to Use Date Picker with Django

The Django forms API have two field types to work with multiple options: <code class="highlighter-rouge">ChoiceField</code> and <code class="highlighter-rouge">ModelChoiceField</code>.

Both use select input as the default widget and they work in a similar way, except that <code class="highlighter-rouge">ModelChoiceField</code> is designed 
to handle QuerySets and work with foreign key relationships.

A basic implementation using a <code class="highlighter-rouge">ChoiceField</code> would be:

<div class="row" id="ChoiceField">
 <div class="eight columns">


<figure class="highlight"><pre><code class="language-python" data-lang="python">class ExpenseForm(forms.Form):
 CHOICES = (
 (11, 'Credit Card'),
 (12, 'Student Loans'),
 (13, 'Taxes'),
 (21, 'Books'),
 (22, 'Games'),
 (31, 'Groceries'),
 (32, 'Restaurants'),
 )
 amount = forms.DecimalField()
 date = forms.DateField()
 category = forms.ChoiceField(choices=CHOICES)</code></pre></figure>


 </div>
 <div class="four columns">
 <img src="https://simpleisbetterthancomplex.com/media/2019/01/form.jpg" alt="Django ChoiceField" style="max-width:100%;" />
 </div>
</div>

<hr />

<h4 id="grouped-choice-field">Grouped Choice Field</h4>

You can also organize the choices in groups to generate the <code class="highlighter-rouge">&lt;optgroup&gt;</code> tags like this:

<div class="row">
 <div class="eight columns">


<figure class="highlight"><pre><code class="language-python" data-lang="python">class ExpenseForm(forms.Form):
 CHOICES = (
 ('Debt', (
 (11, 'Credit Card'),
 (12, 'Student Loans'),
 (13, 'Taxes'),
 )),
 ('Entertainment', (
 (21, 'Books'),
 (22, 'Games'),
 )),
 ('Everyday', (
 (31, 'Groceries'),
 (32, 'Restaurants'),
 )),
 )
 amount = forms.DecimalField()
 date = forms.DateField()
 category = forms.ChoiceField(choices=CHOICES)</code></pre></figure>


 </div>
 <div class="four columns">
 <img src="https://simpleisbetterthancomplex.com/media/2019/01/form2.jpg" alt="Django Grouped ChoiceField" style="max-width:100%;" />
 </div>
</div>

<hr />

<h4 id="grouped-model-choice-field">Grouped Model Choice Field</h4>

When you are using a <code class="highlighter-rouge">ModelChoiceField</code> unfortunately there is no built-in solution.

Recently I found a nice solution on <a href="https://code.djangoproject.com/ticket/27331">Django’s ticket tracker</a>, where 
someone proposed adding an <code class="highlighter-rouge">opt_group</code> argument to the <code class="highlighter-rouge">ModelChoiceField</code>.

While the discussion is still ongoing, <a href="https://code.djangoproject.com/ticket/27331#comment:7">Simon Charette</a> proposed
a really good solution.

Let’s see how we can integrate it in our project.

First consider the following models:

models.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from django.db import models

class Category(models.Model):
 name = models.CharField(max_length=30)
 parent = models.ForeignKey('Category', on_delete=models.CASCADE, null=True)

 def __str__(self):
 return self.name

class Expense(models.Model):
 amount = models.DecimalField(max_digits=10, decimal_places=2)
 date = models.DateField()
 category = models.ForeignKey(Category, on_delete=models.CASCADE)

 def __str__(self):
 return self.amount</code></pre></figure>

So now our category instead of being a regular choices field it is now a model and the <code class="highlighter-rouge">Expense</code> model have a 
relationship with it using a foreign key.

If we create a <code class="highlighter-rouge">ModelForm</code> using this model, the result will be very similar to <a href="#ChoiceField">our first example</a>.

To simulate a grouped categories you will need the code below. First create a new module named fields.py:

fields.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from functools import partial
from itertools import groupby
from operator import attrgetter

from django.forms.models import ModelChoiceIterator, ModelChoiceField


class GroupedModelChoiceIterator(ModelChoiceIterator):
 def __init__(self, field, groupby):
 self.groupby = groupby
 super().__init__(field)

 def __iter__(self):
 if self.field.empty_label is not None:
 yield ("", self.field.empty_label)
 queryset = self.queryset
 # Can't use iterator() when queryset uses prefetch_related()
 if not queryset._prefetch_related_lookups:
 queryset = queryset.iterator()
 for group, objs in groupby(queryset, self.groupby):
 yield (group, [self.choice(obj) for obj in objs])


class GroupedModelChoiceField(ModelChoiceField):
 def __init__(self, *args, choices_groupby, **kwargs):
 if isinstance(choices_groupby, str):
 choices_groupby = attrgetter(choices_groupby)
 elif not callable(choices_groupby):
 raise TypeError('choices_groupby must either be a str or a callable accepting a single argument')
 self.iterator = partial(GroupedModelChoiceIterator, groupby=choices_groupby)
 super().__init__(*args, **kwargs)</code></pre></figure>

And here is how you use it in your forms:

forms.py

<div class="row">
 <div class="eight columns">


<figure class="highlight"><pre><code class="language-python" data-lang="python">from django import forms
from .fields import GroupedModelChoiceField
from .models import Category, Expense

class ExpenseForm(forms.ModelForm):
 category = GroupedModelChoiceField(
 queryset=Category.objects.exclude(parent=None), 
 choices_groupby='parent'
 )

 class Meta:
 model = Expense
 fields = ('amount', 'date', 'category')</code></pre></figure>


 </div>
 <div class="four columns">
 <img src="https://simpleisbetterthancomplex.com/media/2019/01/form3.jpg" alt="Django Grouped ModelChoiceField" style="max-width:100%;" />
 </div>
</div>

Because in the example above I used a self-referencing relationship I had to add the <code class="highlighter-rouge">exclude(parent=None)</code> to hide
the “group categories” from showing up in the select input as a valid option.

<hr />

<h4 id="further-reading">Further Reading</h4>

You can download the code used in this tutorial from GitHub: <a href="https://github.com/sibtc/django-grouped-choice-field-example">github.com/sibtc/django-grouped-choice-field-example</a>

Credits to the solution <a href="https://code.djangoproject.com/ticket/27331#comment:7">Simon Charette on Django Ticket Track</a>.

The Django forms API have two field types to work with multiple options: ChoiceField and ModelChoiceField.
Both use select input as the default widget and they work in a similar way, except that ModelChoiceField is designed 
to handle QuerySets and work with foreign key relationships.
A basic implementation using a ChoiceField would be:
class ExpenseForm(forms.Form):
 CHOICES = (
 (11, 'Credit Card'),
 (12, 'Student Loans'),
 (13, 'Taxes'),
 (21, 'Books'),
 (22, 'Games'),
 (31, 'Groceries'),
 (32, 'Restaurants'),
 )
 amount = forms.DecimalField()
 date = forms.DateField()
 category = forms.ChoiceField(choices=CHOICES)



 
Grouped Choice Field
You can also organize the choices in groups to generate the <optgroup> tags like this:
class ExpenseForm(forms.Form):
 CHOICES = (
 ('Debt', (
 (11, 'Credit Card'),
 (12, 'Student Loans'),
 (13, 'Taxes'),
 )),
 ('Entertainment', (
 (21, 'Books'),
 (22, 'Games'),
 )),
 ('Everyday', (
 (31, 'Groceries'),
 (32, 'Restaurants'),
 )),
 )
 amount = forms.DecimalField()
 date = forms.DateField()
 category = forms.ChoiceField(choices=CHOICES)



 
Grouped Model Choice Field
When you are using a ModelChoiceField unfortunately there is no built-in solution.
Recently I found a nice solution on Django’s ticket tracker, where 
someone proposed adding an opt_group argument to the ModelChoiceField.
While the discussion is still ongoing, Simon Charette proposed
a really good solution.
Let’s see how we can integrate it in our project.
First consider the following models:
models.py
from django.db import models

class Category(models.Model):
 name = models.CharField(max_length=30)
 parent = models.ForeignKey('Category', on_delete=models.CASCADE, null=True)

 def __str__(self):
 return self.name

class Expense(models.Model):
 amount = models.DecimalField(max_digits=10, decimal_places=2)
 date = models.DateField()
 category = models.ForeignKey(Category, on_delete=models.CASCADE)

 def __str__(self):
 return self.amount


So now our category instead of being a regular choices field it is now a model and the Expense model have a 
relationship with it using a foreign key.
If we create a ModelForm using this model, the result will be very similar to our first example.
To simulate a grouped categories you will need the code below. First create a new module named fields.py:
fields.py
from functools import partial
from itertools import groupby
from operator import attrgetter

from django.forms.models import ModelChoiceIterator, ModelChoiceField


class GroupedModelChoiceIterator(ModelChoiceIterator):
 def __init__(self, field, groupby):
 self.groupby = groupby
 super().__init__(field)

 def __iter__(self):
 if self.field.empty_label is not None:
 yield ("", self.field.empty_label)
 queryset = self.queryset
 # Can't use iterator() when queryset uses prefetch_related()
 if not queryset._prefetch_related_lookups:
 queryset = queryset.iterator()
 for group, objs in groupby(queryset, self.groupby):
 yield (group, [self.choice(obj) for obj in objs])


class GroupedModelChoiceField(ModelChoiceField):
 def __init__(self, *args, choices_groupby, **kwargs):
 if isinstance(choices_groupby, str):
 choices_groupby = attrgetter(choices_groupby)
 elif not callable(choices_groupby):
 raise TypeError('choices_groupby must either be a str or a callable accepting a single argument')
 self.iterator = partial(GroupedModelChoiceIterator, groupby=choices_groupby)
 super().__init__(*args, **kwargs)


And here is how you use it in your forms:
forms.py
from django import forms
from .fields import GroupedModelChoiceField
from .models import Category, Expense

class ExpenseForm(forms.ModelForm):
 category = GroupedModelChoiceField(
 queryset=Category.objects.exclude(parent=None), 
 choices_groupby='parent'
 )

 class Meta:
 model = Expense
 fields = ('amount', 'date', 'category')



 
Because in the example above I used a self-referencing relationship I had to add the exclude(parent=None) to hide
the “group categories” from showing up in the select input as a valid option.
Further Reading
You can download the code used in this tutorial from GitHub: github.com/sibtc/django-grouped-choice-field-example
Credits to the solution Simon Charette on Django Ticket Track.

How to Implement Grouped Model Choice Field

JWT stand for JSON Web Token and it is an authentication strategy used by client/server applications where the
client is a Web application using JavaScript and some frontend framework like Angular, React or VueJS.

In this tutorial we are going to explore the specifics of JWT authentication. If you want to learn more about
Token-based authentication using Django REST Framework (DRF), or if you want to know how to start a new DRF project
you can read this tutorial: <a href="/tutorial/2018/11/22/how-to-implement-token-authentication-using-django-rest-framework.html">How to Implement Token Authentication using Django REST Framework</a>.
The concepts are the same, we are just going to switch the authentication backend.

<ul>
 <li><a href="#how-jwt-works">How JWT Works?</a></li>
 <li><a href="#installation--setup">Installation &amp; Setup</a></li>
 <li><a href="#example-code">Example Code</a></li>
 <li><a href="#usage">Usage</a>
 <ul>
 <li><a href="#obtain-token">Obtain Token</a></li>
 <li><a href="#refresh-token">Refresh Token</a></li>
 </ul>
 </li>
 <li><a href="#whats-the-point-of-the-refresh-token">What’s The Point of The Refresh Token?</a></li>
 <li><a href="#further-reading">Further Reading</a></li>
</ul>

<hr />

<h4 id="how-jwt-works">How JWT Works?</h4>

The JWT is just an authorization token that should be included in all requests:

<figure class="highlight"><pre><code class="language-bash" data-lang="bash">curl http://127.0.0.1:8000/hello/ -H 'Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQzODI4NDMxLCJqdGkiOiI3ZjU5OTdiNzE1MGQ0NjU3OWRjMmI0OTE2NzA5N2U3YiIsInVzZXJfaWQiOjF9.Ju70kdcaHKn1Qaz8H42zrOYk0Jx9kIckTn9Xx7vhikY'</code></pre></figure>

The JWT is acquired by exchanging an username + password for an access token and an refresh token.

The access token is usually short-lived (expires in 5 min or so, can be customized though).

The refresh token lives a little bit longer (expires in 24 hours, also customizable). It is comparable to an
authentication session. After it expires, you need a full login with username + password again.

Why is that?

It’s a security feature and also it’s because the JWT holds a little bit more information. If you look closely the
example I gave above, you will see the token is composed by three parts:

<figure class="highlight"><pre><code class="language-bash" data-lang="bash">xxxxx.yyyyy.zzzzz</code></pre></figure>

Those are three distinctive parts that compose a JWT:

<figure class="highlight"><pre><code class="language-bash" data-lang="bash">header.payload.signature</code></pre></figure>

So we have here:

<figure class="highlight"><pre><code class="language-bash" data-lang="bash">header = eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9
payload = eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQzODI4NDMxLCJqdGkiOiI3ZjU5OTdiNzE1MGQ0NjU3OWRjMmI0OTE2NzA5N2U3YiIsInVzZXJfaWQiOjF9
signature = Ju70kdcaHKn1Qaz8H42zrOYk0Jx9kIckTn9Xx7vhikY</code></pre></figure>

This information is encoded using Base64. If we decode, we will see something like this:

header

<figure class="highlight"><pre><code class="language-json" data-lang="json">{
 "typ": "JWT",
 "alg": "HS256"
}</code></pre></figure>

payload

<figure class="highlight"><pre><code class="language-json" data-lang="json">{
 "token_type": "access",
 "exp": 1543828431,
 "jti": "7f5997b7150d46579dc2b49167097e7b",
 "user_id": 1
}</code></pre></figure>

signature

The signature is issued by the JWT backend, using the header base64 + payload base64 + <code class="highlighter-rouge">SECRET_KEY</code>. Upon each request
this signature is verified. If any information in the header or in the payload was changed by the client it will
invalidate the signature. The only way of checking and validating the signature is by using your application’s
<code class="highlighter-rouge">SECRET_KEY</code>. Among other things, that’s why you should always keep your <code class="highlighter-rouge">SECRET_KEY</code> secret!

<hr />

<h4 id="installation--setup">Installation &amp; Setup</h4>

For this tutorial we are going to use the <a href="https://github.com/davesque/django-rest-framework-simplejwt"><code class="highlighter-rouge">djangorestframework_simplejwt</code></a>
library, recommended by the DRF developers.

<figure class="highlight"><pre><code class="language-bash" data-lang="bash">pip install djangorestframework_simplejwt</code></pre></figure>

settings.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">REST_FRAMEWORK = {
 'DEFAULT_AUTHENTICATION_CLASSES': [
 'rest_framework_simplejwt.authentication.JWTAuthentication',
 ],
}</code></pre></figure>

urls.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from django.urls import path
from rest_framework_simplejwt import views as jwt_views

urlpatterns = [
 # Your URLs...
 path('api/token/', jwt_views.TokenObtainPairView.as_view(), name='token_obtain_pair'),
 path('api/token/refresh/', jwt_views.TokenRefreshView.as_view(), name='token_refresh'),
]</code></pre></figure>

<hr />

<h4 id="example-code">Example Code</h4>

For this tutorial I will use the following route and API view:

views.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.permissions import IsAuthenticated


class HelloView(APIView):
 permission_classes = (IsAuthenticated,)

 def get(self, request):
 content = {'message': 'Hello, World!'}
 return Response(content)</code></pre></figure>

urls.py

<figure class="highlight"><pre><code class="language-python" data-lang="python">from django.urls import path
from myapi.core import views

urlpatterns = [
 path('hello/', views.HelloView.as_view(), name='hello'),
]</code></pre></figure>

<hr />

<h4 id="usage">Usage</h4>

I will be using <a href="https://httpie.org">HTTPie</a> to consume the API endpoints via the terminal. But you can also use
<a href="https://curl.haxx.se/">cURL</a> (readily available in many OS) to try things out locally.

Or alternatively, use the DRF web interface by accessing the endpoint URLs like this:

<img src="https://simpleisbetterthancomplex.com/media/2018/12/drf-web.png" alt="DRF JWT Obtain Token" />

<h5 id="obtain-token">Obtain Token</h5>

First step is to authenticate and obtain the token. The endpoint is <code class="highlighter-rouge">/api/token/</code> and it only accepts POST requests.

<figure class="highlight"><pre><code class="language-bash" data-lang="bash">http post http://127.0.0.1:8000/api/token/ username=vitor password=123</code></pre></figure>

<img src="https://simpleisbetterthancomplex.com/media/2018/12/jwt-obtain-token.png" alt="HTTPie JWT Obtain Token" />

So basically your response body is the two tokens:

<figure class="highlight"><pre><code class="language-json" data-lang="json">{
 "access": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQ1MjI0MjU5LCJqdGkiOiIyYmQ1NjI3MmIzYjI0YjNmOGI1MjJlNThjMzdjMTdlMSIsInVzZXJfaWQiOjF9.D92tTuVi_YcNkJtiLGHtcn6tBcxLCBxz9FKD3qzhUg8",
 "refresh": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoicmVmcmVzaCIsImV4cCI6MTU0NTMxMDM1OSwianRpIjoiMjk2ZDc1ZDA3Nzc2NDE0ZjkxYjhiOTY4MzI4NGRmOTUiLCJ1c2VyX2lkIjoxfQ.rA-mnGRg71NEW_ga0sJoaMODS5ABjE5HnxJDb0F8xAo"
}</code></pre></figure>

After that you are going to store both the access token and the refresh token on the client side, usually in
the <a href="https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage">localStorage</a>.

In order to access the protected views on the backend (i.e., the API endpoints that require authentication), you should
include the access token in the header of all requests, like this:

<figure class="highlight"><pre><code class="language-bash" data-lang="bash">http http://127.0.0.1:8000/hello/ "Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQ1MjI0MjAwLCJqdGkiOiJlMGQxZDY2MjE5ODc0ZTY3OWY0NjM0ZWU2NTQ2YTIwMCIsInVzZXJfaWQiOjF9.9eHat3CvRQYnb5EdcgYFzUyMobXzxlAVh_IAgqyvzCE"</code></pre></figure>

<img src="https://simpleisbetterthancomplex.com/media/2018/12/jwt-bearer.png" alt="HTTPie JWT Hello, World!" />

You can use this access token for the next five minutes.

After five min, the token will expire, and if you try to access the view again, you are going to get the following
error:

<figure class="highlight"><pre><code class="language-bash" data-lang="bash">http http://127.0.0.1:8000/hello/ "Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQ1MjI0MjAwLCJqdGkiOiJlMGQxZDY2MjE5ODc0ZTY3OWY0NjM0ZWU2NTQ2YTIwMCIsInVzZXJfaWQiOjF9.9eHat3CvRQYnb5EdcgYFzUyMobXzxlAVh_IAgqyvzCE"</code></pre></figure>

<img src="https://simpleisbetterthancomplex.com/media/2018/12/jwt-expired.png" alt="HTTPie JWT Expired" />

<h5 id="refresh-token">Refresh Token</h5>

To get a new access token, you should use the refresh token endpoint <code class="highlighter-rouge">/api/token/refresh/</code> posting the
refresh token:

<figure class="highlight"><pre><code class="language-python" data-lang="python">http post http://127.0.0.1:8000/api/token/refresh/ refresh=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoicmVmcmVzaCIsImV4cCI6MTU0NTMwODIyMiwianRpIjoiNzAyOGFlNjc0ZTdjNDZlMDlmMzUwYjg3MjU1NGUxODQiLCJ1c2VyX2lkIjoxfQ.Md8AO3dDrQBvWYWeZsd_A1J39z6b6HEwWIUZ7ilOiPE</code></pre></figure>

<img src="https://simpleisbetterthancomplex.com/media/2018/12/jwt-refresh-token.png" alt="HTTPie JWT Refresh Token" />

The return is a new access token that you should use in the subsequent requests.

The refresh token is valid for the next 24 hours. When it finally expires too, the user will need to perform a
full authentication again using their username and password to get a new set of access token + refresh token.

<hr />

<h4 id="whats-the-point-of-the-refresh-token">What’s The Point of The Refresh Token?</h4>

At first glance the refresh token may look pointless, but in fact it is necessary to make sure the user still have
the correct permissions. If your access token have a long expire time, it may take longer to update the information
associated with the token. That’s because the authentication check is done by cryptographic means, instead of querying
the database and verifying the data. So some information is sort of cached.

There is also a security aspect, in a sense that the refresh token only travel in the POST data. And the
access token is sent via HTTP header, which may be logged along the way. So this also give a short window, should
your access token be compromised.

<hr />

<h4 id="further-reading">Further Reading</h4>

This should cover the basics on the backend implementation. It’s worth checking the
<a href="https://github.com/davesque/django-rest-framework-simplejwt">djangorestframework_simplejwt settings</a> for further
customization and to get a better idea of what the library offers.

The implementation on the frontend depends on what framework/library you are using. Some libraries and articles
covering popular frontend frameworks like angular/react/vue.js:

<ul>
 <li><a href="https://github.com/auth0/angular-jwt">Angular JWT library</a></li>
 <li><a href="https://github.com/auth0/angular2-jwt">Angular 2 JWT library</a></li>
 <li><a href="https://auth0.com/blog/secure-your-react-and-redux-app-with-jwt-authentication/">Secure Your React and Redux App with JWT Authentication</a></li>
 <li><a href="https://www.pydanny.com/drf-jwt-axios-vue.html">Authenticating via JWT using Django, Axios, and Vue</a></li>
</ul>

The code used in this tutorial is available at <a href="https://github.com/sibtc/drf-jwt-example">github.com/sibtc/drf-jwt-example</a>.

JWT stand for JSON Web Token and it is an authentication strategy used by client/server applications where the
client is a Web application using JavaScript and some frontend framework like Angular, React or VueJS.
In this tutorial we are going to explore the specifics of JWT authentication. If you want to learn more about
Token-based authentication using Django REST Framework (DRF), or if you want to know how to start a new DRF project
you can read this tutorial: How to Implement Token Authentication using Django REST Framework.
The concepts are the same, we are just going to switch the authentication backend.
How JWT Works?
Installation & Setup
Example Code
Usage
    
Obtain Token
Refresh Token
What’s The Point of The Refresh Token?
Further Reading
How JWT Works?
The JWT is just an authorization token that should be included in all requests:
curl http://127.0.0.1:8000/hello/ -H 'Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQzODI4NDMxLCJqdGkiOiI3ZjU5OTdiNzE1MGQ0NjU3OWRjMmI0OTE2NzA5N2U3YiIsInVzZXJfaWQiOjF9.Ju70kdcaHKn1Qaz8H42zrOYk0Jx9kIckTn9Xx7vhikY'


The JWT is acquired by exchanging an username + password for an access token and an refresh token.
The access token is usually short-lived (expires in 5 min or so, can be customized though).
The refresh token lives a little bit longer (expires in 24 hours, also customizable). It is comparable to an
authentication session. After it expires, you need a full login with username + password again.
Why is that?
It’s a security feature and also it’s because the JWT holds a little bit more information. If you look closely the
example I gave above, you will see the token is composed by three parts:
xxxxx.yyyyy.zzzzz


Those are three distinctive parts that compose a JWT:
header.payload.signature


So we have here:
header = eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9
payload = eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQzODI4NDMxLCJqdGkiOiI3ZjU5OTdiNzE1MGQ0NjU3OWRjMmI0OTE2NzA5N2U3YiIsInVzZXJfaWQiOjF9
signature = Ju70kdcaHKn1Qaz8H42zrOYk0Jx9kIckTn9Xx7vhikY


This information is encoded using Base64. If we decode, we will see something like this:
header
{
  "typ": "JWT",
  "alg": "HS256"
}


payload
{
  "token_type": "access",
  "exp": 1543828431,
  "jti": "7f5997b7150d46579dc2b49167097e7b",
  "user_id": 1
}


signature
The signature is issued by the JWT backend, using the header base64 + payload base64 + SECRET_KEY. Upon each request
this signature is verified. If any information in the header or in the payload was changed by the client it will
invalidate the signature. The only way of checking and validating the signature is by using your application’s
SECRET_KEY. Among other things, that’s why you should always keep your SECRET_KEY secret!
Installation & Setup
For this tutorial we are going to use the djangorestframework_simplejwt
library, recommended by the DRF developers.
pip install djangorestframework_simplejwt


settings.py
REST_FRAMEWORK = {
    'DEFAULT_AUTHENTICATION_CLASSES': [
        'rest_framework_simplejwt.authentication.JWTAuthentication',
    ],
}


urls.py
from django.urls import path
from rest_framework_simplejwt import views as jwt_views

urlpatterns = [
    # Your URLs...
    path('api/token/', jwt_views.TokenObtainPairView.as_view(), name='token_obtain_pair'),
    path('api/token/refresh/', jwt_views.TokenRefreshView.as_view(), name='token_refresh'),
]




Example Code
For this tutorial I will use the following route and API view:
views.py
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.permissions import IsAuthenticated


class HelloView(APIView):
    permission_classes = (IsAuthenticated,)

    def get(self, request):
        content = {'message': 'Hello, World!'}
        return Response(content)


urls.py
from django.urls import path
from myapi.core import views

urlpatterns = [
    path('hello/', views.HelloView.as_view(), name='hello'),
]




Usage
I will be using HTTPie to consume the API endpoints via the terminal. But you can also use
cURL (readily available in many OS) to try things out locally.
Or alternatively, use the DRF web interface by accessing the endpoint URLs like this:

Obtain Token
First step is to authenticate and obtain the token. The endpoint is /api/token/ and it only accepts POST requests.
http post http://127.0.0.1:8000/api/token/ username=vitor password=123



So basically your response body is the two tokens:
{
    "access": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQ1MjI0MjU5LCJqdGkiOiIyYmQ1NjI3MmIzYjI0YjNmOGI1MjJlNThjMzdjMTdlMSIsInVzZXJfaWQiOjF9.D92tTuVi_YcNkJtiLGHtcn6tBcxLCBxz9FKD3qzhUg8",
    "refresh": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoicmVmcmVzaCIsImV4cCI6MTU0NTMxMDM1OSwianRpIjoiMjk2ZDc1ZDA3Nzc2NDE0ZjkxYjhiOTY4MzI4NGRmOTUiLCJ1c2VyX2lkIjoxfQ.rA-mnGRg71NEW_ga0sJoaMODS5ABjE5HnxJDb0F8xAo"
}


After that you are going to store both the access token and the refresh token on the client side, usually in
the localStorage.
In order to access the protected views on the backend (i.e., the API endpoints that require authentication), you should
include the access token in the header of all requests, like this:
http http://127.0.0.1:8000/hello/ "Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQ1MjI0MjAwLCJqdGkiOiJlMGQxZDY2MjE5ODc0ZTY3OWY0NjM0ZWU2NTQ2YTIwMCIsInVzZXJfaWQiOjF9.9eHat3CvRQYnb5EdcgYFzUyMobXzxlAVh_IAgqyvzCE"



You can use this access token for the next five minutes.
After five min, the token will expire, and if you try to access the view again, you are going to get the following
error:
http http://127.0.0.1:8000/hello/ "Authorization: Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoiYWNjZXNzIiwiZXhwIjoxNTQ1MjI0MjAwLCJqdGkiOiJlMGQxZDY2MjE5ODc0ZTY3OWY0NjM0ZWU2NTQ2YTIwMCIsInVzZXJfaWQiOjF9.9eHat3CvRQYnb5EdcgYFzUyMobXzxlAVh_IAgqyvzCE"



Refresh Token
To get a new access token, you should use the refresh token endpoint /api/token/refresh/ posting the
refresh token:
http post http://127.0.0.1:8000/api/token/refresh/ refresh=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ0b2tlbl90eXBlIjoicmVmcmVzaCIsImV4cCI6MTU0NTMwODIyMiwianRpIjoiNzAyOGFlNjc0ZTdjNDZlMDlmMzUwYjg3MjU1NGUxODQiLCJ1c2VyX2lkIjoxfQ.Md8AO3dDrQBvWYWeZsd_A1J39z6b6HEwWIUZ7ilOiPE



The return is a new access token that you should use in the subsequent requests.
The refresh token is valid for the next 24 hours. When it finally expires too, the user will need to perform a
full authentication again using their username and password to get a new set of access token + refresh token.
What’s The Point of The Refresh Token?
At first glance the refresh token may look pointless, but in fact it is necessary to make sure the user still have
the correct permissions. If your access token have a long expire time, it may take longer to update the information
associated with the token. That’s because the authentication check is done by cryptographic means, instead of querying
the database and verifying the data. So some information is sort of cached.
There is also a security aspect, in a sense that the refresh token only travel in the POST data. And the
access token is sent via HTTP header, which may be logged along the way. So this also give a short window, should
your access token be compromised.
Further Reading
This should cover the basics on the backend implementation. It’s worth checking the
djangorestframework_simplejwt settings for further
customization and to get a better idea of what the library offers.
The implementation on the frontend depends on what framework/library you are using. Some libraries and articles
covering popular frontend frameworks like angular/react/vue.js:
Angular JWT library
Angular 2 JWT library
Secure Your React and Redux App with JWT Authentication
Authenticating via JWT using Django, Axios, and Vue
The code used in this tutorial is available at github.com/sibtc/drf-jwt-example.

How to Use JWT Authentication with Django REST Framework

[Django 2.1.3 / Python 3.6.5 / Bootstrap 4.1.3]
In this tutorial we are going to explore some of the Django Crispy Forms features to handle advanced/custom forms
rendering. This blog post started as a discussion in our community forum,
so I decided to compile the insights and solutions in a blog post to benefit a wider audience.
Table of Contents
Introduction
Installation
Basic Form Rendering
Basic Crispy Form Rendering
Custom Fields Placement with Crispy Forms
Crispy Forms Layout Helpers
Custom Crispy Field
Conclusions
Introduction
Throughout this tutorial we are going to implement the following Bootstrap 4 form using Django APIs:

This was taken from Bootstrap 4 official documentation
as an example of how to use form rows.
NOTE!
The examples below refer to a base.html template. Consider the code below:
base.html
<!doctype html>
<html lang="en">
<head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.1.3/css/bootstrap.min.css" integrity="sha384-MCw98/SFnGE8fJT3GXwEOngsV7Zt27NXFoaoApmYm81iuXoPkFOJwJ8ERdknLPMO" crossorigin="anonymous">
</head>
<body>
 <div class="container">
 {% block content %}
 {% endblock %}
 </div>
</body>
</html>




Installation
Install it using pip:
pip install django-crispy-forms


Add it to your INSTALLED_APPS and select which styles to use:
settings.py
INSTALLED_APPS = [
 ...

 'crispy_forms',
]

CRISPY_TEMPLATE_PACK = 'bootstrap4'


For detailed instructions about how to install django-crispy-forms, please refer to this tutorial:
How to Use Bootstrap 4 Forms With Django
Basic Form Rendering
The Python code required to represent the form above is the following:
from django import forms

STATES = (
 ('', 'Choose...'),
 ('MG', 'Minas Gerais'),
 ('SP', 'Sao Paulo'),
 ('RJ', 'Rio de Janeiro')
)

class AddressForm(forms.Form):
 email = forms.CharField(widget=forms.TextInput(attrs={'placeholder': 'Email'}))
 password = forms.CharField(widget=forms.PasswordInput())
 address_1 = forms.CharField(
 label='Address',
 widget=forms.TextInput(attrs={'placeholder': '1234 Main St'})
 )
 address_2 = forms.CharField(
 widget=forms.TextInput(attrs={'placeholder': 'Apartment, studio, or floor'})
 )
 city = forms.CharField()
 state = forms.ChoiceField(choices=STATES)
 zip_code = forms.CharField(label='Zip')
 check_me_out = forms.BooleanField(required=False)


In this case I’m using a regular Form, but it could also be a ModelForm based on a Django model with similar
fields. The state field and the STATES choices could be either a foreign key or anything else. Here I’m just using
a simple static example with three Brazilian states.
Template:
{% extends 'base.html' %}

{% block content %}
 <form method="post">
 {% csrf_token %}
 <table>{{ form.as_table }}</table>
 <button type="submit">Sign in</button>
 </form>
{% endblock %}


Rendered HTML:

Rendered HTML with validation state:

Basic Crispy Form Rendering
Same form code as in the example before.
Template:
{% extends 'base.html' %}

{% load crispy_forms_tags %}

{% block content %}
 <form method="post">
 {% csrf_token %}
 {{ form|crispy }}
 <button type="submit" class="btn btn-primary">Sign in</button>
 </form>
{% endblock %}


Rendered HTML:

Rendered HTML with validation state:

Custom Fields Placement with Crispy Forms
Same form code as in the first example.
Template:
{% extends 'base.html' %}

{% load crispy_forms_tags %}

{% block content %}
 <form method="post">
 {% csrf_token %}
 <div class="form-row">
 <div class="form-group col-md-6 mb-0">
 {{ form.email|as_crispy_field }}
 </div>
 <div class="form-group col-md-6 mb-0">
 {{ form.password|as_crispy_field }}
 </div>
 </div>
 {{ form.address_1|as_crispy_field }}
 {{ form.address_2|as_crispy_field }}
 <div class="form-row">
 <div class="form-group col-md-6 mb-0">
 {{ form.city|as_crispy_field }}
 </div>
 <div class="form-group col-md-4 mb-0">
 {{ form.state|as_crispy_field }}
 </div>
 <div class="form-group col-md-2 mb-0">
 {{ form.zip_code|as_crispy_field }}
 </div>
 </div>
 {{ form.check_me_out|as_crispy_field }}
 <button type="submit" class="btn btn-primary">Sign in</button>
 </form>
{% endblock %}


Rendered HTML:

Rendered HTML with validation state:

Crispy Forms Layout Helpers
We could use the crispy forms layout helpers to achieve the same result as above. The implementation is done inside
the form __init__ method:
forms.py
from django import forms
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Submit, Row, Column

STATES = (
 ('', 'Choose...'),
 ('MG', 'Minas Gerais'),
 ('SP', 'Sao Paulo'),
 ('RJ', 'Rio de Janeiro')
)

class AddressForm(forms.Form):
 email = forms.CharField(widget=forms.TextInput(attrs={'placeholder': 'Email'}))
 password = forms.CharField(widget=forms.PasswordInput())
 address_1 = forms.CharField(
 label='Address',
 widget=forms.TextInput(attrs={'placeholder': '1234 Main St'})
 )
 address_2 = forms.CharField(
 widget=forms.TextInput(attrs={'placeholder': 'Apartment, studio, or floor'})
 )
 city = forms.CharField()
 state = forms.ChoiceField(choices=STATES)
 zip_code = forms.CharField(label='Zip')
 check_me_out = forms.BooleanField(required=False)

 def __init__(self, *args, **kwargs):
 super().__init__(*args, **kwargs)
 self.helper = FormHelper()
 self.helper.layout = Layout(
 Row(
 Column('email', css_class='form-group col-md-6 mb-0'),
 Column('password', css_class='form-group col-md-6 mb-0'),
 css_class='form-row'
 ),
 'address_1',
 'address_2',
 Row(
 Column('city', css_class='form-group col-md-6 mb-0'),
 Column('state', css_class='form-group col-md-4 mb-0'),
 Column('zip_code', css_class='form-group col-md-2 mb-0'),
 css_class='form-row'
 ),
 'check_me_out',
 Submit('submit', 'Sign in')
 )


The template implementation is very minimal:
{% extends 'base.html' %}

{% load crispy_forms_tags %}

{% block content %}
 {% crispy form %}
{% endblock %}


The end result is the same.
Rendered HTML:

Rendered HTML with validation state:

Custom Crispy Field
You may also customize the field template and easily reuse throughout your application. Let’s say we want to use the
custom Bootstrap 4 checkbox:

From the official documentation, the necessary HTML to output the input above:
<div class="custom-control custom-checkbox">
 <input type="checkbox" class="custom-control-input" id="customCheck1">
 <label class="custom-control-label" for="customCheck1">Check this custom checkbox</label>
</div>


Using the crispy forms API, we can create a new template for this custom field in our “templates” folder:
custom_checkbox.html
{% load crispy_forms_field %}

<div class="form-group">
 <div class="custom-control custom-checkbox">
 {% crispy_field field 'class' 'custom-control-input' %}
 <label class="custom-control-label" for="{{ field.id_for_label }}">{{ field.label }}</label>
 </div>
</div>


Now we can create a new crispy field, either in our forms.py module or in a new Python module named fields.py
or something.
forms.py
from crispy_forms.layout import Field

class CustomCheckbox(Field):
 template = 'custom_checkbox.html'


We can use it now in our form definition:
forms.py
class CustomFieldForm(AddressForm):
 def __init__(self, *args, **kwargs):
 super().__init__(*args, **kwargs)
 self.helper = FormHelper()
 self.helper.layout = Layout(
 Row(
 Column('email', css_class='form-group col-md-6 mb-0'),
 Column('password', css_class='form-group col-md-6 mb-0'),
 css_class='form-row'
 ),
 'address_1',
 'address_2',
 Row(
 Column('city', css_class='form-group col-md-6 mb-0'),
 Column('state', css_class='form-group col-md-4 mb-0'),
 Column('zip_code', css_class='form-group col-md-2 mb-0'),
 css_class='form-row'
 ),
 CustomCheckbox('check_me_out'), # <-- Here
 Submit('submit', 'Sign in')
 )


(PS: the AddressForm was defined here and is the same as in the previous example.)
The end result:

Conclusions
There is much more Django Crispy Forms can do. Hopefully this tutorial gave you some extra insights on how to use the
form helpers and layout classes. As always, the official documentation is the best source of information:
Django Crispy Forms layouts docs
Also, the code used in this tutorial is available on GitHub at github.com/sibtc/advanced-crispy-forms-examples.

Advanced Form Rendering with Django Crispy Forms

In this tutorial you are going to learn how to implement Token-based authentication using Django REST Framework (DRF).
The token authentication works by exchanging username and password for a token that will be used in all subsequent
requests so to identify the user on the server side.
The specifics of how the authentication is handled on the client side vary a lot depending on the
technology/language/framework you are working with. The client could be a mobile application using iOS or Android.
It could be a desktop application using Python or C++. It could be a Web application using PHP or Ruby.
But once you understand the overall process, it’s easier to find the necessary resources and documentation for your
specific use case.
Token authentication is suitable for client-server applications, where the token is safely stored. You should never
expose your token, as it would be (sort of) equivalent of a handing out your username and password.
Table of Contents
Setting Up The REST API Project (If you already know how to start a DRF project you can skip this)
Implementing the Token Authentication
User Requesting a Token
Conclusions
Setting Up The REST API Project
So let’s start from the very beginning. Install Django and DRF:
pip install django
pip install djangorestframework


Create a new Django project:
django-admin.py startproject myapi .


Navigate to the myapi folder:
cd myapi


Start a new app. I will call my app core:
django-admin.py startapp core


Here is what your project structure should look like:
myapi/
 |-- core/
 | |-- migrations/
 | |-- __init__.py
 | |-- admin.py
 | |-- apps.py
 | |-- models.py
 | |-- tests.py
 | +-- views.py
 |-- __init__.py
 |-- settings.py
 |-- urls.py
 +-- wsgi.py
manage.py


Add the core app (you created) and the rest_framework app (you installed) to the INSTALLED_APPS, inside the
settings.py module:
myapi/settings.py
INSTALLED_APPS = [
 # Django Apps
 'django.contrib.admin',
 'django.contrib.auth',
 'django.contrib.contenttypes',
 'django.contrib.sessions',
 'django.contrib.messages',
 'django.contrib.staticfiles',

 # Third-Party Apps
 'rest_framework',

 # Local Apps (Your project's apps)
 'myapi.core',
]


Return to the project root (the folder where the manage.py script is), and migrate the database:
python manage.py migrate


Let’s create our first API view just to test things out:
myapi/core/views.py
from rest_framework.views import APIView
from rest_framework.response import Response

class HelloView(APIView):
 def get(self, request):
 content = {'message': 'Hello, World!'}
 return Response(content)


Now register a path in the urls.py module:
myapi/urls.py
from django.urls import path
from myapi.core import views

urlpatterns = [
 path('hello/', views.HelloView.as_view(), name='hello'),
]


So now we have an API with just one endpoint /hello/ that we can perform GET requests. We can use the browser to
consume this endpoint, just by accessing the URL http://127.0.0.1:8000/hello/:

We can also ask to receive the response as plain JSON data by passing the format parameter in the querystring like
http://127.0.0.1:8000/hello/?format=json:

Both methods are fine to try out a DRF API, but sometimes a command line tool is more handy as we can play more easily
with the requests headers. You can use cURL, which is widely available on all major
Linux/macOS distributions:
curl http://127.0.0.1:8000/hello/



But usually I prefer to use HTTPie, which is a pretty awesome Python command line tool:
http http://127.0.0.1:8000/hello/



Now let’s protect this API endpoint so we can implement the token authentication:
myapi/core/views.py
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.permissions import IsAuthenticated # <-- Here


class HelloView(APIView):
 permission_classes = (IsAuthenticated,) # <-- And here

 def get(self, request):
 content = {'message': 'Hello, World!'}
 return Response(content)


Try again to access the API endpoint:
http http://127.0.0.1:8000/hello/



And now we get an HTTP 403 Forbidden error. Now let’s implement the token authentication so we can access this
endpoint.
Implementing the Token Authentication
We need to add two pieces of information in our settings.py module. First include rest_framework.authtoken to
your INSTALLED_APPS and include the TokenAuthentication to REST_FRAMEWORK:
myapi/settings.py
INSTALLED_APPS = [
 # Django Apps
 'django.contrib.admin',
 'django.contrib.auth',
 'django.contrib.contenttypes',
 'django.contrib.sessions',
 'django.contrib.messages',
 'django.contrib.staticfiles',

 # Third-Party Apps
 'rest_framework',
 'rest_framework.authtoken', # <-- Here

 # Local Apps (Your project's apps)
 'myapi.core',
]

REST_FRAMEWORK = {
 'DEFAULT_AUTHENTICATION_CLASSES': [
 'rest_framework.authentication.TokenAuthentication', # <-- And here
 ],
}


Migrate the database to create the table that will store the authentication tokens:
python manage.py migrate



Now we need a user account. Let’s just create one using the manage.py command line utility:
python manage.py createsuperuser --username vitor --email vitor@example.com


The easiest way to generate a token, just for testing purpose, is using the command line utility again:
python manage.py drf_create_token vitor



This piece of information, the random string 9054f7aa9305e012b3c2300408c3dfdf390fcddf is what we are going to use
next to authenticate.
But now that we have the TokenAuthentication in place, let’s try to make another request to our /hello/ endpoint:
http http://127.0.0.1:8000/hello/



Notice how our API is now providing some extra information to the client on the required authentication method.
So finally, let’s use our token!
http http://127.0.0.1:8000/hello/ 'Authorization: Token 9054f7aa9305e012b3c2300408c3dfdf390fcddf'



And that’s pretty much it. For now on, on all subsequent request you should include the header Authorization: Token 9054f7aa9305e012b3c2300408c3dfdf390fcddf.
The formatting looks weird and usually it is a point of confusion on how to set this header. It will depend on the
client and how to set the HTTP request header.
For example, if we were using cURL, the command would be something like this:
curl http://127.0.0.1:8000/hello/ -H 'Authorization: Token 9054f7aa9305e012b3c2300408c3dfdf390fcddf'


Or if it was a Python requests call:
import requests

url = 'http://127.0.0.1:8000/hello/'
headers = {'Authorization': 'Token 9054f7aa9305e012b3c2300408c3dfdf390fcddf'}
r = requests.get(url, headers=headers)


Or if we were using Angular, you could implement an HttpInterceptor and set a header:
import { Injectable } from '@angular/core';
import { HttpRequest, HttpHandler, HttpEvent, HttpInterceptor } from '@angular/common/http';
import { Observable } from 'rxjs';

@Injectable()
export class AuthInterceptor implements HttpInterceptor {
 intercept(request: HttpRequest<any>, next: HttpHandler): Observable<HttpEvent<any>> {
 const user = JSON.parse(localStorage.getItem('user'));
 if (user && user.token) {
 request = request.clone({
 setHeaders: {
 Authorization: `Token ${user.accessToken}`
 }
 });
 }
 return next.handle(request);
 }
}




User Requesting a Token
The DRF provide an endpoint for the users to request an authentication token using their username and password.
Include the following route to the urls.py module:
myapi/urls.py
from django.urls import path
from rest_framework.authtoken.views import obtain_auth_token # <-- Here
from myapi.core import views

urlpatterns = [
 path('hello/', views.HelloView.as_view(), name='hello'),
 path('api-token-auth/', obtain_auth_token, name='api_token_auth'), # <-- And here
]


So now we have a brand new API endpoint, which is /api-token-auth/. Let’s first inspect it:
http http://127.0.0.1:8000/api-token-auth/



It doesn’t handle GET requests. Basically it’s just a view to receive a POST request with username and password.
Let’s try again:
http post http://127.0.0.1:8000/api-token-auth/ username=vitor password=123



The response body is the token associated with this particular user. After this point you store this token and apply
it to the future requests.
Then, again, the way you are going to make the POST request to the API depends on the language/framework you are using.
If this was an Angular client, you could store the token in the localStorage, if this was a Desktop CLI application
you could store in a text file in the user’s home directory in a dot file.
Conclusions
Hopefully this tutorial provided some insights on how the token authentication works. I will try to follow up this
tutorial providing some concrete examples of Angular applications, command line applications and Web clients as well.
It is important to note that the default Token implementation has some limitations such as only one token per user, no
built-in way to set an expiry date to the token.
You can grab the code used in this tutorial at github.com/sibtc/drf-token-auth-example.

How to Implement Token Authentication using Django REST Framework

<div class="info">
 Updated at Nov 8, 2018:
 New video added to the series: How to integrate Django forms with Bootstrap 4.
</div>

In this tutorial series, we are going to explore Django’s authentication system by implementing sign up, login, logout,
password change, password reset and protected views from non-authenticated users. This tutorial is organized in 8
videos, one for each topic, ranging from 4 min to 15 min each.

<ul>
 <li><a href="#setup">Setup</a></li>
 <li><a href="#sign-up">Sign Up</a></li>
 <li><a href="#login">Login</a></li>
 <li><a href="#logout">Logout</a></li>
 <li><a href="#password-change">Password Change</a></li>
 <li><a href="#password-reset">Password Reset</a></li>
 <li><a href="#protecting-views">Protecting Views</a></li>
 <li><a href="#bootstrap-4-forms">Bootstrap 4 Forms (Extra)</a></li>
 <li><a href="#conclusions">Conclusions</a></li>
</ul>

<hr />

<h4 id="setup">Setup</h4>

Starting a Django project from scratch, creating a virtual environment and an initial Django app. After that, we are
going to setup the templates and create an initial view to start working on the authentication.

If you are already familiar with Django, you can skip this video and jump to the <a href="#sign-up">Sign Up</a> tutorial below.

<iframe width="560" height="315" src="https://www.youtube.com/embed/60GTvKCuam8" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>

<hr />

<h4 id="sign-up">Sign Up</h4>

First thing we are going to do is implement a sign up view using the built-in <code class="highlighter-rouge">UserCreationForm</code>. In this video you
are also going to get some insights on basic Django form processing.

<iframe width="560" height="315" src="https://www.youtube.com/embed/9-ALutreCkE" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>

<hr />

<h4 id="login">Login</h4>

In this video tutorial we are going to first include the built-in Django auth URLs to our project and proceed to
implement the login view.

<iframe width="560" height="315" src="https://www.youtube.com/embed/R8yjsg0TlCI" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>

<hr />

<h4 id="logout">Logout</h4>

In this tutorial we are going to include Django logout and also start playing with conditional templates, displaying
different content depending if the user is authenticated or not.

<iframe width="560" height="315" src="https://www.youtube.com/embed/UtasCG2Eb7o" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>

<hr />

<h4 id="password-change">Password Change</h4>

Next The password change is a view where an authenticated user can change their password.

<iframe width="560" height="315" src="https://www.youtube.com/embed/mJkwKsSnWXo" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>

<hr />

<h4 id="password-reset">Password Reset</h4>

This tutorial is perhaps the most complicated one, because it involves several views and also sending emails. In this
video tutorial you are going to learn how to use the default implementation of the password reset process and how to
change the email messages.

<iframe width="560" height="315" src="https://www.youtube.com/embed/JBhpo0o1Ajg" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>

<hr />

<h4 id="protecting-views">Protecting Views</h4>

After implementing the whole authentication system, this video gives you an overview on how to protect some views from
non authenticated users by using the <code class="highlighter-rouge">@login_required</code> decorator and also using class-based views mixins.

<iframe width="560" height="315" src="https://www.youtube.com/embed/o0nvMYxBpRo" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>

<hr />

<h4 id="bootstrap-4-forms">Bootstrap 4 Forms</h4>

Extra video showing how to integrate Django with Bootstrap 4 and how to use Django Crispy Forms to render Bootstrap
forms properly. This video also include some general advices and tips about using Bootstrap 4.

<iframe width="560" height="315" src="https://www.youtube.com/embed/Sy8dVjJqLHI" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe>

<hr />

<h4 id="conclusions">Conclusions</h4>

If you want to learn more about Django authentication and some extra stuff related to it, like how to use Bootstrap
to make your auth forms look good, or how to write unit tests for your auth-related views, you can read the forth part
of my beginners guide to Django: <a href="/series/2017/09/25/a-complete-beginners-guide-to-django-part-4.html">A Complete Beginner’s Guide to Django - Part 4 - Authentication</a>.

Of course the official documentation is the best source of information: <a href="https://docs.djangoproject.com/en/2.1/topics/auth/default/">Using the Django authentication system</a>

The code used in this tutorial: <a href="https://github.com/sibtc/django-auth-tutorial-example">github.com/sibtc/django-auth-tutorial-example</a>

This was my first time recording this kind of content, so your feedback is highly appreciated. Please let me know what
you think!

And don’t forget to <a href="https://www.youtube.com/channel/UCS3lgmo8xYcOGTn_fv2mLgw?sub_confirmation=1">subscribe to my YouTube channel!</a>
I will post exclusive Django tutorials there. So stay tuned! :-)

Updated at Nov 8, 2018:
  New video added to the series: How to integrate Django forms with Bootstrap 4.


In this tutorial series, we are going to explore Django’s authentication system by implementing sign up, login, logout,
password change, password reset and protected views from non-authenticated users. This tutorial is organized in 8
videos, one for each topic, ranging from 4 min to 15 min each.
Setup
Sign Up
Login
Logout
Password Change
Password Reset
Protecting Views
Bootstrap 4 Forms (Extra)
Conclusions
Setup
Starting a Django project from scratch, creating a virtual environment and an initial Django app. After that, we are
going to setup the templates and create an initial view to start working on the authentication.
If you are already familiar with Django, you can skip this video and jump to the Sign Up tutorial below.




Sign Up
First thing we are going to do is implement a sign up view using the built-in UserCreationForm. In this video you
are also going to get some insights on basic Django form processing.




Login
In this video tutorial we are going to first include the built-in Django auth URLs to our project and proceed to
implement the login view.




Logout
In this tutorial we are going to include Django logout and also start playing with conditional templates, displaying
different content depending if the user is authenticated or not.




Password Change
Next The password change is a view where an authenticated user can change their password.




Password Reset
This tutorial is perhaps the most complicated one, because it involves several views and also sending emails. In this
video tutorial you are going to learn how to use the default implementation of the password reset process and how to
change the email messages.




Protecting Views
After implementing the whole authentication system, this video gives you an overview on how to protect some views from
non authenticated users by using the @login_required decorator and also using class-based views mixins.




Bootstrap 4 Forms
Extra video showing how to integrate Django with Bootstrap 4 and how to use Django Crispy Forms to render Bootstrap
forms properly. This video also include some general advices and tips about using Bootstrap 4.




Conclusions
If you want to learn more about Django authentication and some extra stuff related to it, like how to use Bootstrap
to make your auth forms look good, or how to write unit tests for your auth-related views, you can read the forth part
of my beginners guide to Django: A Complete Beginner’s Guide to Django - Part 4 - Authentication.
Of course the official documentation is the best source of information: Using the Django authentication system
The code used in this tutorial: github.com/sibtc/django-auth-tutorial-example
This was my first time recording this kind of content, so your feedback is highly appreciated. Please let me know what
you think!
And don’t forget to subscribe to my YouTube channel!
I will post exclusive Django tutorials there. So stay tuned! :-)

Django Authentication Video Tutorial

&quot;En-Rich&quot; your Python testing

Breaking up django-ninja views

Nullable DRF FloatFields and Javascript

A Tip About DRF Permissions

Custom Exceptions in Django REST Framework

How to Add Django Models to the Wagtail Admin

Using Different Read and Write Serializers in Django REST Framework

Keeping Django Models Ordered

Using Private Packages in Python

Optimized Python

Tips for Using Django&#x27;s ManyToManyField

Sentinel values in Python

Celery and Django and Docker: Oh My!

pytest support for django-test-plus

Django Birthday: Recap

Django Birthday Party

Improved Django Tests

Django Performance: 4 Simple Things

Wagtail 1.0 (beta) best Django CMS?

Loading Django FileField and ImageFields from the file system

Recommended Django Project Layout

Python Dev Tip: DRY your shell with PYTHONSTARTUP

Django Debugging Bookmarklet Trick

Django 1.3 is out - time to upgrade!

Two new Django classes: deployment and the ecosystem

Investing in Yourself - A review of Django 1.1 Testing and Debugging by Karen M. Tracey

Early registration for our Advanced Django class ends soon

Django Training in 2010

Django 1.0 Template Development Review

Django Training

Django Software Foundation

Fret Free -- Introduction to Django and the Django Software Foundation

A Brief Intro to Docker for Djangonauts

Python 3 run command over SSH

Python: atexit

Python 12-factor apps with envparse

Extend Django Templates Smartly

It's weekend and after a very busy week i am back in my home desk and navigating through my checklist. Though i had not put any priority on my checklist, my eye went to A Simple Django version for beginners. Frankly i forgot what was my real idea ove...

<![CDATA[It's weekend and after a very busy week i am back in my home desk and navigating through my checklist. Though i had not put any priority on my checklist, my eye went to <code>A Simple Django version for beginners</code>. Frankly i forgot what was my real idea over it, but i know few of them<ol><li>Running Django inside a single file</li><li>Simple file and folder structure</li></ol><h1 id="heading-running-django-inside-a-single-file">Running Django Inside a Single File</h1>I came up with my own solution from my stackoverflow answers. See Screenshot below.<img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1716061430465/99e8f4c8-8602-4e7f-8a9c-f789680d39d9.png" alt class="image--center mx-auto" />Reference: <a target="_blank" href="https://stackoverflow.com/a/59356081/7587197">https://stackoverflow.com/a/59356081/7587197</a>So looks like Django in a single file is possible. Here, your views and URLs are inside this same file, but we face problem when dealing with models inside this file since Django works on <code>App concept</code> and has its own guidelines on implementing apps like creating <code>apps.py</code> <code>models.py</code> <code>migrations package</code> and so onso now let's try to make it more readable and usable.<h1 id="heading-simple-file-and-folder-structure">Simple file and folder structure</h1>So, continuing from the single file solution, lets create couple of files to make the code readable. (I am assuming the root folder is <code>mdj</code>) so this means every files will stay inside it.<ol><li><code>urls.py</code><pre><code class="lang-python"> urlpatterns = []</code></pre></li><li><code>views.py</code> (empty file for now)</li><li><code>manage.py</code> (The main entry file)<pre><code class="lang-python"> import sys SETTINGS = dict( SECRET_KEY='djangoISsoCOOL', DEBUG=True, ROOT_URLCONF='urls', # so that it can denote urls.py INSTALLED_APPS=[], ) if __name__ == "__main__": import django from django.conf import settings from django.core.management import execute_from_command_line settings.configure(**SETTINGS) django.setup() execute_from_command_line(sys.argv)</code></pre> lets run this with command <code>python manage.py runserver</code> and it works. Now, lets create a simple page to check if view and urls works.</li></ol><pre><code class="lang-python"># views.pyfrom django.http import HttpResponsedef index(request): return HttpResponse("Hello, world.")</code></pre><pre><code class="lang-python"># urls.pyfrom django.urls import pathimport views # import the view# Todo for you : try with other import style as wellurlpatterns = [ path('', views.index),]</code></pre>Now, run the server again using <code>python manage.py runserver</code> and it works.<img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1716065180214/5b7afc54-a6b8-4da1-b8b1-c6b309952cfa.png" alt class="image--center mx-auto" />Now, let's make the model and database to work, but we will need to configure app for this, so create few files to configure<ol><li><code>apps.py</code><pre><code class="lang-python"> from django.apps import AppConfig # just a random name, MDJ=mini django class MDJConfig(AppConfig): name = 'mdj' # name of the root folder</code></pre></li><li><code>models.py</code></li><li><code>migrations package</code> (<code>migrations</code> folder and an empty <code>__init__.py</code> file)</li></ol>and register this apps config location on settings(<code>manage.py file</code>), <code>INSTALLED_APPS</code> as<pre><code class="lang-python"># manage.pySETTINGS = dict( ... INSTALLED_APPS=[ 'apps.MDJConfig', ], ...)</code></pre>Now, lets run the server using, and it did not work this time and we see the error as <code>ModuleNotFoundError: No module named 'mdj'</code> this means, the module, which we assumed to be the root of our project, is not being recognized. So, lets add out <code>root folder path</code> into <code>systems path</code> so that it can be recognized.Add these following in the <code>manage.py</code> file<pre><code class="lang-python">import sysfrom pathlib import Path# BASE_DIR = parent of manage.py fileBASE_DIR = Path(__file__).resolve().parent # this line will do the magicsys.path.append(str(BASE_DIR.parent))</code></pre>And now, run the server, and it works.now let's create our very first sample model<pre><code class="lang-python"># models.pyfrom django.db import modelsclass Sample(models.Model): name = models.CharField(max_length=100)</code></pre>Create migrations using command: <code>python manage.py makemigrations</code> and it works, the migration is created and placed under <code>migrations folder</code>Now, before applying migrations, configure database (<code>sqlite3 for demo</code>)<pre><code class="lang-python"># manage.pySETTINGS = dict( ... DATABASES={ 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': BASE_DIR / 'db.sqlite3', } } ...)</code></pre>and apply migrations using command <code>python manage.py migrate</code> and everything works, the database is created and the migrations are reflected in the database.Open up Django shell using command <code>python manage.py shell</code> to play with the model.<img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1716067810228/d7ebccd6-25a3-4061-96b2-0ceaf46d46f9.png" alt class="image--center mx-auto" />So, the final structure of the project will look like this,<ul><li>manage.py (core entry point contains settings as well)</li><li>urls.py (all urls for the project)</li><li>views.py (all view functions and classes for the project)</li><li>apps.py (app level configurations)</li><li>models.py (the model file which contains db related works)</li><li>migrations/__init__.py (<code>migrations</code> folder and the empty <code>__init__.py</code> file to store migrations when <code>python manage.py makemigrations</code> command is used)</li></ul>The final <code>manage.py</code> looks like this<pre><code class="lang-python">import sysfrom pathlib import PathBASE_DIR = Path(__file__).resolve().parentsys.path.append(str(BASE_DIR.parent))SETTINGS = dict( BASE_DIR=BASE_DIR, SECRET_KEY='djangoISsoCOOL', DEBUG=True, ROOT_URLCONF='urls', # so that it can denote urls.py INSTALLED_APPS=[ 'apps.MDJConfig', ], DATABASES={ 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': BASE_DIR / 'db.sqlite3', } })if __name__ == "__main__": import django from django.conf import settings from django.core.management import execute_from_command_line settings.configure(**SETTINGS) django.setup() execute_from_command_line(sys.argv)</code></pre><h1 id="heading-what-next">What next ?</h1><ol><li>Change <code>models</code> to <code>database</code> which can be done by changing <code>MODELS_MODULE_NAME</code> on <code>django/apps/config.py:10</code> Doing this, the app will now know it needs to load models from <code>database.py</code> file instead of <code>models.py</code></li><li>Changing <code>migrations</code> to <code>databasehistory.</code> To make this work series of changes needs to be done on <code>django.core.management.commands.makemigrations.py</code> file and <code>django.db.migrations.writer.MigrationWriter</code>. I still need to verify doing this myself, since i see lots of things are changed on Django core itself.</li><li>default app name should not be appended when creating table name for models. To make this work, changes are required on <code>django.db.models.options.Options.contribute_to_class</code> to not add <code>app_label</code> if <code>db_table</code> for model is not given</li><li>When (3) is fixed, root folder name can be changed to any without any problems. currently, root folder name is <code>mdj</code> which is hardcoded on some of the files</li><li>When performing all this fixes, create fix and patch it in runtime through <code>manage.py</code> file</li></ol>Find complete code at: <a target="_blank" href="https://github.com/shrawanx/mdj">https://github.com/shrawanx/mdj</a><h3 id="heading-at-the-end-i-feel-this-current-implementation-has-lots-and-lots-of-works-to-do-before-i-can-say-what-the-title-of-this-article-says-but-it-was-fun-trying-and-experimenting-happy-weekend">At the end, i feel this current implementation has lots and lots of works to do before i can say what the title of this article says, but it was fun trying and experimenting. Happy weekend</h3>]]>

A Simple Django version for beginners. Frankly i forgot what was my real idea over it, but i know few of them

Running Django inside a single file

Simple file and folder structure

Running Django Inside a Single File
I came up with my own solution from my stackoverflow answers. See Screenshot below.

Reference: https://stackoverflow.com/a/59356081/7587197
So looks like Django in a single file is possible. Here, your views and URLs are inside this same file, but we face problem when dealing with models inside this file since Django works on App concept and has its own guidelines on implementing apps like creating apps.py models.py migrations package and so on
so now let's try to make it more readable and usable.
Simple file and folder structure
So, continuing from the single file solution, lets create couple of files to make the code readable. (I am assuming the root folder is mdj) so this means every files will stay inside it.

urls.py
 urlpatterns = []

views.py (empty file for now)

manage.py (The main entry file)
 import sys SETTINGS = dict(     SECRET_KEY='djangoISsoCOOL',     DEBUG=True,     ROOT_URLCONF='urls',  # so that it can denote urls.py     INSTALLED_APPS=[], ) if __name__ == "__main__":     import django     from django.conf import settings     from django.core.management import execute_from_command_line     settings.configure(**SETTINGS)     django.setup()     execute_from_command_line(sys.argv)
 lets run this with command python manage.py runserver and it works. Now, lets create a simple page to check if view and urls works.

# views.pyfrom django.http import HttpResponsedef index(request):    return HttpResponse("Hello, world.")
# urls.pyfrom django.urls import pathimport views # import the view# Todo for you : try with other import style as wellurlpatterns = [    path('', views.index),]
Now, run the server again using python manage.py runserver and it works.

Now, let's make the model and database to work, but we will need to configure app for this, so create few files to configure

apps.py
 from django.apps import AppConfig # just a random name, MDJ=mini django class MDJConfig(AppConfig):     name = 'mdj' # name of the root folder

models.py

migrations package (migrations folder and an empty __init__.py file)

and register this apps config location on settings(manage.py file), INSTALLED_APPS as
# manage.pySETTINGS = dict(    ...    INSTALLED_APPS=[         'apps.MDJConfig',    ],    ...)
Now, lets run the server using, and it did not work this time and we see the error as ModuleNotFoundError: No module named 'mdj'
this means, the module, which we assumed to be the root of our project, is not being recognized. So, lets add out root folder path into systems path so that it can be recognized.
Add these following in the manage.py file
import sysfrom pathlib import Path# BASE_DIR = parent of manage.py fileBASE_DIR = Path(__file__).resolve().parent # this line will do the magicsys.path.append(str(BASE_DIR.parent))
And now, run the server, and it works.
now let's create our very first sample model
# models.pyfrom django.db import modelsclass Sample(models.Model):    name = models.CharField(max_length=100)
Create migrations using command: python manage.py makemigrations and it works, the migration is created and placed under migrations folder
Now, before applying migrations, configure database (sqlite3 for demo)
# manage.pySETTINGS = dict(    ...    DATABASES={        'default': {            'ENGINE': 'django.db.backends.sqlite3',            'NAME': BASE_DIR / 'db.sqlite3',        }    }    ...)
and apply migrations using command python manage.py migrate and everything works, the database is created and the migrations are reflected in the database.
Open up Django shell using command python manage.py shell to play with the model.

So, the final structure of the project will look like this,

manage.py (core entry point contains settings as well)

urls.py (all urls for the project)

views.py (all view functions and classes for the project)

apps.py (app level configurations)

models.py (the model file which contains db related works)

migrations/__init__.py (migrations folder and the empty __init__.py file to store migrations when python manage.py makemigrations command is used)

The final manage.py looks like this
import sysfrom pathlib import PathBASE_DIR = Path(__file__).resolve().parentsys.path.append(str(BASE_DIR.parent))SETTINGS = dict(    BASE_DIR=BASE_DIR,    SECRET_KEY='djangoISsoCOOL',    DEBUG=True,    ROOT_URLCONF='urls',  # so that it can denote urls.py    INSTALLED_APPS=[        'apps.MDJConfig',    ],    DATABASES={        'default': {            'ENGINE': 'django.db.backends.sqlite3',            'NAME': BASE_DIR / 'db.sqlite3',        }    })if __name__ == "__main__":    import django    from django.conf import settings    from django.core.management import execute_from_command_line    settings.configure(**SETTINGS)    django.setup()    execute_from_command_line(sys.argv)
What next ?

Change models to database which can be done by changing MODELS_MODULE_NAME on django/apps/config.py:10 Doing this, the app will now know it needs to load models from database.py file instead of models.py

Changing migrations to databasehistory. To make this work series of changes needs to be done on django.core.management.commands.makemigrations.py file and django.db.migrations.writer.MigrationWriter. I still need to verify doing this myself, since i see lots of things are changed on Django core itself.

default app name should not be appended when creating table name for models. To make this work, changes are required on django.db.models.options.Options.contribute_to_class to not add app_label if db_table for model is not given

When (3) is fixed, root folder name can be changed to any without any problems. currently, root folder name is mdj which is hardcoded on some of the files

When performing all this fixes, create fix and patch it in runtime through manage.py file

Find complete code at: https://github.com/shrawanx/mdj
At the end, i feel this current implementation has lots and lots of works to do before i can say what the title of this article says, but it was fun trying and experimenting. Happy weekend
]]>

Django in one file? Or should i call it a mini Django?

In Django, media files can be defined as those files which are uploaded by the users. For examples:

Profile Picture uploads
File Uploads and many more ...

Configurations
On our Django settings settings.py we add MEDIA_URL and MEDIA_ROOT settings
ME...

<![CDATA[In Django, media files can be defined as those files which are uploaded by the users. For examples:<ol><li>Profile Picture uploads</li><li>File Uploads and many more ...</li></ol><h4 id="heading-configurations">Configurations</h4>On our Django settings <code>settings.py</code> we add <code>MEDIA_URL</code> and <code>MEDIA_ROOT</code> settings<pre><code>MEDIA_URL='/media/'MEDIA_ROOT = BASE_DIR /'media'</code></pre>or <pre><code>MEDIA_ROOT = '/var/www/media/'</code></pre><blockquote>Note: <code>MEDIA_ROOT</code> is the folder where your file gets saved.</blockquote><h4 id="heading-creating-a-url-configurations-so-serve-uploaded-files">Creating a URL configurations so serve uploaded files</h4>In static files serving, Django would provide us with a way to serve static files automatically, But to serve the media files we will need to create a URL configurations to serve all media files from <code>MEDIA_ROOT</code><pre><code class="lang-py">from django.conf import settingsfrom django.conf.urls.static import staticurlpatterns = [ # rest of project url patterns]if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)</code></pre><blockquote>Note: we serve media files like this on local development environment only, on production servers we use a different approach. We serve these assets directly through the webserver.Just to try if everything is working, you can create a sample file(<code>image.jpg</code>) inside the <code>MEDIA_ROOT</code> directory, and check if Django is serving it at <code>/media/image.jpg</code></blockquote><h4 id="heading-simple-file-upload-in-django">Simple File Upload in Django</h4><ul><li>When files are submitted from HTML form to server, the file data can be accessed from <code>request.FILES</code> on Django views. <code>request.FILES</code> is a dict like object</li><li>Each key in <code>request.FILES</code> is the name from <code>&lt;input type="file" name=""&gt;</code></li><li>It's mandatory for the HTML forms to have the attribute <code>enctype="multipart/form-data"</code></li><li>Form must be submitted using <code>POST</code> method</li><li>Django has proper model fields <code>ImageField</code> and <code>FileField</code> for handling file uploads</li><li>These uploaded files are stored on filesystem <code>(MEDIA_ROOT)</code> and only the reference of file is stored in <code>ImageField</code> or <code>FileField</code> in Database. So basically these fields are abstraction created by Django to help us deal with file uploads but deep down they are just the <code>CharField</code> on database side</li></ul>Example: A basic file uploads, and handling the file uploads manually on the Django sideon HTML side,<pre><code>&lt;!-- image-uploads.html --&gt;&lt;form method="post" enctype="multipart/form-data"&gt; {% csrf_token %} &lt;input type="file" name="image"&gt; &lt;input type="submit" value="submit"&gt;&lt;/form&gt;</code></pre>on Django view side,<pre><code class="lang-py">from django.core.files.storage import FileSystemStoragefrom django.http import HttpResponsefrom django.shortcuts import renderdef image_upload(request): if request.method == 'POST' and request.FILES['image']: image = request.FILES['image'] fs = FileSystemStorage() # save the image on MEDIA_ROOT folder file_name = fs.save(image.name, image) # get file url with respect to `MEDIA_URL` file_url = fs.url(file_name) return HttpResponse(file_url) else: # render the form return render(request, "image-uploads.html")</code></pre>That't it, now we can process file uploads in Django, save it to the <code>MEDIA_ROOT</code> location automatically using <code>FileSystemStorage()</code> <blockquote>When using Django model and fields with <code>ImageFiled</code> or <code>FileField</code> we don't need to perform the file processing/saving manually like we did just now. Simply we would assign the file to the field, and call the model.save() method like we generally do. I will talk about it in detail in some other tutorial.</blockquote>]]>

Profile Picture uploads
File Uploads and many more ...

Configurations
On our Django settings settings.py we add MEDIA_URL and MEDIA_ROOT settings
MEDIA_URL='/media/'MEDIA_ROOT = BASE_DIR /'media'
or 
MEDIA_ROOT = '/var/www/media/'

Note: MEDIA_ROOT is the folder where your file gets saved.

Creating a URL configurations so serve uploaded files
In static files serving, Django would provide us with a way to serve static files automatically, But to serve the media files we will need to create a URL configurations to serve all media files from MEDIA_ROOT
from django.conf import settingsfrom django.conf.urls.static import staticurlpatterns = [ # rest of project url patterns]if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

Note: we serve media files like this on local development environment only, on production servers we use a different approach. We serve these assets directly through the webserver.
Just to try if everything is working, you can create a sample file(image.jpg) inside the MEDIA_ROOT directory, and check if Django is serving it at /media/image.jpg

Simple File Upload in Django

When files are submitted from HTML form to server, the file data can be accessed from request.FILES on Django views. request.FILES is a dict like object
Each key in request.FILES is the name from <input type="file" name="">
It's mandatory for the HTML forms to have the attribute enctype="multipart/form-data"
Form must be submitted using POST method
Django has proper model fields ImageField and FileField for handling file uploads
These uploaded files are stored on filesystem (MEDIA_ROOT) and only the reference of file is stored in ImageField or FileField in Database. So basically these fields are abstraction created by Django to help us deal with file uploads but deep down they are just the CharField on database side

Example: A basic file uploads, and handling the file uploads manually on the Django side
on HTML side,
<form method="post" enctype="multipart/form-data"> {% csrf_token %} <input type="file" name="image"> <input type="submit" value="submit"></form>
on Django view side,
from django.core.files.storage import FileSystemStoragefrom django.http import HttpResponsefrom django.shortcuts import renderdef image_upload(request): if request.method == 'POST' and request.FILES['image']: image = request.FILES['image'] fs = FileSystemStorage() # save the image on MEDIA_ROOT folder file_name = fs.save(image.name, image) # get file url with respect to `MEDIA_URL` file_url = fs.url(file_name) return HttpResponse(file_url) else: # render the form return render(request, "image-uploads.html")
That't it, now we can process file uploads in Django, save it to the MEDIA_ROOT location automatically using FileSystemStorage() 

When using Django model and fields with ImageFiled or FileField we don't need to perform the file processing/saving manually like we did just now. Simply we would assign the file to the field, and call the model.save() method like we generally do. I will talk about it in detail in some other tutorial.
]]>

Django Media Files

When we develop a web application we also need a way to use and serve static contents like (JS,CSS, and images ...)
In Django, any assets which are required for project development can be called static files. Some examples are:

JS files

CSS files

...

<![CDATA[When we develop a web application we also need a way to use and serve static contents like (JS,CSS, and images ...)In Django, any assets which are required for project development can be called static files. Some examples are:<ol><li>JS files</li><li>CSS files</li><li>Logo and banners which i need to show on webpage</li></ol><blockquote>These <code>static</code> files are put in place by developers rather than the user, User uploaded files like (profile picture, CV) are called <code>media</code> files in Django which we will talk in next tutorial</blockquote><h4 id="heading-configure-static-files-settings">Configure static files settings</h4><ul><li>Make sure <code>django.contrib.staticfiles</code> is included on <code>INSTALLED_APPS</code></li><li>In your <code>settings.py</code> file, add <code>STATIC_URL</code> (e.g.: STATIC_URL = '/static/')</li><li>Store your static files in folder called <code>static</code> inside your django app</li></ul>Apart from storing static files inside django app's <code>static</code> folder, we can also provide Django with list of other directories as well. To do that, we need to configure <code>STATICFILES_DIRS</code> on our <code>settings.py</code> file<pre><code class="lang-plaintext"># settings.pySTATICFILES_DIRS = [ BASE_DIR/"static", "/data/django-project/static-images/", "/var/www/static-django/"]</code></pre><h3 id="heading-linking-static-files-on-html-templates">Linking static files on HTML Templates</h3>Let's assume, <code>logo.jpg</code> exists in our app <code>static</code> folder (any app)Now, your HTML templates would look like,<pre><code>{% load static %}&lt;img src="{% static 'logo.jpg' %}"&gt;</code></pre><blockquote>If you run this template through Django (creating views and URLs) and inspect the HTML source of your page, you will see <code>&lt;img src="{% static 'logo.jpg' %}"</code> replaced by <code>&lt;img src="/static/logo.jpg"&gt;</code>. the <code>/static/</code> part that got appended in the URL is from the <code>STATIC_URL</code> settings we kept on our Django settings <code>(settings.py)</code></blockquote><h3 id="heading-serving-static-files">Serving static files</h3>We just linked our static file on the Templates, but we also need a way to serve those static files, e.g: when browsers requests to <code>/static/logo.jpg</code> then our Django server must send the logo.jpg as response.<ul><li>If we use <code>django.contrib.staticfiles</code> as explained above, <code>python manage.py runserver</code> command will automatically serve static files when <code>DEBUG</code> is set to True <code>[ DEBUG=True on settings.py ]</code></li></ul>So this means, we do not need to create a new URL or view to serve these static files, because Django does this for us<blockquote>This way is not suitable for production, and on production environment we don't user <code>runserver</code> instead we use some <code>wsgi</code> or <code>asgi</code> servers with some webservers like <code>nginx</code>. We we see more about it on Django deployments series.</blockquote><h4 id="heading-static-files-deployment-for-production-deployment-only">Static files Deployment (for production deployment only)</h4>On production environment, since as discussed earlier we don't use Django built in static file serving mechanism, so we need a way to gather and collect all static files from all the static folders into one single folder, so that we can deploy this folder or serve content from this folder.<code>django.contrib.staticfiles</code> provides a command for gathering static files from different applications of the project in a single directory so you can serve them easily. Steps:<ol><li>Set <code>STATIC_ROOT</code> on settings.py <code>(e.g: STATIC_ROOT='/home/static/')</code></li><li>Run <code>collectstatic</code> command <code>(python manage.py collectstatic)</code></li></ol>]]>

In Django, any assets which are required for project development can be called static files. Some examples are:

JS files

CSS files

Logo and banners which i need to show on webpage


These static files are put in place by developers rather than the user, User uploaded files like (profile picture, CV) are called media files in Django which we will talk in next tutorial

Configure static files settings

Make sure django.contrib.staticfiles is included on INSTALLED_APPS

In your settings.py file, add STATIC_URL (e.g.: STATIC_URL = '/static/')

Store your static files in folder called static inside your django app

Apart from storing static files inside django app's static folder, we can also provide Django with list of other directories as well. To do that, we need to configure STATICFILES_DIRS on our settings.py file
# settings.pySTATICFILES_DIRS = [ BASE_DIR/"static", "/data/django-project/static-images/", "/var/www/static-django/"]
Linking static files on HTML Templates
Let's assume, logo.jpg exists in our app static folder (any app)Now, your HTML templates would look like,
{% load static %}<img src="{% static 'logo.jpg' %}">

If you run this template through Django (creating views and URLs) and inspect the HTML source of your page, you will see <img src="{% static 'logo.jpg' %}" replaced by <img src="/static/logo.jpg">. the /static/ part that got appended in the URL is from the STATIC_URL settings we kept on our Django settings (settings.py)

Serving static files
We just linked our static file on the Templates, but we also need a way to serve those static files, e.g: when browsers requests to /static/logo.jpg then our Django server must send the logo.jpg as response.

If we use django.contrib.staticfiles as explained above, python manage.py runserver command will automatically serve static files when DEBUG is set to True [ DEBUG=True on settings.py ]

So this means, we do not need to create a new URL or view to serve these static files, because Django does this for us

This way is not suitable for production, and on production environment we don't user runserver instead we use some wsgi or asgi servers with some webservers like nginx. We we see more about it on Django deployments series.

Static files Deployment (for production deployment only)
On production environment, since as discussed earlier we don't use Django built in static file serving mechanism, so we need a way to gather and collect all static files from all the static folders into one single folder, so that we can deploy this folder or serve content from this folder.
django.contrib.staticfiles provides a command for gathering static files from different applications of the project in a single directory so you can serve them easily. Steps:

Set STATIC_ROOT on settings.py (e.g: STATIC_ROOT='/home/static/')

Run collectstatic command (python manage.py collectstatic)

]]>

Django Static Files

As the name suggests, Django views can also be written in Class based style. The major advantage of using Class based views in Django is

Code reusability and Clean Code

But, when creating a complex Class with lots of inheritance or mixins can make ...

<![CDATA[As the name suggests, Django views can also be written in Class based style. The major advantage of using Class based views in Django is<ul><li>Code reusability and Clean Code</li></ul>But, when creating a complex Class with lots of inheritance or mixins can make the situation hard to debug. To create a Class() based view we subclass <code>django.views.View</code><pre><code class="lang-PY">from django.views import Viewclass DashboardView(View): def get(self, request): # GET method pass def post(self, request): # POST method pass</code></pre>Converting examples from our function() based views to Class() based views<pre><code class="lang-py">from django.views import Viewfrom django.http impoty HttpResponseclass DashboardView(View): def get(self, request): # process view here return HttpResponse("Welcome to Dashboard")</code></pre><pre><code class="lang-py">#urls.pyurlpatterns = [ path('dashboard/', DashboardView),]# this will not work</code></pre>Since URL configurations expects callable function rather than class, we will use <code>.as_view()</code> class method of our View because <code>as_view()</code> returns a function to be used with URLs. This function does series of work for us,<ol><li>calls <code>setup()</code> method to initialize the attributes</li><li>calls <code>dispatch()</code> method which determines if request if <code>GET</code> or <code>POST</code> and send this request to corresponding request method </li></ol>So on our <code>urls.py</code> we do the following,<pre><code class="lang-py"># urls.py# import your view urlpatterns = [ path('dashboard/', DashboardView.as_view()),]</code></pre><h4 id="heading-capturing-url-values-in-class-based-views">Capturing URL values in Class() based views</h4>If you need to capture values from URL here at Class() based view, its similar to the function() based view, just add the new parameters(arguments) in your respective method. <pre><code>#urls.pyurlpatterns = [ path('profile/&lt;str:username&gt;/', ProfileView.as_view()),]</code></pre><pre><code class="lang-py">from django.views import Viewfrom django.http impoty HttpResponseclass ProfileView(View): def get(self, request, username): # process view here # get user info from DB using username return HttpResponse("My Profile")</code></pre><blockquote>Note: To make the development fast and easy, Django provides us with generic class based views as well majorly for performing C-R-U-D operations, which we will talk about in another tutorial <a target="_blank" href="https://docs.djangoproject.com/en/4.1/topics/class-based-views/generic-display/">See Django Docs for Generic class based views</a></blockquote>]]>

Code reusability and Clean Code

But, when creating a complex Class with lots of inheritance or mixins can make the situation hard to debug. 
To create a Class() based view we subclass django.views.View
from django.views import Viewclass DashboardView(View): def get(self, request): # GET method pass def post(self, request): # POST method pass
Converting examples from our function() based views to Class() based views
from django.views import Viewfrom django.http impoty HttpResponseclass DashboardView(View): def get(self, request): # process view here return HttpResponse("Welcome to Dashboard")
#urls.pyurlpatterns = [ path('dashboard/', DashboardView),]# this will not work
Since URL configurations expects callable function rather than class, we will use .as_view() class method of our View because as_view() returns a function to be used with URLs. This function does series of work for us,

calls setup() method to initialize the attributes
calls dispatch() method which determines if request if GET or POST and send this request to corresponding request method 

So on our urls.py we do the following,
# urls.py# import your view urlpatterns = [ path('dashboard/', DashboardView.as_view()),]
Capturing URL values in Class() based views
If you need to capture values from URL here at Class() based view, its similar to the function() based view, just add the new parameters(arguments) in your respective method. 
#urls.pyurlpatterns = [ path('profile/<str:username>/', ProfileView.as_view()),]
from django.views import Viewfrom django.http impoty HttpResponseclass ProfileView(View): def get(self, request, username): # process view here # get user info from DB using username return HttpResponse("My Profile")

Note: To make the development fast and easy, Django provides us with generic class based views as well majorly for performing C-R-U-D operations, which we will talk about in another tutorial See Django Docs for Generic class based views
]]>

Django Views - Class() based

When we talk about views in Django, views are the core part of Django which serves as the main place to process the incoming request.
Basically, we write out the view function in the views.py file, but we can write this function on a different file a...

<![CDATA[When we talk about views in Django, views are the core part of Django which serves as the main place to process the incoming request.Basically, we write out the view function in the <code>views.py</code> file, but we can write this function on a different file as well. We just need to map this function with our URL configuration.Creating a function based view is quite easy, we just need to create a normal python function with first parameter <code>request</code> as mandatory, because this parameter is the <code>Request Object</code> which we may need on our views. Request Objects contains various useful information about the requests like <code>request method</code> ,<code>request data</code> and so on.Also, this function based view must return an <code>HttpResponse</code> or its valid subclasses which is very important since a HTTP Response contains various information which Django configures automatically. Basic Example;<pre><code class="lang-py">from django.http import HttpResponsedef dashboard_view(request): # write your view processing logics here return HttpResponse("Welcome to Dashboard")</code></pre><blockquote>To return a template we use <code>render()</code> function instead of <code>HttpResponse()</code>, but if you look into the code of this shortcut <code>render()</code> function it uses <code>HttpResponse()</code> at the end. <a target="_blank" href="https://github.com/django/django/blob/main/django/shortcuts.py#L17-L25">Django Github : django.shortcuts.render()</a></blockquote><h3 id="heading-allow-only-specific-request-method-on-views">Allow only specific request method on views</h3>When we work with views, we sometime need a way to allow only specific request method like <code>GET</code> or <code>POST</code> according to our need. The basic way to perform this can be by doing if/else check on the view itself <pre><code class="lang-py">from django.http import HttpResponsedef dashboard_view(request): if request.method == 'GET' return HttpResponse("Welcome to Dashboard") else: # send status= 405 which means method not allowed return HttpResponse(status=405)</code></pre>But we can perform this with help of view decorator <code>require_http_methods</code><pre><code class="lang-py">from django.http import HttpResponsefrom django.views.decorators.http import require_http_methods@require_http_methods(["GET"])def dashboard_view(request): # only GET allowed return HttpResponse("Welcome to Dashboard")</code></pre><h4 id="heading-adding-extra-parameter-on-view-to-capture-url-values">Adding extra parameter on view to capture URL values</h4>If you are capturing values from URL then your view function should have parameter to accept this values<pre><code class="lang-py"># urls.pyurlpatterns = [ path('/profile/&lt;str:username&gt;/', user_profile_detail_view) # we used &lt;str&gt; path converter and assigned the value to username]</code></pre><pre><code class="lang-py"># views.pydef user_profile_detail_view(request, username): # do something with the username pass</code></pre>Have a detail read about URL design and URL values capturing at: <a target="_blank" href="https://djangotherightway.com/url-designing-and-url-kwargs-in-django">URL designing and URL kwargs in Django</a>]]>

Basically, we write out the view function in the views.py file, but we can write this function on a different file as well. We just need to map this function with our URL configuration.
Creating a function based view is quite easy, we just need to create a normal python function with first parameter request as mandatory, because this parameter is the Request Object which we may need on our views. Request Objects contains various useful information about the requests like request method ,request data and so on.
Also, this function based view must return an HttpResponse or its valid subclasses which is very important since a HTTP Response contains various information which Django configures automatically. 
Basic Example;
from django.http import HttpResponsedef dashboard_view(request): # write your view processing logics here return HttpResponse("Welcome to Dashboard")

To return a template we use render() function instead of HttpResponse(), but if you look into the code of this shortcut render() function it uses HttpResponse() at the end. Django Github : django.shortcuts.render()

Allow only specific request method on views
When we work with views, we sometime need a way to allow only specific request method like GET or POST according to our need. The basic way to perform this can be by doing if/else check on the view itself 
from django.http import HttpResponsedef dashboard_view(request): if request.method == 'GET' return HttpResponse("Welcome to Dashboard") else: # send status= 405 which means method not allowed return HttpResponse(status=405)
But we can perform this with help of view decorator require_http_methods
from django.http import HttpResponsefrom django.views.decorators.http import require_http_methods@require_http_methods(["GET"])def dashboard_view(request): # only GET allowed return HttpResponse("Welcome to Dashboard")
Adding extra parameter on view to capture URL values
If you are capturing values from URL then your view function should have parameter to accept this values
# urls.pyurlpatterns = [ path('/profile/<str:username>/', user_profile_detail_view) # we used <str> path converter and assigned the value to username]
# views.pydef user_profile_detail_view(request, username): # do something with the username pass
Have a detail read about URL design and URL values capturing at: URL designing and URL kwargs in Django
]]>

Django Views - function() based

I am a long fan and user of Cloudflare and with Cloudflare R2 i am more in love with cloudflare.
Cloudflare R2 is one of the amazing and interesting service that Cloudflare has released. It's called,

Rapid and Reliable Object Storage, minus the egre...

<![CDATA[I am a long fan and user of Cloudflare and with Cloudflare R2 i am more in love with cloudflare.Cloudflare R2 is one of the amazing and interesting service that Cloudflare has released. It's called,<blockquote>Rapid and Reliable Object Storage, minus the egress fees and gives you the freedom to create the multi-cloud architectures you desire with an S3-compatible distributed object storage.</blockquote>Which means, it's a object storage and the amazing part is egress charges is free.You can try and play around R2 for free with its free Monthly Quota and trust me the free limit will be enough to build an app, up and running easily.<h1 id="heading-grab-secret-keys-and-bucket-info-from-cloudflare">Grab secret keys and bucket info from Cloudflare</h1><ol><li>Creating a Bucket On Cloudflare Dashboard go to R2 and create a bucket<img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1657710796774/uwbjxupsQ.png" alt="cloudflare-r2-create-bucket.png" /><blockquote>Note: As of now, Buckets can only be private.</blockquote></li><li>Create API tokens to communicate with R2 Go to <code>Manage R2 API Tokens</code> from R2 Dashboard and create a API token which consist of <code>access_key</code> and <code>secret_key</code></li><li>Make sure you copy these to safe location<ul><li>Account ID : You can get it from the URL section, or from the bucket url or from the right most div on the R2 dashboard</li><li>Bucket name: You just created</li><li>Access key: You just obtained while creating API tokens</li><li>Secret Key: You just obtained while creating API tokens</li></ul></li></ol><h1 id="heading-implementing-on-django">Implementing on Django</h1>Since, R2 is compatible with S3 apis* we can easily use third party packages that are using S3 api for object storage.Let's install the required libraries<pre><code>pip install django-storagespip install boto3</code></pre>on Django <code>settings.py</code> add the following,<pre><code>DEFAULT_FILE_STORAGE = 'storages.backends.s3boto3.S3Boto3Storage'AWS_STORAGE_BUCKET_NAME = '&lt;YOUR_BUCKET_NAME&gt;'AWS_S3_ENDPOINT_URL = 'https://&lt;YOUR_ACCOUNT_ID&gt;.r2.cloudflarestorage.com'AWS_S3_ACCESS_KEY_ID = '&lt;YOUR_ACCESS_KEY&gt;'AWS_S3_SECRET_ACCESS_KEY = '&lt;YOUR_SECRET_KEY&gt;'AWS_S3_SIGNATURE_VERSION = 's3v4'</code></pre><blockquote>Make sure: signature version is <code>s3v4</code> since Cloudflare R2 doesn't support SigV2 and we need to explicitly set it to SigV4</blockquote>That's it, you can use Django freely with R2 now.<h4 id="heading-general-tipshelps">General Tips/Helps</h4><ol><li>Since, R2 currently supports Private bucket only, every object should be pre signed. Using <code>django-storages</code> with the above configurations does that to us automatically. In simple word it means <code>generating a presigned url for object</code></li><li>Since, a bucket cannot be made public as of now, i wouldn't suggest storing static files from Django on R2</li><li>Since Cloudflare R2 api is compatible with S3 api, we are able to use <code>boto3</code> and S3 API to communicate with R2</li><li>Public Buckets are currently in roadmap but not implemented. (I am really waiting and excited for this)</li><li>Learn more about R2 from Cloudflare docs at <a target="_blank" href="https://developers.cloudflare.com/r2/">https://developers.cloudflare.com/r2/</a></li></ol><h5 id="heading-tested-on">Tested on</h5><ul><li>Django==4.0.6</li><li>django-storages==1.12.3</li><li>boto3==1.24.28</li></ul>Last Updated: July 13, 2022]]>

Cloudflare R2 is one of the amazing and interesting service that Cloudflare has released. It's called,

Rapid and Reliable Object Storage, minus the egress fees and gives you the freedom to create the multi-cloud architectures you desire with an S3-compatible distributed object storage.

Which means, it's a object storage and the amazing part is egress charges is free.
You can try and play around R2 for free with its free Monthly Quota and trust me the free limit will be enough to build an app, up and running easily.
Grab secret keys and bucket info from Cloudflare

Creating a Bucket On Cloudflare Dashboard go to R2 and create a bucket


Note: As of now, Buckets can only be private.


Create API tokens to communicate with R2 Go to Manage R2 API Tokens from R2 Dashboard and create a API token which consist of access_key and secret_key

Make sure you copy these to safe location

Account ID : You can get it from the URL section, or from the bucket url or from the right most div on the R2 dashboard
Bucket name: You just created
Access key: You just obtained while creating API tokens
Secret Key: You just obtained while creating API tokens


Implementing on Django
Since, R2 is compatible with S3 apis* we can easily use third party packages that are using S3 api for object storage.
Let's install the required libraries
pip install django-storagespip install boto3
on Django settings.py add the following,
DEFAULT_FILE_STORAGE = 'storages.backends.s3boto3.S3Boto3Storage'AWS_STORAGE_BUCKET_NAME = '<YOUR_BUCKET_NAME>'AWS_S3_ENDPOINT_URL = 'https://<YOUR_ACCOUNT_ID>.r2.cloudflarestorage.com'AWS_S3_ACCESS_KEY_ID = '<YOUR_ACCESS_KEY>'AWS_S3_SECRET_ACCESS_KEY = '<YOUR_SECRET_KEY>'AWS_S3_SIGNATURE_VERSION = 's3v4'

Make sure: signature version is s3v4 since Cloudflare R2 doesn't support SigV2 and we need to explicitly set it to SigV4

That's it, you can use Django freely with R2 now.
General Tips/Helps

Since, R2 currently supports Private bucket only, every object should be pre signed. Using django-storages with the above configurations does that to us automatically. In simple word it means generating a presigned url for object
Since, a bucket cannot be made public as of now, i wouldn't suggest storing static files from Django on R2
Since Cloudflare R2 api is compatible with S3 api, we are able to use boto3 and S3 API to communicate with R2
Public Buckets are currently in roadmap but not implemented. (I am really waiting and excited for this)
Learn more about R2 from Cloudflare docs at https://developers.cloudflare.com/r2/

Tested on

Django==4.0.6
django-storages==1.12.3
boto3==1.24.28

Last Updated: July 13, 2022
]]>

Using Cloudflare R2 with Django for storage

Django under the hood provides an app called Admin a.k.a Django Admin, which provides Admin UI interface/web page for your Django Project. This admin interface can automatically generate CRUD views/ (form/tables) for your models with very minimal set...

<![CDATA[Django under the hood provides an app called Admin a.k.a Django Admin, which provides Admin UI interface/web page for your Django Project. This admin interface can automatically generate CRUD views/ (form/tables) for your models with very minimal setup i.e (Registering your models to admin)This Admin app is usually said to be one of the most powerful parts of DjangoLet's deep to use Django Admin on our projects<h3 id="heading-using-django-admin-registering-models">Using Django Admin/ Registering Models</h3><ol><li>Creating a test Model named Information<pre><code class="lang-py"> # inside your models.py file from django.db import models class Information(models.Model): name = models.CharField(max_length=100) date_of_birth = models.DateField() salary = models.IntegerField()</code></pre><blockquote>Don't forget to create migrations and then migrate </blockquote></li><li>Registering your models to Django Admin<ul><li>Open up <code>admin.py</code> file that exists in your app (when you create django app through <code>manage.py startapp [app]</code> command, you will automatically get this file along other files like <code>models.py</code> that we have been using)</li><li>To let Django Admin work for our models, we simply register our model class on this <code>admin.py</code> file, by using <code>admin.site.register()</code><pre><code class="lang-py">from django.contrib import adminfrom .models import Information # import your modeladmin.site.register(Information) # actual registration</code></pre></li></ul></li><li>Create Superuser to login to Django Admin<ul><li>Because Django also contains a built in Auth/User app which we can use to manage users and authentication, we can easily use this to create our superuser/login mechanism and everything works like a magic</li><li>You can always create a new <code>User</code> app and authentication process, but we will leave that for another tutorial</li><li>On your shell, run <code>python manage.py createsuperuser</code> command</li><li>This command will ask bunch of questions to fill up the <code>User table</code> with attributes <code>is_staff</code> and <code>is_superuser</code> set to True. This, attributes are the table columns</li><li>Django admin/UI login requires <code>is_staff</code> or <code>is_superuser</code> set to True for authorization</li><li>Which means, anyone, any user on our project can initiate login to the admin site but won't get access since other users <code>is_staff</code> and <code>is_superuser</code> are set to False<pre><code>-&gt; python manage.py createsuperuserUsername (leave blank to use 'djangotherightway'): adminEmail address: admin@example.comPassword: Password (again): Superuser created successfully.</code></pre></li></ul></li><li>login to Django Admin Site<ul><li>So, we completed our core process for working out with Django Admin, we now need a URL through which we can access our Admin Site</li><li>Register Admin urls to our <code>urls.py</code><pre><code>from django.contrib import adminfrom django.urls import pathurlpatterns = [ path('admin/', admin.site.urls),]</code></pre></li><li>Now, we can access our admin site through /admin/ url</li><li>I suggest to change this from <code>/admin/</code> to something unguessable, so as to prevent users from bruteforcing this page or accessing this page. In production environment, i usually disable this url path<blockquote>By default, when creating a project using <code>django-admin startproject [project]</code> command, Django will automatically do this for us</blockquote></li><li>Run your Django server using <code>python manage.py runserver</code> and navigate to <code>/admin/</code><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1648874387503/_bLy9801s.png" alt="djangotherightway-django-admin-login-page.png" /></li><li>Now, login using the credentials we just created on Step-3, and you will be able to see the model we registered on Step-2<img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1648874520555/aCXEBFZdH.png" alt="djangotherightway-django-admin-home-page.png" /></li><li>You can now, perform CRUD operations to your models, like add a new object/row, view all objects/rows, update and delete<blockquote>You may see that <code>Groups</code> and <code>Users</code> models are already registered on Django admin through we didn't do it manually. This is because this <code>Auth</code> app has already registered those models on its <code>admin.py</code> file. You can see the code on github <a target="_blank" href="https://github.com/django/django/blob/main/django/contrib/auth/admin.py">here</a></blockquote></li></ul></li></ol><h3 id="heading-customizing-django-admin-site">Customizing Django Admin Site</h3>Django admin site is super customizable, but we will see some basics so that you can get some idea about its customizations.Customizing Admin view for models can be done through <code>admin.ModelAdmin</code> class. We basically create a class using/subclassing <code>admin.ModelAdmin</code> and then tell Django admin to use this custom ModelAdmin while registering a model<ul><li><h4 id="heading-customize-table-display-field">Customize Table display field</h4><ul><li>When you see the table page for your models like from the above example, you will see something like this (assuming you have created two records/objects)<img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1648879239263/Z5KIPUxTN.png?w=1000&amp;h=800" alt="a.png" /></li><li>This table view doesn't look nice, so lets add some columns/fields on this table view using <code>list_display</code> attributes on <code>admin.ModelAdmin</code><pre><code class="lang-py"> # on your admin.py from django.contrib import admin from .models import Information class InformationAdmin(admin.ModelAdmin): list_display = ('name', 'date_of_birth', 'salary') admin.site.register(Information, InformationAdmin)</code></pre></li><li>Now, save the changes and run your server, you will see the table now has name, date_of_birth and salary fields </li><li><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1648879374910/t0eobZTuu.png?w=1000&amp;h=800" alt="django-admin1.png" /></li></ul></li></ul><ul><li><h4 id="heading-add-custom-fields-to-table-list-display">Add custom fields to table List Display</h4><ul><li>Let's create up <code>age</code> field obtained from <code>date_of_birth</code> and display it on the list display table fields <pre><code class="lang-py"> from django.contrib import admin from .models import Information class InformationAdmin(admin.ModelAdmin): list_display = ('name', 'date_of_birth', 'salary', 'age') @admin.display() def age(self, obj): # this is rough implementation of finding # out age from date of birth, so as to keep # this example as easy as possible from datetime import datetime current_year = datetime.today().year born_year = obj.date_of_birth.year return current_year - born_year</code></pre></li><li><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1648880272837/bFckMk2pV.png" alt="Screen Shot 2022-04-02 at 12.02.42.png" /></li></ul></li></ul><ul><li><h4 id="heading-adding-filters">Adding filters</h4><ul><li>We can use list_filters attribute to set filter fields<pre><code class="lang-py"> from django.contrib import admin from .models import Information class InformationAdmin(admin.ModelAdmin): list_filters=['date_of_birth'] admin.site.register(Information,InformationAdmin)</code></pre></li><li><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1648880969794/y1MbLDGsS.png" alt="django-admin-filters.png" /></li></ul></li></ul><blockquote>These were all basics things that we can do with Django Admin interface, but there are much more advance customizations available to use.</blockquote>If i should write more on advanced Customization, let me know in comments.]]>

Admin a.k.a Django Admin, which provides Admin UI interface/web page for your Django Project. This admin interface can automatically generate CRUD views/ (form/tables) for your models with very minimal setup i.e (Registering your models to admin)
This Admin app is usually said to be one of the most powerful parts of Django
Let's deep to use Django Admin on our projects
Using Django Admin/ Registering Models

Creating a test Model named Information
 # inside your models.py file from django.db import models class Information(models.Model):     name = models.CharField(max_length=100)     date_of_birth = models.DateField()     salary = models.IntegerField()

Don't forget to create migrations and then migrate 


Registering your models to Django Admin

Open up admin.py file that exists in your app (when you create django app through manage.py startapp [app] command, you will automatically get this file along other files like models.py that we have been using)

To let Django Admin work for our models, we simply register our model class on this admin.py file, by using admin.site.register()
from django.contrib import adminfrom .models import Information  # import your modeladmin.site.register(Information) # actual registration


Create Superuser to login to Django Admin

Because Django also contains a built in Auth/User app which we can use to manage users and authentication, we can easily use this to create our superuser/login mechanism and everything works like a magic
You can always create a new User app and authentication process, but we will leave that for another tutorial
On your shell, run python manage.py createsuperuser command
This command will ask bunch of questions to fill up the User table with attributes is_staff and is_superuser set to True. This, attributes are the table columns
Django admin/UI login requires is_staff or is_superuser set to True for authorization

Which means, anyone, any user on our project can initiate login to the admin site but won't get access since other users is_staff and is_superuser are set to False
-> python manage.py createsuperuserUsername (leave blank to use 'djangotherightway'): adminEmail address: admin@example.comPassword: Password (again): Superuser created successfully.


login to Django Admin Site

So, we completed our core process for working out with Django Admin, we now need a URL through which we can access our Admin Site

Register Admin urls to our urls.py
from django.contrib import adminfrom django.urls import pathurlpatterns = [  path('admin/', admin.site.urls),]

Now, we can access our admin site through /admin/ url
I suggest to change this from /admin/ to something unguessable, so as to prevent users from bruteforcing this page or accessing this page. In production environment, i usually disable this url path
By default, when creating a project using django-admin startproject [project] command, Django will automatically do this for us


Run your Django server using python manage.py runserver and navigate to /admin/

Now, login using the credentials we just created on Step-3, and you will be able to see the model we registered on Step-2

You can now, perform CRUD operations to your models, like add a new object/row, view all objects/rows, update and delete

You may see that Groups and Users models are already registered on Django admin through we didn't do it manually. This is because this Auth app has already registered those models on its admin.py file. You can see the code on github here



Customizing Django Admin Site
Django admin site is super customizable, but we will see some basics so that you can get some idea about its customizations.
Customizing Admin view for models can be done through admin.ModelAdmin class. We basically create a class using/subclassing admin.ModelAdmin  and then tell Django admin to use this custom ModelAdmin while registering a model

Customize Table display field

When you see the table page for your models like from the above example, you will see something like this (assuming you have created two records/objects)

This table view doesn't look nice, so lets add some columns/fields on this table view using list_display attributes on admin.ModelAdmin
  # on your admin.py   from django.contrib import admin  from .models import Information  class InformationAdmin(admin.ModelAdmin):      list_display = ('name', 'date_of_birth', 'salary')  admin.site.register(Information, InformationAdmin)

Now, save the changes and run your server, you will see the table now has name, date_of_birth and salary fields 




Add custom fields to table List Display

Let's create up age field obtained from date_of_birth and display it on the list display table fields 
  from django.contrib import admin  from .models import Information  class InformationAdmin(admin.ModelAdmin):      list_display = ('name', 'date_of_birth', 'salary', 'age')      @admin.display()      def age(self, obj):          # this is rough implementation of finding          # out age from date of birth, so as to keep          # this example as easy as possible          from datetime import datetime          current_year = datetime.today().year          born_year = obj.date_of_birth.year          return current_year - born_year





Adding filters

We can use list_filters attribute to set filter fields
  from django.contrib import admin  from .models import Information  class InformationAdmin(admin.ModelAdmin):      list_filters=['date_of_birth']  admin.site.register(Information,InformationAdmin)




These were all basics things that we can do with Django Admin interface, but there are much more advance customizations available to use.

If i should write more on advanced Customization, let me know in comments.
]]>

Django Admin (Registering Models, Customizing Admin Site)

Model Field Validation
To validate a model field on application level we can create up a validator which is a callable that take the value to be validated and raises error (ValidationError to be precise) if the value doesn't meet the criteria or it i...

<![CDATA[<h3 id="heading-model-field-validation">Model Field Validation</h3>To validate a model field on application level we can create up a <code>validator</code> which is a callable that take the value to be validated and raises error (<code>ValidationError</code> to be precise) if the value doesn't meet the criteria or it is invalidThe <code>ValidationError</code> it raises can be imported as <code>from django.core.exceptions import ValidationError</code><h4 id="heading-1-individual-field-validation">1. Individual Field validation</h4>We can add callable validators to our model field through <code>validators</code> argumentsLet's take a simple example of a model having a field <code>email</code> which requires <code>@djangotherightway.com</code> emails to be valid<pre><code class="lang-py">from django.core.exceptions import ValidationErrorfrom django.db import modelsdef django_the_right_way_email_validator(email): if not email.endswith('@djangotherightway.com'): raise ValidationError('Email must end with @djangotherightway.com')class Info(models.Model): email = models.EmailField( validators=[django_the_right_way_email_validator] )</code></pre><blockquote>You can add as many validator function/callables to a field</blockquote><h4 id="heading-2-validating-multiple-fields-together">2. Validating multiple fields together</h4>Sometime we come up for a need to validate two or more field together or are dependent on each other, in such scenario we can use <code>clean()</code> method provided by <code>models.Model</code>Let's add up simple requirements on our previous model example. Let's add up <code>phone_number</code> and <code>age</code> to our model, and imagine a situation where <code>phone_number</code> is required if <code>age&gt;20</code><pre><code class="lang-py">from django.core.exceptions import ValidationErrorfrom django.db import modelsdef django_the_right_way_email(email): if not email.endswith('@djangotherightway.com'): raise ValidationError('Email must end with @djangotherightway.com')class Info(models.Model): email = models.EmailField( validators=[django_the_right_way_email] ) # make phone nullable, since phone_number is # required only if age&gt;20 phone_number = models.CharField( max_length=10, null=True, blank=True ) age = models.IntegerField() def clean(self): if self.age &gt; 20: if not self.phone_number: raise ValidationError( 'Phone number is required if age is greater than 20' )</code></pre><h4 id="heading-running-validators">Running Validators</h4>These validators we created will not run automatically when you create/update object/row. To make this validators run, we need to call <code>full_clean()</code> method which under the hood runs all the validator<blockquote>Note: Validators run automatically when using <code>ModelForm</code></blockquote><pre><code class="lang-py"># this code can be on your view func or ...# ...for this example you can use django shell # Open Django shell using: python manage.py shellobj = Info()obj.email = "example@djangotherightway.com"obj.age = 21obj.phone_number = '1234567890'try: obj.full_clean()except ValidationError as e: print(e)else: obj.save()</code></pre><blockquote>Have a look into <a target="_blank" href="https://github.com/django/django/blob/main/django/db/models/base.py#L1397">full_clean() Django code:Github</a> where it runs all individual field validators like <code>django_the_right_way_email</code> in our case and even runs <code>clean()</code> method we implemented for validationsYou can call <code>full_clean()</code> from your models <code>save()</code> method, so that you don't have to manually call <code>full_clean()</code> everytime while validating objects, but this might bring up another issue of <code>full_clean()</code> being called two times in case using <code>ModelForm</code>.</blockquote><h3 id="heading-built-in-validators">Built-in validators</h3>Django already has a collection of validators used for general purpose that we can use openly as a function/callable validator to our <code>Model field</code> or <code>Forms</code> or you own data validationThese built-in validators can be imported from <code>django.core.validators</code> moduleSome list of commonly used built-in validators are <code>validate_email</code>, <code>validate_slug</code>, <code>validate_ipv4_address</code>, <code>validate_ipv6_address</code>, <code>int_list_validator</code>, <code>validate_image_file_extension</code> e.t.cA simple example to demonstrate use of built-in validators<pre><code class="lang-py">from django.db import modelsfrom django.core.validators import validate_emailclass Info(models.Model): # we didn't make email=models.EmailField() # because models.EmailField() would already contain # validate_email validator that checks for # valid email addresses email = models.CharField(validators=[validate_email])</code></pre><h3 id="heading-django-models-meta-class">Django models Meta class</h3>Model Meta class in Django is a way to provide some more information regarding <code>table_name</code> <code>whether model is abstract</code> <code>singular or plural names</code> <code>app_label</code> <code>ordering</code> and many more....<blockquote>Python metaclass is different than that of Django model meta class. Metaclass in Python are class factory where as meta class in Django is completely different which is used to provide additional information about a model to Django. Don't get confused on they sharing the same name during our <code>pronouncing</code> <code>speaking</code> <code>listening</code> but they are way different on writings.</blockquote><h4 id="heading-basic-example-of-creating-meta-options-class-in-django">Basic example of creating <code>Meta</code> options class in Django</h4>Django automatically create a <code>database table</code> for every models in the format of <code>{app_name}_{model_name}</code>, so lets customize this behaviour and provide it with a custom <code>table name</code><pre><code class="lang-py">from django.db import modelsclass Address(models.Model): name = models.CharField(max_length=100) class Meta: db_table = 'address'</code></pre>Now, when we create <code>migrations file</code> and run our migrations through <code>migrate</code> command, django will create a table named <code>address</code> instead of its default <code>{app_name}_address</code><h4 id="heading-available-models-meta-options">Available Models Meta Options</h4><ol><li>abstract<ul><li>if <code>abstract=True</code> this model will be a abstract model class</li></ul></li><li>db_table<ul><li>if <code>db_table</code> is set to a value, Django will take this value to create <code>database table</code> like we saw in previous example</li></ul></li><li>managed<ul><li>if <code>managed=True</code> (default behaviour) Django will create and manage database table for this model</li><li>if <code>managed=False</code> table is not created. This might be useful to integrate already existing table into Django</li></ul></li><li>ordering<ul><li>default ordering when retrieving list of objects/rows</li></ul></li><li>verbose_name<ul><li>Human readable name for the singular object</li></ul></li><li>verbose_name_plural<ul><li>Human readable plural name for the object</li></ul></li></ol><h3 id="heading-abstract-model-base-class-abstracttrue">Abstract Model Base class (abstract=True)</h3>Abstract model base class is also a model class which is used to place common <code>model fields</code> used in other models into a single model so that it can be used/inherited into other <code>model</code>. <ul><li>This type of model will not be used to create and <code>Database Table</code> by the <code>migrations framework</code></li><li>Since, this type of model doesn't create database table, we cannot perform any queries on this model</li><li>This type of models are inherited on other models to obtain features/fields from abstract model to normal model</li><li>So, this abstract base class is useful when you want to group common logics/fields of models into a single model but do not want to create it's corresponding database table</li></ul><h5 id="heading-lets-take-example-of-simple-information-abstract-base-class">Let's take example of simple <code>Information</code> abstract base class</h5><pre><code class="lang-py">from django.db import modelsclass InfoBase(models.Model): name = models.CharField(max_length=100) email = models.EmailField() class Meta: abstract = True</code></pre><h5 id="heading-lets-use-this-abstract-class-to-form-other-normal-model-class">Let's use this abstract class to form other normal model class</h5><pre><code class="lang-py">class User(InfoBase): address = models.CharField(max_length=100)</code></pre>So, the <code>User</code> model will now have fields <code>name</code> <code>email</code> <code>address</code>, where <code>name</code> and <code>email</code> is inherited from the <code>InfoBase</code> abstract model class<ol><li>Override fields in child model Some time, we may need to override some fields from the base class so that it gets changed in our child class. let's take an example we need to change <code>max_length</code> of name in <code>User</code>, we can do it by<pre><code class="lang-py">class User(InfoBase): name = models.CharField(max_length=50) # changed address = models.CharField(max_length=100)</code></pre></li><li>Remove/delete fields in child model Some time, there may occur a case when we need to delete/remove some fields in our child class, we can do it by simply overriding the fields with <code>None</code> value<pre><code class="lang-py">class User(InfoBase): name = models.CharField(max_length=50) email = None address = models.CharField(max_length=100)</code></pre> So, considering this example, <code>User</code> model will only have <code>name</code> and <code>address</code> fields</li></ol>]]>

To validate a model field on application level we can create up a validator which is a callable that take the value to be validated and raises error (ValidationError to be precise) if the value doesn't meet the criteria or it is invalid
The ValidationError it raises can be imported as from django.core.exceptions import ValidationError
1. Individual Field validation
We can add callable validators to our model field through validators arguments
Let's take a simple example of a model having a field email which requires @djangotherightway.com emails to be valid
from django.core.exceptions import ValidationErrorfrom django.db import modelsdef django_the_right_way_email_validator(email):    if not email.endswith('@djangotherightway.com'):        raise ValidationError('Email must end with @djangotherightway.com')class Info(models.Model):    email = models.EmailField(        validators=[django_the_right_way_email_validator]    )

You can add as many validator function/callables to a field

2. Validating multiple fields together
Sometime we come up for a need to validate two or more field together or are dependent on each other, in such scenario we can use clean() method provided by models.Model
Let's add up simple requirements on our previous model example. Let's add up phone_number and age to our model, and imagine a situation where phone_number is required if age>20
from django.core.exceptions import ValidationErrorfrom django.db import modelsdef django_the_right_way_email(email):    if not email.endswith('@djangotherightway.com'):        raise ValidationError('Email must end with @djangotherightway.com')class Info(models.Model):    email = models.EmailField(        validators=[django_the_right_way_email]    )    # make phone nullable, since phone_number is    # required only if age>20    phone_number = models.CharField(        max_length=10, null=True, blank=True    )    age = models.IntegerField()    def clean(self):        if self.age > 20:            if not self.phone_number:                raise ValidationError(                    'Phone number is required if age is greater than 20'                )
Running Validators
These validators we created will not run automatically when you create/update object/row. To make this validators run, we need to call full_clean() method which under the hood runs all the validator

Note: Validators run automatically when using ModelForm

# this code can be on your view func or ...# ...for this example you can use django shell #  Open Django shell using: python manage.py shellobj = Info()obj.email = "example@djangotherightway.com"obj.age = 21obj.phone_number = '1234567890'try:    obj.full_clean()except ValidationError as e:    print(e)else:    obj.save()

Have a look into full_clean() Django code:Github where it runs all individual field validators like django_the_right_way_email in our case and even runs clean() method we implemented for validations
You can call full_clean() from your models save() method, so that you don't have to manually call full_clean() everytime while validating objects, but this might bring up another issue of full_clean() being called two times in case using ModelForm.

Built-in validators
Django already has a collection of validators used for general purpose that we can use openly as a function/callable validator to our Model field or Forms or you own data validation
These built-in validators can be imported from django.core.validators module
Some list of commonly used built-in validators are validate_email, validate_slug, validate_ipv4_address, validate_ipv6_address, int_list_validator, validate_image_file_extension e.t.c
A simple example to demonstrate use of built-in validators
from django.db import modelsfrom django.core.validators import validate_emailclass Info(models.Model):    # we didn't make email=models.EmailField()     #  because models.EmailField() would already contain    #  validate_email validator that checks for     #  valid email addresses    email = models.CharField(validators=[validate_email])
Django models Meta class
Model Meta class in Django is a way to provide some more information regarding table_name whether model is abstract singular or plural names app_label ordering and many more....

Python metaclass is different than that of Django model meta class. Metaclass in Python are class factory where as meta class in Django is completely different which is used to provide additional information about a model to Django. Don't get confused on they sharing the same name during our pronouncing speaking listening but they are way different on writings.

Basic example of creating Meta options class in Django
Django automatically create a database table for every models in the format of {app_name}_{model_name}, so lets customize this behaviour and provide it with a custom table name
from django.db import modelsclass Address(models.Model):    name = models.CharField(max_length=100)    class Meta:        db_table = 'address'
Now, when we create migrations file and run our migrations through migrate command, django will create a table named address instead of its default {app_name}_address
Available Models Meta Options

abstract
if abstract=True this model will be a abstract model class

db_table
if db_table is set to a value, Django will take this value to create database table like we saw in previous example

managed
if managed=True (default behaviour) Django will create and manage database table for this model
if managed=False table is not created. This might be useful to integrate already existing table into Django

ordering
default ordering when retrieving list of objects/rows

verbose_name
Human readable name for the singular object

verbose_name_plural
Human readable plural name for the object


Abstract Model Base class (abstract=True)
Abstract model base class is also a model class which is used to place common model fields used in other models into a single model so that it can be used/inherited into other model. 

This type of model will not be used to create and Database Table by the migrations framework
Since, this type of model doesn't create database table, we cannot perform any queries on this model
This type of models are inherited on other models to obtain features/fields from abstract model to normal model
So, this abstract base class is useful when you want to group common logics/fields of models into a single model but do not want to create it's corresponding database table

Let's take example of simple Information abstract base class
from django.db import modelsclass InfoBase(models.Model):    name = models.CharField(max_length=100)    email = models.EmailField()    class Meta:        abstract = True
Let's use this abstract class to form other normal model class
class User(InfoBase):    address = models.CharField(max_length=100)
So, the User model will now have fields name email address, where name and email is inherited from the InfoBase abstract model class

Override fields in child model 
 Some time, we may need to override some fields from the base class so that it gets changed in our child class. let's take an example we need to change max_length of name in User, we can do it by
class User(InfoBase):     name = models.CharField(max_length=50) # changed     address = models.CharField(max_length=100)

Remove/delete fields in child model
  Some time, there may occur a case when we need to delete/remove some fields in our child class, we can do it by simply overriding the fields with None value
class User(InfoBase):     name = models.CharField(max_length=50)     email = None     address = models.CharField(max_length=100)
 So, considering this example, User model will only have name and address fields

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Django Models Part 4 (Model validation, Model Meta, Abstract Model class)

Model Manager

A Manager is the interface through which we perform ORMs in Django models
By Default, Django automatically adds a Manager with a name of objects. This is the reason we are able to use objects and query to our Models eg: Model.objects.a...

<![CDATA[<h3 id="heading-model-manager">Model Manager</h3><ul><li>A <code>Manager</code> is the interface through which we perform ORMs in Django models</li><li>By Default, Django automatically adds a <code>Manager</code> with a name of <code>objects</code>. This is the reason we are able to use <code>objects</code> and query to our Models <code>eg: Model.objects.all()</code></li><li>We can always create a new Manager and add to our model. We can customize ORM methods or add some more functionality in our Manager for data query</li><li>Atleast one Manager should exist in every models</li></ul>Example to change rename default <code>objects</code> in our model<pre><code class="lang-py">from django.db import modelsclass Info(models.Model): name = models.CharField(max_length=100) data = models.Manager()# Info.objects.all() will not work but Info.data.all() will work</code></pre><h3 id="heading-queryset">QuerySet</h3><ul><li>QuerySet can be defined as a collection of Objects (model objects)</li><li>Until and unless you do something to evaluate a QuerySet <code>(loop, slice with increments,...)</code>, it doesn't hit your database. So, we call it by saying QuerSet is Lazy</li></ul><h4 id="heading-lets-take-an-example-of-basic-model-which-we-will-be-using-in-this-tutorial">Let's take an example of basic model which we will be using in this tutorial</h4><ul><li>All, methods, customizations will be done on basis of this model below</li></ul><pre><code class="lang-py">from django.db import modelsclass User(models.Model): name = models.CharField(max_length=100) age = models.IntegerField()</code></pre><h4 id="heading-queryset-methods">QuerySet Methods</h4><ol><li>filter()<ul><li>Returns a new QuerySet, list of objects that matches the given lookup criteria</li><li>To return list of <code>users</code> whose <code>age</code>=10, we can do <code>User.objects.filter(age=10)</code>;<pre><code class="lang-py">qs = User.objects.filter(age=10)for u in qs:print(u.name, u.age)</code></pre></li><li>Multiple arguments are joined by <code>AND</code> clause when crafting an SQL query</li><li>So, <code>User.objects.filter(age=10, name="John")</code> will return list of <code>users</code> whose <code>age</code> is <code>10</code> <code>AND</code> whose <code>name</code> is <code>John</code></li><li>If you need to join arguments with <code>OR</code> you can use <code>Q</code> objects. e.g. This example will return list of users whose name is <code>John</code> <code>OR</code> <code>Harry</code> <pre><code class="lang-py">from django.db.models import Qqs = User.objects.filter(Q(name='John') | Q(name='Harry'))</code></pre></li></ul></li><li>exclude()<ul><li>Returns a new Queryset, list of objects that do not match the given lookup criteria</li><li>Same like <code>filter()</code> multiple arguments/parameters are joined by <code>AND</code> clause</li><li><code>User.objects.exclude(age=20)</code> will return list of users whose <code>age</code> is not <code>20</code></li></ul></li><li>order_by()<ul><li>Used to perform some ordering for the return QuerySet list</li><li>If you have set default ordering for your models, you don't even have to use this method to order your <code>QuerySet</code>, because the results returned by <code>QuerySet</code> are ordered automatically by the ordering tuple given by the <code>ordering</code> option in models <code>Meta</code><pre><code class="lang-py">class User(models.Model): name = models.CharField(max_length=100) age = models.IntegerField() class Meta: ordering = ['-age'] # - negative sign for descending order and # no sign for asc order</code></pre></li><li><code>User.objects.filter(age=10)</code> on this model will return the list of users whose <code>age</code> is <code>10</code> in descending order of <code>age</code></li><li><code>User.objects.filter(age=10).order_by('age')</code> on this model will return the list of users whose <code>age</code> is <code>10</code> in ascending order of <code>age</code></li><li><code>User.objects.order_by('-name')</code> will return list of users in descending order</li></ul></li></ol><ol><li>none()<ul><li>Calling <code>none()</code> will create a <code>QuerySet</code> that will never return any objects</li><li>This doesn't return any data, so this can be used in place where we need a valid <code>QuerySet</code> but no data</li><li>calling <code>none()</code> will not hit database</li><li>e.g <code>User.objects.none()</code></li></ul></li><li>all()<ul><li>This method is the simplest way to retrieve all objects from the model</li><li><code>User.objects.all()</code> will return list of every users/objects</li></ul></li></ol><h4 id="heading-database-orm-methods-which-do-not-return-a-queryset">Database ORM methods which do not return a QuerySet</h4><ol><li>get()<ul><li><code>User.objects.get(id=1)</code> will return the row/object whose <code>id</code> is <code>1</code></li></ul></li><li>create()<ul><li><code>User.objects.create(name="Peter",age=25)</code> will create a new object/record in database and return that object</li></ul></li><li>first()<ul><li><code>User.objects.filter(id=10).first()</code> will return the first row/object whose <code>id</code> is <code>10</code></li></ul></li><li>last()<ul><li><code>User.objects.filter(id=10).last()</code> will return the last row/object whose <code>id</code> is <code>10</code></li></ul></li><li>delete()<ul><li><code>User.objects.filter(id=10).delete()</code> will delete objects/rows whose <code>id</code> is <code>10</code>. This works like a bulk delete</li><li>You can also perform <code>delete()</code> on model single objects like the objects obtained from <code>get()</code> <code>first()</code> <code>last()</code> methods. This works like a single object delete</li></ul></li><li>count()<ul><li><code>User.objects.filter(id=10).count()</code> will return total number of users/objects whose <code>id</code> is <code>10</code></li></ul></li></ol><h3 id="heading-field-lookups">Field Lookups</h3><ul><li>Field lookups are used to specify meaning to the SQL <code>WHERE</code> clause</li><li>These lookups are crafted and attached with the fields when performing an ORM queries</li><li>It looks like<ul><li><code>field_[LookupType]=value</code> [note the double underscores]</li></ul></li></ul><h4 id="heading-lookups-types">Lookups Types</h4><ol><li>exact (also a default lookup)<ul><li>An exact Match</li><li><code>User.objects.filter(name__exact="Peter")</code> would generate <code>SQL: select .... where name="Peter"</code> and returns the objects/rows whose name is <code>Peter</code><blockquote>If we do not provide a lookup like in the above <code>QuerySet</code> method examples, Django automatically uses <code>exact</code> lookup. This is the reason our ORMs were working even when we didn't pass any lookups</blockquote></li><li>Thus, <code>User.objects.filter(name__exact="Peter")</code> and <code>User.objects.filter(name="Peter")</code> QuerySet is practically the same</li></ul></li><li>iexact<ul><li>Case insensitive match</li><li><code>User.objects.filter(name__iexact="peter")</code> would return QuerySet of the list of users whose name is <code>peter(case insensitive)</code> i.e: <code>peter</code>, <code>Peter</code>, <code>PeTeR</code>, <code>peteR</code> e.t.c</li></ul></li><li>contains<ul><li>Case sensitive containment</li><li><code>User.objects.filter(name__contains="a")</code> would generate <code>SQL: select ..... where name like '%a%'</code> and would return QuerySet of list of users whose <code>name</code> contains/includes <code>a</code></li></ul></li><li>icontains<ul><li>Similar to <code>contains</code> but case-insensitive</li></ul></li><li>gt<ul><li>greater than </li><li><code>User.objects.filter(age_gt=10)</code> would return QuerySet of list of users whose age is greater than 10 i.e 11,12,13,.......</li></ul></li><li>gte<ul><li>greater than or equal to</li><li><ul><li><code>User.objects.filter(age_gte=10)</code> would return QuerySet of list of users whose age is greater than or equals to 10 i.e 10,11,12,13,.......</li></ul></li></ul></li><li>lt<ul><li>less than </li><li><code>User.objects.filter(age_lt=10)</code> would return QuerySet of list of users whose age is less than 10 i.e 9,8,7,......</li></ul></li><li>lte<ul><li>less than or equal to</li><li><ul><li><code>User.objects.filter(age_lte=10)</code> would return QuerySet of list of users whose age is less than or equals to 10 i.e 10,9,8,7,.....</li></ul></li></ul></li></ol><blockquote>There are other plenty of inbuilts lookups. To name some of them; <code>in</code> <code>startswith</code> <code>istartswith</code> <code>range</code> </blockquote>]]>

A Manager is the interface through which we perform ORMs in Django models
By Default, Django automatically adds a Manager with a name of objects. This is the reason we are able to use objects and query to our Models eg: Model.objects.all()
We can always create a new Manager and add to our model. We can customize ORM methods or add some more functionality in our Manager for data query
Atleast one Manager should exist in every models

Example to change rename default objects in our model
from django.db import modelsclass Info(models.Model):    name = models.CharField(max_length=100)    data = models.Manager()# Info.objects.all() will not work but Info.data.all() will work
QuerySet

QuerySet can be defined as a collection of Objects (model objects)
Until and unless you do something to evaluate a QuerySet (loop, slice with increments,...), it doesn't hit your database. So, we call it by saying QuerSet is Lazy

Let's take an example of basic model which we will be using in this tutorial

All, methods, customizations will be done on basis of this model below

from django.db import modelsclass User(models.Model):    name = models.CharField(max_length=100)    age = models.IntegerField()
QuerySet Methods

filter()

Returns a new QuerySet, list of objects that matches the given lookup criteria
To return list of users whose age=10, we can do User.objects.filter(age=10);
qs = User.objects.filter(age=10)for u in qs:print(u.name, u.age)

Multiple arguments are joined by AND clause when crafting an SQL query
So, User.objects.filter(age=10, name="John") will return list of users whose age is 10 AND whose name is John
If you need to join arguments with OR you can use Q objects. e.g. This example will return list of users whose name is John OR Harry 
from django.db.models import Qqs = User.objects.filter(Q(name='John') | Q(name='Harry'))


exclude()

Returns a new Queryset, list of objects that do not match the given lookup criteria
Same like filter() multiple arguments/parameters are joined by AND clause
User.objects.exclude(age=20) will return list of users whose age is not 20


order_by()

Used to perform some ordering for the return QuerySet list

If you have set default ordering for your models, you don't even have to use this method to order your QuerySet, because the results returned by QuerySet are ordered automatically by the ordering tuple given by the ordering option in models Meta
class User(models.Model):  name = models.CharField(max_length=100)  age = models.IntegerField()  class Meta:      ordering = ['-age'] # - negative sign for descending order and                      # no sign for asc order

User.objects.filter(age=10) on this model will return the list of users whose age is 10 in descending order of age
User.objects.filter(age=10).order_by('age') on this model will return the list of users whose age is 10 in ascending order of age
User.objects.order_by('-name') will return list of users in descending order



none()

Calling none() will create a QuerySet that will never return any objects
This doesn't return any data, so this can be used in place where we need a valid QuerySet but no data
calling none() will not hit database
e.g User.objects.none()


all()

This method is the simplest way to retrieve all objects from the model
User.objects.all() will return list of every users/objects


Database ORM methods which do not return a QuerySet

get()
User.objects.get(id=1) will return the row/object whose id is 1

create()
User.objects.create(name="Peter",age=25) will create a new object/record in database and return that object

first()
User.objects.filter(id=10).first() will return the first row/object whose id is 10

last()
User.objects.filter(id=10).last() will return the last row/object whose id is 10

delete()
User.objects.filter(id=10).delete() will delete objects/rows whose id is 10. This works like a bulk delete
You can also perform delete() on model single objects like the objects obtained from get() first() last() methods. This works like a single object delete

count()
User.objects.filter(id=10).count() will return total number of users/objects whose id is 10


Field Lookups

Field lookups are used to specify meaning to the SQL WHERE clause
These lookups are crafted and attached with the fields when performing an ORM queries
It looks like
field_[LookupType]=value [note the double underscores]


Lookups Types

exact (also a default lookup)

An exact Match
User.objects.filter(name__exact="Peter") would generate SQL: select .... where name="Peter" and returns the objects/rows whose name is Peter
If we do not provide a lookup like in the above QuerySet method examples, Django automatically uses exact lookup. This is the reason our ORMs were working even when we didn't pass any lookups

Thus, User.objects.filter(name__exact="Peter") and User.objects.filter(name="Peter") QuerySet is practically the same


iexact

Case insensitive match
User.objects.filter(name__iexact="peter") would return QuerySet of the list of users whose name is peter(case insensitive) i.e: peter, Peter, PeTeR, peteR e.t.c


contains

Case sensitive containment
User.objects.filter(name__contains="a") would generate SQL: select ..... where name like '%a%' and would return QuerySet of list of users whose name contains/includes a


icontains

Similar to contains but case-insensitive


gt

greater than 
User.objects.filter(age_gt=10) would return QuerySet of list of users whose age is greater than 10 i.e 11,12,13,.......


gte

greater than or equal to

User.objects.filter(age_gte=10) would return QuerySet of list of users whose age is greater than or equals to 10 i.e 10,11,12,13,.......



lt

less than 
User.objects.filter(age_lt=10) would return QuerySet of list of users whose age is less than 10 i.e 9,8,7,......


lte

less than or equal to

User.objects.filter(age_lte=10) would return QuerySet of list of users whose age is less than or equals to 10 i.e 10,9,8,7,.....



There are other plenty of inbuilts lookups. To name some of them; in startswith istartswith range 
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