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Python Packages

Python core packages are the modules that are included with the Python interpreter itself. They are designed to provide basic functionality that is needed for most Python programs. You can create your own packages or use packages created by other software developers.

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Use a Package

To use a core Python package, you first need to import it into your program. This can be done using the "import" statement. Once you have imported the package, you can use its functions and classes. For example, to calculate the square root of 2, you would use the following code:

Example:


import math

print(math.sqrt(2))

Output:


1.4142135623730951.

For more information on how to use a core Python package, you can refer to the Python Standard Library documentation: https://docs.python.org/3/library/index.html.

Core Packages

In table below, generated with Bard AI bot, we have listed all Python packages with description and link to original documentation. This list can be used to enhance your know-how. You will learn the features of each package. Get yoursef familiar with all the packages before starting a project.

Package	Description
abc	Abstract base classes
collections	Data structures and functions
datetime	Dates and times
math	Mathematical functions
os	Operating system interface
random	Random number generation
re	Regular expressions
sys	System-specific parameters and functions
time	Time access and conversions
io	Input and output
logging	Logging
subprocess	Subprocess management
threading	Threading
urllib	URL handling
webbrowser	Web browser control

Third Party Packages

Third-party Python packages are software libraries that are developed and maintained by external organizations or individuals. These packages can be used to extend the functionality of Python or to provide specialized functionality that is not included in the standard Python library.

Open source packages are free to use and modify, and they are often developed by a community of contributors. This makes them a valuable resource for Python developers, as they can be used to save time and effort by providing pre-written code for common tasks.

Here is a table of some of the most popular third-party open source Python packages:

Package Name	GitHub Repository	Package Description
requests	A simple HTTP library for Python.	The requests library makes it easy to send HTTP requests and receive responses. It is a popular choice for web scraping and API development.
scrapy	A web scraping framework for Python.	The scrapy framework provides a powerful API for crawling and extracting data from websites. It is a popular choice for web scraping projects.
Flask	A microframework for Python web development.	The Flask framework is a lightweight and easy-to-use framework for creating web applications. It is a popular choice for small and medium-sized web applications.
Django	A high-level Python web framework.	The Django framework is a powerful and flexible framework for creating large and complex web applications. It is a popular choice for enterprise web applications.
NumPy	A library for scientific computing in Python.	The NumPy library provides a powerful API for working with numerical data. It is a popular choice for scientific computing and data analysis.
pandas	A library for data analysis in Python.	The pandas library provides a powerful API for working with tabular data. It is a popular choice for data analysis and data science.

Package manager

A Python package manager is a tool that helps you install, manage, and update Python packages. Packages are collections of Python code that are designed to be reused. They can contain modules, scripts, documentation, and other files.

Some popular Python package managers include:

Pip is the most popular Python package manager. It is built into Python and can install packages from the Python Package Index (PyPI).
Conda is a cross-platform package manager that can install packages from PyPI and other sources. It is often used for scientific computing.
Poetry is a newer package manager that is designed to make it easy to manage Python dependencies. It can create virtual environments and install packages from PyPI and other sources.

Package managers are essential for managing Python dependencies. Dependencies are other Python packages that your code needs to run. Without a package manager, you would have to manually download and install each dependency, which can be time-consuming and error-prone.

Package managers also make it easy to update your dependencies. This is important for security and bug fixes.

Benefits of using a Python package manager

Ease of installation: Package managers make it easy to install packages with a single command.
Dependency management: Package managers can help you to manage the dependencies of your projects. This can help to prevent conflicts between packages.
Version control: Package managers can help you to track the versions of the packages that you are using. This can be helpful for debugging and troubleshooting.
Security: Package managers can help to ensure that you are using the latest, most secure versions of the packages that you are using.

Recommendations

If you are a Python developer, I recommend using a package manager to manage your dependencies. It will make your life easier and help you to write more reliable code.

If you are new to Python, I recommend starting with Pip. It is the most popular Python package manager and it is built into Python. Once you are familiar with Pip, you can explore other package managers, such as Conda and Poetry.

Create a package

To create a package in Python, you first need to create a directory for the package. This directory should contain an "__init__.py" file. The "__init__.py" file is a special file in Python that is used to initialize a package. It is required for any directory that you want to be treated as a Python package.

The __init__.py file can be empty, or it can contain code that is executed when the package is imported. This code can be used to initialize variables, import modules, or define functions.

Once you have created the directory and the "__init__.py" file, you can start adding modules to the package. Modules are Python files that contain code. To add a module to a package, simply create a file in the package directory with the name of the module.

Steps:

Create a new directory for your package.
Create a file named "__init__.py" in the new directory.
Add your Python modules to the package directory.
Create a "setup.py" file in the package directory.
Install the package using the "pip" command.

Here is an example of how to create a package named "mypackage":


mkdir mypackage
cd mypackage
touch __init__.py

The package file name mypackage.py


# __init__.py

def hello_world():
    print("Hello, world!")

Create setup.py file. This is a Python script that is used to install and distribute Python packages. It contains information about the package, such as its name, version, and dependencies. It also contains instructions on how to install the package.

Example:

This setup.py file would install a Python package named mypackage that depends on the numpy and pandas packages.


from setuptools import setup

setup(
    name='mypackage',
    version='1.0',
    packages=['mypackage'],
    install_requires=['numpy', 'pandas'],
)

Installing the package:


pip install --user mypackage

Once you have installed the package, you can import it into your Python programs. For example, the following code will print "Hello, world!" to the console:


import mypackage

mypackage.hello_world()

The folder structure for the "mypackage" package would look like this:


mypackage/
├── __init__.py
└── hello_world.py

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