Are you a tech enthusiast or new to using Python packages? Are you confused about the differences between Pip and Pip3?
It’s essential to understand the difference between these two package managers, especially if you plan on managing packages for both Python 2 and Python 3. In this blog post, I’ll explain the difference between Pip and Pip3, so you can make the best decision for your project.
Pip is a module used to install packages into a particular Python version’s “site-packages” directory and ensure it is available to the relevant interpreter.
Pip3, on the other hand, is an updated pip version specifically used for Python 3. It allows you to create and manage virtual environments and only operates in the Python 3 environment.
To ensure you’re installing packages into the correct interpreter, use pip for Python 2 and pip3 for Python 3.
Now that you have a basic understanding of the difference between Pip and Pip3, let’s delve deeper and examine these package managers in more detail.
What Is a Pip?
Pip is an essential tool for tech enthusiasts. It is a package manager that comes pre-installed with Python versions 3.4 or higher, and it serves as a way to install libraries from the internet that do not come as part of the standard Python library.
Pip includes features such as new functions, improved usability, and quality-of-life upgrades, making it easier to share projects with the world.
To use pip, one can simply open a command prompt and type “pip –version” to see if it is installed. If not, then “py get-pip.py” will install the version of Python that was invoked.
Furthermore, pip commands can be used to install, uninstall, and check what packages have been installed.
What Is Pip3?
Pip3 is the latest version of Pip that has been designed for Python 3. It supports much of the same functionality as pip, such as installing libraries from the internet but can also be used for more specific tasks.
Pip3 uses similar commands as pip and allows developers to easily access libraries that have been downloaded from the internet. Furthermore, it includes commands that can help with managing packages and dependencies, making it easier to share projects with the world.
Pip vs. Pip3
|Installation||Pre-installed in most distributions of Python||Invoked when the python version is invoked, and then installed accordingly|
|Purpose||Used to install various packages for pip vs pip3 various operations||Updated version of Pip used mainly for Python 3|
Why Do We Need Pip in Python?
Installing Python packages is easiest when done with the help of the pip tool.
For instance, if you need to install a third-party package or library, such as requests, you must first install it using Pip.
Pip is a package management system used to install and manage Python-based software packages. Python Package Index, the usual repository for packages and their dependencies, contains several packages (PyPI).
Pip vs. Conda vs. Anaconda
Pip is a Python package manager that allows users to install, update and manage packages from the Python Package Index (PyPI).
It is easy to use and can be installed with almost any version of Python. However, it only works with packages written in pure Python, so more complex libraries like Scikit-learn must be installed separately.
Pip is best for users who only need to install Python packages.
Pros of Pip:
- Easy to use and install
- Only installs Python packages
Cons of Pip:
- Does not work with packages written in other languages
- Does not handle complex libraries like Scikit-learn
Conda is a cross-platform package and environment manager that helps users manage their data science workflows.
It allows them to easily switch between different environments, such as the command line, Jupyter Notebook, etc., in their local machine.
Pros of Conda:
- Can be used to install packages written in different languages
- Includes complex libraries like Scikit-learn
- Allows users to switch between environments easily
Cons of Conda:
- Less intuitive and more difficult to use than a pip
Anaconda is a Python distribution that includes the Conda package manager, along with many other useful data science packages. It can be used to manage all aspects of the data science pipeline, from installation to deployment.
Anaconda is best for teams that need a full-featured data science platform with commercial support.
Pros of Anaconda:
- Includes the Conda package manager
- Comes with many useful data science packages pre-installed
- Provides commercial support for teams needing a full-featured data science platform
Cons of Anaconda:
- May be overkill for users who only need a few packages
- Can be more difficult to use than Pip or Conda alone
Alternatives to Pip
Pip is a powerful package manager for Python, but it’s not the only option.
Other alternatives, such as npm, Homebrew, Yarn, RequireJS, Bower, Browserify, Bundler, Component, PyCharm, and Conda, also provide package management services to tech enthusiasts.
- Npm provides users with an easy-to-use command-line interface for the npm ecosystem. Interestingly, more than 11 million developers are relying on this software.
- Homebrew is great for installing those things that Apple didn’t cover. Yarn caches packages, making downloads quicker and easier than ever.
- Component is perfect for building powerful and reusable UI components.
- Pip and Pip3 are both essential tools for tech enthusiasts.
- Pip is a package manager that comes pre-installed with Python version 3.4 or higher, while Pip3 is the updated version of pip used mainly for Python 3.
- It is important to understand the differences between these two package managers in order to make the best decision for your project.
- Pip and Pip3 both include features such as new functions, improved usability, and quality-of-life upgrades, making it easier to share projects with the world.