pip is a standard package manager used to install and maintain packages for Python. The Python standard library comes with a collection of built-in functions and built-in packages.
Data science packages like scikit-learn and statsmodel are NOT part of the Python standard library. They can be installed through
pip, the standard package manager for Python, via the command line.
Pip has a variety of commands and option flags designed to manage Python packages.
You can print the
pip version the same way you print the Python version. It is important that the
pip version is compatible with the Python version. Here we see that
pip 19.1.1 is compatible with Python 3.5.2.
pip is giving you an upgrade warning, you can upgrade using pip itself:
Viewing a Pip List
Before you make any installs, it is a good idea to see what is already installed. You can use
pip list in the command line, and it will display the Python packages in your current working environment in alphabetical order.
In the following example, you will learn how you can install the
scikit-learn package, which will install the other necessary dependencies.
You may notice from the logs that more then the
scikit-learn package is being installed. This is because
pip will install any other packages that
scikit-learn depends on. These other packages are called dependencies.
Installing a Specific Package Version
pip will always install the latest version, so if you wish to install an older version of
scikit-learn, all you need to do is specify it in the installation statement use a double equal sign:
If the package you are looking to use is already installed but simply out of date. You can update the package in a similar way we upgraded
This upgrade will also upgrade any necessary dependency packages as well, automatically.
Installing and Upgrading the
pip install more than one Python package, the packages can be listed in line with the same
pip install command as long as they are separated with spaces. Here we are installing both
scikit-learn and the
statsmodel package in one line of code.
You can also upgrade multiple packages in one line of code.
Installing Packages With
If you want to install many packages at once, you can save them one package per line in a text file called
requirements.txt. If we preview the file, it looks like this:
It is conventional for Python package developers to create a
requirements.txt file in their Github repositories listing all dependencies for
pip to find and install.
-r option flag in
pip install to install packages from the file specified after the option flag. Keep in mind that naming this file
requirements.txt is conventional but not required.
Using our examples,
pip install -r requirements.txt will have the same effect as
pip install scikit-learn statsmodel. Typing out each package could get messy if you needed to install ten packages. Using the
requirements.txt file is much cleaner.
Interactive Example of Installing Python Dependencies
In the following example, you will work through the setup process for making sure your Python environment has the proper library dependencies installed prior to executing a Python model script.
You will instantiate the
requirements.txt document and add the
scikit-learn library to the
# Add scikit-learn to the requirements.txt file echo "scikit-learn" > requirements.txt # Preview file content cat requirements.txt
When we run the code above, it produces the following result:
$ # Add scikit-learn to the requirements.txt file $ echo "scikit-learn" > requirements.txt $ $ # Preview file content $ cat requirements.txt scikit-learn
To learn more about using pip in the command line, please see this video from our course Data Processing in Shell.
This content is taken from DataCamp’s Data Processing in Shell course by Susan Sun.
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