Further information.

Further information.#

Why do we do `python -m pip install` and not `pip install`#

In some places you will see that to install a Python library you can run the following in the command line:

$ pip install <library>

Instead of:

$ python -m pip install <library>

This will work and most often will have the same effect however it is not recommended.

On some occasions pip, which is the library used to install packages will not correspond to the same python install you are using. To ensure this does not create any problems it is recommended to use python -m pip install <library>.

Here is a short blog post discussing this: https://adamj.eu/tech/2020/02/25/use-python-m-pip-everywhere/.

How to install multiple libraries at a time#

If you want to keep a record of multiple python libraries that you want to install, the convention is to keep them in a file called requirements.txt.

Then to install all the libraries you can run the following in the command line:

$ python -m pip install -r requirements.txt

For example, the requirements.txt file for this software used to write this book looks like:

black==20.8b1
interrogate==1.3.1
invoke==1.4.1
isort==4.3.21
jupyter-book==0.8.1
jupytext==1.6.0
nbval==0.9.6
proselint==0.10.2
pytest==5.4.3

If the version specifications are omitted then the latest versions of the libraries would be installed.

black
interrogate
invoke
isort
jupyter-book
jupytext
nbval
proselint
pytest

What is the Python package index#

The Python package index commonly referred to as PyPI is:

“The Python Package Index (PyPI) is a repository of software for the Python programming language.”

In practical terms it is where developers upload their libraries so that they can be installed with pip.

What is a virtual environment#

When using Python for a number of projects it can be beneficial to isolate the entire software environment for each project. This is done using something called a virtual environment and allows you to have multiple versions of Python and different sets of libraries for different projects.

The standard Python library includes venv for creating virtual environments:

$ python -m venv .venv
$ source .venv/bin/activate   # macOS
$ .venv\Scripts\activate      # Windows

You can read more about venv at:

What is `uv`#

uv is a fast, modern Python package and project manager. It can replace pip, venv, and other tools with a single command-line utility. It is written in Rust and considerably faster than pip for installing packages.

You can install uv by following the instructions at https://docs.astral.sh/uv/.

Managing a project with `uv`#

To create a new project with its own isolated environment:

$ uv init my-project
$ cd my-project

To add a library to the project (this installs it and records the dependency):

$ uv add sympy

To run a script or command inside the project’s environment:

$ uv run python main.py
$ uv run jupyter notebook

uv automatically creates and manages a virtual environment for the project so you do not need to activate it manually.

You can read the full uv documentation at https://docs.astral.sh/uv/.

Further information.

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