Developer Resources

Installing Python Packages

Python's strength lies in its ecosystem of third-party packages. The pip package manager is the standard tool for installing, upgrading, and removing Python packages from the Python Package Index (PyPI).

Virtual Environment Required

Always ensure your virtual environment is activated before installing packages. If you do not see the (.venv) prefix in your terminal prompt, activate your environment first. See Virtual Environments for instructions.

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Installing Packages with pip

Basic Installation

To install a package:

pip install <package-name>

For example, to install NumPy:

pip install numpy

pip will download the package from PyPI and install it into your active virtual environment's site-packages directory.

Installing a Specific Version

To install a specific version of a package:

pip install <package-name>==<version>

For example:

pip install pandas==2.1.4

This is useful when a project requires a specific version for compatibility.

Installing Multiple Packages

You can install multiple packages in a single command:

pip install numpy pandas matplotlib

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Common pip Commands

Command	Purpose
pip install <package>	Install a package
pip install <package>==<version>	Install a specific version
pip install --upgrade <package>	Upgrade a package to the latest version
pip uninstall <package>	Remove a package
pip list	List all installed packages and their versions
pip show <package>	Show detailed information about an installed package
pip freeze	Output installed packages in requirements.txt format

tip

If pip is not recognized as a command, use python -m pip instead. This runs pip through the Python interpreter and works regardless of PATH configuration. For example: python -m pip install numpy.

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Managing Dependencies with requirements.txt

A requirements.txt file lists all the packages your project depends on, along with their versions. This file is essential for team collaboration — it allows anyone to recreate your exact environment.

Creating a requirements.txt

After installing all the packages your project needs, capture them:

pip freeze > requirements.txt

This generates a file like:

matplotlib==3.8.2
numpy==1.26.3
pandas==2.1.4
scipy==1.12.0

Installing from requirements.txt

When you clone a project or set up a new environment, install all dependencies at once:

pip install -r requirements.txt

This reads the file and installs every listed package at the specified version.

Best Practices for requirements.txt

• Commit requirements.txt to version control — This is the primary way other developers know what packages your project needs.
• Update it when you add or remove packages — Run pip freeze > requirements.txt after making changes to your environment.
• Pin versions — The pip freeze output includes exact version numbers (e.g., numpy==1.26.3), which ensures reproducible environments. Do not remove the version specifiers.
• Review before committing — pip freeze captures everything in the environment. If you installed packages for experimentation that are not part of the project, remove them before generating the file.

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Commonly Used Packages for RMC Work

The following packages are commonly used across RMC Python projects. Install only what your specific project needs.

Package	Purpose
numpy	Numerical computing — arrays, linear algebra, random numbers
pandas	Data manipulation — DataFrames, CSV/Excel I/O, data cleaning
matplotlib	Static plotting and visualization
plotly	Interactive plotting and visualization
scipy	Scientific computing — optimization, interpolation, statistics
sympy	Symbolic mathematics — algebra, calculus, equation solving
requests	HTTP requests — calling APIs, downloading data
notebook	Jupyter notebooks — interactive development (see Jupyter Notebooks)
pytest	Testing framework — write and run unit tests for your code
openpyxl	Reading and writing Excel files (used by pandas for .xlsx support)