Python

• Awesome Python: a curated list of Python stuff.

Python IDEs

• VSCode + Python extension.
• PyCharm by Jetbrains.
• Spyder: a free and open source scientific environment for Python.
• Jupyter Lab: a highly extensible, feature-rich notebook authoring application and editing environment

Run Python Notebooks online

• Google Colab: an online jupyter notebook platform for machine learning.
• Binder: make online (e.g., GitHub repo) notebooks executable.

Package Manager for Python

• uv: uv is a drop-in replacement for pip, an extremely fast Python package and project manager written in Rust.
• pixi: pixi supports both conda environment.yml and pip requirements.txt files.
• Anaconda Python: a full set of scientific Python packages with the conda package manager.   - miniforge : minimal installation with conda and mamba package managers and the conda-forge community packages.
  • micromamba: micromamba is a standalone version of the mamba package manager.
• pipenv: the official dependency management tool for Python packages.
• Poetry: Python packaging and dependency management.
• pdm: A modern Python package manager with PEP 582 support.

Python tutorials

General

• Learn Python in Y minutes
• Python cheatsheet
• Automate the Boring Stuff with Python
• Python Course Europe
• A Byte of Python
• Think Python: How to think like a Computer Scientist
• Project Python
• IPython cookbook
• The Hitchhiker’s Guide to Python
• Cracking Python bootcamp
• Replacing bash scripts with Python

Visualizations

• Python Graph Gallery
• Matplotlib official examples
• Seaborn with examples.
• Top 50 matplotlib plots
• Matplotlib, Seaborn, and Plotly tutorial

Scientific

• Python Course | Numerical programming
• QuantEcon Python
• Scipy Lecture Notes
• SciPy Cookbook
• Elegant scipy
• Python Data Science Handbook
• Numpy Tutorial part1. Part2

Data Processing and Machine learning

• Python Pandas Data Frame Basics
• 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets
• Machine Learning Plus
• MIT deep learning

Scientific machine learning

• deepxde : deep learning and differential equations.
• jax : Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more.
• diffrax : Numerical differential equation solvers in JAX.

Setup Python

Setup Python package managers.

miniforge

https://github.com/conda-forge/miniforge is a Python distribution that uses

• community-driven conda-forge repository
• basic conda package manager and the fast new mamba package manager.

Installation

Windows

Download and run the installer in https://github.com/conda-forge/miniforge

Linux

CONDA_PATH="${HOME}/conda"
CONDA_SH="${CONDA_PATH}/etc/profile.d/conda.sh"
CONDA_URL="https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh"

# Download and install
wget -O /tmp/conda.sh "${CONDA_URL}"
bash /tmp/conda.sh -bup "${CONDA_PATH}"
source "${CONDA_SH}"
conda activate base

# conda package manager setup
conda config --set auto_activate_base false
conda config --set default_threads $(nproc)
conda update python --yes && conda update --all --yes

# `bash` and `zsh` integration
conda init bash || true
conda init zsh || true

micromamba

micromamba is a fully statically-linked, self-contained, executable for conda environments.

Installation

Windows:

Invoke-Expression ((Invoke-WebRequest -Uri https://micro.mamba.pm/install.ps1 -UseBasicParsing).Content)

Linux:

"${SHELL}" <(curl -L micro.mamba.pm/install.sh)

Update

micromamba self-update

Commands

micromamba has no “base” environment. Other than that, it shares basically the same commands as conda and mamba.

To create an environment:

micromamba create -n <name> <list of packages>

To create an environment from a spec file

micromamba create -n <name> -f <envfile>

To install an environment to a specific folder

micromamba create -p <dirpath> <list of packages>

To activate an environment:

micromamba activate <name>

To run a command from an environment

micromamba run -n <name> <command>

Or

micromamba run -p <dirpath> <command>