Today was spent setting up two complete learning environments and practicing the fundamentals of both Python (scientific computing) and Rust.
Python / SciPy Environment
- Installed uv, the modern Python package manager
- Fixed a cache permission issue that blocked the setup
- Created a dedicated project at ~/learn-scipy
- Installed the core scientific stack: SciPy, NumPy, Matplotlib, Pandas, and Seaborn
- Added Jupyter Lab for interactive exploration
- Successfully verified the environment (SciPy 1.18.0)
Rust Environment
- Installed and updated Rust with rustup (rustc & cargo 1.97.1)
- Created a new Cargo project at ~/learn-rust
- Added an external crate (rand) and used it
- Wrote and ran several small programs covering:
- Random number generation
- Variables and string interpolation
- Mutable variables and counters
- If / else statements
- Infinite loops with break
- Created an examples/ folder and saved three reusable practice files
- Learned how to compile and run those saved examples independently with rustc
Both environments are now clean, isolated, and ready for continued learning — one focused on scientific computing with Python, the other on systems programming with Rust.