Python Libraries

This is the lookup site. When a notebook elsewhere in the collection reaches for polars or pyecharts or asyncio, the page explaining it is here.

The notes are deliberately uneven in depth. A few pages are exhaustive because the library repays it, with NumPy, Pandas, and the Python class model each running to hundreds of cells. Others are a page of the commands actually used. Depth tracks how often the thing is reached for, not how important it sounds.

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Numerical Core

Page	Covers
NumPy	The largest page on the site, working through arrays, indexing, broadcasting, and the operations built on them
SciPy	The scientific layer above NumPy
NumExpr	Faster evaluation of numerical expressions through multithreading, for when arrays get large enough to matter

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Dataframes

Page	Covers
Pandas	The long reference
Polars	The Rust-backed alternative
Dask	Parallel computing that scales from one machine to a cluster, for datasets larger than memory, integrating with NumPy, pandas, and scikit-learn

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Plotting and Diagrams

Page	Covers
Matplotlib	The default, and what everything else is measured against
ECharts	The most detailed of these, on pyecharts. ECharts describes a chart as one JSON-like option object covering data, axes, series, styling, and interaction. This is the charting library the deep learning notebooks are required to use
Plotly	Interactive publication-quality charts inside Jupyter
Bokeh	Another interactive browser-rendered option
Altair	Declarative interactive plots
Graphviz	Graph and diagram layout from a text description
Mermaid	Diagrams as markdown, which is what the diagram pages in Software Tools are built from
Manim	Programmatic mathematical animation

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The Language Itself

Page	Covers
Python Classes	The object model at length: definition, inheritance, the dunder methods, and the protocols they implement
asyncio	A complete reference targeting Python 3.11 and up, which is the meaningful floor because TaskGroup, asyncio.timeout(), and task.uncancel() all landed there and they change what correct code looks like
Multiprocessing	The other concurrency route, for when the work is CPU-bound
Logging	The standard library logging module
argparse	Command line arguments
Dataclasses	The decorator that writes __init__, __repr__, and __eq__ for you
Datetime	Dates, times, timezones, and formatting
AST	Parsing, inspecting, and transforming Python source as a tree

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Environments and Packaging

Six tools that solve overlapping versions of the same problem, in roughly the order they appeared.

Page	Covers
venv	The one in the standard library
Pipenv	Dependency resolution with a lockfile
Poetry	Dependency management plus packaging
Conda	The scientific-stack option, which handles non-Python dependencies
uv	The Rust-based one this collection actually uses
direnv	Loading and unloading an environment automatically on directory change
Environment Variables	How they work in Linux and how to manage them

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Code Quality and Testing

Page	Covers
Ruff	The fast Python-native linter that replaces flake8 and pylint, and overlaps Black
Ruff Rule Categories	What each rule family prefix means, F, E, W, N, B, and the rest, and why you would enable it
Black	The uncompromising formatter that ends style arguments by making the decisions for you
pytest	Basics through fixtures, plugins, and practice
Monkey Patching	What it is, when it is justified, the risks, and how it shows up in pytest

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Notebooks and Terminal Output

Page	Covers
nbdev	The framework this entire collection is built on, turning notebooks into libraries and docs
Marimo	The reactive notebook alternative, and how it differs from JupyterLab
ipywidgets	Interactive controls inside a notebook
Rich	Terminal output worth looking at: tables, progress, syntax highlighting
tqdm	A progress bar around any loop

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Data In

Page	Covers
Requests and HTTPX	The standard HTTP client against the one that adds async and HTTP/2
BeautifulSoup4	Parsing HTML and XML, mostly for scraping
duckduckgo-search	Programmatic search across words, documents, images, news, and maps
Kaggle	Pulling competition and dataset files
SQLAlchemy	The 2.x-style guide to Python’s ORM and query builder
pytube	Downloading video

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Odds and Ends

Page	Covers
Latexify	Rendering a Python function as the LaTeX equation it implements
Mito	A spreadsheet interface over a dataframe
pivottablesjs	Interactive pivot tables in a notebook

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Not Covered Yet

• The site title says MLtools but the content is general Python. Very little here is machine learning specific; the modelling libraries live in ML Methods and DL Methods.
• No page on typing, despite type hints being unavoidable in modern Python.
• Nothing on pydantic, which is the validation layer most projects reach for.
• pathlib and file handling have no page, only incidental use elsewhere.
• Six environment tools, no recommendation. The pages describe each without saying which to pick, though the collection itself uses uv.
• uv is five cells against a tool the whole repo depends on, so it is the thinnest page relative to its importance.

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