# mCodingLLC/VideosSampleCode

Code from the mCoding sample videos

Repository: https://github.com/mCodingLLC/VideosSampleCode
Canonical: https://ross.abutalabs.com/products/videossamplecode
Language: Python
License: MIT
License Family: permissive
Last push: 2024-10-03T15:13:02+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2118, "days_push": 699, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1132, forks 220 (observed 2026-08-28T04:03:42.741788+00:00)

## What it is
A collection of sample code from the mCoding YouTube channel's Python programming videos, covering topics like async, logging, Docker, itertools, and LLMs. It serves as a companion code repository for educational video content rather than a standalone tool.

## Use cases
- learn python async programming from examples
- find example code for python logging best practices
- study docker tutorial sample code
- see itertools usage examples
- learn how to run a local llm in python
- understand asgi and fastapi lifespan events

## When to choose
- you are following an mCoding video and want the exact source code
- you want small, focused Python examples of specific concepts
- you want MIT-licensed snippets to adapt for learning

## When to avoid
- you need a production-ready library with a stable API
- you expect documentation, tests, or packaging
- you need a cohesive tool rather than many unrelated demos

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools, logging, testing, web-framework
- domain: developer-tools, tutorials, programming-languages
- platform: python, cross-platform
- tags: youtube-samples, python-tutorials, async, docker, itertools, llm

## Member repositories
- mCodingLLC/VideosSampleCode (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:42.741788+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:37:58.061338+00:00, confidence not recorded.
  - readme: https://github.com/mCodingLLC/VideosSampleCode (fetched 2026-08-28T04:03:42.741788+00:00, sha bf65ea983719)
- Data as of 2026-08-30T08:39:29.467469+00:00.