# supzhang/epg

抓取多来源电视节目单(EPG),生成TVXML文件，并提供对外访问接口及后台配置。

Repository: https://github.com/supzhang/epg
Canonical: https://ross.abutalabs.com/products/supzhang-epg
Language: Python
License Family: other
Last push: 2023-11-23T15:23:06+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 90
- inputs: {"age_days": 1272, "days_push": 1014, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1031, forks 310 (observed 2026-08-28T04:03:18.165294+00:00)

## What it is
A Python/Django-based system that scrapes TV program schedules (EPG) from multiple Chinese and Hong Kong/Taiwan sources and generates XMLTV files. It also serves the data via a DIYP-compatible API and provides an admin backend for channel configuration.

## Use cases
- generate xmltv epg files for iptv playlists
- scrape tv program schedules from multiple sources
- serve epg data for perfect player or diyp apps
- self-host a tv guide api
- aggregate channel listings from chinese tv providers

## When to choose
- you need EPG data for Chinese/Hong Kong/Taiwan TV channels in XMLTV format
- you want a self-hosted EPG server with a DIYP-compatible API
- you need automatic source fallback when scraping fails

## When to avoid
- you need EPG for non-Chinese channels or international providers
- you need a production-grade maintained project (no license, author notes uncertain future updates)
- you want a turnkey solution without manual channel curation

## Facets
- artifact type: application
- maturity: maintenance
- function: web-scraping, web-framework, http-server, api-framework, data-science
- domain: media, web-development, self-hosted
- platform: python, self-hosted
- tags: epg, xmltv, iptv, tv-guide, django, diyp, web-crawler, chinese-tv, automation, web-server, linux

## Member repositories
- supzhang/epg (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:18.165294+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 2026-08-30T07:07:29.958343+00:00, confidence not recorded.
  - readme: https://github.com/supzhang/epg (fetched 2026-08-28T04:03:18.165294+00:00, sha 0368d4a9a546)
- Data as of 2026-08-30T08:39:29.467469+00:00.