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How to keep a channel dataset current with incremental updates with Telegram Parser

Refresh an existing export with new posts and changed comments, or run Watch mode for continuous updates.

Credentials. Watch mode keeps the Telethon session open for a long time, so protect the session file and stop the process when you no longer need it.

Who it is forAn analyst tracking a channel over weeks who wants counts and reactions on older posts to stay accurate without full re-exports.

The problemRe-exporting the whole channel each time is slow, and old posts keep changing as comments and reactions arrive.

The outcomeA single dataset file that merges new posts by post_id and comments by comment_id, with counters refreshed on recent posts.

What you need first

  • Docker Desktop (recommended) or Python with the packages in requirements.txt
  • Telegram API credentials: API_ID and API_HASH from https://my.telegram.org/apps
  • A Telegram account session for Telethon, needed only for live exports

Steps

  1. Complete a first export, such as docker compose run --rm cli export json, so a dataset exists.
  2. Run docker compose run --rm cli export json --incremental on a schedule you choose.
  3. For continuous updates, run docker compose run --rm cli watch --poll-interval 30 --refresh-active-posts 20.
  4. Check data/state/ for the saved incremental state and data/raw/ for the updated dataset.

Prompt for your agent

In the TheMyxa/telegram-parser repo, run `docker compose run --rm cli export json --incremental` for channel <channel-username>. Expected output is an updated *_dataset.json in data/raw/ and a state file in data/state/. Verify that the post count did not drop after the run before reporting.

Caveat. Incremental runs depend on the saved state in data/state/, so deleting that folder makes the next run behave like a fresh export.

Use this in your AI agent

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Using the Deduped MCP, get the setup steps for TheMyxa/telegram-parser and "Keep a channel dataset current with incremental updates"

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