baybin-sentinel 2026.6.25.1

Baybin Sentinel: OpenSearch writer

Baybin Sentinel

baybin_sentinel is a Python utility package designed for the Baybin Sentiment Analysis System. It provides specialized writers to streamline the ingestion of social media data into OpenSearch.

Currently supported platforms: Facebook, Threads, PTT, News (RSS / Scrapy), Google Trends.

Installation

(For Crawler Developers) Install Package

pip install -U baybin_sentinel

(For Package Developers) Create Virtual Environment

conda update -n base -c conda-forge conda
conda create -n sentinel python=3.13 pip -y
conda activate sentinel
cd baybin_sentinel
pip install -r requirements.txt
pip install -e .

Configuration

Each writer accepts credentials either as direct parameters or via a config file.

Option A — direct parameters:

writer = PttWriter(
    host="192.168.x.x",
    port=9200,
    user="your_username",
    password="your_password",
    verify_certs=False,
)

Option B — config file (recommended for development):

writer = PttWriter(config_path="/absolute/path/to/config.yaml")

# config.yaml
opensearch:
  host: "your_opensearch_ip"
  port: 9200
  user: "your_username"
  password: "your_password"
  verify_certs: false

Option C — environment variable (recommended for Celery workers / containers):

Set BAYBIN_SENTINEL_CONFIG to the absolute path of your config file. Takes priority over config_path.

export BAYBIN_SENTINEL_CONFIG=/absolute/path/to/config.yaml

Config resolution order: direct params → BAYBIN_SENTINEL_CONFIG env var → config_path argument → default "config.yaml" (relative to CWD).

Index naming convention

Each writer targets a dedicated OpenSearch index following the pattern raw_{platform}_{content_type}s:

Writer	Post index	Comment index
FacebookWriter	raw_facebook_posts	raw_facebook_comments
ThreadsWriter	raw_threads_posts	raw_threads_comments
PttWriter	raw_ptt_posts	—
NewsWriter	raw_news_posts	—
GoogleTrendsWriter	raw_google_trends_posts	—

Field normalization

Each writer accepts pre-normalized data and routes fields to root vs metadata before writing to OpenSearch.

Canonical root-level fields (posts): post_id, platform, client_id, source_name, url, content, author_name, language, timestamp, crawled_at, s3_path

Canonical root-level fields (comments): comment_id, legacy_comment_id, post_id, post_url, platform, client_id, author_id, author_name, content, content_hash, timestamp, crawled_at, created_at, depth, s3_path

Any field not in the canonical set is automatically moved into a nested metadata object.

Validation

Every writer validates the document before writing to OpenSearch. A ValueError is raised immediately if any required field is missing or empty — no silent bad writes.

Required post fields: post_id, platform, client_id, timestamp, crawled_at

Required comment fields: comment_id (or legacy_comment_id), post_id, platform, client_id, content, timestamp, crawled_at

This means:

• You must call normalize_post() / normalize_comment() before passing data to the writer — passing a raw API response directly will raise.
• client_id must always be present — enforces multi-tenancy at the write layer.

Platform field maps

ThreadsWriter — accepts raw output from the internal Threads scraper:

Raw field	Canonical field
text	content (posts and comments)
post_url	url (posts)
author	author_name (posts)
reply_author	author_name (comments)
reply_author_id	author_id (comments)

FacebookWriter — expects pre-normalized post data (output of normalize_post()). Comment field map:

Raw field	Canonical field
reply_author	author_name
reply_author_id	author_id

PttWriter, NewsWriter, GoogleTrendsWriter — expect pre-normalized data with canonical field names already set.

Example (Facebook)

from baybin_sentinel.platforms.facebook import FacebookWriter

writer = FacebookWriter(
    host="192.168.x.x",
    port=9200,
    user="your_username",
    password="your_password",
    verify_certs=False,
)

# Single post with its comments
writer.save(post, comments)

# Bulk posts only
writer.save_bulk_posts(posts)

# Bulk comments only
writer.save_bulk_comments(comments)

Example (Threads)

from baybin_sentinel.platforms.threads import ThreadsWriter

writer = ThreadsWriter(config_path="/path/to/config.yaml")

# Single post with its replies (extracted from post["replies_detail"])
writer.save(post)

# Single post with explicit comments
writer.save(post, comments)

# Bulk posts only
writer.save_bulk_posts(posts)

# Bulk comments for one post
writer.save_bulk_comments(replies, post_url="https://threads.net/...")

Example (PTT)

from baybin_sentinel.platforms.ptt import PttWriter

writer = PttWriter(config_path="/path/to/config.yaml")

writer.save_post(post)
writer.save_bulk_posts(posts)

Example (News)

from baybin_sentinel.platforms.news import NewsWriter

writer = NewsWriter(config_path="/path/to/config.yaml")

writer.save_post(post)
writer.save_bulk_posts(posts)

Example (Google Trends)

from baybin_sentinel.platforms.google_trends import GoogleTrendsWriter

writer = GoogleTrendsWriter(config_path="/path/to/config.yaml")

writer.save_post(post)
writer.save_bulk_posts(posts)

Publishing to PyPI

If you are the maintainer, follow these steps to publish a new version:

1. Update version in pyproject.toml (e.g., 0.2.0).
2. Install build tools:

   pip install build twine
   

3. Build the package:

   rmdir /s /q dist build 2>nul
   python -m build
   

4. Upload to PyPI:

   python -m twine upload dist/*
   

5. Authentication:
   • Username: __token__
   • Password: pypi-your-api-token-here (including the pypi- prefix)