T-Record
========
A lightweight Python library for robust record tracing, status tracking, and detailed logging —
built for automation pipelines and data integrity.
Features
--------
* **ThoughtfulRecord model**
Track each record's status, lifecycle, and traces with robust JSON-serializable objects.
* **Automatic history**
Dumps detailed logs, merges previous runs seamlessly, preserving full audit history.
* **Enhanced HTML reports**
Auto-generates beautiful HTML reports with status summary, traces, diffs, and screenshots.
* **Portable archive**
Packs all data (logs + images + HTML) into a shareable ZIP file.
* **Fail-safe logging**
Internally uses ``try/except`` to ensure tracing never crashes your main process.
Installation
------------
Install via pip::
pip install t-record-lib
Or for local development::
git clone https://github.com/YOUR_ORG/t_record.git
cd t_record
pip install -e .
Quickstart
----------
.. code-block:: python
from t_record.record import configure_records_tracing, ThoughtfulRecord, dump_records, pack_sharable_zip, RecordStatus
# 1. Configure
configure_records_tracing("records_folder")
# 2. Create your record
class MyRecord(ThoughtfulRecord):
id: str
status: RecordStatus = ""
record = MyRecord(id="rec_001")
# 3. Change status or add traces
record.status = Status.RUNNING
record.log_trace("Started processing", reason="Data loaded")
# 4. Save everything
dump_records()
# 5. Create shareable ZIP
pack_sharable_zip("records.zip")
Output files
------------
By default, each run will produce::
/records_folder/{process_name}/{run_id}/
records_logs.json # full structured logs (merged from previous runs)
records_report.html # human-readable dashboard
/images/ # attached screenshots
Plus a zip archive on demand.
Advanced usage
--------------
* Continue an existing run (merges history automatically)::
configure_record_tracing("records_folder")
record = MyRecord(id="rec_001") # picks up previous traces
record.status = Status.COMPLETED
dump_records()
* Add an image trace::
record.log_trace("Reviewed", reason="Visual QC", image="path/to/image.png")
Raw data
{
"_id": null,
"home_page": "https://www.thoughtful.ai/",
"name": "t-record-lib",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.11",
"maintainer_email": null,
"keywords": "t_record",
"author": "Thoughtful",
"author_email": "support@thoughtful.ai",
"download_url": "https://files.pythonhosted.org/packages/73/01/5e0305ba6dfb1e8607bd529aebfd7f3f50eb2b12a4daea147d2c90d28e1f/t_record_lib-0.2.3.tar.gz",
"platform": null,
"description": "T-Record\n========\n\nA lightweight Python library for robust record tracing, status tracking, and detailed logging \u2014\nbuilt for automation pipelines and data integrity.\n\nFeatures\n--------\n\n* **ThoughtfulRecord model**\n Track each record's status, lifecycle, and traces with robust JSON-serializable objects.\n\n* **Automatic history**\n Dumps detailed logs, merges previous runs seamlessly, preserving full audit history.\n\n* **Enhanced HTML reports**\n Auto-generates beautiful HTML reports with status summary, traces, diffs, and screenshots.\n\n* **Portable archive**\n Packs all data (logs + images + HTML) into a shareable ZIP file.\n\n* **Fail-safe logging**\n Internally uses ``try/except`` to ensure tracing never crashes your main process.\n\nInstallation\n------------\n\nInstall via pip::\n\n pip install t-record-lib\n\nOr for local development::\n\n git clone https://github.com/YOUR_ORG/t_record.git\n cd t_record\n pip install -e .\n\nQuickstart\n----------\n\n.. code-block:: python\n\n from t_record.record import configure_records_tracing, ThoughtfulRecord, dump_records, pack_sharable_zip, RecordStatus\n\n # 1. Configure\n configure_records_tracing(\"records_folder\")\n\n # 2. Create your record\n class MyRecord(ThoughtfulRecord):\n id: str\n status: RecordStatus = \"\"\n\n record = MyRecord(id=\"rec_001\")\n\n # 3. Change status or add traces\n record.status = Status.RUNNING\n record.log_trace(\"Started processing\", reason=\"Data loaded\")\n\n # 4. Save everything\n dump_records()\n\n # 5. Create shareable ZIP\n pack_sharable_zip(\"records.zip\")\n\nOutput files\n------------\n\nBy default, each run will produce::\n\n /records_folder/{process_name}/{run_id}/\n records_logs.json # full structured logs (merged from previous runs)\n records_report.html # human-readable dashboard\n /images/ # attached screenshots\n\nPlus a zip archive on demand.\n\nAdvanced usage\n--------------\n\n* Continue an existing run (merges history automatically)::\n\n configure_record_tracing(\"records_folder\")\n record = MyRecord(id=\"rec_001\") # picks up previous traces\n record.status = Status.COMPLETED\n dump_records()\n\n* Add an image trace::\n\n record.log_trace(\"Reviewed\", reason=\"Visual QC\", image=\"path/to/image.png\")\n\n\n\n\n",
"bugtrack_url": null,
"license": null,
"summary": "Cookiecutter template for Thoughtful pip package",
"version": "0.2.3",
"project_urls": {
"Homepage": "https://www.thoughtful.ai/"
},
"split_keywords": [
"t_record"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "73015e0305ba6dfb1e8607bd529aebfd7f3f50eb2b12a4daea147d2c90d28e1f",
"md5": "c479b6733bf3e23e0341349febef52fe",
"sha256": "eec30de0e6ab84b8778e09ed6591a827ecc204e6c960fa30e11b6773c6693091"
},
"downloads": -1,
"filename": "t_record_lib-0.2.3.tar.gz",
"has_sig": false,
"md5_digest": "c479b6733bf3e23e0341349febef52fe",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.11",
"size": 19584,
"upload_time": "2025-07-15T16:44:17",
"upload_time_iso_8601": "2025-07-15T16:44:17.296584Z",
"url": "https://files.pythonhosted.org/packages/73/01/5e0305ba6dfb1e8607bd529aebfd7f3f50eb2b12a4daea147d2c90d28e1f/t_record_lib-0.2.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-07-15 16:44:17",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "t-record-lib"
}
JSON