brasa

Extract finance market data from brazillian financial institutions: B3, ANBIMA, Tesouro Direto, CVM.

Installation

Install from PyPI (published as brasa-marketdata; the import name is still brasa):

pip install brasa-marketdata

Or directly from GitHub (latest main):

pip install git+https://github.com/wilsonfreitas/brasa.git

With uv:

uv add brasa-marketdata
uv add git+https://github.com/wilsonfreitas/brasa.git

Data directory (brasa init / BRASA_DATA_PATH)

brasa stores everything — raw downloads, parsed parquet, and the metadata DB — under a single brasa home. On a fresh install, configure it once:

brasa init

This suggests a platform default (e.g. ~/.local/share/brasa on Linux), lets you confirm or type another path, and persists the choice in ~/.config/brasa/config.toml. Non-interactive variants:

brasa init --data-path /data/brasa   # explicit path, no prompt
brasa init --yes                     # accept the default, no prompt

The BRASA_DATA_PATH environment variable, when set, always takes precedence over the config file — useful for CI, containers, tests, and one-off overrides. Commands that read or write data fail with a clear error until one of the two is configured; template introspection commands (list-templates, deps, graph) work without any configuration.

Changelog

Deterministic Download Status Codes

Every download attempt is now classified with a single, unambiguous status code persisted in the download_trials table:

DB migration: Existing caches are upgraded automatically on startup. Legacy downloaded=1 rows become PASSED; downloaded=0 become FAILED. (The standalone migration script has been removed after being applied; it is recoverable from git history if ever needed.)

See docs/USER_GUIDE.md for full details.

Import Local Files (import_marketdata / brasa import)

Files with no download URL — a one-off vendor file, a manually-provided upload, or a corrected file for backfill — can now be imported using the same validate → gzip → checksum-dedup → parse → store engine as download. Only the acquisition step changes: bytes are read from disk instead of HTTP.

# Backfill a single date into a template that normally downloads via HTTP
brasa import b3-cotahist-daily --path /data/backfill/COTAHIST_D02012024.TXT --arg refdate=2024-01-02

# Bulk import one file per business day using a date pattern
brasa import my-daily-template --path '/data/prices/%Y-%m-%d.csv' --arg refdate=@2026-06-01:2026-06-30

from brasa import import_marketdata

import_marketdata("b3-cotahist-daily", path="/data/backfill/COTAHIST_D02012024.TXT", refdate="2024-01-02")

See docs/CLI.md, docs/API_REFERENCE.md, and docs/TEMPLATES.md for full details.

Publishing to PyPI

brasa is built with hatchling and published manually under the distribution name brasa-marketdata (the PyPI name brasa was already taken by an unrelated project; import brasa is unaffected). Templates and SQL DDL are bundled inside the package (brasa/files/), so the built wheel is self-contained.

1. Bump version in pyproject.toml.

2. Build the wheel and sdist:

   uv build
   

   Distributions are written to dist/.

3. (Optional) Verify the wheel bundles the data files:

   BRASA_BUILD_TEST=1 uv run pytest tests/test_packaging_wheel.py -v
   

4. (Optional) Smoke-test in a clean environment:

   python -m venv /tmp/brasa-smoke
   /tmp/brasa-smoke/bin/pip install dist/brasa_marketdata-*.whl
   /tmp/brasa-smoke/bin/python -c "import brasa; from brasa.engine.template import list_templates; print(len(list_templates()))"
   

5. Publish:

   # TestPyPI dry-run first (recommended)
   uv publish --publish-url https://test.pypi.org/legacy/ --token "$TEST_PYPI_TOKEN"
   # Production
   uv publish --token "$UV_PUBLISH_TOKEN"
   

   A PyPI API token can be supplied via --token, the UV_PUBLISH_TOKEN environment variable, or ~/.pypirc.