Project_CandleFetcher

Project_CandleFetcher is a Python 3.12+ project for acquiring, validating, and storing historical candlestick data from multiple venues.

This Hugging Face Dataset repository contains both:

1. the candlefetcher Python package and its tests/documentation; and
2. the canonical large candlestick CSV dataset under candleset/.

Repository: https://huggingface.co/datasets/MostafaRoohy/Project_CandleFetcher

Repository layout

Project_CandleFetcher/
├── candlefetcher/          # Python package
│   ├── core/               # Candle, symbol, timeframe, and validation domain types
│   ├── fetcher/            # API and bulk-download acquisition families
│   └── util/               # Shared datetime, HTTP, file, logging, and rate-limit utilities
├── candleset/              # Canonical large CSV dataset
├── test/                   # Test suite
│   └── conftest.py         # Shared pytest configuration/fixtures
├── doc/                    # Project documentation
├── playground/             # Experiments and notebooks
├── plan/                   # Project plans
├── env/                    # Environment configuration
├── AGENTS.md               # Repository-specific engineering rules
└── pyproject.toml

Candle dataset layout

Candle files are stored by exchange, market, symbol, and timeframe:

candleset/
└── <exchange>/
    └── <market>/
        └── <symbol>/
            └── <symbol>_<timeframe>.csv

Example:

candleset/binance/futures/JASMYUSDT/JASMYUSDT_M01.csv

The repository is intended to grow with additional exchanges, markets, symbols, and timeframes while keeping that hierarchy stable unless an exchange requires a documented exception.

Large CSV storage

CSV files are tracked through the Git LFS-compatible filter used by Git-Xet:

*.csv filter=lfs diff=lfs merge=lfs -text

That means Git commits contain small pointer objects for CSV files while Hugging Face stores the actual large-file content through Xet storage.

Git-Xet must be installed and integrated with Git on machines that create or update files under candleset/.

Verify the setup with:

git xet --version
git xet install

After the one-time setup, dataset updates use ordinary Git commands:

git pull
git add .
git commit -m "Update candlestick dataset"
git push

New CSV files and modified CSV files are handled by the same *.csv rule automatically. Do not remove the CSV rule from .gitattributes or intentionally commit large CSV contents as ordinary Git blobs.

Canonical candleset/ CSV schema

The Binance Vision playground publishes the repository's canonical per-symbol/timeframe CSV files with these columns:

timestamp
timehuman_iran
open
high
low
close
volume
quote_volume
trade_count
taker_buy_volume
taker_buy_quote_volume

timestamp is the authoritative Unix timestamp. timehuman_iran is an additional human-readable Asia/Tehran representation and is not the partitioning or ordering authority.

The lower-level Binance Vision downloader temporarily works with a richer internal long-form schema before the playground validates and transforms the data into the canonical candleset/ schema above.

Python package

The package metadata currently defines:

• package name: candlefetcher
• Python: >=3.12
• runtime dependencies: numpy, pandas, aiofiles, curl_cffi

Install the repository in editable mode:

python -m pip install -e .

For the test dependencies:

python -m pip install -e '.[test]'

Run the test suite with:

pytest

Binance Vision example

The project exposes synchronous and asynchronous Binance Vision acquisition helpers. A small synchronous example:

from candlefetcher.fetcher.download.binance_vision import download_binance_vision_candles

result = download_binance_vision_candles(
    symbols    = 'BTCUSDT',
    timeframes = 'M01',
    start      = '2024-01',
    end        = '2024-02',
    market     = 'spot',
    output     = 'file/binance_vision_raw.csv',
)

print(result)

start is inclusive and end is exclusive after request normalization. Friendly YYYY, YYYY-MM, and YYYY-MM-DD bounds are supported by the Binance Vision request model.

Use playground/binance_vision_downloader.ipynb when publishing canonical files into candleset/; the playground performs the additional transformation and structural audit before atomic publication.

Development rules

Read AGENTS.md before modifying the project. It is the repository authority for:

• architecture and repository layout;
• mandatory shared utilities;
• code formatting and docstring conventions;
• test/documentation expectations;
• Git authorship and commit policy;
• handling of candleset/ and Git-Xet-managed CSV files.

Canonical remote

The canonical Git remote is the Hugging Face Dataset repository:

https://huggingface.co/datasets/MostafaRoohy/Project_CandleFetcher

A historical GitHub repository may still exist, but it is not assumed to be synchronized with this repository unless explicitly requested.