alpha-isnow 0.1.7

A library to for https://alpha.isnow.ai

alpha-isnow

alpha-isnow is a Python library to load daily asset data (Stocks, ETFs, Indices, and Cryptocurrencies) from Cloudflare R2 and merge them into a single Pandas DataFrame. The library:

• Lists parquet files stored under bucket_name/ds/<repo_id>/*.parquet for each asset.
• Validates that the monthly slices (files named as YYYY.MM.parquet) are continuous with no missing months.
• Supports loading data concurrently using a configurable number of threads (default is 4).
• Uses Python's built-in logging module to log messages to the console (default level is ERROR).

Installation

When you install alpha-isnow via pip, its dependencies (pandas, s3fs, boto3) will be automatically installed. To install the package:

pip install alpha-isnow

Usage

from alpha.datasets import load_daily, AssetType

# Load all available months of stock data
df = load_daily(
    asset_type=AssetType.Stocks,
    token={  # Optional, defaults to environment variables
        "R2_ENDPOINT_URL": "your-r2-endpoint",
        "R2_ACCESS_KEY_ID": "your-access-key",
        "R2_SECRET_ACCESS_KEY": "your-secret-key",
    }
)

# Load a specific range of months
df_range = load_daily(
    asset_type=AssetType.ETFs, 
    month_range=("2023.01", "2023.03")
)

print(f"Loaded {len(df)} records")

Function Parameters

The load_daily function accepts the following parameters:

• asset_type (AssetType): The type of asset to load (Stocks, ETFs, Indices, or Cryptocurrencies)
• month_range (tuple[str, str] | None): Optional tuple (start, end) with month strings in 'YYYY.MM' format. If None, loads all available months
• symbols (list[str] | None): Optional list of symbols to load. If None, loads all available symbols. If sp500 is in the list, it will be removed and SP500 symbols will be added.
• threads (int): Number of threads to use for concurrent loading (default: 4)
• adjust (bool): Whether to adjust prices using the adjustment factor (default: True)
• to_usd (bool): Whether to convert prices to USD (default: True)
  • For Forex: Inverts exchange rates (e.g., EURUSD becomes USDEUR)
  • For Indices: Converts to USD using corresponding currency exchange rates
• rate_to_price (bool): For Bonds, whether to convert interest rates to prices (default: True)
• token (dict | None): Optional dictionary containing R2 credentials:

  {
      "R2_ENDPOINT_URL": "your-r2-endpoint",
      "R2_ACCESS_KEY_ID": "your-access-key",
      "R2_SECRET_ACCESS_KEY": "your-secret-key"
  }
  

  If None, environment variables are used
• cache (bool): Whether to use local caching for improved performance (default: False)

The package uses a namespace package structure, so even though the package name is alpha-isnow, you import it with from alpha.datasets import ...

Logging Configuration

The library uses Python's standard logging module with a default level of ERROR. You can configure the logging level to get more detailed information:

import logging
from alpha.datasets import set_log_level

# Set log level for all modules to DEBUG
set_log_level(logging.DEBUG)

# Or set log level for a specific module
set_log_level(logging.INFO, module="loader")

Available log levels:

• logging.DEBUG: Detailed debugging information
• logging.INFO: Confirmation that things are working as expected
• logging.WARNING: Indication that something unexpected happened
• logging.ERROR: Error that prevented a function from working (default)
• logging.CRITICAL: Critical error that prevents the program from continuing

Example with logging enabled:

import logging
from alpha.datasets import set_log_level, load_daily, AssetType

# Enable informational logging
set_log_level(logging.INFO)

# Now load data (with logging output)
df = load_daily(AssetType.Stocks, month_range=("2023.01", "2023.02"))

Development

Installation for Development

For development, install the package in editable mode with development dependencies:

pip install -e ".[dev]"

This will install:

• Runtime dependencies (pandas, s3fs, boto3, pyarrow)
• Development tools:
  • pytest: For running tests
  • black: For code formatting
  • isort: For import sorting
  • mypy: For type checking
  • flake8: For code quality checks
  • build: For building distribution packages
  • twine: For uploading to PyPI

Building and Releasing

To build distribution packages:

# Build both wheel and source distribution
python -m build

# The packages will be created in the dist/ directory

To release to PyPI:

# Upload to PyPI (requires PyPI credentials)
python -m twine upload dist/*

# Or upload to TestPyPI first (recommended for first-time releases)
python -m twine upload --repository testpypi dist/*

Note: You only need to upload the latest version. PyPI will maintain the version history automatically.

To upload a specific version:

# Upload specific version files
python -m twine upload dist/alpha_isnow-<version>

# Or upload to TestPyPI
python -m twine upload --repository testpypi dist/alpha_isnow-<version>

PyPI Configuration

Before uploading to PyPI, you need to configure your credentials. Create or edit ~/.pypirc file:

[pypi]
username = __token__
password = your-pypi-token

[testpypi]
username = __token__
password = your-testpypi-token

Replace your-pypi-token and your-testpypi-token with your actual PyPI and TestPyPI tokens. You can generate these tokens from your PyPI account settings.

Local Cache

The library implements a local caching mechanism to improve data loading performance:

• Cache location: ~/.alpha_isnow_cache/
• Cache format: Parquet files named as {repo_name}_{month}.parquet
• Cache validity: 24 hours
• Performance: Loading from cache is typically 100x faster than loading from R2

Running Tests

# Run all tests
pytest tests/

# Run specific test file
pytest tests/test_loader.py

# Run tests with verbose output
pytest -v tests/test_loader.py

Code Quality

The project follows Python best practices:

• Code formatting with black
• Import sorting with isort
• Type checking with mypy
• Code quality checks with flake8

All code changes should pass these checks before being committed.