tyche-transforms 0.1.6

Transformation functions for Tyche market data pipelines

Tyche Transforms

This package provides the transformation functions defined in MARKETS_INFO.md for Tyche market data pipelines, operating on xarray DataArray inputs. The intent is to keep the same implementations between local development and the Chainlink adapter.

Install

uv pip install tyche-transforms

For development:

uv pip install -e ".[test]"

Usage

import pandas as pd
import xarray as xr
from tyche_transforms.transforms import daily_average, hdd, runlen_lt

times = pd.date_range("2024-01-01", periods=3)
data = xr.DataArray([15.0, 10.0, 8.0], dims="time", coords={"time": times})
print(daily_average(data))
print(hdd(data))
print(runlen_lt(data, threshold=9.0))

GitHub Actions

This repo includes a workflow that runs tests on every push/PR and publishes to PyPI when you push a tag matching v* (for example v0.2.0). To enable publishing:

1. Add a repository secret named PYPI_API_TOKEN containing your PyPI token.
2. Push a version tag:

git tag v0.2.0
git push origin v0.2.0

Transformation Functions

DataArray -> DataArray

• CONVERT_M_TO_MM (0 args): convert meters to millimeters.
• CONVERT_KELVIN_TO_CELSIUS (0 args): convert Kelvin to Celsius.
• CUMULATIVE_TO_INCREMENT (0 args): convert cumulative totals to daily increments.
• DAILY_AVERAGE (0 args): resample to daily mean values.
• DAILY_SUM (0 args): resample to daily sum values.
• DAILY_MAX (0 args): resample to daily maximum values.
• DAILY_MIN (0 args): resample to daily minimum values.
• HDD (0 args): daily temperature -> HDD series (base 18 C).
• CDD (0 args): daily temperature -> CDD series (base 18 C).

DataArray -> Scalar

• SUM (0 args): sum over window -> scalar.
• AVG (0 args): average over window -> scalar.
• MAX (0 args): max over window -> scalar.
• INDEX_OF_MAX_VALUE (0 args): index of the max value -> scalar.
• MIN (0 args): min over window -> scalar.
• DATE_MAX (0 args): timestamp of the max value -> scalar (timestamp).
• DATE_FIRST:threshold (1 arg): timestamp of first value > threshold, or epoch pd.Timestamp(0) if none -> scalar (timestamp).
• RUNLEN_LT:threshold (1 arg): longest run length where value < threshold -> scalar.
• RUNLEN_GT:threshold (1 arg): longest run length where value > threshold -> scalar.

Scalar -> Scalar

• ABS (0 args): absolute value of a scalar -> scalar.
• SUBTRACT_V:threshold (1 arg): subtract a scalar to the given threshold -> scalar.