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EarthDaily Agriculture🔗

earthdaily-agriculture is a Python toolkit for bulk analytics extraction from the EarthDaily Agriculture APIs — vegetation-index time series, weather, crop detection, disease risk, emergence/harvest, scoring, and more. Every analytic is exposed as an extractor that turns a DataFrame of fields (id + geometry + optional crop/dates) into a tidy results DataFrame, with shared token management, column mapping, parallel bulk processing, optional caching, and HTML reporting.

Install🔗

pip install earthdaily-agriculture

import earthdaily.agriculture

The package installs into the shared earthdaily namespace, alongside sibling packages such as earthdaily-earthone. Python 3.10–3.12 is supported.

Quick start🔗

from earthdaily.agriculture.services.workflow_manager import WorkflowManager
from earthdaily.agriculture.extractors.coverage_function import CoverageExtractor
import pandas as pd

# 1. Authenticate + load config (reads credentials from the environment / .env)
manager = WorkflowManager("prod")

# 2. A DataFrame of fields — minimally an id + a WKT geometry
entities = pd.DataFrame([
    {"id": "field_001", "geometry": "POLYGON ((...))"},
])

# 3. Configure an extractor and run it in bulk
coverage = CoverageExtractor(manager.bearer_token, manager.token_expiration, config=manager.config)
coverage.setup_coverage_parameters(vegetation_index="NDVI", start_date="2025-01-01", clear_cover_min=95)
results = coverage.process_entity_coverage_bulk_parallel(entity_list=entities, max_workers=5)

Every extractor follows the same shape: __init__(token, expiration, config) → setup_<type>_parameters(...) → process_<type>_bulk_parallel(entity_list=...).

Where to go next🔗