Skip to main content

dcp-tools

Manage and load data to Data Commons Platform instances

PyPI PyPI - Python Version Docs Lint/format: Ruff

A Data Commons Platform instance takes your data as CSVs in a fixed variable-per-row shape, plus a config.json that maps each CSV's columns onto the Data Commons schema. If you're defining your own statistical variables, entities, or properties rather than reusing existing ones, you also need MCF (Meta Content Framework) files describing them. dcp-tools builds and validates that bundle in Python (or from the CLI) and uploads it to Cloud Storage to trigger the platform's ingestion workflow.

This package was published as bblocks-datacommons-tools until version 0.1.1, and imported as bblocks.datacommons_tools. Installing the old distribution now pulls in dcp-tools and redirects those imports with a DeprecationWarning, so existing code keeps working. Update imports to dcp_tools when convenient.

Install

pip install dcp-tools

Or from GitHub:

pip install git+https://github.com/ONEcampaign/dcp-tools

Quickstart

This builds a config and MCF for a source, a provenance, one input file, and one statistical variable, then exports the bundle to disk.

from pathlib import Path

import pandas as pd
from dcp_tools import CustomDataManager

manager = CustomDataManager()
manager.add_source(dcid="ONEData", url="https://data.one.org")
manager.add_provenance(
    dcid="ONEClimateFinance",
    url="https://datacommons.one.org/data/climate-finance-files",
    source="ONEData",
)

data = pd.DataFrame({
    "country": ["Kenya", "Kenya", "Vietnam"],
    "year": [2022, 2023, 2023],
    "variable": ["climateFinanceProvidedCommitments"] * 3,
    "value": [12.4, 15.1, 8.7],
})
manager.add_input_file(
    file_name="climate_finance/one_cf_provider_commitments.csv",
    provenance="ONEClimateFinance",
    data=data,
    column_mappings={
        "observationAbout": "country",
        "date": "year",
        "variable": "variable",
        "value": "value",
    },
    observation_properties={"unit": "USDollar"},
)

manager.add_variable_to_mcf(
    dcid="climateFinanceProvidedCommitments",
    name="Climate finance commitments (bilateral)",
    description="Funding committed for climate adaptation and mitigation projects",
    stat_type="dcid:measuredValue",
)

manager.add_mcf_file("*.mcf", provenance="ONEClimateFinance")

out_dir = Path("export/climate_finance")
out_dir.mkdir(parents=True, exist_ok=True)
manager.export_all(out_dir)

export_all writes config.json, the CSV, and both MCF files under out_dir. Since we never called set_import_name, config.json defaults importName to the export directory's name, and column mappings and the provenance name are resolved to full dcids:

{
    "importName": "climate_finance",
    "inputFiles": [
        {
            "filename": "climate_finance/one_cf_provider_commitments.csv",
            "provenance": "dcid:provenance/ONEClimateFinance",
            "columnMappings": {
                "dcid:variableMeasured": "variable",
                "dcid:observationDate": "year",
                "dcid:value": "value",
                "dcid:observationAbout": "country"
            },
            "observationProperties": {"unit": "USDollar"},
            "format": "variablePerRow"
        },
        {
            "pattern": "*.mcf",
            "provenance": "dcid:provenance/ONEClimateFinance"
        }
    ]
}

Loading it

Once you have a bundle on disk, dcp_tools.gcp_utilities uploads it and triggers ingestion:

from dcp_tools.gcp_utilities import (
    get_kg_settings,
    run_ingestion_workflow,
    upload_to_cloud_storage,
)

settings = get_kg_settings(source="env", env_file="customDC.env")
upload_to_cloud_storage(settings=settings, directory="export/climate_finance")
run_ingestion_workflow(settings=settings)

run_ingestion_workflow triggers the DCP (Data Commons Platform) ingestion workflow, which ingests the new data and serves it. There's no separate redeploy step to run. See the loading-data docs for the full settings reference, and the dcp-tools CLI (upload, ingest, pipeline), which wraps this same flow.

Contributing

Contributions are welcome! See CONTRIBUTING for how to get started, report bugs, and submit changes.

Metadata

Release files for dcp-tools 1.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dcp-tools 1.0.1
File Size Uploaded
dcp_tools-1.0.1.tar.gz 46.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for dcp-tools 1.0.1
File Interpreter ABI Platform
dcp_tools-1.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 103.5 kB

Release files / dcp_tools-1.0.1.tar.gz

Download URL dcp_tools-1.0.1.tar.gz
Size 46.7 kB
Tags Source
SHA-256 checksum
How to use checksums
d73eb5c93095b47f601a6ffd92f8dd94b2ffe090797eef5e96415f61141c1244
BLAKE2b-256 checksum
How to use checksums
376015df64896af5efa8adba07ec9be4df6d35a181c8aaf507c4290eea70fada
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.13.0 {"installer":{"name":"uv","version":"0.13.0","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release files / dcp_tools-1.0.1-py3-none-any.whl

Download URL dcp_tools-1.0.1-py3-none-any.whl
Size 56.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
1686bbfbf0edef4db88d73e4a2e5d3f9d11a28c6f37bf4307c0c7a7c6e3e96d3
BLAKE2b-256 checksum
How to use checksums
b424d17e45df5db6b176ece631d5351c3bfe04015eba3a14c745b83dff429b97
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.13.0 {"installer":{"name":"uv","version":"0.13.0","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page