Skip to main content

D.ata C.ollection F.ramework - Define a data source, run dcf, query the data

Project description

dcf

PyPI Python License

D.ata C.ollection F.ramework

uvx --from dcf-core dcf init

How it works

  1. Define a data collector in YAML — source, schema, cadence
  2. Run it with dcf run
  3. Query data from your data lake

Quickstart

Get real data. From an API. Into your Lakehouse. Query it with SQL. In 5 lines.

mkdir dcf-demo && cd dcf-demo
uvx --from dcf-core dcf init
uv sync
uv run dcf run so_questions
uv run dcf query 'SELECT * FROM stackoverflow.so_questions'

dcf init creates pyproject.toml, project.yml, .gitignore, collectors/, and an example collector.


Example

dcf collector

name: so_questions
namespace: stackoverflow

source:
  type: http
  url: https://api.stackexchange.com/2.3/questions
  method: GET
  response:
    records_path: items
  params:
    - {name: site,     type: string,  value: stackoverflow}
    - {name: tagged,   type: string,  value: "python;data-engineering"}
    - {name: order,    type: string,  value: asc}
    - {name: sort,     type: string,  value: creation}
    - {name: pagesize, type: integer, value: 100}
    - {name: fromdate, type: string,  format: "%s"}
    - {name: todate,   type: string,  format: "%s"}
  schema:
    columns:
      - {name: question_id,   path: question_id,   type: integer}
      - {name: title,         path: title,         type: string}
      - {name: score,         path: score,         type: integer}
      - {name: answer_count,  path: answer_count,  type: integer}
      - {name: view_count,    path: view_count,    type: integer}
      - {name: creation_date, path: creation_date, type: integer}
      - {name: link,          path: link,          type: string}

cadence:
  strategy: incremental
  primary_key: question_id
  iterate:
    - type: date_range
      params: [fromdate, todate]
      start: "2024-01-01"
      end: today
      step: 30 days

deployment:
  schedule: "0 8 * * *"

dcf run

uv run dcf run so_questions

dcf query

uv run dcf query 'SELECT * FROM stackoverflow.so_questions LIMIT 5'

Contributing

git clone https://github.com/zephschafer/dcf && cd dcf && uv sync

Point a local project at your checkout:

[tool.uv.sources]
dcf-core = { path = "../dcf", editable = true }

To verify changes:

uv run dcf run so_questions
uv run dcf query 'SELECT * FROM stackoverflow.so_questions'

Releasing: bump version in pyproject.toml and push to main — GitHub Actions publishes to PyPI automatically.


Package structure

dcf/
├── cli.py              Entry point (Typer)
├── config/
│   ├── models.py       Pydantic models for collector YAML
│   └── loader.py       YAML loading + env var resolution
├── engine/
│   ├── runner.py       Outer loop (iterate → fetch → project → write)
│   ├── fetcher.py      HTTP and Python source fetchers
│   ├── iterator.py     Date range and categorical iteration
│   ├── projector.py    Schema projection and path extraction
│   └── transforms.py   Column transforms
├── writer/
│   └── iceberg.py      Write strategies (incremental / append / full_refresh)
└── gcp/                GCP auth, provisioning, Terraform wrappers

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dcf_core-1.0.5.tar.gz (61.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dcf_core-1.0.5-py3-none-any.whl (65.5 kB view details)

Uploaded Python 3

File details

Details for the file dcf_core-1.0.5.tar.gz.

File metadata

  • Download URL: dcf_core-1.0.5.tar.gz
  • Upload date:
  • Size: 61.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.14 {"installer":{"name":"uv","version":"0.11.14","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}

File hashes

Hashes for dcf_core-1.0.5.tar.gz
Algorithm Hash digest
SHA256 f7e5aecbb1adfea5e63bab691611c580d52f25296217131b7d87d483b1552ffd
MD5 19476e700f2cba8964c77c5c849784c7
BLAKE2b-256 7f9f319dc5e8250f37e7e4185d33a3e153cdb5a1d5a548ef59631c6bf04f6de1

See more details on using hashes here.

File details

Details for the file dcf_core-1.0.5-py3-none-any.whl.

File metadata

  • Download URL: dcf_core-1.0.5-py3-none-any.whl
  • Upload date:
  • Size: 65.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.14 {"installer":{"name":"uv","version":"0.11.14","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}

File hashes

Hashes for dcf_core-1.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 8d40e822ecc8695e4c0e3e4019e19d5d141efc7b6f7950f976fb53898503f488
MD5 d0674e295a082d825ea1990bd2b32a1e
BLAKE2b-256 b3d704b44b7c87b7c28d984ed282e3ccf7bb06435832711373fff55fa034cf4b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page