Skip to main content

FastETL custom package Apache Airflow provider.

Project description

FastETL's logo. It's a Swiss army knife with some open tools

FastETL framework, modern, versatile, does almost everything.

Este texto também está disponível em português: 🇧🇷LEIAME.md.


CI Tests

FastETL is a plugins package for Airflow for building data pipelines for a number of common scenarios.

Main features:

  • Full or incremental replication of tables in SQL Server, Postgres and MySQL databases
  • Load data from GSheets and from spreadsheets on Samba/Windows networks
  • Extracting CSV from SQL
  • Clean data using custom data patching tasks (e.g. for messy geographical coordinates, mapping canonical values for columns, etc.)
  • Querying the Brazilian National Official Gazette's (DOU's) API
  • Using a Open Street Routing Machine service to calculate route distances
  • Using CKAN or dados.gov.br's API to update dataset metadata
  • Using Frictionless Tabular Data Packages to write OpenDocument Text format data dictionaries

This framework is maintained by a network of developers from many teams at the Ministry of Management and Innovation in Public Services and is the cumulative result of using Apache Airflow, a free and open source tool, starting in 2019.

For government: FastETL is widely used for replication of data queried via Quartzo (DaaS) from Serpro.

Installation in Airflow

FastETL implements the standards for Airflow plugins. To install it, simply add the apache-airflow-providers-fastetl package to your Python dependencies in your Airflow environment.

Or install it with

pip install apache-airflow-providers-fastetl

To see an example of an Apache Airflow container that uses FastETL, check out the airflow2-docker repository.

To ensure appropriate results, please make sure to install the msodbcsql17 and unixodbc-dev libraries on your Apache Airflow workers.

Tests

The test suite uses Docker containers to simulate a complete use environment, including Airflow and the databases. For that reason, to execute the tests, you first need to install Docker and docker-compose.

For people using Ubuntu 20.04, you can just type on the terminal:

snap install docker

For other versions and operating systems, see the official Docker documentation.

To build the containers:

make setup

To run the tests, use:

make setup && make tests

To shutdown the environment, use:

make down

Usage examples

The main FastETL feature is the DbToDbOperator operator. It copies data between postgres and mssql databases. MySQL is also supported as a source.

Here goes an example:

from datetime import datetime
from airflow import DAG
from fastetl.operators.db_to_db_operator import DbToDbOperator

default_args = {
    "start_date": datetime(2023, 4, 1),
}

dag = DAG(
    "copy_db_to_db_example",
    default_args=default_args,
    schedule_interval=None,
)


t0 = DbToDbOperator(
    task_id="copy_data",
    source={
        "conn_id": airflow_source_conn_id,
        "schema": source_schema,
        "table": table_name,
    },
    destination={
        "conn_id": airflow_dest_conn_id,
        "schema": dest_schema,
        "table": table_name,
    },
    destination_truncate=True,
    copy_table_comments=True,
    chunksize=10000,
    dag=dag,
)

More detail about the parameters and the workings of DbToDbOperator can bee seen on the following files:

How to contribute

To be written on the CONTRIBUTING.md document (issue #4).

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

apache-airflow-providers-fastetl-0.0.12.tar.gz (74.4 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file apache-airflow-providers-fastetl-0.0.12.tar.gz.

File metadata

File hashes

Hashes for apache-airflow-providers-fastetl-0.0.12.tar.gz
Algorithm Hash digest
SHA256 3b32f4f26da4520c5ceff5d30972c2b182a1c4e598bbc48447721b67b948c3e7
MD5 078a2f875c8b7d91b7c7a3250d6262cb
BLAKE2b-256 ce87b34288cd0be7fcca32cb2471a17b22903a3dc50be64370da302528423c8d

See more details on using hashes here.

File details

Details for the file apache_airflow_providers_fastetl-0.0.12-py3-none-any.whl.

File metadata

File hashes

Hashes for apache_airflow_providers_fastetl-0.0.12-py3-none-any.whl
Algorithm Hash digest
SHA256 9ddb7f0bec30a7313da82d8565d5f17e5978ed6b9eab382784dc6f0d6c5ff1b2
MD5 db3abce3fbf438a2a0ab1992f15bd23c
BLAKE2b-256 2ce98f1b5101129e0c6c864356efb62e23e0294767ef0543fb5facb26eb3e977

See more details on using hashes here.

Supported by

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