python pandas etl example

Luigi is an open source Python package developed by Spotify. Make learning your daily ritual. ETL is the process of fetching data from one or many systems and loading it into a target data warehouse after doing some intermediate transformations. Like with all types of analysis, there are always tradeoffs to be made and pros and cons of using particular techniques over others. Airflow’s core technology revolves around the construction of Directed Acyclic Graphs (DAGs), which allows its scheduler to spread your tasks across an array of workers without requiring you to define precise parent-child relationships between data flows. It is designed for efficient and intuitive handling and processing of structured data. Originally developed at Airbnb, Airflow is the new open source hotness of modern data infrastructure. Since yesterday I have airflow running on a vm ubuntu-postgres solution. Bonobo is a lightweight, code-as-configuration ETL framework for Python. One of Carry’s differentiating features is that it can automatically create and store views based on migrated SQL data for the user’s future reference.

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In the load process, the transformed data is loaded into the target warehouse database. It’s designed to make the management of long-running batch processes easier, so it can handle tasks that go far beyond the scope of ETL--but it does ETL pretty well, too. Whether you are looking for just standard ETL functionality or if you are looking for more add-on features and sophistication, Python may be a good choice.
Bubbles is written in Python, but is actually designed to be technology agnostic. petl has a lot of the same capabilities as pandas, but is designed more specifically for ETL work and doesn’t include built-in analysis features, so it might be right for you if you’re interested purely in ETL. It’s set up to work with data objects--representations of the data sets being ETL’d--in order to maximize flexibility in the user’s ETL pipeline. The team at Capital One Open Source Projects has developed locopy, a Python library for ETL tasks using Redshift and Snowflake that supports many Python DB drivers and adapters for Postgres. The project was conceived when the developer realized the majority of his organization’s data was stored in an Oracle 9i database, which has been unsupported since 2010. etlalchemy was designed to make migrating between relational databases with different dialects easier and faster. As an alternative to going pure Python in your ETL deployment, you may want to take a look at Avik Cloud.

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