ibis
PySpark-Boilerplate
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| ibis | PySpark-Boilerplate | |
|---|---|---|
| 22 | 1 | |
| 4,041 | 390 | |
| 7.2% | - | |
| 10.0 | 2.5 | |
| 4 days ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | - |
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ibis
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This Week In Python
ibis – portable Python dataframe library
- FLaNK Stack 26 February 2024
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Quarto
The main benefit is that you get a Python (or R, Julia or Rust) interpreter. So you can evaluate code. A good example of the value of this is the Ibis docs which use Quarto: https://ibis-project.org/
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Polars – A bird's eye view of Polars
Ive found polars quite intuitive, though for python, I lean more towards [ibis](https://ibis-project.org/). The interface is nearly identical, but ibis has the benefit if building sql queries before pulling any actual data (like dbplyr) — whereas polars requires the data to be in-memory (at least for rdb’s, though correct me if Im wrong)
this to me seems like a good argument for only using ibis, but Im happy to be convinced otherwise
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Vanna.ai: Chat with your SQL database
Please add Ibis Birdbrain https://ibis-project.github.io/ibis-birdbrain/ to the list. Birdbrain is an AI-powered data bot, built on Ibis and Marvin, supporting more than 18 database backends.
See https://github.com/ibis-project/ibis and https://ibis-project.org for more details.
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How to Use Pandas for Data Analysis
Ibis: The portable Python dataframe library
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Upcoming Data Engineering Tools
We have Ibis which helps you write generic analytics pipelines and it supports multiple backends and you can either run these pipeline on a query processing engine or a pyspark cluster or even on Pandas or Polars.
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A LLM+OLAP Solution
Ibis could also be a target. It compiles queries written in python to multiple dataframe libraries, and SQL targets.
- DuckDB: Querying JSON files as if they were tables
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DuckDB – in-process SQL OLAP database management system
You might be interested in checking out Ibis (https://ibis-project.org/). It provides a dataframe-like API, abstracting over many common execution engines (duckdb, postgres, bigquery, spark, ...). Ibis wrapping duckdb has pretty much replaced pandas as my tool of choice for local data analysis. All the performance of duckdb with all the ergonomics of a dataframe API. (disclaimer: I contribute to Ibis for work).
PySpark-Boilerplate
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Tracking mentions began in Dec 2020.
What are some alternatives?
snowflake-connector-python - Snowflake Connector for Python
Apache Impala - Apache Impala
pangres - SQL upsert using pandas DataFrames for PostgreSQL, SQlite and MySQL with extra features
sqlite_scanner - DuckDB extension to read and write to SQLite databases
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
nodejs-polars - nodejs front-end of polars
cookiecutter-django - Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly.
katacoda
etl-markup-toolkit - ETL Markup Toolkit is a spark-native tool for expressing ETL transformations as configuration
django-clickhouse - This project's goal is to build Yandex ClickHouse database into Django project.
store - PostgreSQL shopping cart
prql - PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement