Optimus
fugue
Our great sponsors
| Optimus | fugue | |
|---|---|---|
| - | 11 | |
| 1,441 | 1,869 | |
| 0.9% | 1.9% | |
| 1.9 | 6.7 | |
| 8 days ago | 10 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Optimus
We haven't tracked posts mentioning Optimus yet.
Tracking mentions began in Dec 2020.
fugue
- FLaNK Stack Weekly 22 January 2024
-
Daft: A High-Performance Distributed Dataframe Library for Multimodal Data
Please integrate it with Fugue.
https://github.com/fugue-project/fugue
- Fugue: A unified interface for distributed computing
- [Discussion] Open Source beats Google's AutoML for Time series
- Ask HN: How do you test SQL?
-
Replacing Pandas with Polars. A Practical Guide
Fugue is an interesting library in this space , though I haven’t tried it
https://github.com/fugue-project/fugue
A unified interface for distributed computing. Fugue executes SQL, Python, and Pandas code on Spark, Dask and Ray without any rewrites.
-
The hand-picked selection of the best Python libraries and tools of 2022
fugue — distributed computing done easy
-
[P] Open data transformations in Python, no SQL required
This looks similar to fugue, am I right? How do they compare?
-
What the Duck?!
I am looking forward to how Substrait could help removing this friction. It aims to provide a standardised intermediate query language (lower level than SQL) to connect frontend user interfaces like SQL or data frame libraries with backend analytical computing engines. It is linked to the Arrow ecosystem. Something like Ibis or Fugue could become the front and DuckDB the backend engine.
-
Pyspark now provides a native Pandas API
There's dask-sql, but I think it is being abandoned for fugue-project. I'm actually excited for this project as it is trying to provide a backend agnostic solution, which would seem like a difficult, lofty goal. I wish them luck.
What are some alternatives?
AWS Data Wrangler - pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
modin - Modin: Scale your Pandas workflows by changing a single line of code
sweetviz - Visualize and compare datasets, target values and associations, with one line of code.
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
ga-extractor - Tool for extracting Google Analytics data suitable for migrating to other platforms/databases
mlToolKits - learningOrchestra is a distributed Machine Learning integration tool that facilitates and streamlines iterative processes in a Data Science project.
zef - Toolkit for graph-relational data across space and time
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
xarray - N-D labeled arrays and datasets in Python
flashtext - Extract Keywords from sentence or Replace keywords in sentences.
chispa - PySpark test helper methods with beautiful error messages