fugue
pg-mem
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fugue | pg-mem | |
---|---|---|
11 | 14 | |
1,876 | 1,802 | |
2.3% | - | |
6.7 | 6.6 | |
6 days ago | 6 days ago | |
Python | TypeScript | |
Apache License 2.0 | MIT License |
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.
fugue
- FLaNK Stack Weekly 22 January 2024
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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?
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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.
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The hand-picked selection of the best Python libraries and tools of 2022
fugue — distributed computing done easy
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[P] Open data transformations in Python, no SQL required
This looks similar to fugue, am I right? How do they compare?
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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.
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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.
pg-mem
- Setting up PostgreSQL for running integration tests
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Show HN: I open-sourced the in-memory PostgreSQL I built at work for E2E tests
I've used pgmem https://github.com/oguimbal/pg-mem for the last couple of years for the same thing.
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Ask HN: How do you test SQL?
I was wondering the other day how to classify tests that use a test double like pg-mem, which isn't a mock but isn't the Dockerized test DB either :
https://github.com/oguimbal/pg-mem
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How to test nestjs modules?
In my case, I use TypeORM with PostgreSQL, and there's pg-mem to run an instance in memory, it supports most of the common functionality of PostgreSQL but you will need to do some adjustment to your code to be within the limits.
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Working with offline data
Postgres in the browser is possible through pg-mem: "pg-mem is an experimental in-memory emulation of a postgres database" but it also suffers from no persistence. If you can persist to a file somewhere then read it in on startup (and if your local data isn't huge) this might work.
- Pg-mem: An in-memory re-implementation of PostgreSQL in JavaScript
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Haskell as a first timer - Am I missing something ? Or is something broken ?
Dont get me wrong: I am trying to contribute to opensource as well, so I get that supporting small projects can be demanding. There's nothing wrong in not spending your weekends on OS. But not asking for help, nor specifying that a project is unmaintained, nor even answering issues & pull requests for years feels just wrong.
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Ask HN: What Are You Working On?
A pure Javascript in memory emulation of Posgres, to help writing better node tests https://github.com/oguimbal/pg-mem
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pg-mem, an in memory postgres DB instance for your unit tests, is now bound to multiple libraries (Knex, Typeorm, Slonik, pg, pg-promise) ... suggestions for the next one ?
Okay, I had a bit of spare time,I've implemented that, and it is now available with [email protected]
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Zero delay development & unit testing iterations
To get a glimpse of what I'm talking about, you can clone this repo and follow "Development" instructions (by the way this is a small OS lib I maintain, I wrote about it here)
What are some alternatives?
modin - Modin: Scale your Pandas workflows by changing a single line of code
NeDB - The JavaScript Database, for Node.js, nw.js, electron and the browser
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.
Prisma - Next-generation ORM for Node.js & TypeScript | PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, MongoDB and CockroachDB
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
Lowdb - Simple and fast JSON database
mlToolKits - learningOrchestra is a distributed Machine Learning integration tool that facilitates and streamlines iterative processes in a Data Science project.
typescript-clean-architecture - It is my attempt to create Clean Architecture based application in TypeScript.
xarray - N-D labeled arrays and datasets in Python
maplibre-gl-js - MapLibre GL JS - Interactive vector tile maps in WebGL2
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
database-js - Common Database Interface for Node