piccolo
Kedro
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piccolo | Kedro | |
---|---|---|
7 | 29 | |
1,266 | 9,353 | |
3.9% | 1.5% | |
8.6 | 9.7 | |
8 days ago | 7 days ago | |
Python | Python | |
MIT License | 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.
piccolo
- Piccolo, a Lightweight and Async Pydantic V2 Python ORM
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[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try Piccolo instead of SQLAlchemy
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Python projects with best practices on Github?
One other project that I enjoyed reading - to integrate with, is Picollo ORM (https://github.com/piccolo-orm/piccolo). The code is really readable.
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Piccolo - a modern, async query builder / ORM for Postgres
Hi, I'm a big fan of Postgres, and have been working on Piccolo for the last few years.
- GitHub - piccolo-orm/piccolo: A fast, user friendly ORM and query builder which supports asyncio.
- Piccolo: Python fast, user friendly ORM and query builder with asyncio
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Piccolo, an async query builder and ORM for Python
Give Piccolo a go. It is already being used in production, and is improving at a rapid pace. If you have any feedback or questions, let us know on Github. Thanks!
Kedro
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Nextflow: Data-Driven Computational Pipelines
Interesting, thanks for sharing. I'll definitely take a look, although at this point I am so comfortable with Snakemake, it is a bit hard to imagine what would convince me to move to another tool. But I like the idea of composable pipelines: I am building a tool (too early to share) that would allow to lay Snakemake pipelines on top of each other using semi-automatic data annotations similar to how it is done in kedro (https://github.com/kedro-org/kedro).
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A Polars exploration into Kedro
# pyproject.toml [project] dependencies = [ "kedro @ git+https://github.com/kedro-org/kedro@3ea7231", "kedro-datasets[pandas.CSVDataSet,polars.CSVDataSet] @ git+https://github.com/kedro-org/kedro-plugins@3b42fae#subdirectory=kedro-datasets", ]
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What are some open-source ML pipeline managers that are easy to use?
So there's 2 sides to pipeline management: the actual definition of the pipelines (in code) and how/when/where you run them. Some tools like prefect or airflow do both of them at once, but for the actual pipeline definition I'm a fan of https://kedro.org. You can then use most available orchestrators to run those pipelines on whatever schedule and architecture you want.
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How do data scientists combine Kedro and Databricks?
We have set up a milestone on GitHub so you can check in on our progress and contribute if you want to. To suggest features to us, report bugs, or just see what we're working on right now, visit the Kedro projects on GitHub.
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How do you organize yourself during projects?
you could use a project framework like kedro to force you to be more disciplined about how you structure your projects. I'd also recommend checking out this book: Edna Ridge - Guerrilla Analytics: A Practical Approach to Working with Data
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Futuristic documentation systems in Python, part 1: aiming for more
Recently I started a position as Developer Advocate for Kedro, an opinionated data science framework, and one of the things we're doing is exploring what are the best open source tools we can use to create our documentation.
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Python projects with best practices on Github?
You can also check out Kedro, it’s like the Flask for data science projects and helps apply clean code principles to data science code.
- Data Science/ Analyst Zertifikate für den Job Markt?
- What are examples of well-organized data science project that I can see on Github?
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Dabbling with Dagster vs. Airflow
An often overlooked framework used by NASA among others is Kedro https://github.com/kedro-org/kedro. Kedro is probably the simplest set of abstractions for building pipelines but it doesn't attempt to kill Airflow. It even has an Airflow plugin that allows it to be used as a DSL for building Airflow pipelines or plug into whichever production orchestration system is needed.
What are some alternatives?
tortoise-orm - Familiar asyncio ORM for python, built with relations in mind
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
prisma-client-py - Prisma Client Python is an auto-generated and fully type-safe database client designed for ease of use
Dask - Parallel computing with task scheduling
piccolo_admin - A powerful web admin for your database.
cookiecutter-pytorch - A Cookiecutter template for PyTorch Deep Learning projects.
django-firebird - Firebird SQL backend for Django web framework
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
yt-dlp-bot - Self-hosted Video Download Telegram Bot 🇺🇦
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!