django-sql-explorer
Ray
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django-sql-explorer | Ray | |
---|---|---|
4 | 42 | |
2,200 | 30,879 | |
0.6% | 2.8% | |
8.3 | 10.0 | |
1 day 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.
django-sql-explorer
- Online Django Development Sprint, October 19-20.
- Saving Filtered Querysets for Future Access
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3% of 666 Python codebases we checked had a silently failing unit test
https://github.com/ansible-community/ara/pull/358 https://github.com/b12io/orchestra/pull/830 https://github.com/batiste/django-page-cms/pull/210 https://github.com/carpentries/amy/pull/2130 https://github.com/celery/django-celery/pull/612 https://github.com/django-cms/django-cms/pull/7241 https://github.com/django-oscar/django-oscar/pull/3867 https://github.com/esrg-knights/Squire/pull/253https://github.com/Frojd/django-react-templatetags/pull/64 https://github.com/groveco/django-sql-explorer/pull/474 https://github.com/jazzband/django-silk/pull/550 https://github.com/keras-team/keras/pull/16073 https://github.com/ministryofjustice/cla_backend/pull/773 https://github.com/nitely/Spirit/pull/306 https://github.com/python/pythondotorg/pull/1987 https://github.com/rapidpro/rapidpro/pull/1610 https://github.com/ray-project/ray/pull/22396 https://github.com/saltstack/salt/pull/61647 https://github.com/Swiss-Polar-Institute/project-application/pull/483 https://github.com/UEWBot/dipvis/pull/216
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Show HN: Django SQL Dashboard
Very cool! I wrote Django SQL Explorer[0], and this looks very similar in spirit, but an emphasis on visualization that Explorer does not have (to the extent it has a focus, it's more on providing a reasonable way to write complex queries and re-use them).
These types of tools are extremely handy.
Ray
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Open Source Advent Fun Wraps Up!
22. Ray | Github | tutorial
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Fine-Tuning Llama-2: A Comprehensive Case Study for Tailoring Custom Models
Training times for GSM8k are mentioned here: https://github.com/ray-project/ray/tree/master/doc/source/te...
- Ray – an open source project for scaling AI workloads
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Methods to keep agents inside grid world.
Here's a reference from RLlib that points to docs and an example, and here's one from one of my projects that includes all my own implementations
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TransformerXL + PPO Baseline + MemoryGym
RLlib
- Is dynamic action masking possible in Rllib?
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AWS re:Invent 2022 Recap | Data & Analytics services
⦿ AWS Glue Data Quality - Automatic data quality rule recommendations based on your data AWS Glue for Ray - Data integration with Ray (ray.io), a popular new open-source compute framework that helps you scale Python workloads
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Think about it for a second
https://ray.io (just dropping the link)
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Elixir Livebook now as a desktop app
I've wondered whether it's easier to add data analyst stuff to Elixir that Python seems to have, or add features to Python that Erlang (and by extension Elixir) provides out of the box.
By what I can see, if you want multiprocessing on Python in an easier way (let's say running async), you have to use something like ray core[0], then if you want multiple machines you need redis(?). Elixir/Erlang supports this out of the box.
Explorer[1] is an interesting approach, where it uses Rust via Rustler (Elixir library to call Rust code) and uses Polars as its dataframe library. I think Rustler needs to be reworked for this usecase, as it can be slow to return data. I made initial improvements which drastically improves encoding (https://github.com/elixir-nx/explorer/pull/282 and https://github.com/elixir-nx/explorer/pull/286, tldr 20+ seconds down to 3).
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Learn various techniques to reduce data processing time by using multiprocessing, joblib, and tqdm concurrent
Adding these for anyone who had a similar question about Ray vs dask 1, 2, 3
What are some alternatives?
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
optuna - A hyperparameter optimization framework
django-tastypie - Creating delicious APIs for Django apps since 2010.
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
django-modern-rpc - Simple XML-RPC and JSON-RPC server for modern Django
Faust - Python Stream Processing
Python Blogs - A curated list of python programming language blogs
gevent - Coroutine-based concurrency library for Python
django-template - A battle-tested Django 2.1 project template with configurations for AWS, Heroku, App Engine, and Docker.
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
django-admin-interface - :superhero: :zap: django's default admin interface with superpowers - customizable themes, popup windows replaced by modals and many other features.
SCOOP (Scalable COncurrent Operations in Python) - SCOOP (Scalable COncurrent Operations in Python)