Litestar
Litestar is a powerful, flexible yet opinionated ASGI framework, focused on building APIs, and offers high-performance data validation and parsing, dependency injection, first-class ORM integration, authorization primitives, and much more that's needed to get applications up and running.
https://github.com/litestar-org/litestar
Litestar is a powerful, flexible yet opinionated ASGI framework, focused on building APIs, and offers high-performance data validation and parsing, dependency injection, first-class ORM integration, authorization primitives, and much more that's needed to get applications up and running.
https://github.com/litestar-org/litestar
GitHub
GitHub - litestar-org/litestar: Production-ready, Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant…
Production-ready, Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs - litestar-org/litestar
How to add serverless functions to Django in 6 minutes (with HTMX and AWS Lambda)
This article discusses the integration of serverless functions with Django, highlighting how developers can leverage the benefits of serverless computing for specific tasks in a Django application. It explores the advantages of serverless architecture and provides practical insights for implementation.
https://www.photondesigner.com/articles/serverless-functions-django
This article discusses the integration of serverless functions with Django, highlighting how developers can leverage the benefits of serverless computing for specific tasks in a Django application. It explores the advantages of serverless architecture and provides practical insights for implementation.
https://www.photondesigner.com/articles/serverless-functions-django
Photondesigner
How to add serverless functions with Django in 6 mins (with HTMX and AWS Lambda) 🧠
Add serverless functions. Banish background worker mess.
ludwig-ai / ludwig
Low-code framework for building custom LLMs, neural networks, and other AI models
https://github.com/ludwig-ai/ludwig
Low-code framework for building custom LLMs, neural networks, and other AI models
https://github.com/ludwig-ai/ludwig
GitHub
GitHub - ludwig-ai/ludwig: Low-code framework for building custom LLMs, neural networks, and other AI models
Low-code framework for building custom LLMs, neural networks, and other AI models - ludwig-ai/ludwig
Galactic
Galactic provides cleaning and curation tools for massive unstructured text datasets. It's designed to help you curate fine-tuning datasets, create document collections for retrieval-augmented generation (RAG), and even perform deduplication of web-scale datasets for LLM pre-training. This
https://github.com/taylorai/galactic
Galactic provides cleaning and curation tools for massive unstructured text datasets. It's designed to help you curate fine-tuning datasets, create document collections for retrieval-augmented generation (RAG), and even perform deduplication of web-scale datasets for LLM pre-training. This
https://github.com/taylorai/galactic
GitHub
GitHub - taylorai/galactic: data cleaning and curation for unstructured text
data cleaning and curation for unstructured text. Contribute to taylorai/galactic development by creating an account on GitHub.
HomeHarvest
Python package for real estate scraping, supporting Zillow, Realtor.com & Redfin.
https://github.com/ZacharyHampton/HomeHarvest
Python package for real estate scraping, supporting Zillow, Realtor.com & Redfin.
https://github.com/ZacharyHampton/HomeHarvest
GitHub
GitHub - ZacharyHampton/HomeHarvest: Python package for scraping real estate property data
Python package for scraping real estate property data - ZacharyHampton/HomeHarvest
neulab / prompt2model
prompt2model - Generate Deployable Models from Natural Language Instructions
https://github.com/neulab/prompt2model
prompt2model - Generate Deployable Models from Natural Language Instructions
https://github.com/neulab/prompt2model
GitHub
GitHub - neulab/prompt2model: prompt2model - Generate Deployable Models from Natural Language Instructions
prompt2model - Generate Deployable Models from Natural Language Instructions - neulab/prompt2model
Python 3.12.0 release candidate 3 now available
https://pythoninsider.blogspot.com/2023/09/python-3120-release-candidate-3-now.html
https://pythoninsider.blogspot.com/2023/09/python-3120-release-candidate-3-now.html
Blogspot
Python Insider: Python 3.12.0 release candidate 3 now available
EuroPython 2023 Videos
Here are all the videos for the conference, brought to you by the EuroPython 2023 Team and the EuroPython Society.
https://www.youtube.com/playlist?list=PL8uoeex94UhFcwvAfWHybD7SfNgIUBRo-
Here are all the videos for the conference, brought to you by the EuroPython 2023 Team and the EuroPython Society.
https://www.youtube.com/playlist?list=PL8uoeex94UhFcwvAfWHybD7SfNgIUBRo-
PyGraft
Configurable Generation of Schemas and Knowledge Graphs at Your Fingertips.
https://github.com/nicolas-hbt/pygraft
Configurable Generation of Schemas and Knowledge Graphs at Your Fingertips.
https://github.com/nicolas-hbt/pygraft
GitHub
GitHub - nicolas-hbt/pygraft: Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips - nicolas-hbt/pygraft
19X faster response time
Lincoln Loop optimized a large publishing platform's database performance. Overall, the database performance increased 19 times.
https://lincolnloop.com/insights/optimizing-response-time-19x-faster/
Lincoln Loop optimized a large publishing platform's database performance. Overall, the database performance increased 19 times.
https://lincolnloop.com/insights/optimizing-response-time-19x-faster/
Lincoln Loop
19X faster response time
Lincoln Loop optimized a large publishing platform's database performance. Overall, the database performance increased 19 times.
facebookresearch / codellama
Inference code for CodeLlama models
https://github.com/facebookresearch/codellama
Inference code for CodeLlama models
https://github.com/facebookresearch/codellama
GitHub
GitHub - meta-llama/codellama: Inference code for CodeLlama models
Inference code for CodeLlama models. Contribute to meta-llama/codellama development by creating an account on GitHub.
vpselector
Visual Pandas Selector: Visualize and interactively select time-series data.
https://github.com/manumerous/vpselector
Visual Pandas Selector: Visualize and interactively select time-series data.
https://github.com/manumerous/vpselector
GitHub
GitHub - manumerous/vpselector: Visual Pandas Selector: Visualize and interactively select time-series data
Visual Pandas Selector: Visualize and interactively select time-series data - manumerous/vpselector
Speeding up Floyd-Steinberg dithering: an optimization exercise
A worked out example: optimizing low-level code to get significant performance and memory improvements.
https://pythonspeed.com/articles/optimizing-dithering/
A worked out example: optimizing low-level code to get significant performance and memory improvements.
https://pythonspeed.com/articles/optimizing-dithering/
Python⇒Speed
Speeding up your code when multiple cores aren’t an option
Parallelism isn’t the only answer: often you can optimize low-level code to get significant performance improvements.
Why Are There So Many Python Dataframes?
This post explores the proliferation of Python dataframes, dissecting the reasons behind their prevalence in data science and analysis, shedding light on the various libraries and frameworks that contribute to their abundance.
https://ponder.io/why-are-there-so-many-python-dataframes/
This post explores the proliferation of Python dataframes, dissecting the reasons behind their prevalence in data science and analysis, shedding light on the various libraries and frameworks that contribute to their abundance.
https://ponder.io/why-are-there-so-many-python-dataframes/
Ponder
Why Are There So Many Python Dataframes?
Introduction As I floated in the slow, crystalline current of the Rhine in Basel in the middle of the 2023 Python Dataframe Summit, I found myself asking: