whylogs
Pelican
whylogs | Pelican | |
---|---|---|
6 | 23 | |
2,548 | 12,263 | |
0.9% | 1.1% | |
9.0 | 8.7 | |
3 days ago | 13 days ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
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.
whylogs
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The hand-picked selection of the best Python libraries and tools of 2022
whylogs — model monitoring
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Data Validation tools
Have a look at whylogs. Nice profiling functionality incl. definition of constraints on profiles: https://github.com/whylabs/whylogs
- [D] Open Source ML Organisations to contribute to?
- whylogs: The open standard for data logging
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I am Alessya Visnjic, co-founder and CEO of WhyLabs. I am here to talk about MLOps, AI Observability and our recent product announcements. Ask me anything!
WhyLabs has an open-source first approach. We maintain an open standard for data and ML logging https://github.com/whylabs/whylogs, which allows anybody to begin logging statistical properties of data in their data pipeline, ML inference, feature stores, etc. These statistical profiles capture all the key signals to enable observability in a given component. This unique approach means that we can run a fully SaaS service, which allows for huge scalability (in both the size of models and their number), and ensures that our customers are able to maintain their data autonomy. We maintain a huge array of integrations for whylogs, including Python, Spark, Kafka, Ray, Flask, MLflow, Kubeflow, etc… Once the profiles are captured systematically, they are centralized in the WhyLabs platform, where we organize them, run forecasting and anomaly detection on each metric, and surface alerts to users. The platform itself has a zero-config design philosophy, meaning all monitoring configurations can be set up using smart baselines and require no manual configuration. The TL;DR here is the focus on open source integrations, working with data at massive/streaming scale, and removing manual effort from maintaining configuration.
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Machine learning’s crumbling foundations – by Cory Doctorow
This is why we've been trying to encourage people to think about lightweight data logging as a mitigation for data quality problems. Similar to how we monitor applications with Prometheus, we should approach ML monitoring with the same rigor.
Disclaimer: I'm one of the authors. We spend a lot of effort to build the standard for data logging here: https://github.com/whylabs/whylogs. It's meant to be a lightweight and open standard for collecting statistical signatures of your data without having to run SQL/expensive analysis.
Pelican
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Patterns for Personal Web Sites
In my experience, [Pelican](https://getpelican.com/) does a good job of allowing you to edit themes on all pages at once with its static page generator.
There are a lot of built in features designed more for blog-like websites, but I’ve found it pretty easy to make my personal website with it.
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How To Choose the Best Static Site Generator and Deploy it to Kinsta for Free
Pelican is a preferred option for Python developers.
- Pelican: Static site generator written in Python. Requires no database
- Why isn’t there a python version of Jekyll / Hugo
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How to host final project (flask web application) on permanent server?
There's also Pelican but I haven't used it and seeing as Github serves static pages I'd imagine it builds and deploys your page and is done with it.
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Ask HN: Which Python or Rust-based static site generators to use as of 2023?
I use Pelican (https://getpelican.com/) for my blog, which works decently for me. It is a static site generator written in Python.
But you probably won't learn much Python by using it (or Rust when using a generator written in it) since you probably won't need to change anything in it.
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Creating a Python Wiki application
Surely a "local private wiki ... not web based ... on a desktop application" is not really a "wiki" at all, but rather a "static site generator" with a built-in "search". If that's what you want, there's a Python app called Pelican. Writing such an app from scratch isn't really a beginners project.
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Top ten popular static site generators (SSG) in 2023
Pelican — best for Python developers
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Trying to work around a Jekyll site-building tutorial without using Jekyll
You can - you'd basically just create a python script that parses your HTML/CSS files and replaces strings with values from your YAML. However I wouldn't recommend that unless you're just using this as an opportunity to learn Python. If you want to standup a real site and you want to use python, I'd recommend a Python static site generator like Pelican or Nikola.
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Help me find a suitable static site generator
As you're familiar with Python, how about https://getpelican.com?
What are some alternatives?
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
Lektor - The lektor static file content management system
graphsignal-python - Graphsignal Tracer for Python
Nikola - A static website and blog generator
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Hugo - The world’s fastest framework for building websites.
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Hyde - A Python Static Website Generator
datatap-python - Focus on Algorithm Design, Not on Data Wrangling
Jekyll - :globe_with_meridians: Jekyll is a blog-aware static site generator in Ruby
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
Cactus - Static site generator for designers. Uses Python and Django templates.