requests
scikit-learn
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requests | scikit-learn | |
---|---|---|
87 | 81 | |
51,359 | 58,046 | |
0.5% | 1.0% | |
8.4 | 9.9 | |
3 days ago | 6 days ago | |
Python | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" 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.
requests
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Revived the promise made six years ago for Requests 3
For many years now, Requests has been frozen. Being left in a vegetative state and not evolving, this blocked millions of developers from using more advanced features.
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Ask HN: Is Python async/await some kind of joke?
- Ubiquitous “requests” library used in most docs examples, no async support https://github.com/psf/requests
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10 Github repositories to achieve Python mastery
Explore here.
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urllib3 v2.0.0 is now generally available!
It's Lukasa (his name is Cory, there's Łukasz in PSF though, but that's a different person). Looking at him, he made significant contributions to the requests repo: https://github.com/psf/requests/graphs/contributors
- I built a chatbot that lets you talk to any Github repository
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I Could Rewrite Curl
> I'd love to see the look on some of these people's faces when they find out that tool/software/whatever they use is actually using libcurl under the hood.
Python dependencies (does not include curl)
https://devguide.python.org/getting-started/setup-building/i...
The "requests" module in Python (does not use curl)
https://github.com/psf/requests
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Development environment for the Python requests package
This part can be found in the README of the GitHub repository.
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Trying to install autoscan from https://github.com/NiNiyas/autoscan and stuck with no idea what the problem is.
Looking around for similar errors I found this issue where they recommended trying to use a newer version of the urllib3 library.
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Pain when going back to other languages
but I appreciate the fact that there is an issue about it, it's acknowledged and .. unfixable, it would now break too many things https://github.com/psf/requests/issues/2002
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How do you decide when to keep a project in a single python file vs break it up into multiple files?
The requests package has been the golden standard for package structure for as long as I can remember.
scikit-learn
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AutoCodeRover resolves 22% of real-world GitHub in SWE-bench lite
Thank you for your interest. There are some interesting examples in the SWE-bench-lite benchmark which are resolved by AutoCodeRover:
- From sympy: https://github.com/sympy/sympy/issues/13643. AutoCodeRover's patch for it: https://github.com/nus-apr/auto-code-rover/blob/main/results...
- Another one from scikit-learn: https://github.com/scikit-learn/scikit-learn/issues/13070. AutoCodeRover's patch (https://github.com/nus-apr/auto-code-rover/blob/main/results...) modified a few lines below (compared to the developer patch) and wrote a different comment.
There are more examples in the results directory (https://github.com/nus-apr/auto-code-rover/tree/main/results).
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Polars
sklearn is adding support through the dataframe interchange protocol (https://github.com/scikit-learn/scikit-learn/issues/25896). scipy, as far as I know, doesn't explicitly support dataframes (it just happens to work when you wrap a Series in `np.array` or `np.asarray`). I don't know about PyTorch but in general you can convert to numpy.
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[D] Major bug in Scikit-Learn's implementation of F-1 score
Wow, from the upvotes on this comment, it really seems like a lot of people think that this is the correct behavior! I have to say I disagree, but if that's what you think, don't just sit there upvoting comments on Reddit; instead go to this PR and tell the Scikit-Learn maintainers not to "fix" this "bug", which they are currently planning to do!
- Contraction Clustering (RASTER): A fast clustering algorithm
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Ask HN: Learning new coding patterns – how to start?
I was in a similar boat to yours - Worked in data science and since then have made a move to data engineering and software engineering for ML services.
I would recommend you look into the Design Patterns book by the Gang of Four. I found it particularly helpful to make extensible code that doesn't break specially with abstract classes, builders and factories. I would also recommend looking into the book The Object Oriented Thought Process to understand why traditional OOP is build the way it is.
You can also look into the source code of popular data science libraries such as sklearn (https://github.com/scikit-learn/scikit-learn/tree/main/sklea...) and see how a lot of them have Base classes to define shared functionality between object of the same nature.
As others mentioned, I would also encourage you to try and implement design patterns in your everyday work - maybe you can make a Factory to load models or preprocessors that follow the same Abstract class?
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Transformers as Support Vector Machines
It looks like you've been the victim of some misinformation. As Dr_Birdbrain said, an SVM is a convex problem with unique global optimum. sklearn.SVC relies on libsvm which initializes the weights to 0 [0]. The random state is only used to shuffle the data to make probability estimates with Platt scaling [1]. Of the random_state parameter, the sklearn documentation for SVC [2] says
Controls the pseudo random number generation for shuffling the data for probability estimates. Ignored when probability is False. Pass an int for reproducible output across multiple function calls. See Glossary.
[0] https://github.com/scikit-learn/scikit-learn/blob/2a2772a87b...
[1] https://en.wikipedia.org/wiki/Platt_scaling
[2] https://scikit-learn.org/stable/modules/generated/sklearn.sv...
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How to Build and Deploy a Machine Learning model using Docker
Scikit-learn Documentation
- Planning to get a laptop for ML/DL, is this good enough at the price point or are there better options at/below this price point?
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Link Prediction With node2vec in Physics Collaboration Network
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy.
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WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole.
What are some alternatives?
urllib3 - urllib3 is a user-friendly HTTP client library for Python
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
httplib2 - Small, fast HTTP client library for Python. Features persistent connections, cache, and Google App Engine support. Originally written by Joe Gregorio, now supported by community.
Surprise - A Python scikit for building and analyzing recommender systems
grequests - Requests + Gevent = <3
Keras - Deep Learning for humans
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
tensorflow - An Open Source Machine Learning Framework for Everyone
treq - Python requests like API built on top of Twisted's HTTP client.
gensim - Topic Modelling for Humans
Uplink - A Declarative HTTP Client for Python
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.