Python

Python utility for tracking third party dependencies within a library - GitHub - IBM/import-tracker: Python utility for tracking third party dependencies within a library

I show toy implementations of Python decorator patterns that may be useful for Data Scientists.

Memray is a memory profiler for Python. Contribute to bloomberg/memray development by creating an account on GitHub.

The Thread class allows you to create and manage new threads of execution in Python. Although the threads have been available since Python 2, it is not widely used, perhaps because of misunderstand…

A Python Library for Graph Outlier Detection (Anomaly Detection) - GitHub - pygod-team/pygod: A Python Library for Graph Outlier Detection (Anomaly Detection)

Loading complete JSON files into Python can use too much memory, leading to slowness or crashes. The solution: process JSON data one chunk at a time.

Learn what it means for code to be Pythonic and explore three ways you can write clear, Pythonic code right now.

It’s almost 2021. Memory is inexpensive and it’s easy to access cloud platforms like Amazon Web Services (AWS) or Google Cloud Platform…

Pydbantic inherits its’ name from pydantic, a library for “Data parsing and validation using Python type hints”.

There are so many amazing Python libraries out there that it's hard to keep track of all of them. That's why we share with you our hand-picked selection of some top libraries.

In this course, you'll learn what an exception is and how it differs from a syntax error. You'll learn about raising exceptions, making assertions, and catching exceptions to change the control flow of your program using the try, except, else, and finally keywords.

I do a lot of web scraping in my spare time, and have been chasing down different formats and code snippets to make a large amount of network requests locally, with controls for rate limiting and error handling.

Diagram as Code

Decision tree visualization

A guide to writing more responsive and performant programs

In this tutorial, you'll learn how you can configure, extend, and optimize Visual Studio Code for a more effective and productive Python development environment. By digging into this customizable code editor and IDE, you'll put yourself on track to be a VS Code power user.

A collection of simple python mini projects to enhance your python skills - Python-World/python-mini-projects: A collection of simple python mini projects to enhance your python skills

Most intros to LSTM models use natural language processing as the motivating application, but LSTMs can be a good option for multivariable time series regression and classification as well. Here's how to structure the data and model to make it work.

Learn how to carry out the Cohort Analysis to better understand the customers’ behavior

The "breathing k-means" algorithm with datasets and example notebooks - gittar/breathing-k-means: The "breathing k-means" algorithm with datasets and example notebooks

I have more than one Python environment configured in my Debian OS. Is there a way to list all configured environments in Linux? This is different from the possible duplicate as indicated in the c...

Learn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library./bbr/br/ Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio/i teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading.

So I have a dataset that I would like to remove stop words from using stopwords.words('english') I'm struggling how to use this within my code to just simply take out these words. I have a list ...

Suppose I have pandas DataFrame like this: >>> df = pd.DataFrame({'id':[1,1,1,2,2,2,2,3,4],'value':[1,2,3,1,2,3,4,1,1]}) >>> df id value 0 1 1 1 1 2 2 1 ...

Merlion: A Machine Learning Framework for Time Series Intelligence - salesforce/Merlion: Merlion: A Machine Learning Framework for Time Series Intelligence

Histogramming for analysis powered by boost-histogram - scikit-hep/hist: Histogramming for analysis powered by boost-histogram