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News & links about Python programming.
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Processing large JSON files in Python without running out of memory

If you need to process a large JSON file in Python, it’s very easy to run out of memory. One common solution is streaming parsing, aka lazy parsing, iterative parsing, or chunked processing. Let’s see how you can apply this technique to JSON processing.

https://pythonspeed.com/articles/json-memory-streaming/
Atomos – Atomic Primitives for Python

https://atomos.readthedocs.io/en/latest/
You Can Do Really Cool Things With Functions In Python

Here are a few not-so-common things you can do with functions in Python, including closures and partial function application. Functions are incredibly powerful and you can use them to write code that's really clean and often a lot shorter than when relying on classes and object-oriented programming.

https://www.youtube.com/watch?v=ph2HjBQuI8Y
How we parallelized 600+ pandas functions with Modin

Scaling up pandas is hard. With Modin, we took a first-principles approach to parallelizing the pandas API. Rather than focus on implementing what we knew was easy, we developed a theoretical basis for dataframes—the abstraction underlying pandas—and derived a dataframe algebra that can express the 600+ pandas operators in under 20 algebraic operators.

https://ponder.io/how-do-we-parallelized-600-pandas-functions-with-modin/
Text Similarity w/ Levenshtein Distance in Python

Building a Plagiarism Detection Pipeline in Python.

https://t.co/sBwLcaclXt
Real Time Inference on Raspberry Pi 4 (30 fps!)

https://pytorch.org/tutorials/intermediate/realtime_rpi.html
Working with Image Data in Python

In this video I show how to work with image data in python! Using the popular python packages matplotlib and opencv you will learn how to open image data, how the data is formatted, some ways to manipulate the data and save it off in a different format.

https://www.youtube.com/watch?v=kSqxn6zGE0c
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Efficient Pandas Dataframes in Python

In this video Rob Mulla teaches how to make your pandas dataframes more efficient by casting dtypes correctly. This will make your code faster, use less memory and smaller when saving to disk or a database.

https://www.youtube.com/watch?v=u4_c2LDi4b8
Object Oriented Programming (OOPS) in Python

Object oriented programming is an effective way of writing code. You create classes which are ...

https://www.machinelearningplus.com/python/object-oriented-programming-oops-in-python/
This Is Why Python Data Classes Are Awesome

Data classes in Python are really powerful and not just for representing structured data. In this video I show you what you can do with dataclasses as well as new capabilities that have been added in Python 3.10.

https://www.youtube.com/watch?v=CvQ7e6yUtnw