cheatsheets
CPython
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cheatsheets | CPython | |
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126 | 1302 | |
7,219 | 59,047 | |
0.9% | 1.7% | |
7.1 | 10.0 | |
23 days ago | 3 days ago | |
Python | Python | |
BSD 2-clause "Simplified" License | GNU General Public License v3.0 or later |
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cheatsheets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Matplotlib - A Python 2D plotting library.
- Ask HN: What plotting tools should I invest in learning?
- Help with an array
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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What else should I complete before applying for a data analyst role?
programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not https://cs50.harvard.edu/python/2022/ https://matplotlib.org/
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[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
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[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
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About to lose access to MATLAB, is Python a realistic replacement for DSP algorithm development?
Edit: recommended libraries A python version of Matlab plotting down to the syntaxes matching.
- What is something you wish there was a Python module for?
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Suggestions for Udemy, Coursera, DataCamp, Pluralsight courses for Pandas and Visualization? So many options out there...project-based ones would be ideal. Or the ones to avoid or overrated courses?
https://matplotlib.org https://seaborn.pydata.org
CPython
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Open source at Fastly is getting opener
Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).
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C++ Safety, in Context
In my understanding, no. I believe it was bpo-4489 [1], and I couldn't find a matching advisory from the PSF's database [2] which should contain all historical advisories as well.
- The GIL can now be disabled in Python's main branch
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Eloquent JavaScript 4th edition (2024)
How do you mean? CPython uses karatsuba's for large numbers which should be asymptotically fast
https://github.com/python/cpython/blob/d864b0094f9875c5613cb...
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Top Paying Programming Technologies 2024
24. Python - $78,331
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What is really an API? Examples, Code + History
a. Setting Up: Make sure you have Python and pip (package installer) installed. If you do not have Python, you can install the latest version from the Python ecosystem here
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How to make a turtle racing game in Python
First, if you don't have Python installed on your machine, go to python.org to download the latest version of Python and then install it right away.
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PySimpleGUI 4 will be sunsetted in Q2 2024
You missed that they gave an example that does work—Java Swing is bundled with the JVM, making it more or less part of the standard library. Python itself also has Tkinter, which exists inside the cpython repo and is installed with Python [0].
C++ may not work, but most other languages (especially VM-based) can and many do.
[0] https://github.com/python/cpython/blob/3.12/Lib/tkinter/__in...
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Memray – A Memory Profiler for Python
I collected a list of profilers (also memory profilers, also specifically for Python) here: https://github.com/albertz/wiki/blob/master/profiling.md
Currently I actually need a Python memory profiler, because I want to figure out whether there is some memory leak in my application (PyTorch based training script), and where exactly (in this case, it's not a problem of GPU memory, but CPU memory).
I tried Scalene (https://github.com/plasma-umass/scalene), which seems to be powerful, but somehow the output it gives me is not useful at all? It doesn't really give me a flamegraph, or a list of the top lines with memory allocations, but instead it gives me a listing of all source code lines, and prints some (very sparse) information on each line. So I need to search through that listing now by hand to find the spots? Maybe I just don't know how to use it properly.
I tried Memray, but first ran into an issue (https://github.com/bloomberg/memray/issues/212), but after using some workaround, it worked now. I get a flamegraph out, but it doesn't really seem accurate? After a while, there don't seem to be any new memory allocations at all anymore, and I don't quite trust that this is correct.
There is also Austin (https://github.com/P403n1x87/austin), which I also wanted to try (have not yet).
Somehow this experience so far was very disappointing.
(Side node, I debugged some very strange memory allocation behavior of Python before, where all local variables were kept around after an exception, even though I made sure there is no reference anymore to the exception object, to the traceback, etc, and I even called frame.clear() for all frames to really clear it. It turns out, frame.f_locals will create another copy of all the local variables, and the exception object and all the locals in the other frame still stay alive until you access frame.f_locals again. At that point, it will sync the f_locals again with the real (fast) locals, and then it can finally free everything. It was quite annoying to find the source of this problem and to find workarounds for it. https://github.com/python/cpython/issues/113939)
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Setting Up the Environment
Python, a versatile and powerful programming language, can be easily installed from its official website: https://www.python.org/. This section will guide you through the installation process on various operating systems, including Windows, macOS, and Linux.
What are some alternatives?
RustPython - A Python Interpreter written in Rust
finplot - Performant and effortless finance plotting for Python
ipython - Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
Vulpix - Fast, unopinionated, minimalist web framework for .NET core inspired by express.js
manim - A community-maintained Python framework for creating mathematical animations.
Visual Studio Code - Visual Studio Code
Fast-F1 - FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
Automatic-Udemy-Course-Enroller-GET-PAID-UDEMY-COURSES-for-FREE - Do you want to LEARN NEW STUFF for FREE? Don't worry, with the power of web-scraping and automation, this script will find the necessary Udemy coupons & enroll you for PAID UDEMY COURSES, ABSOLUTELY FREE!
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Camunda BPM - Flexible framework for workflow and decision automation with BPMN and DMN. Integration with Quarkus, Spring, Spring Boot, CDI.
Django - The Web framework for perfectionists with deadlines.
go - The Go programming language