4 pre-commit Plugins to Automate Code Reviewing and Formatting in Python
Write High-Quality Code with black, flake8, isort, and interrogateContinue reading on Towards Data ...
https://towardsdatascience.com/4-pre-commit-plugins-to-automate-code-reviewing-and-formatting-in-python-c80c6d2e9f5
Write High-Quality Code with black, flake8, isort, and interrogateContinue reading on Towards Data ...
https://towardsdatascience.com/4-pre-commit-plugins-to-automate-code-reviewing-and-formatting-in-python-c80c6d2e9f5
Efficient Pagination in Django and Postgres
This article will help you understand Django’s pagination limitations and offer three alternative methods that will improve your application’s performance. Along the way, you’ll see the tradeoffs and use cases for each method so you can decide which is the best fit for your application.
https://pganalyze.com/blog/pagination-django-postgres
This article will help you understand Django’s pagination limitations and offer three alternative methods that will improve your application’s performance. Along the way, you’ll see the tradeoffs and use cases for each method so you can decide which is the best fit for your application.
https://pganalyze.com/blog/pagination-django-postgres
pganalyze
Efficient Pagination: PostgreSQL and Django
We look at 3 different methods for pagination with Django and Postgres and explain their benefits and tradeoffs so you can decide which is the best fit for you.
A Natural Language Processing (NLP) Primer
Overview of common NLP tasks using Python.
https://t.co/EfZyeAsUy9
Overview of common NLP tasks using Python.
https://t.co/EfZyeAsUy9
Medium
A Natural Language Processing (NLP) Primer
Overview of common NLP tasks using Python
Moving SciPy to the Meson build system
https://labs.quansight.org/blog/2021/07/moving-scipy-to-meson/
https://labs.quansight.org/blog/2021/07/moving-scipy-to-meson/
Quansight Labs
Moving SciPy to the Meson build system
Let's start with an announcement: SciPy now builds with
Meson on Linux, and the full test suite passes!
This is a pretty exciting milestone, and good news for SciPy maintainers and
contributors - they
Meson on Linux, and the full test suite passes!
This is a pretty exciting milestone, and good news for SciPy maintainers and
contributors - they
MaskFormer
Per-Pixel Classification is Not All You Need for Semantic Segmentation.
https://github.com/facebookresearch/MaskFormer
Per-Pixel Classification is Not All You Need for Semantic Segmentation.
https://github.com/facebookresearch/MaskFormer
GitHub
GitHub - facebookresearch/MaskFormer: Per-Pixel Classification is Not All You Need for Semantic Segmentation (NeurIPS 2021, spotlight)
Per-Pixel Classification is Not All You Need for Semantic Segmentation (NeurIPS 2021, spotlight) - facebookresearch/MaskFormer
Introducing Triton: Open-Source GPU Programming for Neural Networks
Triton is an open-source Python-like programming language which enables researchers with no CUDA experience to write highly efficient GPU code—most of the time on par with what an expert would be able to produce. Triton makes it possible to reach peak hardware performance with relatively little effort.
https://openai.com/blog/triton/
Triton is an open-source Python-like programming language which enables researchers with no CUDA experience to write highly efficient GPU code—most of the time on par with what an expert would be able to produce. Triton makes it possible to reach peak hardware performance with relatively little effort.
https://openai.com/blog/triton/
Openai
Introducing Triton: Open-source GPU programming for neural networks
We’re releasing Triton 1.0, an open-source Python-like programming language which enables researchers with no CUDA experience to write highly efficient GPU code—most of the time on par with what an expert would be able to produce.
Towards data-centric machine learning: a short review
Data-centric machine learning shifts the focus from fiddling model
hyperparameters, to ensuring ...
https://ljvmiranda921.github.io/notebook/2021/07/30/data-centric-ml/
Data-centric machine learning shifts the focus from fiddling model
hyperparameters, to ensuring ...
https://ljvmiranda921.github.io/notebook/2021/07/30/data-centric-ml/
ljvmiranda921.github.io
Study notes on data-centric machine learning
Data-centric machine learning shifts the focus from fiddling model hyperparameters to ensuring quality data across all. This post is a short review on variou...
Python PDF Handling Tutorial
In this tutorial, learn how to do various operations like: Extracting and Adding Pages, Texts, Images, Tables, Watermark and much more on a PDF file using Python.
https://github.com/prajwollamichhane11/PDF-Handling-With-Python
In this tutorial, learn how to do various operations like: Extracting and Adding Pages, Texts, Images, Tables, Watermark and much more on a PDF file using Python.
https://github.com/prajwollamichhane11/PDF-Handling-With-Python
GitHub
GitHub - prajwollamichhane11/PDF-Handling-With-Python: Performing the following operations using python on PDF.
Performing the following operations using python on PDF. - prajwollamichhane11/PDF-Handling-With-Python
How to install Python Poetry in GitHub Actions in MUCH faster way
We use Poetry in a GitHub project. There's a pyproject.toml file (and a poetry.lock file) which ...
https://www.peterbe.com/plog/install-python-poetry-github-actions-faster
We use Poetry in a GitHub project. There's a pyproject.toml file (and a poetry.lock file) which ...
https://www.peterbe.com/plog/install-python-poetry-github-actions-faster
Peterbe
How to install Python Poetry in GitHub Actions in MUCH faster way - Peterbe.com
Python, OCaml, and Machine Learning (2020)
https://signalsandthreads.com/python-ocaml-and-machine-learning/
https://signalsandthreads.com/python-ocaml-and-machine-learning/
Signalsandthreads
Signals and Threads Podcast
Listen in on Jane Street’s Ron Minsky as he has conversations with engineers working on everything from clock synchronization to reliable multicast, build systems to reconfigurable hardware. Get a peek at how Jane Street approaches problems, and how those…
Uniform Random Sampling of Strings from Context-Free Grammar
https://rahul.gopinath.org/post/2021/07/27/random-sampling-from-context-free-grammar/
https://rahul.gopinath.org/post/2021/07/27/random-sampling-from-context-free-grammar/
rahul.gopinath.org
Uniform Random Sampling of Strings from Context-Free Grammar
Research in Software Engineering from Rahul Gopinath
NumPy views: saving memory, leaking memory, and subtle bugs
https://pythonspeed.com/articles/numpy-memory-views/
https://pythonspeed.com/articles/numpy-memory-views/
Python⇒Speed
NumPy views: saving memory, leaking memory, and subtle bugs
NumPy uses memory views transparently, as a way to save memory. But you need to understand how they work, so you don’t leak memory, or modify data by mistake.
More Python Code Smells: Avoid These 7 Smelly Snags
These are 7 code smells to avoid + a bonus smell. The author describes each smell using a Python example and then shows you how to fix it. At the end of the video, there are few general tips to help you avoid introducing code smells in the first place in your design.
https://www.youtube.com/watch?v=zmWf_cHyo8s
These are 7 code smells to avoid + a bonus smell. The author describes each smell using a Python example and then shows you how to fix it. At the end of the video, there are few general tips to help you avoid introducing code smells in the first place in your design.
https://www.youtube.com/watch?v=zmWf_cHyo8s
YouTube
More Python Code Smells: Avoid These 7 Smelly Snags
💡 Learn how to design great software in 7 steps: https://arjan.codes/designguide.
These are 7 code smells to avoid plus a bonus smell. I describe each smell using a Python example and then show you how to fix it. At the end of the video, I have a few general…
These are 7 code smells to avoid plus a bonus smell. I describe each smell using a Python example and then show you how to fix it. At the end of the video, I have a few general…
Python3 Tips For Reverse Engineers
Five tips to level up your reverse engineering with Python 3.
https://www.youtube.com/watch?v=TrAwfQlfDd8
Five tips to level up your reverse engineering with Python 3.
https://www.youtube.com/watch?v=TrAwfQlfDd8
YouTube
Python3 Tips For Reverse Engineers
Five tips to level up your reverse engineering with Python 3. Expand for more...
-----
OALABS DISCORD
https://discord.gg/6h5Bh5AMDU
OALABS PATREON
https://www.patreon.com/oalabs
OALABS TIP JAR
https://ko-fi.com/oalabs
OALABS GITHUB
https://github.com/OALabs…
-----
OALABS DISCORD
https://discord.gg/6h5Bh5AMDU
OALABS PATREON
https://www.patreon.com/oalabs
OALABS TIP JAR
https://ko-fi.com/oalabs
OALABS GITHUB
https://github.com/OALabs…
How Airbnb Built “Wall” to prevent data bugs
In this post we will outline the challenges we faced while adding a massive number of data checks (i.e. data quality, accuracy, completeness and anomaly checks) to prevent data bugs company-wide, and how that motivated us to build a new framework to easily add data checks at scale.
https://medium.com/airbnb-engineering/how-airbnb-built-wall-to-prevent-data-bugs-ad1b081d6e8f
In this post we will outline the challenges we faced while adding a massive number of data checks (i.e. data quality, accuracy, completeness and anomaly checks) to prevent data bugs company-wide, and how that motivated us to build a new framework to easily add data checks at scale.
https://medium.com/airbnb-engineering/how-airbnb-built-wall-to-prevent-data-bugs-ad1b081d6e8f
Medium
How Airbnb Built “Wall” to prevent data bugs
Gaining trust in data with extensive data quality, accuracy and anomaly checks
A Large-Scale Security-Oriented Static Analysis of Python Packages in PyPI
This paper examines various security issues in Python packages with static analysis. The dataset is based on a snapshot of all packages stored to the Python Package Index (PyPI). In total, over 197 thousand packages and over 749 thousand security issues are covered.
https://arxiv.org/pdf/2107.12699.pdf
This paper examines various security issues in Python packages with static analysis. The dataset is based on a snapshot of all packages stored to the Python Package Index (PyPI). In total, over 197 thousand packages and over 749 thousand security issues are covered.
https://arxiv.org/pdf/2107.12699.pdf