[P] Human Action Classification: Reproducible baselines for UCF-101 (87%) and Stanford40 (88.5%) with training code + pretrained models
# Human Action Classification: Reproducible Research Baselines
Hey r/MachineLearning! I built reproducible baselines for human action recognition that I wish existed when I started.
# 🎯 What This Is
**Not an attempt to beat or compare with SOTA.** This is a reference baseline for research and development. Most repos I found are unmaintained with irreproducible results, with no pretrained models. This repo provides:
* ✅ Reproducible training pipeline
* ✅ Pretrained models on HuggingFace
* ✅ Complete documentation
* ✅ Two approaches: Video (temporal) + Image (pose-based)
# 📊 Results
**Video Models (UCF-101 - 101 classes):**
* MC3-18: **87.05%** accuracy (published: 85.0%)
* R3D-18: **83.80%** accuracy (published: 82.8%)
**Image Models (Stanford40 - 40 classes):**
* ResNet50: **88.5%** accuracy
* Real-time: 90 FPS with pose estimation
# 🎬 Demo (Created using test samples)
https://i.redd.it/diopygguk72g1.gif
# 🔗 Links
* GitHub: [https://github.com/dronefreak/human-action-classification](https://github.com/dronefreak/human-action-classification)
* HuggingFace Models:
* MC3-18: [https://huggingface.co/dronefreak/mc3-18-ucf101](https://huggingface.co/dronefreak/mc3-18-ucf101)
* R3D-18: [https://huggingface.co/dronefreak/r3d-18-ucf101](https://huggingface.co/dronefreak/r3d-18-ucf101)
* Stanford40 Models: [https://huggingface.co/dronefreak/human-action-classification-stanford40](https://huggingface.co/dronefreak/human-action-classification-stanford40)
# 💡 Why I Built This
Every video classification paper cites UCF-101, but finding working code is painful:
* Repos abandoned 3+ years ago
* Tensorflow 1.x dependencies
* Missing training scripts
* No pretrained weights
This repo is what I needed: a clean starting point with modern PyTorch, complete training code, and published pre-trained models.
# 🤝 Contributions Welcome
Looking for help with:
* Additional datasets (Kinetics, AVA, etc.)
* Two-stream
/r/MachineLearning
https://redd.it/1p16kqx
# Human Action Classification: Reproducible Research Baselines
Hey r/MachineLearning! I built reproducible baselines for human action recognition that I wish existed when I started.
# 🎯 What This Is
**Not an attempt to beat or compare with SOTA.** This is a reference baseline for research and development. Most repos I found are unmaintained with irreproducible results, with no pretrained models. This repo provides:
* ✅ Reproducible training pipeline
* ✅ Pretrained models on HuggingFace
* ✅ Complete documentation
* ✅ Two approaches: Video (temporal) + Image (pose-based)
# 📊 Results
**Video Models (UCF-101 - 101 classes):**
* MC3-18: **87.05%** accuracy (published: 85.0%)
* R3D-18: **83.80%** accuracy (published: 82.8%)
**Image Models (Stanford40 - 40 classes):**
* ResNet50: **88.5%** accuracy
* Real-time: 90 FPS with pose estimation
# 🎬 Demo (Created using test samples)
https://i.redd.it/diopygguk72g1.gif
# 🔗 Links
* GitHub: [https://github.com/dronefreak/human-action-classification](https://github.com/dronefreak/human-action-classification)
* HuggingFace Models:
* MC3-18: [https://huggingface.co/dronefreak/mc3-18-ucf101](https://huggingface.co/dronefreak/mc3-18-ucf101)
* R3D-18: [https://huggingface.co/dronefreak/r3d-18-ucf101](https://huggingface.co/dronefreak/r3d-18-ucf101)
* Stanford40 Models: [https://huggingface.co/dronefreak/human-action-classification-stanford40](https://huggingface.co/dronefreak/human-action-classification-stanford40)
# 💡 Why I Built This
Every video classification paper cites UCF-101, but finding working code is painful:
* Repos abandoned 3+ years ago
* Tensorflow 1.x dependencies
* Missing training scripts
* No pretrained weights
This repo is what I needed: a clean starting point with modern PyTorch, complete training code, and published pre-trained models.
# 🤝 Contributions Welcome
Looking for help with:
* Additional datasets (Kinetics, AVA, etc.)
* Two-stream
/r/MachineLearning
https://redd.it/1p16kqx
GitHub
GitHub - dronefreak/human-action-classification: Modern human action classification system using MediaPipe pose estimation and…
Modern human action classification system using MediaPipe pose estimation and PyTorch deep learning, achieving 47x faster inference than the original TensorFlow implementation. Supports 100+ model ...
Pyrefly Beta Release (fast language server & type checker)
As of v0.42.0, Pyrefly has now graduated from Alpha to Beta.
At a high level, this means:
- The IDE extension is ready for production use right now
- The core type-checking features are robust, with some edge cases that will be addressed as we make progress towards a later stable v1.0 release
Below is a peek at some of the goodies that have been shipped since the Alpha launch in May:
Language Server/IDE:
- automatic import refactoring
- Jupyter notebook support
- Type stubs for third-party packages are now shipped with the VS Code extension
Type Checking:
- Improved type inference & type narrowing
- Special handling for Pydantic and Django
- Better error messages
For more details, check out the release announcement blog: https://pyrefly.org/blog/pyrefly-beta/
/r/Python
https://redd.it/1p1axnq
As of v0.42.0, Pyrefly has now graduated from Alpha to Beta.
At a high level, this means:
- The IDE extension is ready for production use right now
- The core type-checking features are robust, with some edge cases that will be addressed as we make progress towards a later stable v1.0 release
Below is a peek at some of the goodies that have been shipped since the Alpha launch in May:
Language Server/IDE:
- automatic import refactoring
- Jupyter notebook support
- Type stubs for third-party packages are now shipped with the VS Code extension
Type Checking:
- Improved type inference & type narrowing
- Special handling for Pydantic and Django
- Better error messages
For more details, check out the release announcement blog: https://pyrefly.org/blog/pyrefly-beta/
/r/Python
https://redd.it/1p1axnq
GitHub
GitHub - facebook/pyrefly: A fast type checker and language server for Python
A fast type checker and language server for Python - facebook/pyrefly
Django 6.0 release candidate 1 released
https://www.djangoproject.com/weblog/2025/nov/19/django-60-rc-released/
/r/django
https://redd.it/1p1a7q4
https://www.djangoproject.com/weblog/2025/nov/19/django-60-rc-released/
/r/django
https://redd.it/1p1a7q4
Django Project
Django 6.0 release candidate 1 released
Posted by Natalia Bidart on Nov. 19, 2025
Twenty years of Django releases
On November 16th 2005 - Django got its first release: 0.90 (don’t ask). Twenty years later, today we just shipped the first release candidate of [Django 6.0](https://docs.djangoproject.com/en/dev/releases/6.0/). I compiled a few stats for the occasion:
* **447 releases over 20 years**. Average of 22 per year. Seems like 2025 is special because we’re at 38.
* **131 security vulnerabilities addressed** in those releases. Lots of people poking at potential problems!
* **262,203 releases of Django-related packages**. Average of 35 per day, today we’re at 52 so far.
Full blog post: [Twenty years of Django releases](https://www.djangoproject.com/weblog/2025/nov/19/twenty-years-of-django-releases/). And we got JetBrains to extend their [30% off offer](https://www.jetbrains.com/pycharm/promo/support-django/) as a birthday gift of sorts
/r/Python
https://redd.it/1p1euh3
On November 16th 2005 - Django got its first release: 0.90 (don’t ask). Twenty years later, today we just shipped the first release candidate of [Django 6.0](https://docs.djangoproject.com/en/dev/releases/6.0/). I compiled a few stats for the occasion:
* **447 releases over 20 years**. Average of 22 per year. Seems like 2025 is special because we’re at 38.
* **131 security vulnerabilities addressed** in those releases. Lots of people poking at potential problems!
* **262,203 releases of Django-related packages**. Average of 35 per day, today we’re at 52 so far.
Full blog post: [Twenty years of Django releases](https://www.djangoproject.com/weblog/2025/nov/19/twenty-years-of-django-releases/). And we got JetBrains to extend their [30% off offer](https://www.jetbrains.com/pycharm/promo/support-django/) as a birthday gift of sorts
/r/Python
https://redd.it/1p1euh3
Django Project
Twenty years of Django releases
Posted by Thibaud Colas on Nov. 19, 2025
Python for Beginners: Build a Simple QR Code Generator in Minutes!
https://youtu.be/v5_lKGfnDmQ?si=VhbXqCo9_NoZBmE1
/r/djangolearning
https://redd.it/1p1b2js
https://youtu.be/v5_lKGfnDmQ?si=VhbXqCo9_NoZBmE1
/r/djangolearning
https://redd.it/1p1b2js
YouTube
Python Project for Beginners 🐍
In this beginner-friendly Python tutorial, you’ll learn how to create a simple QR Code Generator using just a few lines of code! This is a perfect first project for anyone starting with Python.
We’ll walk step-by-step through:
✔ Installing the required library…
We’ll walk step-by-step through:
✔ Installing the required library…
My first real project in python
Hi, I'm 15 and I recently started python. For my firt project I did a calculator.
Here is the program:
num1=int(input("choisissez un nombre"))
num2=int(input("choisissez un nombre")) #sélection des nombres
operator=int(input("choisissez un operateur 1=+ ;2=- ;3=/ "))
if operator ==1:
result=num1+num2
elif operator ==2: #calcule
result=num1-num2
elif operator ==3:
result=num1/num2
print("voici votre résultat",result)
I'm here for advice on this program and more generally on python.
If you have little project like this I take too.
Thank you for reading.
/r/Python
https://redd.it/1p1khap
Hi, I'm 15 and I recently started python. For my firt project I did a calculator.
Here is the program:
num1=int(input("choisissez un nombre"))
num2=int(input("choisissez un nombre")) #sélection des nombres
operator=int(input("choisissez un operateur 1=+ ;2=- ;3=/ "))
if operator ==1:
result=num1+num2
elif operator ==2: #calcule
result=num1-num2
elif operator ==3:
result=num1/num2
print("voici votre résultat",result)
I'm here for advice on this program and more generally on python.
If you have little project like this I take too.
Thank you for reading.
/r/Python
https://redd.it/1p1khap
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Thursday Daily Thread: Python Careers, Courses, and Furthering Education!
# Weekly Thread: Professional Use, Jobs, and Education 🏢
Welcome to this week's discussion on Python in the professional world! This is your spot to talk about job hunting, career growth, and educational resources in Python. Please note, this thread is not for recruitment.
---
## How it Works:
1. Career Talk: Discuss using Python in your job, or the job market for Python roles.
2. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
3. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally.
---
## Guidelines:
- This thread is not for recruitment. For job postings, please see r/PythonJobs or the recruitment thread in the sidebar.
- Keep discussions relevant to Python in the professional and educational context.
---
## Example Topics:
1. Career Paths: What kinds of roles are out there for Python developers?
2. Certifications: Are Python certifications worth it?
3. Course Recommendations: Any good advanced Python courses to recommend?
4. Workplace Tools: What Python libraries are indispensable in your professional work?
5. Interview Tips: What types of Python questions are commonly asked in interviews?
---
Let's help each other grow in our careers and education. Happy discussing! 🌟
/r/Python
https://redd.it/1p1o6zl
# Weekly Thread: Professional Use, Jobs, and Education 🏢
Welcome to this week's discussion on Python in the professional world! This is your spot to talk about job hunting, career growth, and educational resources in Python. Please note, this thread is not for recruitment.
---
## How it Works:
1. Career Talk: Discuss using Python in your job, or the job market for Python roles.
2. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
3. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally.
---
## Guidelines:
- This thread is not for recruitment. For job postings, please see r/PythonJobs or the recruitment thread in the sidebar.
- Keep discussions relevant to Python in the professional and educational context.
---
## Example Topics:
1. Career Paths: What kinds of roles are out there for Python developers?
2. Certifications: Are Python certifications worth it?
3. Course Recommendations: Any good advanced Python courses to recommend?
4. Workplace Tools: What Python libraries are indispensable in your professional work?
5. Interview Tips: What types of Python questions are commonly asked in interviews?
---
Let's help each other grow in our careers and education. Happy discussing! 🌟
/r/Python
https://redd.it/1p1o6zl
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
R Segment Anything Model 3 (SAM 3) is released
Abstract: We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short noun phrases (e.g., “yellow school bus”), image exemplars, or a combination of both. Promptable Concept Segmentation (PCS) takes such prompts and returns segmentation masks and unique identities for all matching object instances. To advance PCS, we build a scalable data engine that produces a high-quality dataset with 4M unique concept labels, including hard negatives, across images and videos. Our model consists of an image-level detector and a memory-based video tracker that share a single backbone. Recognition and localization are decoupled with a presence head, which boosts detection accuracy. SAM 3 doubles the accuracy of existing systems in both image and video PCS, and improves previous SAM capabilities on visual segmentation tasks. We open source SAM 3 along with our new Segment Anything with Concepts (SA-Co) benchmark for promptable concept segmentation.
Paper: https://ai.meta.com/research/publications/sam-3-segment-anything-with-concepts/
Demo: https://aidemos.meta.com/segment-anything
Code: https://github.com/facebookresearch/sam3
Website: https://ai.meta.com/sam3
/r/MachineLearning
https://redd.it/1p1cfvx
Abstract: We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short noun phrases (e.g., “yellow school bus”), image exemplars, or a combination of both. Promptable Concept Segmentation (PCS) takes such prompts and returns segmentation masks and unique identities for all matching object instances. To advance PCS, we build a scalable data engine that produces a high-quality dataset with 4M unique concept labels, including hard negatives, across images and videos. Our model consists of an image-level detector and a memory-based video tracker that share a single backbone. Recognition and localization are decoupled with a presence head, which boosts detection accuracy. SAM 3 doubles the accuracy of existing systems in both image and video PCS, and improves previous SAM capabilities on visual segmentation tasks. We open source SAM 3 along with our new Segment Anything with Concepts (SA-Co) benchmark for promptable concept segmentation.
Paper: https://ai.meta.com/research/publications/sam-3-segment-anything-with-concepts/
Demo: https://aidemos.meta.com/segment-anything
Code: https://github.com/facebookresearch/sam3
Website: https://ai.meta.com/sam3
/r/MachineLearning
https://redd.it/1p1cfvx
Meta
SAM 3: Segment Anything with Concepts | Research - AI at Meta
We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks
objects in images and videos based on concept prompts,...
objects in images and videos based on concept prompts,...
Flask-Assets-Pipeline: Modern assets pipeline with esbuild, tailwind and more
https://github.com/hyperflask/flask-assets-pipeline
/r/flask
https://redd.it/1p1z9gt
https://github.com/hyperflask/flask-assets-pipeline
/r/flask
https://redd.it/1p1z9gt
GitHub
GitHub - hyperflask/flask-assets-pipeline: Modern asset pipeline for Flask
Modern asset pipeline for Flask. Contribute to hyperflask/flask-assets-pipeline development by creating an account on GitHub.
Is it possible that i get typehints / auto complete for jinja html? in vsc
I was seeing a full flask course where the tutor was using pycharm, he changed the templating somthing and he was kinda getting typehints , Is this possible for vsc, I have installed jinja, jinja better but still i am not getting those
/r/flask
https://redd.it/1p1u87x
I was seeing a full flask course where the tutor was using pycharm, he changed the templating somthing and he was kinda getting typehints , Is this possible for vsc, I have installed jinja, jinja better but still i am not getting those
/r/flask
https://redd.it/1p1u87x
Reddit
From the flask community on Reddit
Explore this post and more from the flask community
whereproc: a small CLI that tells you where a running process’s executable actually lives
I’ve been working on some small, practical command-line utilities, and this one turned out to be surprisingly useful, so I packaged it up and put it on PyPI.
What My Project Does
whereproc answers a question I kept hitting in day-to-day work: "What executable is actually backing this running process?"
Target Audience
whereproc is useful for anyone:
debugging PATH issues
finding the real location of app bundles / snap packages
scripting around PID or exe discovery
process verification and automation
Comparison
There are existing tools that overlap with some functionality (
- whereproc always shows the resolved executable path, which many platform tools obscure or hide behind symlinks.
- It unifies behavior across platforms. The same command works the same way on Linux, macOS, and Windows.
- It provides multiple match modes (substring, exact, regex, command-line search) instead of
/r/Python
https://redd.it/1p1p990
I’ve been working on some small, practical command-line utilities, and this one turned out to be surprisingly useful, so I packaged it up and put it on PyPI.
What My Project Does
whereproc is a command-line tool built on top of psutil that inspects running processes and reports the full filesystem path of the executable backing them. It supports substring, exact-match, and regex searches, and it can match against either the process name or the entire command line. Output can be human-readable, JSON, or a quiet/scripting mode that prints only the executable path.whereproc answers a question I kept hitting in day-to-day work: "What executable is actually backing this running process?"
Target Audience
whereproc is useful for anyone:
debugging PATH issues
finding the real location of app bundles / snap packages
scripting around PID or exe discovery
process verification and automation
Comparison
There are existing tools that overlap with some functionality (
ps, pgrep, pidof, Windows Task Manager, Activity Monitor, Process Explorer), but:- whereproc always shows the resolved executable path, which many platform tools obscure or hide behind symlinks.
- It unifies behavior across platforms. The same command works the same way on Linux, macOS, and Windows.
- It provides multiple match modes (substring, exact, regex, command-line search) instead of
/r/Python
https://redd.it/1p1p990
Reddit
From the Python community on Reddit: whereproc: a small CLI that tells you where a running process’s executable actually lives
Explore this post and more from the Python community
how obvious is this retry logic bug to you?
I was writing a function to handle a 429 error from NCBI API today, its a recursive retry function, thought it looked clean but..
well the code ran without errors, but downstream I kept getting
Here is the snippet (simplified).
def fetchdatawithretry(retries=10):
try:
return apiclient.getdata()
except RateLimitError:
if retries > 0:
print(f"Rate limit hit. Retrying... {retries} left")
time.sleep(1)
fetchdatawithretry(retries - 1)
else:
/r/Python
https://redd.it/1p1yzzd
I was writing a function to handle a 429 error from NCBI API today, its a recursive retry function, thought it looked clean but..
well the code ran without errors, but downstream I kept getting
None values in the output instead of the API data response. It drove me crazy because the logs showed the retries were happening and "succeeding."Here is the snippet (simplified).
def fetchdatawithretry(retries=10):
try:
return apiclient.getdata()
except RateLimitError:
if retries > 0:
print(f"Rate limit hit. Retrying... {retries} left")
time.sleep(1)
fetchdatawithretry(retries - 1)
else:
/r/Python
https://redd.it/1p1yzzd
Reddit
From the Python community on Reddit
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Flask-Security vs a la carte (login, authorize, dance)?
I've used flask-login for many years, bolting on my own roles/permissions system, email authentication, password management, etc. Am looking to finally make an upgrade to some standard tools, but am having trouble deciding between the all-in-one pallets project flask-security and an a la carte approach with flask-login, flask-authorize, and flask-dance (plus probably others).
Have you used either stack? What did you like/dislike about it?
/r/flask
https://redd.it/1p25oya
I've used flask-login for many years, bolting on my own roles/permissions system, email authentication, password management, etc. Am looking to finally make an upgrade to some standard tools, but am having trouble deciding between the all-in-one pallets project flask-security and an a la carte approach with flask-login, flask-authorize, and flask-dance (plus probably others).
Have you used either stack? What did you like/dislike about it?
/r/flask
https://redd.it/1p25oya
Reddit
From the flask community on Reddit
Explore this post and more from the flask community
Latest Python Podcasts & Conference Talks (week 47, 2025)
Hi r/Python!
As part of Tech Talks Weekly, I'll be posting here every week with all the latest Python conference talks and podcasts. To build this list, I'm following over 100 software engineering conferences and even more podcasts. This means you no longer need to scroll through messy YT subscriptions or RSS feeds!
In addition, I'll periodically post compilations, for example a list of the most-watched Python talks of 2025.
The following list includes all the Python talks and podcasts published in the past 7 days (2025-11-13 - 2025-11-20).
Let's get started!
# 1. Conference talks
# PyData Seattle 2025
1. **"Khuyen Tran & Yibei Hu - Multi-Series Forecasting at Scale with StatsForecast | PyData Seattle 2025"** ⸱ +200 views ⸱ 17 Nov 2025 ⸱ 00h 39m 36s
2. **"Sebastian Duerr - Evaluation is all you need | PyData Seattle 2025"** ⸱ +200 views ⸱ 17 Nov 2025 ⸱ 00h 43m 28s
3. **"Bill Engels - Actually using GPs in practice with PyMC | PyData Seattle 2025"** ⸱ +200 views ⸱ 17 Nov 2025 ⸱ 00h 44m 15s
4. **"Everett Kleven - Why Models Break Your Pipelines | PyData Seattle 2025"** ⸱ +200 views ⸱ 17 Nov 2025 ⸱ 00h 36m 04s
5. **"Ojas Ankurbhai Ramwala - Explainable AI for Biomedical Image Processing | PyData Seattle 2025"** ⸱ +100 views ⸱ 17 Nov 2025 ⸱
/r/Python
https://redd.it/1p23zun
Hi r/Python!
As part of Tech Talks Weekly, I'll be posting here every week with all the latest Python conference talks and podcasts. To build this list, I'm following over 100 software engineering conferences and even more podcasts. This means you no longer need to scroll through messy YT subscriptions or RSS feeds!
In addition, I'll periodically post compilations, for example a list of the most-watched Python talks of 2025.
The following list includes all the Python talks and podcasts published in the past 7 days (2025-11-13 - 2025-11-20).
Let's get started!
# 1. Conference talks
# PyData Seattle 2025
1. **"Khuyen Tran & Yibei Hu - Multi-Series Forecasting at Scale with StatsForecast | PyData Seattle 2025"** ⸱ +200 views ⸱ 17 Nov 2025 ⸱ 00h 39m 36s
2. **"Sebastian Duerr - Evaluation is all you need | PyData Seattle 2025"** ⸱ +200 views ⸱ 17 Nov 2025 ⸱ 00h 43m 28s
3. **"Bill Engels - Actually using GPs in practice with PyMC | PyData Seattle 2025"** ⸱ +200 views ⸱ 17 Nov 2025 ⸱ 00h 44m 15s
4. **"Everett Kleven - Why Models Break Your Pipelines | PyData Seattle 2025"** ⸱ +200 views ⸱ 17 Nov 2025 ⸱ 00h 36m 04s
5. **"Ojas Ankurbhai Ramwala - Explainable AI for Biomedical Image Processing | PyData Seattle 2025"** ⸱ +100 views ⸱ 17 Nov 2025 ⸱
/r/Python
https://redd.it/1p23zun
www.techtalksweekly.io
Tech Talks Weekly | Substack
Join 7,200+ Software Engineers and Engineering Leaders who receive a free weekly email with all the recently published podcasts and conference talks. Stop scrolling through messy YT subscriptions. Stop FOMO. Easy to unsubscribe. No spam, ever. Click to read…
Youtube channels to learn django
Suggest some good yt channels to learn django
/r/django
https://redd.it/1p2112e
Suggest some good yt channels to learn django
/r/django
https://redd.it/1p2112e
Reddit
From the django community on Reddit
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Going build-free with native JavaScript modules
https://www.djangoproject.com/weblog/2025/nov/19/going-build-free-with-native-javascript-modules
/r/django
https://redd.it/1p2c9qt
https://www.djangoproject.com/weblog/2025/nov/19/going-build-free-with-native-javascript-modules
/r/django
https://redd.it/1p2c9qt
Django Project
Going build-free with native JavaScript modules
Posted by James Bligh on Nov. 19, 2025
Why do we repeat type hints in docstrings?
I see a lot of code like this:
def foo(x: int) -> int:
"""Does something
Parameters:
x (int): Description of x
Returns:
int: Returning value
"""
return x
Isn’t the type information in the docstring redundant? It’s already specified in the function definition, and as actual code, not strings.
/r/Python
https://redd.it/1p2c50c
I see a lot of code like this:
def foo(x: int) -> int:
"""Does something
Parameters:
x (int): Description of x
Returns:
int: Returning value
"""
return x
Isn’t the type information in the docstring redundant? It’s already specified in the function definition, and as actual code, not strings.
/r/Python
https://redd.it/1p2c50c
Reddit
From the Python community on Reddit
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Friday Daily Thread: r/Python Meta and Free-Talk Fridays
# Weekly Thread: Meta Discussions and Free Talk Friday 🎙️
Welcome to Free Talk Friday on /r/Python! This is the place to discuss the r/Python community (meta discussions), Python news, projects, or anything else Python-related!
## How it Works:
1. Open Mic: Share your thoughts, questions, or anything you'd like related to Python or the community.
2. Community Pulse: Discuss what you feel is working well or what could be improved in the /r/python community.
3. News & Updates: Keep up-to-date with the latest in Python and share any news you find interesting.
## Guidelines:
All topics should be related to Python or the /r/python community.
Be respectful and follow Reddit's Code of Conduct.
## Example Topics:
1. New Python Release: What do you think about the new features in Python 3.11?
2. Community Events: Any Python meetups or webinars coming up?
3. Learning Resources: Found a great Python tutorial? Share it here!
4. Job Market: How has Python impacted your career?
5. Hot Takes: Got a controversial Python opinion? Let's hear it!
6. Community Ideas: Something you'd like to see us do? tell us.
Let's keep the conversation going. Happy discussing! 🌟
/r/Python
https://redd.it/1p2jgiv
# Weekly Thread: Meta Discussions and Free Talk Friday 🎙️
Welcome to Free Talk Friday on /r/Python! This is the place to discuss the r/Python community (meta discussions), Python news, projects, or anything else Python-related!
## How it Works:
1. Open Mic: Share your thoughts, questions, or anything you'd like related to Python or the community.
2. Community Pulse: Discuss what you feel is working well or what could be improved in the /r/python community.
3. News & Updates: Keep up-to-date with the latest in Python and share any news you find interesting.
## Guidelines:
All topics should be related to Python or the /r/python community.
Be respectful and follow Reddit's Code of Conduct.
## Example Topics:
1. New Python Release: What do you think about the new features in Python 3.11?
2. Community Events: Any Python meetups or webinars coming up?
3. Learning Resources: Found a great Python tutorial? Share it here!
4. Job Market: How has Python impacted your career?
5. Hot Takes: Got a controversial Python opinion? Let's hear it!
6. Community Ideas: Something you'd like to see us do? tell us.
Let's keep the conversation going. Happy discussing! 🌟
/r/Python
https://redd.it/1p2jgiv
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