Python script to batch-download YouTube playlists in any audio format/bitrate (w/ metadata support)
I couldn’t find a reliable tool that lets me download YouTube playlists in audio format exactly how I wanted (for car listening, offline use, etc.), so I built my own script using
# 🔧 Features:
Download entire playlists in any audio format: `.mp3`, `.m4a`, `.wav`
Set any bitrate: 128 / 192 / 256 kbps or max available
Batch download multiple playlists at once
Embed metadata (artist, title, album, etc.) automatically
It’s written in Python, simple to use, and fully open-source.
It was created using ChatGPT and It performs as described.
Feel free use it ,if you need it
📽️ [YouTube tutorial link\] -https://youtu.be/HVd4rXc958Q
💻 [GitHub repo link\] - https://github.com/dheerajv1/AutoYT-Audio
/r/Python
https://redd.it/1lot7nn
I couldn’t find a reliable tool that lets me download YouTube playlists in audio format exactly how I wanted (for car listening, offline use, etc.), so I built my own script using
yt-dlp.# 🔧 Features:
Download entire playlists in any audio format: `.mp3`, `.m4a`, `.wav`
Set any bitrate: 128 / 192 / 256 kbps or max available
Batch download multiple playlists at once
Embed metadata (artist, title, album, etc.) automatically
It’s written in Python, simple to use, and fully open-source.
It was created using ChatGPT and It performs as described.
Feel free use it ,if you need it
📽️ [YouTube tutorial link\] -https://youtu.be/HVd4rXc958Q
💻 [GitHub repo link\] - https://github.com/dheerajv1/AutoYT-Audio
/r/Python
https://redd.it/1lot7nn
YouTube
How to use AutoYT- audio
here the github link
https://github.com/dheerajv1/AutoYT-Audio
.
.
.
.
Music track: Daydreams by Pufino
Source: https://freetouse.com/music
No Copyright Music for Videos (Free)
https://github.com/dheerajv1/AutoYT-Audio
.
.
.
.
Music track: Daydreams by Pufino
Source: https://freetouse.com/music
No Copyright Music for Videos (Free)
Is it unreasonable to pair Django with Astro as well as htmx?
So basically you have a website that is completely static up until the login page. Does Django’s project structure work well with this? Where you can basically use Astro to efficiently develop the static pages and not have to use “bloated” Django or rather ssr as a whole for the completely static portions. Then I’m also not sure if Django is suitable to be used with htmx, but I really like the concept of not having to reload the entire page request. It’s kind of like Astro’s island architecture but for ssr in a backwards twisted way where you could make the comparison.
I’m also torn between using golang with Templ to learn backend development or going with Django in python. Htmx and Astro pair-ability is definitely a must, so if it’s easily doable without some hacky round about way in Django, then I will probably go with that for simplicity, employability, and overall more widespread use.
/r/djangolearning
https://redd.it/1ln514x
So basically you have a website that is completely static up until the login page. Does Django’s project structure work well with this? Where you can basically use Astro to efficiently develop the static pages and not have to use “bloated” Django or rather ssr as a whole for the completely static portions. Then I’m also not sure if Django is suitable to be used with htmx, but I really like the concept of not having to reload the entire page request. It’s kind of like Astro’s island architecture but for ssr in a backwards twisted way where you could make the comparison.
I’m also torn between using golang with Templ to learn backend development or going with Django in python. Htmx and Astro pair-ability is definitely a must, so if it’s easily doable without some hacky round about way in Django, then I will probably go with that for simplicity, employability, and overall more widespread use.
/r/djangolearning
https://redd.it/1ln514x
Reddit
From the djangolearning community on Reddit
Explore this post and more from the djangolearning community
What is the best vps (interms of price) to host my django + react app.....(i have a background process script too)
/r/djangolearning
https://redd.it/1llmq48
/r/djangolearning
https://redd.it/1llmq48
Reddit
From the djangolearning community on Reddit
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How do you choose your Django hosting provider?
Hey guys, what are your usual go-to solutions when you're hosting your Django projects, and why?
Is price the most important factor, or is it the feature set, credibility of the company, or how do you choose the right one?
I'm conducting a small research project to gain a deeper understanding of this topic. Thank you for your help
/r/django
https://redd.it/1lp00rp
Hey guys, what are your usual go-to solutions when you're hosting your Django projects, and why?
Is price the most important factor, or is it the feature set, credibility of the company, or how do you choose the right one?
I'm conducting a small research project to gain a deeper understanding of this topic. Thank you for your help
/r/django
https://redd.it/1lp00rp
Reddit
From the django community on Reddit
Explore this post and more from the django community
Making a Simple HTTP Server with Asyncio Protocols
Hey,
If you're curious about how Asyncio Protocols work (and how you they can be used to build a super simple HTTP server) check out this article: https://jacobpadilla.com/articles/asyncio-protocols
/r/Python
https://redd.it/1lpcaec
Hey,
If you're curious about how Asyncio Protocols work (and how you they can be used to build a super simple HTTP server) check out this article: https://jacobpadilla.com/articles/asyncio-protocols
/r/Python
https://redd.it/1lpcaec
Jacob Padilla
Making a Simple HTTP Server with Asyncio Protocols
Learn how to build a fast, minimal HTTP server using asyncio.Protocol, complete with routing, parsing, and response handling from scratch!
Best alternatives to Django?
Are there other comprehensive alternatives to Django that allow for near plug and play use with lots of features that you personally think is better?
I wouldn't consider alternatives such as Flask viable for bigger solo projects due to a lack of builtin features unless the project necessitates it.
/r/Python
https://redd.it/1lp3r3j
Are there other comprehensive alternatives to Django that allow for near plug and play use with lots of features that you personally think is better?
I wouldn't consider alternatives such as Flask viable for bigger solo projects due to a lack of builtin features unless the project necessitates it.
/r/Python
https://redd.it/1lp3r3j
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
pyfiq -- Minimal Redis-backed FIFO queues for Python
What My Project Does
pyfiq is a minimal Redis-backed FIFO task queue for Python. It lets you decorate functions with `@fifo(...)`, and they'll be queued for execution in strict order processed by threaded background workers utilizing Redis BLPOP.
It's for I/O-bound tasks like HTTP requests, webhook dispatching, or syncing with third-party APIs-- especially when execution order matters, but you don't want the complexity of Celery or external workers.
This project is for:
Developers writing code for integrating with external systems
People who want simple, ordered background task execution
Anyone who don't like Celery, AWS Lambda, etc, for handling asynchronous processing
Comparison to Existing Solutions
Unlike:
Celery, which requires brokers, workers, and doesn't preserve ordering by default
AWS Lambda queues, which don't guarantee FIFO unless using with SQS FIFO + extra setup
pyfiq is:
Embedded: runs in the app process
Order-preserving: one queue, multiple consumers, with strict FIFO
Zero-config: no services to orchestrate
It's designed to be very simple, and only provide ordered execution of tasks. The code is rudimentary right now, and there's a lot of room for improvement.
Background
I'm working on an event-driven sync mechanism, and needed something to offload sync logic in the background, reliably and in-order. I could've
/r/Python
https://redd.it/1lpfkei
What My Project Does
pyfiq is a minimal Redis-backed FIFO task queue for Python. It lets you decorate functions with `@fifo(...)`, and they'll be queued for execution in strict order processed by threaded background workers utilizing Redis BLPOP.
It's for I/O-bound tasks like HTTP requests, webhook dispatching, or syncing with third-party APIs-- especially when execution order matters, but you don't want the complexity of Celery or external workers.
This project is for:
Developers writing code for integrating with external systems
People who want simple, ordered background task execution
Anyone who don't like Celery, AWS Lambda, etc, for handling asynchronous processing
Comparison to Existing Solutions
Unlike:
Celery, which requires brokers, workers, and doesn't preserve ordering by default
AWS Lambda queues, which don't guarantee FIFO unless using with SQS FIFO + extra setup
pyfiq is:
Embedded: runs in the app process
Order-preserving: one queue, multiple consumers, with strict FIFO
Zero-config: no services to orchestrate
It's designed to be very simple, and only provide ordered execution of tasks. The code is rudimentary right now, and there's a lot of room for improvement.
Background
I'm working on an event-driven sync mechanism, and needed something to offload sync logic in the background, reliably and in-order. I could've
/r/Python
https://redd.it/1lpfkei
Reddit
From the Python community on Reddit: pyfiq -- Minimal Redis-backed FIFO queues for Python
Explore this post and more from the Python community
Simple beginners guide
Python-Tutorial-2025.vercel.app
It's still a work in progress as I intend to continue to add to it as I learn. I tried to make it educational while keeping things simple for beginners. Hope it helps someone.
/r/Python
https://redd.it/1lphzws
Python-Tutorial-2025.vercel.app
It's still a work in progress as I intend to continue to add to it as I learn. I tried to make it educational while keeping things simple for beginners. Hope it helps someone.
/r/Python
https://redd.it/1lphzws
Reddit
From the Python community on Reddit
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Code Sharing and Execution Platform Security Risks?
Currently working on a Python code sharing and execution platform aimed at letting users rapidly prototype with different libraries, frameworks, and external APIs. I am aware of the general security concerns and the necessity of running code in isolation (I am using GCP containers and Gvisor). Some concerns I'm thinking of:
\- crypto mining
\- network allowances leading to malicious code on external sites
\- container reuse
Wondering what everyones thoughts are on these concerns and if there are specific security measures I should be implementing beyond isolation and code-parsing for standard attacks?
/r/Python
https://redd.it/1lpflqb
Currently working on a Python code sharing and execution platform aimed at letting users rapidly prototype with different libraries, frameworks, and external APIs. I am aware of the general security concerns and the necessity of running code in isolation (I am using GCP containers and Gvisor). Some concerns I'm thinking of:
\- crypto mining
\- network allowances leading to malicious code on external sites
\- container reuse
Wondering what everyones thoughts are on these concerns and if there are specific security measures I should be implementing beyond isolation and code-parsing for standard attacks?
/r/Python
https://redd.it/1lpflqb
Reddit
From the Python community on Reddit
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Built a CLI tool that bridges multiple Python backtesting libraries to live APIs!
I just released my first significant open-source project, tackling an interesting architectural challenge. Different Python backtesting libraries (zipline, backtrader, vectorbt, backtesting.py) all have completely different APIs, but deploying strategies to live trading means rewriting everything from scratch.
So I built StrateQueue, a universal adapter between any backtesting library and live broker APIs. The technical challenge was normalizing signals across multiple library architectures and creating a clean plugin system for broker integrations, achieving \~11ms signal processing latency.
The CLI makes deployment dead simple:
stratequeue deploy \
--strategy examples/strategies/sma.py \
--symbol AAPL \
--timeframe 1m
DEMO
Since this is my first major open source contribution, I'd love feedback on code organization, API design, and Python best practices. The adapter pattern implementation was particularly fun to solve.
If you're interested in fintech applications with Python, I'd welcome contributors to help expand broker integrations or optimize performance. Even if you're just curious about the architecture, a GitHub star would help with visibility!
GITHUB
DOCS
TL;DR:
What my project does: StrateQueue is the fastest way from backtest to live trading
Target
/r/Python
https://redd.it/1lp470w
I just released my first significant open-source project, tackling an interesting architectural challenge. Different Python backtesting libraries (zipline, backtrader, vectorbt, backtesting.py) all have completely different APIs, but deploying strategies to live trading means rewriting everything from scratch.
So I built StrateQueue, a universal adapter between any backtesting library and live broker APIs. The technical challenge was normalizing signals across multiple library architectures and creating a clean plugin system for broker integrations, achieving \~11ms signal processing latency.
The CLI makes deployment dead simple:
stratequeue deploy \
--strategy examples/strategies/sma.py \
--symbol AAPL \
--timeframe 1m
DEMO
Since this is my first major open source contribution, I'd love feedback on code organization, API design, and Python best practices. The adapter pattern implementation was particularly fun to solve.
If you're interested in fintech applications with Python, I'd welcome contributors to help expand broker integrations or optimize performance. Even if you're just curious about the architecture, a GitHub star would help with visibility!
GITHUB
DOCS
TL;DR:
What my project does: StrateQueue is the fastest way from backtest to live trading
Target
/r/Python
https://redd.it/1lp470w
Reddit
https://preview.redd.it/cli-tool-zipline-backtrader-vectorbt-alpaca-ibkr-in-10-v0-uyukppv3l2af1.gif?width=1080&crop=smart&auto…
Want to gain experience
I am learning django nowadays and want to know how real projects work, so if someone is working on some django project and need someone's help I am ready to help so I can learn. (For free)
Even if you don't want my help please share your repo. So I can see how exactly we work in real world project in django.
/r/djangolearning
https://redd.it/1lpqzam
I am learning django nowadays and want to know how real projects work, so if someone is working on some django project and need someone's help I am ready to help so I can learn. (For free)
Even if you don't want my help please share your repo. So I can see how exactly we work in real world project in django.
/r/djangolearning
https://redd.it/1lpqzam
Reddit
From the djangolearning community on Reddit
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CSRF token missing error
I realize this may not be Flask specific problem. But I was hoping for some tips anyway. The status of my current project, is that it works OK on development, but behaves different on production.
The only difference I can note, is that the moment I test my password reset link on production, I will never ever be able to login AGAIN, no matter what I try/refresh/URLed. I did not test the password reset link on development, as I had trouble doing so with a localhost mail server. So this makes it difficult to pinpoint the source of error.
(NOTE: sending the password reset email itself works. there admin_required and login_required decorators elsewhere, but not complete, will removing ALL endpoint protection make it easier to debug?)
As you can tell, Im quite (relatively) noob in this. Any tips is extremely appreciated.
Attached is the pic, as well as much of the code. (The code is an amalgamation from different sources, simplified)
# ===== from: https://nrodrig1.medium.com/flask-mail-reset-password-with-token-8088119e015b
@app.route('/send-reset-email')
def sendresetemail():
s=Serializer(app.config'SECRET_KEY')
token = s.dumps({'someid': currentuser.mcfId})
/r/flask
https://redd.it/1lpljag
I realize this may not be Flask specific problem. But I was hoping for some tips anyway. The status of my current project, is that it works OK on development, but behaves different on production.
The only difference I can note, is that the moment I test my password reset link on production, I will never ever be able to login AGAIN, no matter what I try/refresh/URLed. I did not test the password reset link on development, as I had trouble doing so with a localhost mail server. So this makes it difficult to pinpoint the source of error.
(NOTE: sending the password reset email itself works. there admin_required and login_required decorators elsewhere, but not complete, will removing ALL endpoint protection make it easier to debug?)
As you can tell, Im quite (relatively) noob in this. Any tips is extremely appreciated.
Attached is the pic, as well as much of the code. (The code is an amalgamation from different sources, simplified)
# ===== from: https://nrodrig1.medium.com/flask-mail-reset-password-with-token-8088119e015b
@app.route('/send-reset-email')
def sendresetemail():
s=Serializer(app.config'SECRET_KEY')
token = s.dumps({'someid': currentuser.mcfId})
/r/flask
https://redd.it/1lpljag
Medium
Flask_mail Reset Password with Token
This is a simple application to remind me of the key parts to setting up a flask app with a token to reset password. This tutorial does not…
async_rithmic: a fully async Rithmic gateway for algorithmic trading
# What My Project Does
`async_rithmic` is an open-source Python SDK that brings fully asynchronous access to the [Rithmic API](https://www.rithmic.com/) (a popular low-latency gateway for futures market data and trading).
With `async_rithmic`, you can:
* Place, modify, and cancel orders in a modern, non-blocking way.
* Easily subscribe to market data and build real-time event-driven trading systems.
* Retrieve historical market data
# Links
* [GitHub Project link](https://github.com/rundef/async_rithmic)
* [Documentation link](https://async-rithmic.readthedocs.io/en/latest/)
# Why I Built It
The only other Python wrapper I'm aware of is outdated, unmaintained and has a flawed architecture. I needed something:
* Fully async (for use with asyncio and fast, concurrent pipelines)
* Open source, with a clean, idiomatic API
* Easy to use in an event-driven trading system
After building several bots and backtesting platforms, I decided to open-source my own implementation to help others save time and avoid re-inventing the wheel.
# Target audience
* Python developers working with low-latency, event-driven trading or market data pipelines
* Quantitative researchers and algo traders who want fast access to Rithmic feeds for futures trading
* Anyone building their own backtesting or trading framework with a focus on modern async patterns
/r/Python
https://redd.it/1lpvht5
# What My Project Does
`async_rithmic` is an open-source Python SDK that brings fully asynchronous access to the [Rithmic API](https://www.rithmic.com/) (a popular low-latency gateway for futures market data and trading).
With `async_rithmic`, you can:
* Place, modify, and cancel orders in a modern, non-blocking way.
* Easily subscribe to market data and build real-time event-driven trading systems.
* Retrieve historical market data
# Links
* [GitHub Project link](https://github.com/rundef/async_rithmic)
* [Documentation link](https://async-rithmic.readthedocs.io/en/latest/)
# Why I Built It
The only other Python wrapper I'm aware of is outdated, unmaintained and has a flawed architecture. I needed something:
* Fully async (for use with asyncio and fast, concurrent pipelines)
* Open source, with a clean, idiomatic API
* Easy to use in an event-driven trading system
After building several bots and backtesting platforms, I decided to open-source my own implementation to help others save time and avoid re-inventing the wheel.
# Target audience
* Python developers working with low-latency, event-driven trading or market data pipelines
* Quantitative researchers and algo traders who want fast access to Rithmic feeds for futures trading
* Anyone building their own backtesting or trading framework with a focus on modern async patterns
/r/Python
https://redd.it/1lpvht5
Rithmic, LLC
Rithmic, LLC | We Put Your Trades First
Rithmic, LLC is a leading provider of direct market access (DMA) trade execution software to the global financial community. Boasting high speed, low latency, ultra-low latency and massive throughput capabilities, the Rithmic software infrastructure is a…
This simple CPU benchmark tool is my first Python project.
Hey all, I just joined this community and decided to share my first actual project! It is a benchmark tool that creates a CPU score, also dependant upon read/write speeds of the RAM, by calculating prime numbers. Link to the Github repository: https://github.com/epicracer7490/PyMark/blob/main/README.md
It's just a fun hobby project, made in a few hours. Feel free to share your results!
It can be unaccurate because, unlike Geekbench etc. it runs single-core and is dependant on Pythons CPU usage priority. Here's my result: Intel i7-12650H, CPU SCORE = 4514.82 (Length: 7, Count: 415991)
/r/Python
https://redd.it/1lpvh4u
Hey all, I just joined this community and decided to share my first actual project! It is a benchmark tool that creates a CPU score, also dependant upon read/write speeds of the RAM, by calculating prime numbers. Link to the Github repository: https://github.com/epicracer7490/PyMark/blob/main/README.md
It's just a fun hobby project, made in a few hours. Feel free to share your results!
It can be unaccurate because, unlike Geekbench etc. it runs single-core and is dependant on Pythons CPU usage priority. Here's my result: Intel i7-12650H, CPU SCORE = 4514.82 (Length: 7, Count: 415991)
/r/Python
https://redd.it/1lpvh4u
GitHub
PyMark/README.md at main · epicracer7490/PyMark
A simple CPU + RAM benchmark tool using python. Requires Python 3.10 or higher - epicracer7490/PyMark
Best Resources to Learn Django in 2025?
Hey everyone,
I'm looking to get into Django and would really appreciate some guidance on the best resources out there in 2025. I'm comfortable with Python and have done some basic web dev (HTML/CSS/JS), but I'm new to backend frameworks like Django.
What I'm hoping to find:
A beginner-friendly roadmap or course
Up-to-date tutorials (text or video)
Good books or documentation
Projects or exercises to practice
I’ve seen a few tutorials floating around, but I want to make sure I'm learning from sources that are relevant and align with Django’s latest version.
Any tips, recommendations, or personal favorites would be hugely appreciated!
Thanks in advance 🙏
/r/django
https://redd.it/1lpy3kr
Hey everyone,
I'm looking to get into Django and would really appreciate some guidance on the best resources out there in 2025. I'm comfortable with Python and have done some basic web dev (HTML/CSS/JS), but I'm new to backend frameworks like Django.
What I'm hoping to find:
A beginner-friendly roadmap or course
Up-to-date tutorials (text or video)
Good books or documentation
Projects or exercises to practice
I’ve seen a few tutorials floating around, but I want to make sure I'm learning from sources that are relevant and align with Django’s latest version.
Any tips, recommendations, or personal favorites would be hugely appreciated!
Thanks in advance 🙏
/r/django
https://redd.it/1lpy3kr
Reddit
From the django community on Reddit
Explore this post and more from the django community
Flask Security Best Practices for Software Engineers
Hi all,
I'm Ahmad, founder of Corgea. We've built a scanner that can find vulnerabilities in Flask applications, so we decided to write a guide for software engineers on Flask security best practices:
https://corgea.com/Learn/flask-security-best-practices-2025
In this article, we’ve covered:
Common Flask security misconfigurations we keep seeing in the wild
How to safely manage your secret keys, sessions, and cookies
Input validation and preventing common attacks like XSS and SQL Injection
Best practices for authentication and password storage
Deployment hardening tips (headers, HTTPS, etc.)
Real code examples for each practice
We’ve written this with both new Flask developers and experienced engineers in mind.
Would love feedback from the community → What’s a Flask security mistake you’ve seen (or made 😅) that others should know about?
Anything else you’d like us to add in future updates?
PS: We love Flask and have used it for some of our services ❤️
/r/flask
https://redd.it/1lpylrt
Hi all,
I'm Ahmad, founder of Corgea. We've built a scanner that can find vulnerabilities in Flask applications, so we decided to write a guide for software engineers on Flask security best practices:
https://corgea.com/Learn/flask-security-best-practices-2025
In this article, we’ve covered:
Common Flask security misconfigurations we keep seeing in the wild
How to safely manage your secret keys, sessions, and cookies
Input validation and preventing common attacks like XSS and SQL Injection
Best practices for authentication and password storage
Deployment hardening tips (headers, HTTPS, etc.)
Real code examples for each practice
We’ve written this with both new Flask developers and experienced engineers in mind.
Would love feedback from the community → What’s a Flask security mistake you’ve seen (or made 😅) that others should know about?
Anything else you’d like us to add in future updates?
PS: We love Flask and have used it for some of our services ❤️
/r/flask
https://redd.it/1lpylrt
Corgea
Flask Security Best Practices 2025 - Corgea - Home
Corgea is an AI-native security platform that automatically finds, triages, and fixes insecure code. Sign up today for free to try Corgea.
The logging module is from 2002. Here's how to use it in 2025
The logging module is powerful, but I noticed a lot of older tutorials teach outdated patterns you shouldn't use. So I put together an article that focuses on understanding the modern picture of Python logging.
It covers structured JSON output, centralizing logging configuration, using contextvars to automatically enrich your logs with request-specific data, and other useful patterns for modern observability needs.
If there's anything I missed or could improve, please let me know!
/r/Python
https://redd.it/1lq2zq0
The logging module is powerful, but I noticed a lot of older tutorials teach outdated patterns you shouldn't use. So I put together an article that focuses on understanding the modern picture of Python logging.
It covers structured JSON output, centralizing logging configuration, using contextvars to automatically enrich your logs with request-specific data, and other useful patterns for modern observability needs.
If there's anything I missed or could improve, please let me know!
/r/Python
https://redd.it/1lq2zq0
Dash0
Application Logging in Python: Recipes for Observability · Dash0
Stop debugging with unstructured text Learn to build a robust Python logging system with structured JSON automatic context and full request lifecycle tracking