I have a angular with django backend. I am trying to implement redis with celery and rabbit mq for parallel processing so that when I am sending multiple request to backend, it could be in a quene and then work accordingly.
How do I do it?
/r/djangolearning
https://redd.it/1j6jcfc
How do I do it?
/r/djangolearning
https://redd.it/1j6jcfc
Reddit
I have a angular with django backend. I am trying to implement redis with celery and rabbit mq for parallel processing so that…
27K subscribers in the djangolearning community. A group dedicated to learning Django, a Python web framework.
How Does a Django Project Work in Real-World Startups? Seeking Insights from Experienced Developers
Hey everyone,
We’ve just started a new startup, and after some research, we’ve decided to go with Django for our backend. Right now, I’m the one leading the Django team, but my experience is mostly in freelancing. Managing a team and handling the entire tech process—from planning to deployment—is something new for me, and I’d love to hear from experienced Django developers about how things work in real-world projects.
Here are the main things I’d love to understand:
1. Planning & Architecture – How do you structure a Django project for long-term scalability?
2. Git & GitHub Workflow – Best practices for managing a team using GitHub (branches, PRs, CI/CD).
3. Scaling Considerations – Differences in approach for a small project vs. a high-scale system.
4. Is Django a Good Choice for a Low-Scale Project? – Would you recommend Django for early-stage startups, or is it overkill?
5. Deployment – What are the best deployment strategies for Django in 2024? Docker, Kubernetes, traditional servers?
6. Technology Stack – What are the essential tools (DB, caching, task queues, etc.) used in professional Django setups?
7. Security & Best Practices – How do you keep a Django project secure in production?
8. Team Management – How do you manage a team of
/r/django
https://redd.it/1j6pc54
Hey everyone,
We’ve just started a new startup, and after some research, we’ve decided to go with Django for our backend. Right now, I’m the one leading the Django team, but my experience is mostly in freelancing. Managing a team and handling the entire tech process—from planning to deployment—is something new for me, and I’d love to hear from experienced Django developers about how things work in real-world projects.
Here are the main things I’d love to understand:
1. Planning & Architecture – How do you structure a Django project for long-term scalability?
2. Git & GitHub Workflow – Best practices for managing a team using GitHub (branches, PRs, CI/CD).
3. Scaling Considerations – Differences in approach for a small project vs. a high-scale system.
4. Is Django a Good Choice for a Low-Scale Project? – Would you recommend Django for early-stage startups, or is it overkill?
5. Deployment – What are the best deployment strategies for Django in 2024? Docker, Kubernetes, traditional servers?
6. Technology Stack – What are the essential tools (DB, caching, task queues, etc.) used in professional Django setups?
7. Security & Best Practices – How do you keep a Django project secure in production?
8. Team Management – How do you manage a team of
/r/django
https://redd.it/1j6pc54
Reddit
From the django community on Reddit
Explore this post and more from the django community
Sunday Daily Thread: What's everyone working on this week?
# Weekly Thread: What's Everyone Working On This Week? 🛠️
Hello /r/Python! It's time to share what you've been working on! Whether it's a work-in-progress, a completed masterpiece, or just a rough idea, let us know what you're up to!
## How it Works:
1. Show & Tell: Share your current projects, completed works, or future ideas.
2. Discuss: Get feedback, find collaborators, or just chat about your project.
3. Inspire: Your project might inspire someone else, just as you might get inspired here.
## Guidelines:
Feel free to include as many details as you'd like. Code snippets, screenshots, and links are all welcome.
Whether it's your job, your hobby, or your passion project, all Python-related work is welcome here.
## Example Shares:
1. Machine Learning Model: Working on a ML model to predict stock prices. Just cracked a 90% accuracy rate!
2. Web Scraping: Built a script to scrape and analyze news articles. It's helped me understand media bias better.
3. Automation: Automated my home lighting with Python and Raspberry Pi. My life has never been easier!
Let's build and grow together! Share your journey and learn from others. Happy coding! 🌟
/r/Python
https://redd.it/1j6upf0
# Weekly Thread: What's Everyone Working On This Week? 🛠️
Hello /r/Python! It's time to share what you've been working on! Whether it's a work-in-progress, a completed masterpiece, or just a rough idea, let us know what you're up to!
## How it Works:
1. Show & Tell: Share your current projects, completed works, or future ideas.
2. Discuss: Get feedback, find collaborators, or just chat about your project.
3. Inspire: Your project might inspire someone else, just as you might get inspired here.
## Guidelines:
Feel free to include as many details as you'd like. Code snippets, screenshots, and links are all welcome.
Whether it's your job, your hobby, or your passion project, all Python-related work is welcome here.
## Example Shares:
1. Machine Learning Model: Working on a ML model to predict stock prices. Just cracked a 90% accuracy rate!
2. Web Scraping: Built a script to scrape and analyze news articles. It's helped me understand media bias better.
3. Automation: Automated my home lighting with Python and Raspberry Pi. My life has never been easier!
Let's build and grow together! Share your journey and learn from others. Happy coding! 🌟
/r/Python
https://redd.it/1j6upf0
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Getting a CORS error in browser console when making request from NextJS frontend to Django backend
Hello!
I'm attempting to make a request from my locally running NextJS frontend (**http://localhost:3000**) to my locally running Django server (**http://127.0.0.1:8000**). However, I'm running into an error on making the request:
`Access to fetch at 'http://127.0.0.1:8000/api/test' from origin 'http://localhost:3000' has been blocked by CORS policy: No 'Access-Control-Allow-Origin' header is present on the requested resource. If an opaque response serves your needs, set the request's mode to 'no-cors' to fetch the resource with CORS disabled.`
I did some reading on CORS on MDN here (https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) and did this in my settings.py + installed `django-cors-headers`:
ALLOWED_HOSTS = ["localhost", "127.0.0.1"]
CORS_ALLOW_HEADERS = ["test", "content-type", "authorization", "x-csrftoken", "x-requested-with"]
CORS_ALLOWED_ORIGINS = ["http://localhost:3000"]
CORS_ALLOW_METHODS = ["GET", "POST", "PUT", "PATCH", "DELETE", "OPTIONS"]
CORS_ALLOW_CREDENTIALS = True
MIDDLEWARE = [
"corsheaders.middleware.CorsMiddleware",
"django.middleware.common.CommonMiddleware",
"django.middleware.csrf.CsrfViewMiddleware",
"django.middleware.security.SecurityMiddleware",
"django.contrib.sessions.middleware.SessionMiddleware",
"django.contrib.auth.middleware.AuthenticationMiddleware",
"django.contrib.messages.middleware.MessageMiddleware",
/r/django
https://redd.it/1j6t85n
Hello!
I'm attempting to make a request from my locally running NextJS frontend (**http://localhost:3000**) to my locally running Django server (**http://127.0.0.1:8000**). However, I'm running into an error on making the request:
`Access to fetch at 'http://127.0.0.1:8000/api/test' from origin 'http://localhost:3000' has been blocked by CORS policy: No 'Access-Control-Allow-Origin' header is present on the requested resource. If an opaque response serves your needs, set the request's mode to 'no-cors' to fetch the resource with CORS disabled.`
I did some reading on CORS on MDN here (https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) and did this in my settings.py + installed `django-cors-headers`:
ALLOWED_HOSTS = ["localhost", "127.0.0.1"]
CORS_ALLOW_HEADERS = ["test", "content-type", "authorization", "x-csrftoken", "x-requested-with"]
CORS_ALLOWED_ORIGINS = ["http://localhost:3000"]
CORS_ALLOW_METHODS = ["GET", "POST", "PUT", "PATCH", "DELETE", "OPTIONS"]
CORS_ALLOW_CREDENTIALS = True
MIDDLEWARE = [
"corsheaders.middleware.CorsMiddleware",
"django.middleware.common.CommonMiddleware",
"django.middleware.csrf.CsrfViewMiddleware",
"django.middleware.security.SecurityMiddleware",
"django.contrib.sessions.middleware.SessionMiddleware",
"django.contrib.auth.middleware.AuthenticationMiddleware",
"django.contrib.messages.middleware.MessageMiddleware",
/r/django
https://redd.it/1j6t85n
MDN Web Docs
Cross-Origin Resource Sharing (CORS) - HTTP | MDN
Cross-Origin Resource Sharing (CORS) is an HTTP-header based mechanism that allows a server to indicate any origins (domain, scheme, or port) other than its own from which a browser should permit loading resources. CORS also relies on a mechanism by which…
Meet Jonq: The jq wrapper that makes JSON Querying feel easier
Yo sup folks! Introducing Jonq(JsON Query) Gonna try to keep this short. I just hate writing jq syntaxes. I was thinking how can we make the syntaxes more human-readable. So i created a python wrapper which has syntaxes like sql+python
Inspiration
Hate the syntax in JQ. Super difficult to read.
What My Project Does
Built on top of jq for speed and flexibility. Instead of wrestling with some syntax thats really hard to manipulate, I thought maybe just combine python and sql syntaxes and wrap it around JQ.
Key Features
SQL-Like Queries: Write select field1, field2 if condition to grab and filter data.
Aggregations: Built-in functions like sum(), avg(), count(), max(), and min() (Will expand it if i have more use cases on my end or if anyone wants more features)
Nested Data Made Simple: Traverse nested jsons with ease I guess (e.g., user.profile.age).
Sorting and Limiting: Add keywords to order your results or cap the output.
Comparison:
JQ
JQ is a beast but tough to read....
In Jonq, queries look like plain English instructions. No more decoding a string of pipes and brackets.
Here’s an example to prove it:
JSON File:
Example
{"name": "Andy", "age": 30},
{"name": "Bob", "age":
/r/Python
[https://redd.it/1j6ykrs
Yo sup folks! Introducing Jonq(JsON Query) Gonna try to keep this short. I just hate writing jq syntaxes. I was thinking how can we make the syntaxes more human-readable. So i created a python wrapper which has syntaxes like sql+python
Inspiration
Hate the syntax in JQ. Super difficult to read.
What My Project Does
Built on top of jq for speed and flexibility. Instead of wrestling with some syntax thats really hard to manipulate, I thought maybe just combine python and sql syntaxes and wrap it around JQ.
Key Features
SQL-Like Queries: Write select field1, field2 if condition to grab and filter data.
Aggregations: Built-in functions like sum(), avg(), count(), max(), and min() (Will expand it if i have more use cases on my end or if anyone wants more features)
Nested Data Made Simple: Traverse nested jsons with ease I guess (e.g., user.profile.age).
Sorting and Limiting: Add keywords to order your results or cap the output.
Comparison:
JQ
JQ is a beast but tough to read....
In Jonq, queries look like plain English instructions. No more decoding a string of pipes and brackets.
Here’s an example to prove it:
JSON File:
Example
{"name": "Andy", "age": 30},
{"name": "Bob", "age":
/r/Python
[https://redd.it/1j6ykrs
Reddit
From the Python community on Reddit: Meet Jonq: The jq wrapper that makes JSON Querying feel easier
Explore this post and more from the Python community
Example data repository using Async Postgres, SQLAlchemy, Pydantic
What My Project Does
This is a data repository example which provides a clean, type-safe interface for creating, retrieving, and updating jobs in a PostgreSQL database. It leverages SQLModel (SQLAlchemy + Pydantic) for a modern, fully typed approach to database interactions with async support.
Target Audience
Python developers who use data-access patterns such has Martin Fowler's Repository pattern.
Comparison
This is in contrast to how I normally implement data repositories. I usually hand-craft my data repositories and load sql/*.sql files from disk. This allows for anyone who knows SQL to add new sql files or edit existing ones. This pattern has served me well in other languages such as: Clojure, Crystal, C#, Go, Ruby, etc.
However, in this project, I wanted to explore using the following choices: Async Postgres, SQLAlchemy ORM, Pydantic. SQLAlchemy also provides implicit support for connection pooling.
Project url: https://gitlab.com/ejstembler/python-repository-example
/r/Python
https://redd.it/1j6zwrh
What My Project Does
This is a data repository example which provides a clean, type-safe interface for creating, retrieving, and updating jobs in a PostgreSQL database. It leverages SQLModel (SQLAlchemy + Pydantic) for a modern, fully typed approach to database interactions with async support.
Target Audience
Python developers who use data-access patterns such has Martin Fowler's Repository pattern.
Comparison
This is in contrast to how I normally implement data repositories. I usually hand-craft my data repositories and load sql/*.sql files from disk. This allows for anyone who knows SQL to add new sql files or edit existing ones. This pattern has served me well in other languages such as: Clojure, Crystal, C#, Go, Ruby, etc.
However, in this project, I wanted to explore using the following choices: Async Postgres, SQLAlchemy ORM, Pydantic. SQLAlchemy also provides implicit support for connection pooling.
Project url: https://gitlab.com/ejstembler/python-repository-example
/r/Python
https://redd.it/1j6zwrh
martinfowler.com
Repository
Mediates between the domain and data mapping layers using a
collection-like interface for accessing domain objects.
collection-like interface for accessing domain objects.
Should I keep a native web app setup and put all the load in aws or optimised both front-end and backend?
So in the current setup, I have a django with angular hosted on GCP. My company is saying so keep the front-end as it is with no queue system and just keep send the multiple request to backend with could be completed via multi threading. Is it a good approach or is a better way?
/r/djangolearning
https://redd.it/1j6yeys
So in the current setup, I have a django with angular hosted on GCP. My company is saying so keep the front-end as it is with no queue system and just keep send the multiple request to backend with could be completed via multi threading. Is it a good approach or is a better way?
/r/djangolearning
https://redd.it/1j6yeys
Reddit
From the djangolearning community on Reddit
Explore this post and more from the djangolearning community
What's the best way to tell number of downloads from pypi - is https://pepy.tech downloads real?
What's the best way to tell number of downloads from pypi? is https://pepy.tech downloads real?
We've open sourced lately, and it shows me i have 46k downloads, but I only have 100+ stars in github, just felt a bit unreal.
or maybe i should use this one?
https://pypistats.org/packages/
Thanks!
/r/Python
https://redd.it/1j719o6
What's the best way to tell number of downloads from pypi? is https://pepy.tech downloads real?
We've open sourced lately, and it shows me i have 46k downloads, but I only have 100+ stars in github, just felt a bit unreal.
or maybe i should use this one?
https://pypistats.org/packages/
Thanks!
/r/Python
https://redd.it/1j719o6
pepy.tech
pepy.tech - PyPI Stats | Python Package Download Analytics & Insights
Track PyPI package downloads and analytics
Vehicle application charts and combining them accurately and easily
Hi all
I have a bit of a unique problem. I work with a lot of vehicle application charts as part of my job. I often receive application charts in separate files either as a group of products (brakes headlight batteries etc all in the same chart) or an app chart for a single product (brakes). They will always have some form of make model year and sometimes displacement and vehicle type . The columns can be in any order. The charts can also be presented in either a horizontal format with columns for each product with skus in the columns or vertically with a column with the product name and a sku beside it. There is no guarantee of consistency between the names of the columns in the charts and they can often be thousands of lines. I am wondering if there is a python script out there to quickly and accurately combine these charts so that the vehicle information,product information all cell contents line up (maybe someone would be willing to write me a quick vba code?) I have tried power query and it doesn’t seem to do the trick. I was going to attach an
/r/Python
https://redd.it/1j780he
Hi all
I have a bit of a unique problem. I work with a lot of vehicle application charts as part of my job. I often receive application charts in separate files either as a group of products (brakes headlight batteries etc all in the same chart) or an app chart for a single product (brakes). They will always have some form of make model year and sometimes displacement and vehicle type . The columns can be in any order. The charts can also be presented in either a horizontal format with columns for each product with skus in the columns or vertically with a column with the product name and a sku beside it. There is no guarantee of consistency between the names of the columns in the charts and they can often be thousands of lines. I am wondering if there is a python script out there to quickly and accurately combine these charts so that the vehicle information,product information all cell contents line up (maybe someone would be willing to write me a quick vba code?) I have tried power query and it doesn’t seem to do the trick. I was going to attach an
/r/Python
https://redd.it/1j780he
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Creating a sampler, mixer, and recording audio to disk in Python
# Background
I am posting a series of Python scripts that demonstrate using Supriya, a Python API for SuperCollider, in a dedicated subreddit. Supriya makes it possible to create synthesizers, sequencers, drum machines, and music, of course, using Python.
All demos are posted here: r/supriya\_python.
The code for all demos can be found in this GitHub repo.
These demos assume knowledge of the Python programming language. They do not teach how to program in Python. Therefore, an intermediate level of experience with Python is required.
# The demo
In the latest demo, I show how to create a sampler, a more complex sequencer, a mixer, and how to record audio to disk. This demo is much more complex than any of the previous demos, so the post is quite long.
Happy belated 303 day!
/r/Python
https://redd.it/1j78nqr
# Background
I am posting a series of Python scripts that demonstrate using Supriya, a Python API for SuperCollider, in a dedicated subreddit. Supriya makes it possible to create synthesizers, sequencers, drum machines, and music, of course, using Python.
All demos are posted here: r/supriya\_python.
The code for all demos can be found in this GitHub repo.
These demos assume knowledge of the Python programming language. They do not teach how to program in Python. Therefore, an intermediate level of experience with Python is required.
# The demo
In the latest demo, I show how to create a sampler, a more complex sequencer, a mixer, and how to record audio to disk. This demo is much more complex than any of the previous demos, so the post is quite long.
Happy belated 303 day!
/r/Python
https://redd.it/1j78nqr
Reddit
r/supriya_python
A place to learn and share information about Supriya, the Python API for SuperCollider.
A feature-rich Telegram support bot (open source)
Hey everyone! I'd like to share a Telegram support bot I've developed.
**What My Project Does**
In its core it works like other support bots: users message the bot, and admins reply via an admin group. But the project adds some more features on top of that.
**Target Audience**
I've added a bunch of features that make it especially useful for organizations providing tech or legal help. But it also works well for an anonymous Telegram channel just wanting to leave a contact.
**Comparison**
The bot is open source (MIT), lightweight, and dockerized. Built with Python and SQLite, using aiogram and SQLAlchemy.
Here's a list of advanced features making it different from other bots:
* Multi-bot support: run any number of bots in one process; each with separate database and settings
* Threaded admin chats: each user gets a separate topic in the admin group
* Menu builder: the bot can show a menu with actions, you only need to describe it via a simple TOML config
* Self-destructing messages on user side if there is a security concern
* Broadcasts: admins can send a message to all the bot users directly from the admin group
* Weekly stats: usage statistics are reported in admin group every 7 days
* Google Sheets logging: archive
/r/Python
https://redd.it/1j7774b
Hey everyone! I'd like to share a Telegram support bot I've developed.
**What My Project Does**
In its core it works like other support bots: users message the bot, and admins reply via an admin group. But the project adds some more features on top of that.
**Target Audience**
I've added a bunch of features that make it especially useful for organizations providing tech or legal help. But it also works well for an anonymous Telegram channel just wanting to leave a contact.
**Comparison**
The bot is open source (MIT), lightweight, and dockerized. Built with Python and SQLite, using aiogram and SQLAlchemy.
Here's a list of advanced features making it different from other bots:
* Multi-bot support: run any number of bots in one process; each with separate database and settings
* Threaded admin chats: each user gets a separate topic in the admin group
* Menu builder: the bot can show a menu with actions, you only need to describe it via a simple TOML config
* Self-destructing messages on user side if there is a security concern
* Broadcasts: admins can send a message to all the bot users directly from the admin group
* Weekly stats: usage statistics are reported in admin group every 7 days
* Google Sheets logging: archive
/r/Python
https://redd.it/1j7774b
Reddit
From the Python community on Reddit: A feature-rich Telegram support bot (open source)
Explore this post and more from the Python community
This media is not supported in your browser
VIEW IN TELEGRAM
[P] I built Reddit Wrapped – let an LLM analyze and roast your Reddit profile
/r/MachineLearning
https://redd.it/1j7c45g
/r/MachineLearning
https://redd.it/1j7c45g
R How to start writting papers as an independent researcher
Hey Guys, so I have a master's in AI and work in the AI field, for a while now I wanted to try to write papers to send to conferences, but I dont know how to start or how to do it. I also feel kinda overwhelmed since I feel that if I write a paper by myself, a lone author who has never had anything written before and is backed by no organization, even if I write something interesting, people wont take it seriously. I also changed continents, so its kinda difficult to try to make connections with my original university, so I was wondering if there are any groups of independent researchers where I could connect with. I would welcome any kind of advice really, since most of my connections dont write papers, less in the AI field, so I dont know where to start.
/r/MachineLearning
https://redd.it/1j74rx0
Hey Guys, so I have a master's in AI and work in the AI field, for a while now I wanted to try to write papers to send to conferences, but I dont know how to start or how to do it. I also feel kinda overwhelmed since I feel that if I write a paper by myself, a lone author who has never had anything written before and is backed by no organization, even if I write something interesting, people wont take it seriously. I also changed continents, so its kinda difficult to try to make connections with my original university, so I was wondering if there are any groups of independent researchers where I could connect with. I would welcome any kind of advice really, since most of my connections dont write papers, less in the AI field, so I dont know where to start.
/r/MachineLearning
https://redd.it/1j74rx0
Reddit
From the MachineLearning community on Reddit
Explore this post and more from the MachineLearning community
[Project] mkdocs-typer2: Automatic documentation for Typer CLI applications
Hello Python community! I wanted to share a project I've been working on that might be useful for developers building command-line applications with Typer.
# What My Project Does
`mkdocs-typer2` is a MkDocs plugin that automatically generates documentation for Typer CLI applications. It works by:
1. Leveraging Typer's built-in documentation generation system
2. Processing the output and seamlessly integrating it into your MkDocs site
3. Offering an optional "pretty" mode that formats CLI arguments and options in elegant tables instead of lists
4. Supporting both global configuration and per-documentation block customization
Installation is straightforward:
pip install mkdocs-typer2
Usage is simple - just add a directive to your Markdown files:
::: mkdocs-typer2
:module: my_module.cli
:name: my-cli
:pretty: true
# Target Audience
This plugin is meant for:
* Python developers building CLI applications with Typer
* Teams who want to maintain high-quality documentation without extra effort
* Open source project maintainers looking to improve their user documentation
* Anyone who values clean, consistent, and professional-looking documentation
This is a production-ready tool designed to solve a real problem in documentation workflows. It's particularly useful in projects where CLI documentation needs to
/r/Python
https://redd.it/1j7d34e
Hello Python community! I wanted to share a project I've been working on that might be useful for developers building command-line applications with Typer.
# What My Project Does
`mkdocs-typer2` is a MkDocs plugin that automatically generates documentation for Typer CLI applications. It works by:
1. Leveraging Typer's built-in documentation generation system
2. Processing the output and seamlessly integrating it into your MkDocs site
3. Offering an optional "pretty" mode that formats CLI arguments and options in elegant tables instead of lists
4. Supporting both global configuration and per-documentation block customization
Installation is straightforward:
pip install mkdocs-typer2
Usage is simple - just add a directive to your Markdown files:
::: mkdocs-typer2
:module: my_module.cli
:name: my-cli
:pretty: true
# Target Audience
This plugin is meant for:
* Python developers building CLI applications with Typer
* Teams who want to maintain high-quality documentation without extra effort
* Open source project maintainers looking to improve their user documentation
* Anyone who values clean, consistent, and professional-looking documentation
This is a production-ready tool designed to solve a real problem in documentation workflows. It's particularly useful in projects where CLI documentation needs to
/r/Python
https://redd.it/1j7d34e
Reddit
From the Python community on Reddit: [Project] mkdocs-typer2: Automatic documentation for Typer CLI applications
Explore this post and more from the Python community
Monday Daily Thread: Project ideas!
# Weekly Thread: Project Ideas 💡
Welcome to our weekly Project Ideas thread! Whether you're a newbie looking for a first project or an expert seeking a new challenge, this is the place for you.
## How it Works:
1. **Suggest a Project**: Comment your project idea—be it beginner-friendly or advanced.
2. **Build & Share**: If you complete a project, reply to the original comment, share your experience, and attach your source code.
3. **Explore**: Looking for ideas? Check out Al Sweigart's ["The Big Book of Small Python Projects"](https://www.amazon.com/Big-Book-Small-Python-Programming/dp/1718501242) for inspiration.
## Guidelines:
* Clearly state the difficulty level.
* Provide a brief description and, if possible, outline the tech stack.
* Feel free to link to tutorials or resources that might help.
# Example Submissions:
## Project Idea: Chatbot
**Difficulty**: Intermediate
**Tech Stack**: Python, NLP, Flask/FastAPI/Litestar
**Description**: Create a chatbot that can answer FAQs for a website.
**Resources**: [Building a Chatbot with Python](https://www.youtube.com/watch?v=a37BL0stIuM)
# Project Idea: Weather Dashboard
**Difficulty**: Beginner
**Tech Stack**: HTML, CSS, JavaScript, API
**Description**: Build a dashboard that displays real-time weather information using a weather API.
**Resources**: [Weather API Tutorial](https://www.youtube.com/watch?v=9P5MY_2i7K8)
## Project Idea: File Organizer
**Difficulty**: Beginner
**Tech Stack**: Python, File I/O
**Description**: Create a script that organizes files in a directory into sub-folders based on file type.
**Resources**: [Automate the Boring Stuff: Organizing Files](https://automatetheboringstuff.com/2e/chapter9/)
Let's help each other grow. Happy
/r/Python
https://redd.it/1j7lij0
# Weekly Thread: Project Ideas 💡
Welcome to our weekly Project Ideas thread! Whether you're a newbie looking for a first project or an expert seeking a new challenge, this is the place for you.
## How it Works:
1. **Suggest a Project**: Comment your project idea—be it beginner-friendly or advanced.
2. **Build & Share**: If you complete a project, reply to the original comment, share your experience, and attach your source code.
3. **Explore**: Looking for ideas? Check out Al Sweigart's ["The Big Book of Small Python Projects"](https://www.amazon.com/Big-Book-Small-Python-Programming/dp/1718501242) for inspiration.
## Guidelines:
* Clearly state the difficulty level.
* Provide a brief description and, if possible, outline the tech stack.
* Feel free to link to tutorials or resources that might help.
# Example Submissions:
## Project Idea: Chatbot
**Difficulty**: Intermediate
**Tech Stack**: Python, NLP, Flask/FastAPI/Litestar
**Description**: Create a chatbot that can answer FAQs for a website.
**Resources**: [Building a Chatbot with Python](https://www.youtube.com/watch?v=a37BL0stIuM)
# Project Idea: Weather Dashboard
**Difficulty**: Beginner
**Tech Stack**: HTML, CSS, JavaScript, API
**Description**: Build a dashboard that displays real-time weather information using a weather API.
**Resources**: [Weather API Tutorial](https://www.youtube.com/watch?v=9P5MY_2i7K8)
## Project Idea: File Organizer
**Difficulty**: Beginner
**Tech Stack**: Python, File I/O
**Description**: Create a script that organizes files in a directory into sub-folders based on file type.
**Resources**: [Automate the Boring Stuff: Organizing Files](https://automatetheboringstuff.com/2e/chapter9/)
Let's help each other grow. Happy
/r/Python
https://redd.it/1j7lij0
YouTube
Build & Integrate your own custom chatbot to a website (Python & JavaScript)
In this fun project you learn how to build a custom chatbot in Python and then integrate this to a website using Flask and JavaScript.
Starter Files: https://github.com/patrickloeber/chatbot-deployment
Get my Free NumPy Handbook: https://www.python-engi…
Starter Files: https://github.com/patrickloeber/chatbot-deployment
Get my Free NumPy Handbook: https://www.python-engi…
I have a angular + Django backend . When I am click on a button, it calls an api which starts execution of a process via python. It takes almost 2mins to complete the process. Now I want that suppose when a user closes the tab, the api call should be cancelled. How to achieve that?
/r/djangolearning
https://redd.it/1j7acrn
/r/djangolearning
https://redd.it/1j7acrn
Reddit
From the djangolearning community on Reddit
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The current landscape of UI components and design systems for Django applications
When I start developing a new web application, it's almost always a Django project. ORM, migrations, templates, etc. It's that familiar all-in-one package we've all come to love.
But the one area that keeps bugging me is how to add componentization of the UI and fill in a design system to the components. I don't want to always start from the scratch when starting a new project but I haven't solved this issue for me.
I know I could just use template snippets for reusability but it feels off and I've seen myself how quickly the DX of going through template after another falls off.
So what's the current rave for adding components to a Django codebase? Web components? django-components? Daisy UI? django-cotton? And how about adding a design system in? Tailwind? Bootstrap 5?
Note that I don't want a full-fledged SPA with a UI framework like React or Svelte on the client-side. The more SSR the merrier.
Would love to hear your experiences and suggestions.
/r/django
https://redd.it/1j7jtmr
When I start developing a new web application, it's almost always a Django project. ORM, migrations, templates, etc. It's that familiar all-in-one package we've all come to love.
But the one area that keeps bugging me is how to add componentization of the UI and fill in a design system to the components. I don't want to always start from the scratch when starting a new project but I haven't solved this issue for me.
I know I could just use template snippets for reusability but it feels off and I've seen myself how quickly the DX of going through template after another falls off.
So what's the current rave for adding components to a Django codebase? Web components? django-components? Daisy UI? django-cotton? And how about adding a design system in? Tailwind? Bootstrap 5?
Note that I don't want a full-fledged SPA with a UI framework like React or Svelte on the client-side. The more SSR the merrier.
Would love to hear your experiences and suggestions.
/r/django
https://redd.it/1j7jtmr
Reddit
From the django community on Reddit
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Implemented 20 RAG Techniques in a Simpler Way
# What My Project Does
I created a comprehensive learning project in a Jupyter Notebook to implement RAG techniques such as self-RAG, fusion, and more.
# Target audience
This project is designed for students and researchers who want to gain a clear understanding of RAG techniques in a simplified manner.
# Comparison
Unlike other implementations, this project does not rely on LangChain or FAISS libraries. Instead, it uses only basic libraries to guide users understand the underlying processes. Any recommendations for improvement are welcome.
# GitHub
Code, documentation, and example can all be found on GitHub:
https://github.com/FareedKhan-dev/all-rag-techniques
/r/Python
https://redd.it/1j7rl6o
# What My Project Does
I created a comprehensive learning project in a Jupyter Notebook to implement RAG techniques such as self-RAG, fusion, and more.
# Target audience
This project is designed for students and researchers who want to gain a clear understanding of RAG techniques in a simplified manner.
# Comparison
Unlike other implementations, this project does not rely on LangChain or FAISS libraries. Instead, it uses only basic libraries to guide users understand the underlying processes. Any recommendations for improvement are welcome.
# GitHub
Code, documentation, and example can all be found on GitHub:
https://github.com/FareedKhan-dev/all-rag-techniques
/r/Python
https://redd.it/1j7rl6o
This is just the beginning and I'm crumbling with Django learning curve
I cannot thank everyone enough for motivating me to learn Django regardless of my age in the last post. And I'm trying to work on it. But, yet I find all this code overwhelming. I have been just following UDEMY tutorial. Sometimes the code work, sometimes does not. And I had to look up over the internet to fix it . And that searching takes like 30 minutes for each bug I encounter. Prolly, it is because I have no partner to learn with. Nevertheless, just look at the code I just posted. I was understanding until Employee.objects.all() from models was called and displayed in template. But, now with this foreign key, select_related and even with line 30,37 where employees are called with array position. I cannot comprehend it much. Should I just go through this again and again and practice or is there any easy way out. or any books to help me. I guess tutorial is not the way. Please please please help me overcome this learning curve. I do not wanna feel overwhelmed. I have already finished 30 hours of video and practice along with. And I can only give 3 hours everyday for 1 year
/r/django
https://redd.it/1j7e35h
I cannot thank everyone enough for motivating me to learn Django regardless of my age in the last post. And I'm trying to work on it. But, yet I find all this code overwhelming. I have been just following UDEMY tutorial. Sometimes the code work, sometimes does not. And I had to look up over the internet to fix it . And that searching takes like 30 minutes for each bug I encounter. Prolly, it is because I have no partner to learn with. Nevertheless, just look at the code I just posted. I was understanding until Employee.objects.all() from models was called and displayed in template. But, now with this foreign key, select_related and even with line 30,37 where employees are called with array position. I cannot comprehend it much. Should I just go through this again and again and practice or is there any easy way out. or any books to help me. I guess tutorial is not the way. Please please please help me overcome this learning curve. I do not wanna feel overwhelmed. I have already finished 30 hours of video and practice along with. And I can only give 3 hours everyday for 1 year
/r/django
https://redd.it/1j7e35h
Reddit
From the django community on Reddit
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Performance gains of the Python 3.14 tail-call interpreter were largely due to benchmark errors
I was really surprised and confused by last month's claims of a 15% speedup for the new interpreter. It turned out it was an error in the benchmark setup, caused by a bug in LLVM 19.
See https://blog.nelhage.com/post/cpython-tail-call/ and the correction in https://docs.python.org/3.14/whatsnew/3.14.html#whatsnew314-tail-call
A 5% speedup is still nice though!
/r/Python
https://redd.it/1j7usy1
I was really surprised and confused by last month's claims of a 15% speedup for the new interpreter. It turned out it was an error in the benchmark setup, caused by a bug in LLVM 19.
See https://blog.nelhage.com/post/cpython-tail-call/ and the correction in https://docs.python.org/3.14/whatsnew/3.14.html#whatsnew314-tail-call
A 5% speedup is still nice though!
/r/Python
https://redd.it/1j7usy1
Reddit
From the Python community on Reddit: A new type of interpreter has been added to Python 3.14 with much better performance
Explore this post and more from the Python community
I built Lightweight & Flexible AI Agent Manager
# What My Project Does
I built a simple, lightweight tool that allows developers to create and manage AI agents efficiently. This package provides:
* **Agent Definition**: Assign roles and instructions to agents.
* **Model Flexibility**: Easily switch between popular LLMs.
* **Tool Integration**: Equip agents with tools for specific tasks.
* **Multi-Agent Orchestration**: Seamlessly manage interactions between agents.
# Target Audience
This tool is designed for developers working with **Django, Flask, FastAPI**, and other Python frameworks who need:
* A **lightweight** and **flexible** alternative to Langchain/Langraph.
* Easy integration into **views, background tasks**, and other workflows.
* A **simpler learning curve** without excessive abstraction.
# Comparison with Existing Tools
Unlike **Langchain, Langraph, and Pydantic**, which have a **steep learning curve** and heavy abstractions, this package is:
✅ **Lightweight & Minimal** – No unnecessary overhead.
✅ **Flexible** – Use it wherever you want.
✅ **Supports Multiple LLMs** – Easily switch between:
* OpenAI
* Grok
* DeepSeek
* Anthropic
* Llama
* GenAI (Gemini)
# GitHub
Check it out and show some love by **giving stars ⭐ and feedback**!
🔗 [**https://github.com/sandeshnaroju/agents\_manager**](https://github.com/sandeshnaroju/agents_manager)
/r/Python
https://redd.it/1j7td2q
# What My Project Does
I built a simple, lightweight tool that allows developers to create and manage AI agents efficiently. This package provides:
* **Agent Definition**: Assign roles and instructions to agents.
* **Model Flexibility**: Easily switch between popular LLMs.
* **Tool Integration**: Equip agents with tools for specific tasks.
* **Multi-Agent Orchestration**: Seamlessly manage interactions between agents.
# Target Audience
This tool is designed for developers working with **Django, Flask, FastAPI**, and other Python frameworks who need:
* A **lightweight** and **flexible** alternative to Langchain/Langraph.
* Easy integration into **views, background tasks**, and other workflows.
* A **simpler learning curve** without excessive abstraction.
# Comparison with Existing Tools
Unlike **Langchain, Langraph, and Pydantic**, which have a **steep learning curve** and heavy abstractions, this package is:
✅ **Lightweight & Minimal** – No unnecessary overhead.
✅ **Flexible** – Use it wherever you want.
✅ **Supports Multiple LLMs** – Easily switch between:
* OpenAI
* Grok
* DeepSeek
* Anthropic
* Llama
* GenAI (Gemini)
# GitHub
Check it out and show some love by **giving stars ⭐ and feedback**!
🔗 [**https://github.com/sandeshnaroju/agents\_manager**](https://github.com/sandeshnaroju/agents_manager)
/r/Python
https://redd.it/1j7td2q