how much time to learn Django ?
i have a project on django (ERP app) in which i need to understand app already developed , add new features , mantain app.. i need to estimate workload of this. Knowing that i have an intermediate level of python, what is the range of time that this project would take ?
/r/django
https://redd.it/1hy4z8q
i have a project on django (ERP app) in which i need to understand app already developed , add new features , mantain app.. i need to estimate workload of this. Knowing that i have an intermediate level of python, what is the range of time that this project would take ?
/r/django
https://redd.it/1hy4z8q
Reddit
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Django Developer Job at Spotter
Hi everyone! I recently applied for a Django Developer position at Spotte (Spotter Labs). After passing an initial screening, I was told to complete a coding assessment with the promise of a $100 USD reward upon successful completion.
Has anyone else done this task and actually moved forward in the process? Did you get paid and proceed to the next stage, or do you think this might be a scam? I know some might say "why not try," but I’m really stressed with my current work and don’t have the time to invest in this. If I end up spending time on it and nothing comes of it, that would be pretty disappointing.
/r/django
https://redd.it/1hy36cz
Hi everyone! I recently applied for a Django Developer position at Spotte (Spotter Labs). After passing an initial screening, I was told to complete a coding assessment with the promise of a $100 USD reward upon successful completion.
Has anyone else done this task and actually moved forward in the process? Did you get paid and proceed to the next stage, or do you think this might be a scam? I know some might say "why not try," but I’m really stressed with my current work and don’t have the time to invest in this. If I end up spending time on it and nothing comes of it, that would be pretty disappointing.
/r/django
https://redd.it/1hy36cz
Reddit
From the django community on Reddit
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Django APIs combined with iOS learning resources.
I've been learning Django and started building an iOS app as a first project. I followed a few iOS tutorials and used ChatGPT to get help whenever i get stuck. I struggle to fully grasp the communication and sending data between iOS and Django. I was just wondering if anyone know any good courses or resources for learning more about the Django REST API and building iOS apps that interact with Django and a database.
/r/django
https://redd.it/1hy1rpy
I've been learning Django and started building an iOS app as a first project. I followed a few iOS tutorials and used ChatGPT to get help whenever i get stuck. I struggle to fully grasp the communication and sending data between iOS and Django. I was just wondering if anyone know any good courses or resources for learning more about the Django REST API and building iOS apps that interact with Django and a database.
/r/django
https://redd.it/1hy1rpy
Reddit
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I created a linter for your dependencies (requirements.txt file!)
Hey there. I've been working on a dependencies-related product for the last year. A lot of engineering teams that I've seen are building their own internal tooling to check on dependencies.
In short, people either update too frequently or don't update at all.
So, I decided to create a simple linter that checks all the main issues and best practices, comes with sensible defaults, and allows you to adjust it to your needs.
It supports npm/yarn, Go, pip, and Cargo. Any feedback is welcome!
Link: https://github.com/DepsHubHQ/depshub
What My Project Does
Checks your requirements.txt file on 20+ rules.
Target Audience
Mostly developers running it locally or on the CI. Still in beta.
Comparison
There are no popular linters for dependencies at all. The most popular tool to deal with dependencies is dependabot but it works in a completely different way.
/r/Python
https://redd.it/1hy1q3n
Hey there. I've been working on a dependencies-related product for the last year. A lot of engineering teams that I've seen are building their own internal tooling to check on dependencies.
In short, people either update too frequently or don't update at all.
So, I decided to create a simple linter that checks all the main issues and best practices, comes with sensible defaults, and allows you to adjust it to your needs.
It supports npm/yarn, Go, pip, and Cargo. Any feedback is welcome!
Link: https://github.com/DepsHubHQ/depshub
What My Project Does
Checks your requirements.txt file on 20+ rules.
Target Audience
Mostly developers running it locally or on the CI. Still in beta.
Comparison
There are no popular linters for dependencies at all. The most popular tool to deal with dependencies is dependabot but it works in a completely different way.
/r/Python
https://redd.it/1hy1q3n
GitHub
GitHub - DepsHubHQ/depshub: Dependency management toolkit: linter, updater, security scanner and more!
Dependency management toolkit: linter, updater, security scanner and more! - DepsHubHQ/depshub
Calling all drf repo owners - I'll do your work for you for free
Ok, slightly click-bait-ey title, but hear me out.
I'm a senior dev with over a decade of django experience, and nearly 2 decades working in AI. I have created a django specific AI to work as a mid level developer and I'd like to get some feedback on it's performance 'in the wild'.
The easiest way to do this at the moment is for me to manage it and to let it have a branch of it's own (so it's easy for you to optionally ignore anything it does). I use OpenAI and I'll cover all the costs. I'm happy to be effectively interviewed, share details of past projects (privately) etc., whatever processes you need to go through to validate this being worthwhile.
The repo can be open source or private, it can work with django, but it's not great at UI design, thus DRF, but I'm willing to try it on a django repo if there is appetite.
I use this in my current job, I'm head of department and thus able to make the call myself. I've also allowed friends to use it with their work and in general it's a positive experience - fire the request off, grab a drink and
/r/django
https://redd.it/1hydw9e
Ok, slightly click-bait-ey title, but hear me out.
I'm a senior dev with over a decade of django experience, and nearly 2 decades working in AI. I have created a django specific AI to work as a mid level developer and I'd like to get some feedback on it's performance 'in the wild'.
The easiest way to do this at the moment is for me to manage it and to let it have a branch of it's own (so it's easy for you to optionally ignore anything it does). I use OpenAI and I'll cover all the costs. I'm happy to be effectively interviewed, share details of past projects (privately) etc., whatever processes you need to go through to validate this being worthwhile.
The repo can be open source or private, it can work with django, but it's not great at UI design, thus DRF, but I'm willing to try it on a django repo if there is appetite.
I use this in my current job, I'm head of department and thus able to make the call myself. I've also allowed friends to use it with their work and in general it's a positive experience - fire the request off, grab a drink and
/r/django
https://redd.it/1hydw9e
Reddit
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Can you suggest correct model to make for given problem?
I am assigned with a task of adding a reward/penalty type function to our work site. its a point based system.
here is what the system already has.
Employees: Users
Tasks: employees/managers create and assign task, task detail, task deadline etc., you can mark task complete, amend deadline(if self assigned), update status (ongoing, pending, completed, on hold)
points function: points added if task marked complete before deadline, points removed if missed deadline. A manager can override points like negate penalty if there is a valid reason. managers can manually add or deduct points for other things like positive for finding bugs and negative for AWOL or submitting buggy code repeatedly etc. Task based points are calculated automatically while other types are assigned manually. Managers can override points awarded automatically given valid reason. eg: If -3 points are added for missing a deadline but the employee missed it due to being hospitalised then manager would just add/award +3 points to cancel it out. So all manually given points are called manual_adjustment_points.
so I am trying to make a model as the first step. But I keep feeling I am missing something. My current model is as following.
Model: Rewards:
/r/djangolearning
https://redd.it/1hxduv3
I am assigned with a task of adding a reward/penalty type function to our work site. its a point based system.
here is what the system already has.
Employees: Users
Tasks: employees/managers create and assign task, task detail, task deadline etc., you can mark task complete, amend deadline(if self assigned), update status (ongoing, pending, completed, on hold)
points function: points added if task marked complete before deadline, points removed if missed deadline. A manager can override points like negate penalty if there is a valid reason. managers can manually add or deduct points for other things like positive for finding bugs and negative for AWOL or submitting buggy code repeatedly etc. Task based points are calculated automatically while other types are assigned manually. Managers can override points awarded automatically given valid reason. eg: If -3 points are added for missing a deadline but the employee missed it due to being hospitalised then manager would just add/award +3 points to cancel it out. So all manually given points are called manual_adjustment_points.
so I am trying to make a model as the first step. But I keep feeling I am missing something. My current model is as following.
Model: Rewards:
/r/djangolearning
https://redd.it/1hxduv3
Reddit
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Separate package
apps = ['silk']
if settings.DEBUG and all(app in settings.INSTALLED_APPS for app in apps):
urlpatterns += [
path('silk/', include('silk.urls', namespace='silk')),
]
It worked fine, but is this the correct approach?
/r/django
https://redd.it/1hy1oql
apps = ['silk']
if settings.DEBUG and all(app in settings.INSTALLED_APPS for app in apps):
urlpatterns += [
path('silk/', include('silk.urls', namespace='silk')),
]
It worked fine, but is this the correct approach?
/r/django
https://redd.it/1hy1oql
Reddit
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Saturday Daily Thread: Resource Request and Sharing! Daily Thread
# Weekly Thread: Resource Request and Sharing 📚
Stumbled upon a useful Python resource? Or are you looking for a guide on a specific topic? Welcome to the Resource Request and Sharing thread!
## How it Works:
1. Request: Can't find a resource on a particular topic? Ask here!
2. Share: Found something useful? Share it with the community.
3. Review: Give or get opinions on Python resources you've used.
## Guidelines:
Please include the type of resource (e.g., book, video, article) and the topic.
Always be respectful when reviewing someone else's shared resource.
## Example Shares:
1. Book: "Fluent Python" \- Great for understanding Pythonic idioms.
2. Video: Python Data Structures \- Excellent overview of Python's built-in data structures.
3. Article: Understanding Python Decorators \- A deep dive into decorators.
## Example Requests:
1. Looking for: Video tutorials on web scraping with Python.
2. Need: Book recommendations for Python machine learning.
Share the knowledge, enrich the community. Happy learning! 🌟
/r/Python
https://redd.it/1hyivpf
# Weekly Thread: Resource Request and Sharing 📚
Stumbled upon a useful Python resource? Or are you looking for a guide on a specific topic? Welcome to the Resource Request and Sharing thread!
## How it Works:
1. Request: Can't find a resource on a particular topic? Ask here!
2. Share: Found something useful? Share it with the community.
3. Review: Give or get opinions on Python resources you've used.
## Guidelines:
Please include the type of resource (e.g., book, video, article) and the topic.
Always be respectful when reviewing someone else's shared resource.
## Example Shares:
1. Book: "Fluent Python" \- Great for understanding Pythonic idioms.
2. Video: Python Data Structures \- Excellent overview of Python's built-in data structures.
3. Article: Understanding Python Decorators \- A deep dive into decorators.
## Example Requests:
1. Looking for: Video tutorials on web scraping with Python.
2. Need: Book recommendations for Python machine learning.
Share the knowledge, enrich the community. Happy learning! 🌟
/r/Python
https://redd.it/1hyivpf
YouTube
Data Structures and Algorithms in Python - Full Course for Beginners
A beginner-friendly introduction to common data structures (linked lists, stacks, queues, graphs) and algorithms (search, sorting, recursion, dynamic programming) in Python. This course will help you prepare for coding interviews and assessments.
🔗 Course…
🔗 Course…
How Much Should I Charge for Developing a Custom ERP System?
**Hi everyone,**
I’m currently building a web-based ERP system for a small manufacturing company in India. Here are some of the features I’ll be including:
1. **Production Module**
* **Step-by-Step Process Management**:
* Tracks production steps with barcode scanning.
* Input/output validation for each step.
* Automatically progresses to the next step after scanning.
* **Real-Time Monitoring**: Provides an overview of ongoing production processes.
* **Defect Tracking**: Logs and reports defective items at each step.
2. **Stock Monitoring**
* **Real-Time Inventory Tracking**: Automatically updates stock levels as materials are used or replenished.
* **Low Stock Alerts**: Sends notifications for stock reaching minimum thresholds.
* **Department-Wise Inventory Management**: Manages separate stock data for each department.
3. **Reporting Capability**
* **Production Reports**: Detailed insights into completed and ongoing production.
* **Inventory Reports**: Tracks usage and availability trends.
* **Financial Reports**: Summarizes costs, revenue, and invoicing.
* **Customizable Reports**: Exportable to Excel or PDF.
4. **Invoicing Module**
* Generates and manages customer invoices.
* Tracks payment statuses.
/r/django
https://redd.it/1hyoi69
**Hi everyone,**
I’m currently building a web-based ERP system for a small manufacturing company in India. Here are some of the features I’ll be including:
1. **Production Module**
* **Step-by-Step Process Management**:
* Tracks production steps with barcode scanning.
* Input/output validation for each step.
* Automatically progresses to the next step after scanning.
* **Real-Time Monitoring**: Provides an overview of ongoing production processes.
* **Defect Tracking**: Logs and reports defective items at each step.
2. **Stock Monitoring**
* **Real-Time Inventory Tracking**: Automatically updates stock levels as materials are used or replenished.
* **Low Stock Alerts**: Sends notifications for stock reaching minimum thresholds.
* **Department-Wise Inventory Management**: Manages separate stock data for each department.
3. **Reporting Capability**
* **Production Reports**: Detailed insights into completed and ongoing production.
* **Inventory Reports**: Tracks usage and availability trends.
* **Financial Reports**: Summarizes costs, revenue, and invoicing.
* **Customizable Reports**: Exportable to Excel or PDF.
4. **Invoicing Module**
* Generates and manages customer invoices.
* Tracks payment statuses.
/r/django
https://redd.it/1hyoi69
Reddit
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[Dataset][R] 19,762 Garbage Images for Building AI Recycling Solutions
Hi ML community!
I’m excited to share the **Garbage Classification V2 Dataset**, featuring **19,762 high-quality images** of garbage categorized into **10 distinct classes** (e.g., metal, plastic, clothes, and paper).
# Why this matters:
* Train AI models for **automated waste sorting and recycling**.
* Develop **waste segregation apps** or sustainability-focused tools.
* Create innovative **computer vision projects** for environmental impact.
🔗 **Dataset Link:** [Garbage Classification V2](https://www.kaggle.com/datasets/sumn2u/garbage-classification-v2/)
This dataset has been used in the research paper, *"Managing Household Waste Through Transfer Learning,"* proving its utility in real-world applications.
Looking forward to seeing how you can use it to promote sustainability!
/r/MachineLearning
https://redd.it/1hyfaoc
Hi ML community!
I’m excited to share the **Garbage Classification V2 Dataset**, featuring **19,762 high-quality images** of garbage categorized into **10 distinct classes** (e.g., metal, plastic, clothes, and paper).
# Why this matters:
* Train AI models for **automated waste sorting and recycling**.
* Develop **waste segregation apps** or sustainability-focused tools.
* Create innovative **computer vision projects** for environmental impact.
🔗 **Dataset Link:** [Garbage Classification V2](https://www.kaggle.com/datasets/sumn2u/garbage-classification-v2/)
This dataset has been used in the research paper, *"Managing Household Waste Through Transfer Learning,"* proving its utility in real-world applications.
Looking forward to seeing how you can use it to promote sustainability!
/r/MachineLearning
https://redd.it/1hyfaoc
Kaggle
Garbage Dataset
A Comprehensive Image Dataset for Garbage Classification and Recycling
Are there any actual use cases of Python in Excel?
I’m trying to understand how useful it really is/ having not really touched it at all, I imagine someone versed in Python could optimize some of their workflow were they forced to work in excel. But given the fundamental processing limitations of excel I can’t imagine how scalable this is. Has anyone had practical experience using the Python - excel plugin to accomplish things easier than you could in either excel or Python alone and if so, what?
/r/Python
https://redd.it/1hylc50
I’m trying to understand how useful it really is/ having not really touched it at all, I imagine someone versed in Python could optimize some of their workflow were they forced to work in excel. But given the fundamental processing limitations of excel I can’t imagine how scalable this is. Has anyone had practical experience using the Python - excel plugin to accomplish things easier than you could in either excel or Python alone and if so, what?
/r/Python
https://redd.it/1hylc50
Reddit
From the Python community on Reddit
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Long time listener, first time caller
I have been using Django for the last few years and always wanted to check flask out.
2 days ago i started playing around with it.... I love it.
Compared to Django development has been so fast and way more flexible (which can be good and bad)
I have built a basic app with user auth and org level and test deployed using mongodb, gunicorn, docker on google cloud run all within a day basically
Great job devs 👍
Sorry for the useless post but thought id share my experience
/r/flask
https://redd.it/1hxu65g
I have been using Django for the last few years and always wanted to check flask out.
2 days ago i started playing around with it.... I love it.
Compared to Django development has been so fast and way more flexible (which can be good and bad)
I have built a basic app with user auth and org level and test deployed using mongodb, gunicorn, docker on google cloud run all within a day basically
Great job devs 👍
Sorry for the useless post but thought id share my experience
/r/flask
https://redd.it/1hxu65g
Reddit
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Open source Contribution
Can anyone guide me through the steps of contributing to Django?
/r/django
https://redd.it/1hyw6nv
Can anyone guide me through the steps of contributing to Django?
/r/django
https://redd.it/1hyw6nv
Reddit
From the django community on Reddit
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PyGAD 3.4.0 Released: Python library for optimization using the genetic algorithm.
PyGAD is a Python library for solving general-purpose optimization problems using the genetic algorithm.
GitHub repository: https://github.com/ahmedfgad/GeneticAlgorithmPython
Documentation: https://pygad.readthedocs.io
Quick release notes:
1. The
2. The
3. Created a new method called
4. The
5. While making prediction using the
6. The
7. More bug fixes.
/r/Python
https://redd.it/1hyxjqi
PyGAD is a Python library for solving general-purpose optimization problems using the genetic algorithm.
GitHub repository: https://github.com/ahmedfgad/GeneticAlgorithmPython
Documentation: https://pygad.readthedocs.io
Quick release notes:
1. The
delay_after_gen parameter is removed from the `pygad.GA` class constructor. 2. The
plot_pareto_front_curve() method added to the pygad.visualize.plot.Plot class to visualize the Pareto front for multi-objective problems. 3. Created a new method called
unique_float_gene_from_range() inside the pygad.helper.unique.Unique class to find a unique floating-point number from a range.4. The
Matplotlib library is only imported when a method inside the pygad/visualize/plot.py script is used. 5. While making prediction using the
pygad.torchga.predict() function, no gradients are calculated.6. The
gene_type parameter of the pygad.helper.unique.Unique.unique_int_gene_from_range() method accepts the type of the current gene only instead of the full gene_type list.7. More bug fixes.
/r/Python
https://redd.it/1hyxjqi
GitHub
GitHub - ahmedfgad/GeneticAlgorithmPython: Source code of PyGAD, a Python 3 library for building the genetic algorithm and training…
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch). - ahmedfgad/GeneticAlgorithmPython
Docker + uv - virtual environments
# Why?
uv uses an existing virtual environment(.venv) or creates one if it doesn't exist. But, using a Python virtual environment inside a Docker container is generally unnecessary and can even be counterproductive. As a container itself provides an isolated environment and does not need further isolation using virtual environments. When you create a Docker image, it includes its own filesystem, libraries, and dependencies. Using a virtual environment in container adds unneeded steps and unnecessary complexity. You'd need to create and activate the virtual environment during container startup. We can avoid this.
# How?
we can use uv for package installation in Docker without a virtual environment using "--system" flag
uv pip install --system <package>
uv pip install --system -r requirements.txt
NOTE: "uv run" and **"uv add"**NOTE: "uv run" and "uv add" commands will create virtual environment(.venv), if it doesn't exist. So, you will not be using those command inside the container. But, use them with in your local development virtual environment.
RUN uv add gunicorn ❌
CMD "uv", "run", "app.py" ❌
Instead use only "uv pip install --system" and simple "python" commands
RUN uv pip
/r/django
https://redd.it/1hz0s59
# Why?
uv uses an existing virtual environment(.venv) or creates one if it doesn't exist. But, using a Python virtual environment inside a Docker container is generally unnecessary and can even be counterproductive. As a container itself provides an isolated environment and does not need further isolation using virtual environments. When you create a Docker image, it includes its own filesystem, libraries, and dependencies. Using a virtual environment in container adds unneeded steps and unnecessary complexity. You'd need to create and activate the virtual environment during container startup. We can avoid this.
# How?
we can use uv for package installation in Docker without a virtual environment using "--system" flag
uv pip install --system <package>
uv pip install --system -r requirements.txt
NOTE: "uv run" and **"uv add"**NOTE: "uv run" and "uv add" commands will create virtual environment(.venv), if it doesn't exist. So, you will not be using those command inside the container. But, use them with in your local development virtual environment.
RUN uv add gunicorn ❌
CMD "uv", "run", "app.py" ❌
Instead use only "uv pip install --system" and simple "python" commands
RUN uv pip
/r/django
https://redd.it/1hz0s59
docs.astral.sh
uv
uv is an extremely fast Python package and project manager, written in Rust.
API request logging built for privacy and performance (works with Flask)
https://apitally.io/blog/request-log-release-announcement
/r/flask
https://redd.it/1hy2jag
https://apitally.io/blog/request-log-release-announcement
/r/flask
https://redd.it/1hy2jag
apitally.io
API request logging built for privacy and performance - Apitally Blog
Introducing the new request logging feature in Apitally that connects API metrics & insights with the ability to drill down and inspect individual requests.
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[P] Built a Snake game with a Diffusion model as the game engine. It runs in near real-time 🤖 It predicts next frame based on user input and current frames.
/r/MachineLearning
https://redd.it/1hz1l2j
/r/MachineLearning
https://redd.it/1hz1l2j
I built a django based crowdfunding platform - Fundly 🎊
Hey everyone! I wanted to share a crowdfunding platform I built using Django 5 and Bootstrap. It's a versatile platform that can be used for any type of fundraising campaigns - from creative projects to personal causes.
GitHub: https://github.com/manjurulhoque/fundly
Key Features:
🔐 User Management:
User registration & authentication
Profile management with avatars
Account settings & password management
💰 Campaign Management:
Create & manage fundraising campaigns
Rich text editor for descriptions
Campaign categorization & status tracking
Progress tracking & image uploads
Social sharing functionality
💳 Donation System:
Anonymous donation option
Donation tracking & statistics
Donation comments
📊 Dashboard Features:
User campaign dashboard
Campaign statistics
Donation history
Performance metrics
Admin dashboard with full CRUD
🔍 Search & Discovery:
Category-based browsing
Search functionality
Featured campaigns
Recent campaigns showcase
Campaign filtering
Tech Stack:
Backend: Python 3.x, Django 5.x, SQLite
Frontend: Bootstrap 4, jQuery, Font Awesome
Additional: TinyMCE Editor, Chartjs
The platform is fully responsive and includes features like campaign progress tracking, member management, and detailed analytics. Perfect for anyone looking to start their own crowdfunding website!
Would love to hear your thoughts and feedback! Feel free to check out the repo, star it if you like it, or contribute if you're interested.
/r/django
https://redd.it/1hz4w6c
Hey everyone! I wanted to share a crowdfunding platform I built using Django 5 and Bootstrap. It's a versatile platform that can be used for any type of fundraising campaigns - from creative projects to personal causes.
GitHub: https://github.com/manjurulhoque/fundly
Key Features:
🔐 User Management:
User registration & authentication
Profile management with avatars
Account settings & password management
💰 Campaign Management:
Create & manage fundraising campaigns
Rich text editor for descriptions
Campaign categorization & status tracking
Progress tracking & image uploads
Social sharing functionality
💳 Donation System:
Anonymous donation option
Donation tracking & statistics
Donation comments
📊 Dashboard Features:
User campaign dashboard
Campaign statistics
Donation history
Performance metrics
Admin dashboard with full CRUD
🔍 Search & Discovery:
Category-based browsing
Search functionality
Featured campaigns
Recent campaigns showcase
Campaign filtering
Tech Stack:
Backend: Python 3.x, Django 5.x, SQLite
Frontend: Bootstrap 4, jQuery, Font Awesome
Additional: TinyMCE Editor, Chartjs
The platform is fully responsive and includes features like campaign progress tracking, member management, and detailed analytics. Perfect for anyone looking to start their own crowdfunding website!
Would love to hear your thoughts and feedback! Feel free to check out the repo, star it if you like it, or contribute if you're interested.
/r/django
https://redd.it/1hz4w6c
GitHub
GitHub - manjurulhoque/fundly: A Django-based crowdfunding platform focused on healthcare campaigns. Users can create fundraising…
A Django-based crowdfunding platform focused on healthcare campaigns. Users can create fundraising initiatives, manage donations, and track progress in real-time. Features include secure payment pr...