SciPy 1.15.0 released: Full sparse array support, new differentiation module, Python 3.13t support
# SciPy 1.15.0 Release Notes
SciPy
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been a number of deprecations and API changes
in this release, which are documented below. All users are encouraged to
upgrade to this release, as there are a large number of bug-fixes and
optimizations. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with
Our development attention will now shift to bug-fix releases on the
1.15.x branch, and on adding new features on the main branch.
This release requires Python
# Highlights of this release
Sparse arrays are now fully functional for 1-D and 2-D arrays. We recommend that all new code use sparse arrays instead of sparse matrices and that developers start to migrate their existing code from sparse matrix to sparse array: [`migration_to_sparray`](https://scipy.github.io/devdocs/reference/sparse.migration_to_sparray.html). Both `sparse.linalg` and `sparse.csgraph` work with either sparse matrix or sparse array and work internally with sparse array.
Sparse arrays now provide basic support for n-D arrays in the COO format including
/r/Python
https://redd.it/1hsqtz1
# SciPy 1.15.0 Release Notes
SciPy
1.15.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been a number of deprecations and API changes
in this release, which are documented below. All users are encouraged to
upgrade to this release, as there are a large number of bug-fixes and
optimizations. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with
python -Wd and check for DeprecationWarning s). Our development attention will now shift to bug-fix releases on the
1.15.x branch, and on adding new features on the main branch.
This release requires Python
3.10-3.13 and NumPy 1.23.5 or greater.# Highlights of this release
Sparse arrays are now fully functional for 1-D and 2-D arrays. We recommend that all new code use sparse arrays instead of sparse matrices and that developers start to migrate their existing code from sparse matrix to sparse array: [`migration_to_sparray`](https://scipy.github.io/devdocs/reference/sparse.migration_to_sparray.html). Both `sparse.linalg` and `sparse.csgraph` work with either sparse matrix or sparse array and work internally with sparse array.
Sparse arrays now provide basic support for n-D arrays in the COO format including
add, subtract, reshape, transpose, matmul, dot, tensordot and others. More functionality is/r/Python
https://redd.it/1hsqtz1
GitHub
Release SciPy 1.15.0 Β· scipy/scipy
SciPy 1.15.0 Release Notes
SciPy 1.15.0 is the culmination of 6 months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have b...
SciPy 1.15.0 is the culmination of 6 months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have b...
Interactive Image Background Remover (open source Photoroom Alternative)
https://github.com/pricklygorse/Interactive-Image-Background-Remover
## What My Project Does
Removes backgrounds from images both automatically and interactively. The key feature of this is you can click parts of the image to remove them, refine and fine tune the background removal, instead of just getting an output and that is it. The workflow is building up a mask from parts of the image, using open weights background removal models to achieve this. It can use both unguided whole-image models (u2net, disnet, rmbg, birefnet) and guided models (segment anything variants). There is also a manual paintbrush if the models struggle.
I've also implemented background colours, simple blurred background and drop shadow effects.
My aim is to work vaguely towards an open source local Photoroom alternative. Its a very very long way from that, but as is, it should be functional for most background removal tasks that many other services struggle with.
## Target Audience
Anyone who needs to remove backgrounds from photos, and wants a "click to remove" workflow, instead of relying on outputs of unguided whole-image removal services. It is a hobby project tailored around my use cases but hopefully stable enough for sharing. The code is pretty rough in places as its my first GUI app
## Comparison
I started
/r/Python
https://redd.it/1hsx9ok
https://github.com/pricklygorse/Interactive-Image-Background-Remover
## What My Project Does
Removes backgrounds from images both automatically and interactively. The key feature of this is you can click parts of the image to remove them, refine and fine tune the background removal, instead of just getting an output and that is it. The workflow is building up a mask from parts of the image, using open weights background removal models to achieve this. It can use both unguided whole-image models (u2net, disnet, rmbg, birefnet) and guided models (segment anything variants). There is also a manual paintbrush if the models struggle.
I've also implemented background colours, simple blurred background and drop shadow effects.
My aim is to work vaguely towards an open source local Photoroom alternative. Its a very very long way from that, but as is, it should be functional for most background removal tasks that many other services struggle with.
## Target Audience
Anyone who needs to remove backgrounds from photos, and wants a "click to remove" workflow, instead of relying on outputs of unguided whole-image removal services. It is a hobby project tailored around my use cases but hopefully stable enough for sharing. The code is pretty rough in places as its my first GUI app
## Comparison
I started
/r/Python
https://redd.it/1hsx9ok
GitHub
GitHub - pricklygorse/Interactive-Image-Background-Remover: Python Tkinter GUI for interactive image background removal
Python Tkinter GUI for interactive image background removal - pricklygorse/Interactive-Image-Background-Remover
So is Django + Vue a good stack?
Hi, I have been stuck in tutorial hell for a while now and decided to build a project for my school. Essentially, its a webpage will allow students to interact with teachers and each other. Can't say much more than that because it is a pretty good business idea and I want to monetise it in the future.
It will need an authentication system, and it will involve the users updating information (so not view only, its dynamic), so a database would be necessary. Because students are using it there has to be no security issues, and it has to be visually pleasing.
I found a teacher at my school that is willing to help me out. He has some experience in Vue, and because I am reasonably familiar with Python, I thought of handling the back end with Django and the front-end with Vue, but I have come across people saying that this is an inefficient stack that doesn't make the best of either technology.
I also tried Firebase initially but couldn't get it to work with Vue because of a ton of "vulnerabilities" that I had no idea how to get rid of, no matter how many times a ran the
/r/django
https://redd.it/1hsvvkk
Hi, I have been stuck in tutorial hell for a while now and decided to build a project for my school. Essentially, its a webpage will allow students to interact with teachers and each other. Can't say much more than that because it is a pretty good business idea and I want to monetise it in the future.
It will need an authentication system, and it will involve the users updating information (so not view only, its dynamic), so a database would be necessary. Because students are using it there has to be no security issues, and it has to be visually pleasing.
I found a teacher at my school that is willing to help me out. He has some experience in Vue, and because I am reasonably familiar with Python, I thought of handling the back end with Django and the front-end with Vue, but I have come across people saying that this is an inefficient stack that doesn't make the best of either technology.
I also tried Firebase initially but couldn't get it to work with Vue because of a ton of "vulnerabilities" that I had no idea how to get rid of, no matter how many times a ran the
/r/django
https://redd.it/1hsvvkk
Reddit
From the django community on Reddit
Explore this post and more from the django community
Do you know a site or a person I can work for as a volunteer in Django?
I have finished learning Django a year ago and have done some private projects and also have intermediate knowledge of HTML and CSS. I have recently learned DRF and have worked on some of my own projectsΨ But I want to work on real projects, develop and keep up with project experts and learn from them and gain experience in this field.
Is it possible to get help?
/r/django
https://redd.it/1hsxytf
I have finished learning Django a year ago and have done some private projects and also have intermediate knowledge of HTML and CSS. I have recently learned DRF and have worked on some of my own projectsΨ But I want to work on real projects, develop and keep up with project experts and learn from them and gain experience in this field.
Is it possible to get help?
/r/django
https://redd.it/1hsxytf
Reddit
From the django community on Reddit
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Saturday Daily Thread: Resource Request and Sharing! Daily Thread
# Weekly Thread: Resource Request and Sharing π
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! π
/r/Python
https://redd.it/1ht11yp
# Weekly Thread: Resource Request and Sharing π
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! π
/r/Python
https://redd.it/1ht11yp
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.
π Courseβ¦
π Courseβ¦
Pycamo: Camouflage Pattern Generator
My project : Github:Pycamo.
What My Project Does:
Pycamo can generate camouflage from a input image base on fractal noise. It's have GUI so you can use it easily. You can custommize: Size, precentage of each color, complexity of pattern.
Target Audience:
It's just a toy
Comparison:
I have seen several camouflage generators online. Camogen Github: Camogen is the one I have found to have the best results. I know my tool is not as good as Camogen but I still wanted to create my own.
/r/Python
https://redd.it/1ht68e9
My project : Github:Pycamo.
What My Project Does:
Pycamo can generate camouflage from a input image base on fractal noise. It's have GUI so you can use it easily. You can custommize: Size, precentage of each color, complexity of pattern.
Target Audience:
It's just a toy
Comparison:
I have seen several camouflage generators online. Camogen Github: Camogen is the one I have found to have the best results. I know my tool is not as good as Camogen but I still wanted to create my own.
/r/Python
https://redd.it/1ht68e9
GitHub
GitHub - Minhtrna/Pycamo: Python Camouflage Pattern Generator, GUI available
Python Camouflage Pattern Generator, GUI available - Minhtrna/Pycamo
Phitter - A Python library for Statistical Distribution Fitting
I just encountered [Phitter](https://github.com/phitterio/phitter-kernel), a Python library that makes statistical distribution fitting both powerful and intuitive. Not my project, but looks very interesting!
# What is Phitter?
Phitter is a robust Python library that helps you identify and fit the most appropriate statistical distributions to your datasets. Think of it as your Swiss Army knife for probability distribution analysis - whether you're working with continuous or discrete data, Phitter has got you covered.
# Key Features:
* Support for 80+ probability distributions (both continuous and discrete)
* Three goodness-of-fit tests (Chi-Square, Kolmogorov-Smirnov, Anderson-Darling)
* Beautiful visualizations (histograms, PDFs, ECDFs, Q-Q plots)
* Parallel processing support for large datasets
* Comprehensive documentation and modeling guides
# Show Me The Code!
Here's how simple it is to get started:
import phitter
# Basic usage
data = [your_data_here]
phi = phitter.PHITTER(data)
phi.fit()
# Get a summary of the top k distributions
print(phi.summarize(k=5))
# Plot the results
phi.plot_histogram_distributions() # Shows fitted distributions
phi.plot_ecdf() # Empirical Cumulative Distribution Function
Want more control?
/r/Python
https://redd.it/1hsqp3x
I just encountered [Phitter](https://github.com/phitterio/phitter-kernel), a Python library that makes statistical distribution fitting both powerful and intuitive. Not my project, but looks very interesting!
# What is Phitter?
Phitter is a robust Python library that helps you identify and fit the most appropriate statistical distributions to your datasets. Think of it as your Swiss Army knife for probability distribution analysis - whether you're working with continuous or discrete data, Phitter has got you covered.
# Key Features:
* Support for 80+ probability distributions (both continuous and discrete)
* Three goodness-of-fit tests (Chi-Square, Kolmogorov-Smirnov, Anderson-Darling)
* Beautiful visualizations (histograms, PDFs, ECDFs, Q-Q plots)
* Parallel processing support for large datasets
* Comprehensive documentation and modeling guides
# Show Me The Code!
Here's how simple it is to get started:
import phitter
# Basic usage
data = [your_data_here]
phi = phitter.PHITTER(data)
phi.fit()
# Get a summary of the top k distributions
print(phi.summarize(k=5))
# Plot the results
phi.plot_histogram_distributions() # Shows fitted distributions
phi.plot_ecdf() # Empirical Cumulative Distribution Function
Want more control?
/r/Python
https://redd.it/1hsqp3x
GitHub
GitHub - phitterio/phitter-kernel: Phitter is a phython library for accurately fitting statistical distributions to datasets, offeringβ¦
Phitter is a phython library for accurately fitting statistical distributions to datasets, offering intuitive usage, comprehensive visualization, and support for multiple distributions to enhance d...
How to create a dynamic formset by reading data from an uploaded file and then allow it to be modified before final submission and storage
Hi,
I have the following usecase:
1) Users can upload a csv file of their bank transactions.
2) The file is parsed and converted into transactions instances and categorized. The categories and list of transactions are shown to the user.
3) The user can then make some modifications (e.g., change categories) and finally submit the formset leading to all transactions being saved in the database.
I am currently struggling with the (3) step and not able to get a formset work which is populated from data not yet in database.
Does anyone have examples of how to solve this? I can share code snippets of course.
Are there better alternatives for this problem? May be HTMX, given that formsets have such bad reviews.
p.s. my current approach is as follows:
I handle the uploaded csv file in the POST view and extract transactions. Using these transaction instances, I populate a formset and then render it. However, when I submit the formset no data is saved.
Any help highly appreciated!
/r/django
https://redd.it/1hss4oy
Hi,
I have the following usecase:
1) Users can upload a csv file of their bank transactions.
2) The file is parsed and converted into transactions instances and categorized. The categories and list of transactions are shown to the user.
3) The user can then make some modifications (e.g., change categories) and finally submit the formset leading to all transactions being saved in the database.
I am currently struggling with the (3) step and not able to get a formset work which is populated from data not yet in database.
Does anyone have examples of how to solve this? I can share code snippets of course.
Are there better alternatives for this problem? May be HTMX, given that formsets have such bad reviews.
p.s. my current approach is as follows:
I handle the uploaded csv file in the POST view and extract transactions. Using these transaction instances, I populate a formset and then render it. However, when I submit the formset no data is saved.
Any help highly appreciated!
/r/django
https://redd.it/1hss4oy
Reddit
From the django community on Reddit
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Accessing foreign key in a template.
I'll use the typical models given with Django examples and explain the problem I'm having.
I'm listing the books out in a template and need to access the author of each book. I've tried {{book.author.name}} and it doesn't work. I've also seen recommendations to use {{book.author_set.all.0}}, but that doesn't work either. Any guidance on whether or not this is possible and how to go about it is appreciated.
/r/djangolearning
https://redd.it/1ht9o67
I'll use the typical models given with Django examples and explain the problem I'm having.
class Author(models.Model): name = models.CharField()class Book(models.Model): name = models.CharField() author = models.ForeignKey(Author)I'm listing the books out in a template and need to access the author of each book. I've tried {{book.author.name}} and it doesn't work. I've also seen recommendations to use {{book.author_set.all.0}}, but that doesn't work either. Any guidance on whether or not this is possible and how to go about it is appreciated.
/r/djangolearning
https://redd.it/1ht9o67
Reddit
From the djangolearning community on Reddit
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Motor Control Simulator in Python
I made a motor control simulator in Python, going over the theory and implementation.
Let me know what you think:
https://youtu.be/CC1rBmhWIqo
/r/Python
https://redd.it/1hted1s
I made a motor control simulator in Python, going over the theory and implementation.
Let me know what you think:
https://youtu.be/CC1rBmhWIqo
/r/Python
https://redd.it/1hted1s
YouTube
Motor Control Simulation: Theory & Implementation
In this video I go over the theory and implementation of a motor control simulation I made.
0:07: Simple circuits
1:30: Ohm's law and Faraday's law
3:55: 3 Phase equations
6:05: Solving equations
10:04: Ramped commands
11:25: PI control
12:12: Third harmonicβ¦
0:07: Simple circuits
1:30: Ohm's law and Faraday's law
3:55: 3 Phase equations
6:05: Solving equations
10:04: Ramped commands
11:25: PI control
12:12: Third harmonicβ¦
Dataclass Wizard: V1 Opt-in Out Now!
# What My Project Does
The Dataclass Wizard simplifies working with Python
Whether youβre working with simple or complex data structures, Dataclass Wizard eliminates boilerplate and optimizes performance, making it easier than ever to handle data.
# Target Audience
Dataclass Wizard is designed for Python developers who:
Work with `dataclasses`, `TypedDict`, or `NamedTuple`.
Need to serialize or deserialize JSON effortlessly.
Value performance and clean, readable code.
Want advanced features like aliasing, recursive type support, or handling complex types.
From API development to data pipelines, if youβre tired of manual conversions or inefficient workflows, this library is for you.
# Comparison
Compared to alternatives like Pydantic, Dataclass Wizard offers:
A lightweight and pure Python solution with minimal dependencies.
Support for
Better performance for specific tasks such as handling `NamedTuple` or recursive types.
An easy-to-extend and intuitive API.
With the upcoming V1 release, the core logic has been rewritten to provide an even more streamlined and powerful experience, addressing inefficiencies and simplifying the libraryβs usage.
# What's New
#
/r/Python
https://redd.it/1htey5l
# What My Project Does
The Dataclass Wizard simplifies working with Python
dataclasses by offering seamless de/serialization to/from JSON. With robust support for features like aliases, recursive types, and a magic-like user experience, this library transforms how you interact with data models in Python.Whether youβre working with simple or complex data structures, Dataclass Wizard eliminates boilerplate and optimizes performance, making it easier than ever to handle data.
# Target Audience
Dataclass Wizard is designed for Python developers who:
Work with `dataclasses`, `TypedDict`, or `NamedTuple`.
Need to serialize or deserialize JSON effortlessly.
Value performance and clean, readable code.
Want advanced features like aliasing, recursive type support, or handling complex types.
From API development to data pipelines, if youβre tired of manual conversions or inefficient workflows, this library is for you.
# Comparison
Compared to alternatives like Pydantic, Dataclass Wizard offers:
A lightweight and pure Python solution with minimal dependencies.
Support for
dataclasses out of the box, rather than relying on custom models.Better performance for specific tasks such as handling `NamedTuple` or recursive types.
An easy-to-extend and intuitive API.
With the upcoming V1 release, the core logic has been rewritten to provide an even more streamlined and powerful experience, addressing inefficiencies and simplifying the libraryβs usage.
# What's New
#
/r/Python
https://redd.it/1htey5l
Reddit
From the Python community on Reddit: Dataclass Wizard: V1 Opt-in Out Now!
Explore this post and more from the Python community
My first python package - MathSpell. Convert numbers to words contextually.
Hi everyone,
I wanted to share a Python package I recently (yesterday) developed called
# Target Audience:
I thought it might be useful for others working on data preprocessing tasks for applications such as text to speech.
# What my project does:
Context aware conversion of numbers into words, handling ordinals, currencies, and years without needing manual configuration.
# Comparisons
Easy to Use: You can simply pass your text to the `analyze_text` function.
Saves Time: It removes the complexity of setting up
# Usage Example
from mathspell import analyzetext
text = "I have $100 and I was born in 1990. This is the 1st time."
transformed = analyzetext(text)
print(transformed)
Output:
I have one hundred dollars and I was born in nineteen ninety. This is the first time.
# Current Limitations
English Only: Currently designed for English. Supporting other languages would require additional work.
Early Development Stage: I developed this
/r/Python
https://redd.it/1htjhrt
Hi everyone,
I wanted to share a Python package I recently (yesterday) developed called
mathspell. It was created to assist with number-to-word conversions in my main project.# Target Audience:
I thought it might be useful for others working on data preprocessing tasks for applications such as text to speech.
# What my project does:
Context aware conversion of numbers into words, handling ordinals, currencies, and years without needing manual configuration.
# Comparisons
Easy to Use: You can simply pass your text to the `analyze_text` function.
Saves Time: It removes the complexity of setting up
num2words for different contexts. It does the heavy lifting by configuring different use cases with reliable libraries (num2words, spaCy, re)# Usage Example
from mathspell import analyzetext
text = "I have $100 and I was born in 1990. This is the 1st time."
transformed = analyzetext(text)
print(transformed)
Output:
I have one hundred dollars and I was born in nineteen ninety. This is the first time.
# Current Limitations
English Only: Currently designed for English. Supporting other languages would require additional work.
Early Development Stage: I developed this
/r/Python
https://redd.it/1htjhrt
Reddit
From the Python community on Reddit: My first python package - MathSpell. Convert numbers to words contextually.
Explore this post and more from the Python community
I Made a Django Deployment Tutorial with PythonAnywhereβSo Grateful It Exists!
I love PythonAnywhere. When I was learning Python, it was a total game-changerβbeing able to open a browser anywhere and just code was amazing. It gave me a safe space to experiment and learn without the hassle of setting things up.
What makes me appreciate it even more now is how much they give back. Their free tier is fantastic, and their paid plans are affordable. Theyβve made coding so accessible, and Iβm genuinely grateful for that.
Back when I was a complete Django newb, I tried deploying on it but struggled a littleβLooking back I think it was probably a typo in the WSGI configuration which made me assume it was too complicated and I switched to other services.
However, more recently I came to realize how simple PythonAnywhere makes it. Features like persistent disks (even in the free tier!) make it such a practical choice, especially for beginners.
A couple of nights ago, I stayed up late to create a "code with me" style tutorial where I deploy a simple Django e-commerce project. If youβre new to deployment or just curious about PythonAnywhere, I hope this helps!
π Check out the tutorial here: https://youtu.be/1nBhFUF6aQ0
Have you tried PythonAnywhere before? Whatβs your go-to
/r/django
https://redd.it/1hteuwv
I love PythonAnywhere. When I was learning Python, it was a total game-changerβbeing able to open a browser anywhere and just code was amazing. It gave me a safe space to experiment and learn without the hassle of setting things up.
What makes me appreciate it even more now is how much they give back. Their free tier is fantastic, and their paid plans are affordable. Theyβve made coding so accessible, and Iβm genuinely grateful for that.
Back when I was a complete Django newb, I tried deploying on it but struggled a littleβLooking back I think it was probably a typo in the WSGI configuration which made me assume it was too complicated and I switched to other services.
However, more recently I came to realize how simple PythonAnywhere makes it. Features like persistent disks (even in the free tier!) make it such a practical choice, especially for beginners.
A couple of nights ago, I stayed up late to create a "code with me" style tutorial where I deploy a simple Django e-commerce project. If youβre new to deployment or just curious about PythonAnywhere, I hope this helps!
π Check out the tutorial here: https://youtu.be/1nBhFUF6aQ0
Have you tried PythonAnywhere before? Whatβs your go-to
/r/django
https://redd.it/1hteuwv
YouTube
How to Deploy a Django Project on Python Anywhere with MySQL Database [free] | Live Coding Tutorial
Let's deploy a Django e-commerce project on PythonAnywhere together! PythonAnywhere offers an easy-to-use platform with free hosting and a built-in MySQL database, making it an excellent choice for deploying Django apps. Weβll walk through the entire deploymentβ¦
makemigrations error
Requested setting CSRF_FAILURE_VIEW, but settings are not configured. You must either define the environment variable DJANGO_SETTINGS_MODULE or call settings.configure() before accessing settings.
when i makemigrations it shows like this, can anyone help me out
/r/djangolearning
https://redd.it/1htjwlx
Requested setting CSRF_FAILURE_VIEW, but settings are not configured. You must either define the environment variable DJANGO_SETTINGS_MODULE or call settings.configure() before accessing settings.
when i makemigrations it shows like this, can anyone help me out
/r/djangolearning
https://redd.it/1htjwlx
Reddit
From the djangolearning community on Reddit
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Sunday Daily Thread: What's everyone working on this week?
# Weekly Thread: What's Everyone Working On This Week? π οΈ
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! π
/r/Python
https://redd.it/1hts9ju
# Weekly Thread: What's Everyone Working On This Week? π οΈ
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! π
/r/Python
https://redd.it/1hts9ju
Reddit
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What do you name your initial project? I have always thought "main" but I'm thinking as I am learning that may not be correct or the best
Currently have my projects setup as
/Users/<USERNAME>/Developer/Python/django/<PROJECT_NAME>/main/
tree example below
.
βββ README.md
βββ WIP_README.md
βββ main
β βββ accounts
β β βββ __init__.py
β β βββ __pycache__
β β β βββ __init__.cpython-312.pyc
β β βββ admin.py
β β βββ apps.py
β β βββ forms.py
β β βββ migrations
β β β βββ __init__.py
β β β βββ __pycache__
β β β βββ __init__.cpython-312.pyc
β β βββ models.py
β β βββ templates
β β β βββ accounts
β β β βββ login.html
β β β βββ signup.html
β β β βββ signup_2.html
β β βββ tests.py
β β βββ urls.py
/r/djangolearning
https://redd.it/1htj6qq
Currently have my projects setup as
/Users/<USERNAME>/Developer/Python/django/<PROJECT_NAME>/main/
tree example below
.
βββ README.md
βββ WIP_README.md
βββ main
β βββ accounts
β β βββ __init__.py
β β βββ __pycache__
β β β βββ __init__.cpython-312.pyc
β β βββ admin.py
β β βββ apps.py
β β βββ forms.py
β β βββ migrations
β β β βββ __init__.py
β β β βββ __pycache__
β β β βββ __init__.cpython-312.pyc
β β βββ models.py
β β βββ templates
β β β βββ accounts
β β β βββ login.html
β β β βββ signup.html
β β β βββ signup_2.html
β β βββ tests.py
β β βββ urls.py
/r/djangolearning
https://redd.it/1htj6qq
Reddit
From the djangolearning community on Reddit
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Sorting Algorithm Visualizations! (with sound) (+ some DSA implementations)
(TLDR, Project here --> https://github.com/pythonioncoder/DSA-Visualizations)
Hey guys!
I just finished a DSA course and decided to implement some of the stuff I learned in a GitHub repo. I also made visualizations for the sorts I learned, so feel free to check it out! It's been a long-time dream of mine to make sorting algorithm visualizations like the famous ones online, but I could never get the hang of it. So, with that in mind, I hope you can appreciate the stuff I've created!
What the project is:
A GitHub repo full of DSA implementations from Linked Lists to BSTs, alongside various sorting algorithms and visualizations implemented in Python using Matplotlib, Numpy, and Pygame.
Target Audience:
Whoever wants to learn more about DSA and Sorting Algos in Python, or just wants to see some cool animations using Matplotlib.
Comparison:
Similar to Timo Bagman's 'Sound of Sorting' project that went viral on youtube a while ago, except on Python.
/r/Python
https://redd.it/1htuwqi
(TLDR, Project here --> https://github.com/pythonioncoder/DSA-Visualizations)
Hey guys!
I just finished a DSA course and decided to implement some of the stuff I learned in a GitHub repo. I also made visualizations for the sorts I learned, so feel free to check it out! It's been a long-time dream of mine to make sorting algorithm visualizations like the famous ones online, but I could never get the hang of it. So, with that in mind, I hope you can appreciate the stuff I've created!
What the project is:
A GitHub repo full of DSA implementations from Linked Lists to BSTs, alongside various sorting algorithms and visualizations implemented in Python using Matplotlib, Numpy, and Pygame.
Target Audience:
Whoever wants to learn more about DSA and Sorting Algos in Python, or just wants to see some cool animations using Matplotlib.
Comparison:
Similar to Timo Bagman's 'Sound of Sorting' project that went viral on youtube a while ago, except on Python.
/r/Python
https://redd.it/1htuwqi
GitHub
GitHub - pythonioncoder/DSA-Visualizations: DSA and Visualizations for various sorting algorithms
DSA and Visualizations for various sorting algorithms - pythonioncoder/DSA-Visualizations
Introcuding kokoro-onnx TTS
Hey everyone!
I recently worked on the kokoro-onnx package, which is a TTS (text-to-speech) system built with onnxruntime, based on the new kokoro model (https://huggingface.co/hexgrad/Kokoro-82M)
The model is really cool and includes multiple voices, including a whispering feature similar to Eleven Labs.
It works faster than real-time on macOS M1. The package supports Linux, Windows, macOS x86-64, and arm64!
You can find the package here:
https://github.com/thewh1teagle/kokoro-onnx
Also, thereβs a demo at the bottom.
/r/Python
https://redd.it/1htwitw
Hey everyone!
I recently worked on the kokoro-onnx package, which is a TTS (text-to-speech) system built with onnxruntime, based on the new kokoro model (https://huggingface.co/hexgrad/Kokoro-82M)
The model is really cool and includes multiple voices, including a whispering feature similar to Eleven Labs.
It works faster than real-time on macOS M1. The package supports Linux, Windows, macOS x86-64, and arm64!
You can find the package here:
https://github.com/thewh1teagle/kokoro-onnx
Also, thereβs a demo at the bottom.
/r/Python
https://redd.it/1htwitw
huggingface.co
hexgrad/Kokoro-82M Β· Hugging Face
Weβre on a journey to advance and democratize artificial intelligence through open source and open science.
Is learning django not good?
I am a student and learning django. I have made 2-3 basics projects using django and django rest framework. But none of my friends or even my seniors are using django. They all are using the javascript frameworks like node.js or next.js. I just wanted to ask is django not used in companies?
Is it not worth it to learn django??
/r/djangolearning
https://redd.it/1hstzgf
I am a student and learning django. I have made 2-3 basics projects using django and django rest framework. But none of my friends or even my seniors are using django. They all are using the javascript frameworks like node.js or next.js. I just wanted to ask is django not used in companies?
Is it not worth it to learn django??
/r/djangolearning
https://redd.it/1hstzgf
Reddit
From the djangolearning community on Reddit
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I made another project template, but for a python package (python, uv, pytest and more)
Hey everyone,
last time, i shared a template to get started with a generative AI project named "generative-ai-project-template". https://github.com/AmineDjeghri/generative-ai-project-template
Now i created another template for packaging python libraries named "Python-Package-Template. You can check it out https://github.com/AmineDjeghri/python-package-template
π οΈ Key Features
Engineering tools:
β’ β Package management: UV
β’ β Code quality: Pre-commit hooks with Ruff & Detect-secrets
β’ β Logging: Colorful logs with Loguru
β’ β Unit tests: Pytest
β’ β Dockerized: Dockerfile & docker-compose for your evaluation pipeline
β’ β Make commands: Simplify your workflow (install, run, test)
CI/CD & Maintenance tools:
β’ β Pipelines: GitHub Actions (.github/workflows) & GitLab CI (.gitlab-ci.yml)
β’ β Local CI/CD pipelines: Run GitHub Actions with act and GitLab CI with gitlab-ci-local
Documentation tools:
β’ β Documentation website: MkDocs + mkdocs-material
β’ β GitHub Pages deployment: Easy deployment with mkdocs gh-deploy
Any feedback, issues, or PRs are welcome!
/r/Python
https://redd.it/1hu0ojq
Hey everyone,
last time, i shared a template to get started with a generative AI project named "generative-ai-project-template". https://github.com/AmineDjeghri/generative-ai-project-template
Now i created another template for packaging python libraries named "Python-Package-Template. You can check it out https://github.com/AmineDjeghri/python-package-template
π οΈ Key Features
Engineering tools:
β’ β Package management: UV
β’ β Code quality: Pre-commit hooks with Ruff & Detect-secrets
β’ β Logging: Colorful logs with Loguru
β’ β Unit tests: Pytest
β’ β Dockerized: Dockerfile & docker-compose for your evaluation pipeline
β’ β Make commands: Simplify your workflow (install, run, test)
CI/CD & Maintenance tools:
β’ β Pipelines: GitHub Actions (.github/workflows) & GitLab CI (.gitlab-ci.yml)
β’ β Local CI/CD pipelines: Run GitHub Actions with act and GitLab CI with gitlab-ci-local
Documentation tools:
β’ β Documentation website: MkDocs + mkdocs-material
β’ β GitHub Pages deployment: Easy deployment with mkdocs gh-deploy
Any feedback, issues, or PRs are welcome!
/r/Python
https://redd.it/1hu0ojq
GitHub
GitHub - AmineDjeghri/generative-ai-project-template: Template for a new generative ai project using uv, nicegui, fastapi, llmsβ¦
Template for a new generative ai project using uv, nicegui, fastapi, llms (cloud & local with litellm and ollama) and langfuse for llm observability - AmineDjeghri/generative-ai-project-template