Beautiful Pancakes - A simple way to implement file writing and opening on PyQt's QGraphicsScene

Hey all!

# I am a relatively new Python programmer with experience in PyQt blah blah blah...

Anyways, when I was creating QGraphicsScene test files, I wanted to figure out a way to write QGraphicsItems to files, and then read those files to open them. This really doesn't exist for PyQt/PySide, as I have only found ways to do that in C++ Qt.

*So thats why I just finished Beautiful Pancakes today, [here's the repository\](https://github.com/ktechhydle/beautiful_pancakes).*

# What my project does

Implements file reading and writing for QGraphicsScenes with full support for file dialogs. PySide6 and PyQt5 supported.

# Target audience

It's great for basic to complex scenes, but I will try to update it and eventually make it work for advanced and performance heavy scenes.

# Comparison

There are alternatives, but most are written in C++. I have yet to find a PyQt version.

All serialization/deserialization is done in Pickle.

I hope you enjoy.

/r/Python
https://redd.it/1eznfvj

Django Full Course for Beginners
https://youtu.be/6whz7Ujfpw0?si=sw2A2G1VifKbdVBf

/r/djangolearning
https://redd.it/1ezhuec

vectorized CIE distance in basiccolormath 3.0

[ShayHill/basic\colormath: Simple color conversion and perceptual (DeltaE CIE 2000) difference (github.com)](https://github.com/ShayHill/basiccolormath)

# What My Project Does

Everything I wanted to salvage from the [python-colormath](https://github.com/gtaylor/python-colormath/tree/master) library ... with no numpy deps and 14x speed.

* Perceptual (DeltaE CIE 2000) and Euclidean distance between colors
* Conversion between RGB, HSV, HSL, and 8-bit hex colors
* Simple, one-way conversion to Lab
* Some convenience functions for RGB tuples and 8-bit hex color strings

# Target Audience

Meant for production.

# vectorized functions

If you have numpy installed in your env, basic\colormath will provide vectorized versions of most functions.

|Function|Vectorized Function|
|:-|:-|
|float_to_8bit_int|floats_to_uint8|
|get_delta_e|get_deltas_e|
|get_delta_e_hex|get_deltas_e_hex|
|get_delta_e_lab|get_deltas_e_lab|
|get_euclidean|get_euclideans|
|get_euclidean_hex|get_euclideans_hex|
|get_sqeuclidean|get_sqeuclideans|
|get_sqeuclidean_hex|get_sqeuclideans_hex|
|hex_to_rgb|hexs_to_rgb|
|hsl_to_rgb|hsls_to_rgb|
|hsv_to_rgb|hsvs_to_rgb|
|rgb_to_hex|rgbs_to_hex|
|rgb_to_hsl|rgbs_to_hsl|
|rgb_to_hsv|rgbs_to_hsv|
|rgb_to_lab|rgbs_to_lab|

# Comparison

Sadly, python-colormath has been abandoned, long enough now that a numpy function on which it relies has been not only deprecated but removed. If you still need to use python-colormath, patch np.asscalar:

import numpy as np
import numpy.typing as npt

def patchasscalar(a: npt.NDArraynp.float64) -> float:
"""Alias for np.item(). Patch np.asscalar for colormath.

:param a: numpy array
:return: input array as scalar
"""


/r/Python
https://redd.it/1ezjfx2

No vote of non-confidence as a result of recent events

Here is the python.org discussion affirming the Steering Council's actions with respect to Tim Peters, David Mertz, and Karl Knechtel.

/r/Python
https://redd.it/1f00qdo

Okrolearn a machine learning library which is for powerful analzys and training while being light

I’m excited to share a project I’ve been working on called okrolearn. Which was created to allow for powerful analazys features and neural network training capabilities my own ideas while being as light as possible.

Target audience:

Machine learning enjoyers, mobile machine learning coders, data scientists.

Comparison:

Compared to things like pytorch or tensorflow it has better macOS support, better cpu usage, is way more light weight, is designed for lighter models, has features that these don't have,

What my project does:

* Trainin machine learning models

* Deploy models

* Is light

* Have analazys features such as correlation heatmaps, plotting kmeans, histograms, plotting losses, paramaters, etc.

* Manage layers for models, convolutional, l regularisation, batch, instance, dropout normalisers

* Have gpu support, custom kernels on gpu

* Have experimental features such as suggesting architecture and layers based on temperature and input data

* Have better macOS support

* Have better cpu performance

Why did I create this for simpler models or models that had to be lightweight tensorflow or pytorch didn't do a good job, I also wanted this library to be mainly in python, also converting pytorch tensors back to numpy arrays for me to analyse them was to slow and annoying, there were also ideas that I wanted to implement on

/r/Python
https://redd.it/1f02lho

Make-like task runner in Python

I made a complete Make-like build tool & task runner in Python.

I wanted to adopt Make's scheme of rules, targets, recipes, and dependencies mainly because it's simple, intuitive, and widely used.

Inspiration for the project came from using doit for similar tasks, and growing tired of the confusing API. There are other similar tools out there, but what I wanted was a lightweight, easy-to-use, flexible, and well documented task runner & dependency resolver for a data processing pipeline in Python.

GitHub: https://github.com/gird-dev/gird

Simple example & comparison with doit: https://stackoverflow.com/a/77752742

Rule definition example: https://github.com/gird-dev/gird?tab=readme-ov-file#example-girdfilepy

/r/Python
https://redd.it/1f028a6

A Dead Simple Work Queue Using SQLite

I wrote an article on using sqlite3 to create an asynchronous task queue. I am hoping to share it in case anyone is interested and also to get some feedback. Please let me know what you think, and thank you! https://blog.tomhuibregtse.com/a-dead-simple-work-queue-using-sqlite

/r/Python
https://redd.it/1f06ft5

Flask Full Tutorial For Beginners
https://youtu.be/klaRFL8UfNs?si=bopWI1sgWqTwJFT8

/r/flask
https://redd.it/1f09ctm

Django site ready - but having trouble deploying in azure as web app or docker (inexperienced)

Hey y’all! Been working on a project and ready to drop the MVP on azure for UAT. But even though I’m azure fundamentals certified I am lacking in the deployment department and can’t quite get my azure web app up and clearing a 200 status code. Looking for help or even a recommendation for experienced help to get me familiar with the process.

Here’s where I’m at:
1. Django project with 2 apps, email and Postgres DB, all working in dev
2. Have a “deployment.py” file that is referenced if os.environ() finds an azure host name, otherwise debug version of settings.py is used
3. Deployed the app via GitHub repo connected to azure. In the deployment logs I get a warning that “Django must be in the requirements.py file” but it is. No other errors seen
4. When accessing the webpage using the azure temporary url I get a 504 error.
5. I can’t troubleshoot much further since I can’t find where other logs are located and the documentation I have found is outdated and doesn’t match the current azure UI

Any help or leads for troubleshooting are appreciated! Please feel free to ask for more info if I haven’t provided it!

/r/djangolearning
https://redd.it/1f07rqp

How to schedule a daily recurring function?

Hello everyone

So I built a basic backend and was wondering - how can I implement a function that has to run for example every day at 1pm?

Is there a classic way in Flask to do this?

Thank you very much!

/r/flask
https://redd.it/1f097gr

Doing testing in flask application.

Hi I am build an web application in flask using flask sqlalchemy and flask login for now.

Here is my conftest.pyfile

from app import createapp, db
from config import TestConfig
from flasklogin import FlaskLoginClient
import pytest

@pytest.fixture(scope="session")
def app():
app = createapp(TestConfig)
app.testclientclass = FlaskLoginClient

with app.appcontext():
db.createall()

yield app

@pytest.fixture(scope="session")
def client(app):
return app.testclient()


here is my test_auth.py

def testsignupget(client):
res = client.get("/auth/signup")
assert b"<h2>Register Form</h2>" in res.data

def testsignuppost(client, app):
res = client.post("/auth/signup", data={


/r/flask
https://redd.it/1f0dak2

flash message.. show only 1 at a time.

how can I clear the current flash message before showing another.
I don't want to have a list of them show on the screen.




this is my code for show the messages

<footer class="mt-auto fixed-bottom">
{% with messages = get_flashed_messages(with_categories=true) %}
{% if messages %}
{% for category, message in messages %}
{% if category == 'message' %}
<div class="alert alert-warning" role="alert">
{% else %}
<div class="alert alert-{{ category }}" role="alert">
{% endif %}
{{ message }}
</div>
{% endfor %}
{% endif %}
{% endwith %}
</footer>

/r/flask
https://redd.it/1ezde6j

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/1f0jb7c

Looking for a Job Urgently.

Hey guys, i know this is not the place for this and i know its a long shot, but i think it is worth a shot.

my name is Goodluck, 20 years old.

i recently wrote my final exams in college, so i'm almost a college graduate in Computer science. i need a job as soon as possible. I'm proficient in python and can build flask apps. i am a fast learner, so the things i don't know, i can pick up on the job without being a burden or slowing down the workflow. i know some people would advice to get an official job, but i haven't been lucky enough to get one. Most of the ones i've seen on twitter were either closed or just scams to get me to create an account with the job application service. I've applied for a few and i got rejected in all.

I'm looking for a python backend entry/intern role. I've never really worked in a real life industry since i mostly learnt from tutorials on Youtube and torrent courses, but i know i can handle an intern role. I don't mind working as an assistant to someone and i don't

/r/flask
https://redd.it/1ezok6c

How to elegantly use pydantic to parse YAML files containing rust enum types ?

I have been working on how to convert YAML containing enum defined by Rust to Pydantic recently, and finally I have the following solution.

from enum import Enum, IntEnum
from typing import Any, Union

from pydantic import BaseModel, Discriminator, Tag
from typing_extensions import Annotated

class TypeKey:
pass
def constructor(loader, node):
data = loader.construct_mapping(node)
data[TypeKey] = node.tag[1:]
return data


def make_constructor_enum(cls):
if isinstance(cls, type(IntEnum)):
def constructor_enum(loader, node):
data_str = loader.construct_scalar(node)
for item in cls:


/r/Python
https://redd.it/1f0oud5

Track migration files in git : What are the good practices ?

The title is quite explanatory, I am still unsure of what is the best way to go about it. What do you guys do ?

/r/django
https://redd.it/1f0s0gc

I switched from full stack to streamlit/python and it reduced my development time to 2 weeks !

Just 2 months ago, I was always building full stack apps that took me ages to build and rarely found any traction.

I am pretty good with python, so I was looking for a quick way to prototype my idea and validate it.

The hidden gem there was Streamlit, a python package that makes it possible to turn your scripts into apps and deploy them on the cloud.

You don’t have to worry about backend or even only limited on frontend. Your job is just to integrate the functionality. I am not associated to Streamlit anyhow, but I just wanted to show for anyone who did not know it before that it is a great way for prototyping. 🙏

In my case, I have connected the OpenAI API, built out a custom python script, connected a Supabase Database and integrated it into the Streamlit front end.

It is also possible to use common packages like pandas or matplotlib to visualise results pretty easily and make them interactive. 🆙

/r/Python
https://redd.it/1f07c7d

🛠️ Hands-On with llmio: Let's Build an AI Task Manager 🤩

Hey r/Python and fellow developers!

Earlier this week, I shared an introduction to [**llmio**](https://github.com/badgeir/llmio), a lightweight Python library I developed for building LLM-based agents with ease. I really appreciate the positive feedback and the support from those who checked it out!

Today, I’m following up with something every developer has probably built at least once—a todo-list app! 🤩 Yes, it’s a classic, but it’s also a perfect example to show how llmio can be used in real-world applications. Specifically, I’ve put together a [notebook](https://github.com/badgeir/llmio/blob/main/examples/notebooks/simple_task_manager.ipynb) that demonstrates how to create a simple Task Manager using `llmio`.

### 🔧 A Quick Recap of Key Features:

- **Type Annotation-Based Tooling**: Define tools effortlessly using Python’s type annotations.
- **Broad API Compatibility**: Works out of the box with OpenAI, Azure, Google Gemini, AWS, and Huggingface APIs.
- **Lightweight**: A minimalistic library that integrates seamlessly into your projects without adding unnecessary bulk.

### 💻 Demo: Building a Task Manager with `llmio`

In this [notebook](https://github.com/badgeir/llmio/blob/main/examples/notebooks/simple_task_manager.ipynb), I walk through how to build a Task Manager that can list, create, update, and delete tasks. This example showcases `llmio`'s ability to leverage LLMs for practical applications while maintaining control over task execution and context management.

### 🚀 Getting Started:

- **Install**: `pip install llmio`
- **Example**:
```python


/r/Python
https://redd.it/1f0upad

Any hints/ideas on how to make this?

/r/django
https://redd.it/1f0vhdx

Let's write FizzBuzz in a functional style for no good reason

# What My Project Does

Here is something that started out as a simple joke, but has evolved into an exercise in functional programming and property testing in Python:

https://hiphish.github.io/blog/2024/08/25/lets-write-fizzbuzz-in-functional-style/

I have wanted to try out property testing with Hypothesis for quite a while, and this seemed a good opportunity. I hope you enjoy the read.

Link to the final source code:

- https://gitlab.com/HiPhish/functional-fizzbuzz
- https://github.com/HiPhish/functional-fizzbuzz

# Target Audience

This is a toy project

# Comparison

Not sure what to compare this to

/r/Python
https://redd.it/1f0ywkp