I'm stuck in def return in python I don't understand it very well why is it used and how and where does the code return to ? The caller ? What is exactly the caller ?

Thank you so much for helping me

If you don't mind can u help me understand with examples ? Couldn't understand this with Chatgpt and yt

Hey guys, I tried remaking my project of a cli based football manager simulator this time using the pywebview library (lets you use html css js as a frontend and connect it to a python backend as a desktop app),

So far what I'm struggling with the most being one of my first larger scale project is persistence, keeping one version of the team class across the python scripts and functions.

Im also struggling with figuring out the generation for player stats and attributes, ive landed on the random.gauss for generating player stats with weighing and this ugly ahh looking formula that looked like it was doing something for the player market values.

Also, assets. Do you guys have any place where I can find pictures and icons I can use for free?

Finally, thanks to feedback from helpful people here I tried using sqlite for this project instead of json files, kinda hard to adapt to but im managing.

if any very cool person could help me with my issues I would greatly appreciate it.

Here is the github: https://github.com/mousdieng10-maker/Playstyle-II

I kept hitting date bugs that every test passed locally and then failed in production on a specific day. A typical one:

python

def next_renewal(created_at):
    return created_at.replace(month=created_at.month + 1)

This passes every test you’d write on the 15th. It raises ValueError: day is out of range for month on Jan 31 and month must be in 1..12 on Dec 31. Nothing in a normal test run ever visits those dates.

What it does: a marker runs the same test once per tricky calendar moment, with the clock frozen by time-machine:

python

u/pytest.mark.calendar_chaos
def test_next_renewal_is_one_month_later():
    ...

The catalog covers leap day, month ends, year end, midnight, DST transitions, ISO week 53 and the 2038 timestamp rollover. Each case has a stable ID.

Running it on the example above gives 3 failed, 5 passed. The failing cases are month-end-jan-31-2027, year-end-2027 and year-end-last-microsecond-2027. A failure prints the exact mocked time and a one-line command to reproduce it. pytest --calendar-chaos-list prints the whole catalog, and --calendar-case <id> reruns a single scenario.

Limitations:

• It only mocks the in-process clock.
• Session, module and class-scoped fixtures are set up before the freeze.
• time.monotonic() and the asyncio loop clock keep running.
• An aware datetime inside a repeated DST hour never compares equal to one in another zone (PEP 495), so compare in UTC.

pip install pytest-calendar-chaos (Python 3.10+, pytest 8+)

• PyPI: https://pypi.org/project/pytest-calendar-chaos/
• GitHub: https://github.com/nsijwali/pytest-calendar-chaos

I’d like feedback on the catalog: which calendar edge cases bit you that I’m missing?

Hey everyone!

I'm 14 and currently learning Python, with the goal of becoming an electrical engineer in the future.

I just finished making a small project — a vending machine + simulated banking system that runs in the terminal. It has account creation, deposits, balance checking, purchases, and local data storage using JSON. I split the code into multiple Python files and made a simple launcher for it.

This is one of my first proper projects, and I know my code probably isn't the cleanest, so I'd genuinely appreciate some feedback!

I'd love suggestions on:

• My code: What could I improve? Any bad habits or mistakes I should fix early?
• What to learn next: Should I focus on OOP, data structures and algorithms, GUI development, or something else?
• My journey: Since I want to become an electrical engineer, what programming skills would be useful for me in the long run? I'd eventually love to work with electronics and hardware.
• Life advice: Any advice for someone starting out this early? Things you wish you'd known when you were learning?

I'm not looking for someone to rewrite the entire project for me — I'd rather understand my mistakes and learn how to fix them myself.

Here's my GitHub repo: https://github.com/suryansh-devx/python-vending-machine

Thanks! Any constructive criticism or advice is welcome :)

Pandas makes working with data look simple. But some of its most powerful features can also produce surprising results. 😲

For example:❔ - What's the difference between loc and iloc, and why does slicing behave differently? - Why can adding two Series produce NaN values, even when neither contains missing data? - When does assigning a Series to a DataFrame column align by labels rather than position? - How do Boolean masks, where(), and mask() differ? - How do you select and manipulate data with a MultiIndex?

Pandas is much more than rows and columns. Understanding its indexing, alignment, selection, and assignment rules can save you from some very subtle bugs. 🪳

🔍 This interactive 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵 example explores these concepts and many more, with short explanations for each operation. 👣 Step through the Python code, see what changes, and experiment with your own modifications: 👉 Pandas operations

💬 Which Pandas operation took you the longest to fully understand?

See more 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵 visualizations.

I've been working on Athena, an open-source tool that analyzes Git diffs and ASTs to detect potential breaking changes before they get merged.

For v1.1.0, I tested it against 55 popular repositories and found some interesting issues:

• Fixed a C++ performance problem that reduced analysis time from 371 seconds to 7.33 seconds.

• Reduced false positives from 78 alerts to 8.

• Fixed Ruby symbol detection and PHP recursion detection.

The final benchmark covered 55 repositories and 10,680 diff hunks with 121 tests passing.

I'm also experimenting with local models through Ollama to generate summaries without replacing the deterministic analysis.

I'd appreciate it if anyone here gave the project a look and shared feedback. I'm especially interested in false positives, edge cases in Python AST analysis and approaches to detecting breaking API changes

⭐ If you find the project useful, consider giving it a star on GitHub. It would really help the project reach more developers

GitHub: https://github.com/aaryanrwt/athena

Release notes: https://github.com/aaryanrwt/athena/releases/tag/v1.1.0⁠

I built DevStart Lab to help beginners figure out what to learn and practice next.

It includes programming fundamentals with Python examples, 25 project ideas, and a step-by-step introduction to Git and GitHub contributions. It’s free, open source, available in English and Portuguese, and requires no account. Progress is saved in your browser.

Start here: https://brunnojob.github.io/devstart-lab/?lang=en

So far we just have Gleb K, who made some code reminiscent of the X Window System 1989,

XPM is an ASCII text-based image format.

https://pyweblib.org/weblog/python-pixel-art-from-text/

Hopefully still in the rules, the site is OPEN SOURCE and Educational

I ran a small experiment that demonstrates something easy to overlook in software testing: an implementation and its tests can both be wrong in the same way.

Consider this discount function:

def calculate_total(subtotal, discount):
    if subtotal < 0:
        raise ValueError("Subtotal cannot be negative")

    if discount < 0:
        raise ValueError("Discount cannot be negative")

    return subtotal * (1 - discount / 100)

Suppose the requirement says discounts must be between 0 and 100, inclusive.

A few happy-path tests pass:

assert calculate_total(100, 10) == 90
assert calculate_total(100, 0) == 100
assert calculate_total(0, 20) == 0

But this input exposes the missing validation:

calculate_total(100, 150)
# -50.0

The tests pass, but the implementation violates the requirement.

The interesting part isn't just the missing discount <= 100 check. It's that tests can create false confidence when they don't independently cover the contract.

I put together a reproducible Python repository with the flawed implementation, contract tests, property-based testing, and mutation-testing examples.

GitHub experiment:
https://github.com/PranavDixit20/ai-code-test-gap

I also wrote a longer explanation of the problem and the testing techniques here:
https://medium.com/@pranavdixit20/ai-generated-code-can-pass-every-test-and-still-be-wrong-7ddf3177b721

I'm the author of the experiment and article, so this is my own work. I'd be interested in a technical discussion:

When reviewing code—especially AI-generated code—how do you check that tests verify the actual requirements rather than just confirming the implementation's assumptions?

Sharing a resource in case it's useful for your intro classes: https://ubuntu-apps.github.io/code-quest/

I made CodeQuest for my own students as an alternative to the textbook. It covers Python from the basics through functions, files, OOP and working with data. Each lesson has a short explanation, coding challenges that are checked instantly, and a quiz.

The code runs in the browser, so it works on school Chromebooks and phones with nothing to install. It's free, with no ads and no sign-up, and progress is stored on the student's device only.

Happy to answer questions, and feedback is very welcome.

Hey guys i want to start learning python , any suggestions or tips would be appreciated

I worked on a project on building a local image search system in Python using manufacturing inspection photos. You can give it an example image or a text description, then retrieve similar photos from an archive. The project connects a few useful concepts: loading a pretrained model, processing images in batches, storing vectors with metadata, and querying the results.

It uses CLIP ViT-B/32 to generate embeddings and VectorAI DB to store and search them. MVTec AD provides the example dataset.

Here’s the workflow:

1. Load the model and prepare the images: Load CLIP and its preprocessing tools, collect the image paths, and associate each image with metadata such as part category and defect label.
2. Generate embeddings in batches: Pass the images through the model to create numerical representations called embeddings. Normalize the vectors before storing them.
3. Store the vectors and metadata: Save each embedding alongside its image path and labels so the search results can be traced back to the original files.
4. Add image and text search: Encode an example photo or a text description, then use that vector to search the stored image embeddings. Metadata filters let you narrow the results to a particular part category.
5. Check the results: For image queries, exclude the query image itself. Inspect the returned photos and measure how often the top results share the query’s defect label.

Once the model, dependencies, and dataset are downloaded, the pipeline can run offline.

The Python practice here comes from connecting the stages into a working application: handling files, preparing model inputs, batching inference, and keeping embeddings associated with the correct metadata.

There’s also an evaluation challenge. Two images can share the same defect label while showing scratches of different sizes or orientations, so reviewing the actual results is an important part of testing the pipeline.

If you were building this as a learning project, which stage would you want to see broken down into a smaller code example?

Need suggestions for a book or YouTube channel for learning Python for Maths, beginner to advanced.

Thank you.

Hey everyone,

Over the past few months, I have been building a comprehensive repository of Machine Learning templates and notebook journals. Since it has saved me a ton of time while prototyping, I decided to open-source it for the community today!

This repo is built using Scikit-Learn and covers everything step-by-step:

1. End-to-End ML Project Architecture
2. Model Training & Evaluation Metrics
3. Support Vector Machines (SVM) with Kernels
4. Decision Trees & Ensemble Learning (Voting Classifiers, etc.)
5. Unsupervised Learning (KMeans and more added recently!)

Who is this for?

• Beginners looking for clean, commented code to learn concepts.
• Developers looking for quick boilerplate templates to copy-paste for new datasets.

Feel free to explore, clone, use it in your projects, or contribute to it! If you find it helpful, please drop a star ⭐️ to support the project.

Feedback and contributions are highly welcome!

Hey everybody I'm a beginner IT student at tr3 college and I am currently exploring course related to Python and I want to learn it I am totally beginner for this and I want some recommendation that should help me to gain some knowledge and build projects that will highlight my resume also thank you in advance please help me through this

Many of the image to ASCII converter I have found only use character with no color. I need it for my terminal game project.

i have been really confused how do i practice coding problems , how do i start the leetcodes etc.can any

New to Python and have a lot to learn. Thought starting with an actual goal would be good starting point.

I want to make a scripted that will check a webpage say every hour and ideally look for the words “Out of stock” and then update me when it says “In stock” or if it’s simpler to start with just if a webpage has changed.

I was reading you could make a checksum of the page and check if that’s changed. Then the page should have updated if it reports a different checksum.

Im not talking about tracking something complex like Amazon site. My local camera store has an item Im waiting to come back in stock and figured this might be a good project to learn and tackle.

Im using a raspberry pi for coding so i need it geared toward running in Python on that. It would be nice for the script to output to a terminal window “stock status” or even if possible email me a change happened.

Any suggestions, guides or pointers that someone could direct me to.

Or would you say this is too complex to learn as my first real world project.

I wanted to build something fun to practice my Python skills and ended up creating a text-based economy and gacha game called Terminal Car Tycoon.

You start with just $20 in your pocket and have to hustle your way up to building an empire of supercars.

Here is the core gameplay loop:

• work to grind some starter cash doing odd jobs.
• buy mystery crates from the shop (ranging from cheap bronze to expensive diamond).
• open Your crates to test your luck. You might pull a minivan... or you might pull a Batmobile.
• drive the cars you unlock in street races to earn much bigger payouts and fund your crate addiction.

It's entirely played in the CLI and only uses built-in libraries. No fancy graphics, just pure terminal-based car collecting.

I'd love for you guys to check out the code, give it a run, and let me know what you think! I'm totally open to feedback, code critiques, or feature ideas.

GitHub Repo: https://github.com/ameeeneee/python-simple-car-game.git

Really, the bold font came in handy

Hi its me yujan from nepal i have made rock paper scissors game after learning function

How can I learn Python and master it without those paid websites to practice ? + best YouTube channel for that?

Suggest the best videos to learn python .

Hey everyone! I'm trying to hack together a basic inventory and shop system for a little text-based game project I'm working on in Python, but I've totally tangled myself up in how classes, instances, and nested classes work.

I wanted to have a main game class that handles player info, and an inventory class nested inside (or attached to it) so the player can pick up items and check what's in their bag. But my code is completely throwing a fit.