Hi there! I've completed a project recently that I would like to share. It is a productivity tracker that allows you to record how much time you spend working on something. Here is a link to it https://github.com/tossik8/tracker. I made this project because I wanted to improve my time management. Feel free to leave your feedback and I hope some of you find it useful as well! submitted by /u/EstimateConfident492 [link] [comments]

Hey everyone, I’ve been working on a fullstack template aimed at solo devs or indie hackers who want to build and ship something without spending money on infrastructure. I put a lot of effort into making sure everything works out of the box and included step-by-step guides so you can actually deploy it—even if you’ve never done it before. What’s in it: Detailed Tutorials & config template to eploy backend to Vercel and frontend to Cloudflare (both have free tiers) Supabase for database and auth (also free tier) Generate frontend client based on backend API Dashboard with metrics and analytics User management and role-based access control Sign up / sign in with OAuth Task management with full CRUD Pre-configured dev setup with Docker and hot reload it’s meant to be used as a quick project starter for app developed by a single person, It followed solid backend/frontend practices, used modern tools (React 19, TypeScript, Tailwind, OpenAPI, etc.), and tried to keep the architecture clean and easy to extend. frontend is based on this great project called shadcn-admin (https://github.com/satnaing/shadcn-admin) If you’re trying to build and deploy a real app with no cost, this could be interesting to you. Whether you’re making a SaaS, a side project, or just want to understand the fullstack flow better, I hope this saves you some time. Still actively improving it, so any feedback is appreciated. Github [github-fullstack-solopreneur-template](https://github.com/raceychan/fullstack-solopreneur-template/tree/master) submitted by /u/Last_Difference9410 [link] [comments]

EDIT: I admit I was wrong, most of what I named wasn't Flask's fault, but my Python incompetence thank you all for telling me that. And I realised the speed argument was bullshit /serious I like webdevelopment. I have my own website that I regularly maintain, built with svelteKit. It has a frontend (ofc) and a backend using the GitHub API. Recently our coding teacher gave us the assignment to make a website with a function backend, but we HAD to use Flask for backend. This is because our school only taught us python, and no JavaScript. Keep in mind we had to make a regular website (without backend) before this assignment, also without teaching Javascript. Now I have some experience with Flask, and I can safely say that I feel nothing but pure hate for it. I am not joking when I say this is the worst and most hate inducing assignment I have ever gotten from school. I asked my fellow classmates what they thought of it and I have only heared one response: "I hate it". Keep in mind in our school coding is not mandatory and everyone who participates does so because they chose to. Its a combination of Pythons incredibly annoying indentation, Pythons lack of semicolon use, The slowness of both Flask and Python, Flasks annoying syntax for making new pages, HTML files being turned into django-HTML, which blocks the use of normal HTML formatters which is essential for bigger projects, and also removes the normal HTML autocomplete, Flaskforms being (in my experience) being incredibly weird, Having to include way to many libraries, Hard to read error messages (subjective ofc), The availability of way better options, and more (like my teacher easily being the worst one I currently have) result in a hate towards Flask, and also increased my dislike of python in general. I know that some of those are Pythons quirks and thingeys, but they do contribute so I am including them. Please tell me that I am not the only one who hates Flask submitted by /u/DefenitlyNotADolphin [link] [comments]

I’ve been working on a Python-focused book called Mastering Modern Time Series Forecasting — written to bridge the gap between theory and practice for time series modeling. It covers a wide range of methods, from classical models like ARIMA, ETS, Theta, MSTL, TBATS to modern machine learning and deep learning techniques like CatBoost, LightGBM, Transformers, N-BEATS, and TFT. The focus is on both fundamentals and practical implementation, using tools like statsforecast, mlforecast, neuralforecast, scikit-learn, statsmodels, PyTorch, and Darts. Topics include handling messy time series data, feature engineering, evaluation, and deployment. 📘 The book is in early release (220+ pages) and growing fast. 📂 A companion GitHub repo is live and code will be added progressively: 🔗 GitHub Repo I’m publishing the book on Gumroad and LeanPub — links will be in the comments if anyone’s interested. Open to feedback or discussion — thanks for reading! submitted by /u/predict_addict [link] [comments]

This is just a question out of curiosity, but back in 1999 I had to work with Python and Zope, as time progressed, I noticed that Zope is hardly if ever mentioned anywhere. Is Zope still being used? Or has it kinda fallen into obscurity? Or has it evolved in to something else ? submitted by /u/RevolutionarySeven7 [link] [comments]

Hey everybody! I just wanted to share a small library I wrote for some internal tooling that I thought could be useful for the wider community, called SimplePyQ. The motivation for this was to have something minimalistic and self-contained that could handle basic task queueing without any external dependencies (such as Airflow, Redis, RabbitMQ, Celery, etc) to minimize the time and effort to get that part of a project up and running, so that I could focus on the actual things that I needed. There's a long list of potential improvements and new features this library could have, so I wanted to get some real feedback from users to see if it's worth spending the time. You can find more information and share your ideas on our GitHub. Do you have any questions? Ask away! TL;DR to keep the automod happy What My Project Does It's a minimalistic task queueing library with minimal external dependencies. Target Audience Any kind users, ideally suitable for fast "zero to value" projects. Comparison Much simpler to set up and use compared to Celery. Even more minimalistic with less requirements than RQ. submitted by /u/kevindewald [link] [comments]

Weekly Thread: Professional Use, Jobs, and Education 🏢 Welcome to this week's discussion on Python in the professional world! This is your spot to talk about job hunting, career growth, and educational resources in Python. Please note, this thread is not for recruitment. How it Works: Career Talk: Discuss using Python in your job, or the job market for Python roles. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally. Guidelines: This thread is not for recruitment. For job postings, please see r/PythonJobs or the recruitment thread in the sidebar. Keep discussions relevant to Python in the professional and educational context. Example Topics: Career Paths: What kinds of roles are out there for Python developers? Certifications: Are Python certifications worth it? Course Recommendations: Any good advanced Python courses to recommend? Workplace Tools: What Python libraries are indispensable in your professional work? Interview Tips: What types of Python questions are commonly asked in interviews? Let's help each other grow in our careers and education. Happy discussing! 🌟 submitted by /u/AutoModerator [link] [comments]

I've seen some people saying that Python isn't really necessary to get started in the field, but I began learning it specifically because I plan to move into cybersecurity in the future. I’d love to hear from people already working in the area — how much does Python actually matter? submitted by /u/Wendellcesar [link] [comments]

Hey r/Python, I wanted to share a project I've been working on: a simple but powerful AI-powered chatbot for WhatsApp, with Python at its core. Here's the GitHub link upfront for those who want to dive in: https://github.com/YonkoSam/whatsapp-python-chatbot What My Project Does The project is an open-source Python application that acts as the "brain" for a WhatsApp chatbot. It listens for incoming messages, sends them to Google's Gemini AI for an intelligent response, and then replies back to the user on WhatsApp. The entire backend logic is written in Python, making it easy to customize and extend. Target Audience This is primarily for Python hobbyists, developers, and tinkerers. It's perfect if you want to: Create a personal AI assistant on your phone. Automate simple FAQs for a small community or project. Have a fun, practical project to learn how to connect Python with external APIs (like Gemini and a WhatsApp gateway). It's not designed for large-scale enterprise use, which would be better served by the official (and much more complex/expensive) WhatsApp Business API. Comparison to Alternatives I built this because I saw a gap between the different existing solutions: vs. The Official WhatsApp Business API: The official API is powerful but can be very expensive and complex to get approved for and set up. My project is a lightweight, low-cost alternative ($6/month for the gateway) that's accessible to individual developers and small projects without the corporate overhead. vs. Other Open-Source Libraries (e.g., whatsapp-web.js): Many open-source libraries that directly interface with WhatsApp are fantastic but can be unstable and break with every WhatsApp update. I made a conscious trade-off to use a stable, low-cost gateway API for the connection. This lets you focus on the fun part—the Python logic—instead of constantly fixing the connection. vs. No-Code Platforms: No-code builders are easy but are closed-source and lock you into their ecosystem. This project is fully open-source. You have 100% control over the Python code to add any custom integration or logic you can dream of. I'd love to get feedback from the community on the approach and any ideas for new features. Happy to answer any questions about the implementation submitted by /u/samla123li [link] [comments]

So today I was working with set intersections, and found myself needing to check if a given intersection was empty or not. I started with: if not set1 & set2: return False return True which I thought could be reduced to a single line, which is where I made my initial mistakes: ``` oops, not actually returning a boolean return set1 & set2 oops, neither of these are coerced to boolean return set1 & set2 == True return True == set1 & set2 stupid idea that works return not not set1 & set2 what I should have done to start with return bool(set1 & set2) but maybe the right way to do it is...? return len(set1 & set2) > 0 ``` Maybe I haven't discovered the ~zen~ of python yet, but I am finding myself sort of frustrated with truthiness, and missing what I would consider semantically clear interfaces to collections that are commonly found in other languages. For example, rust is_empty, java isEmpty(), c++ empty(), ruby empty?. Of course there are other languages like JS and Lua without explicit isEmpty semantics, so obviously there is a spectrum here, and while I prefer the explicit approach, it's clear that this was an intentional design choice for python and for a few other languages. Anyway, it got me thinking about the ergonomics of truthiness, and had me wondering if there are other pitfalls to watch out for, or better yet, some other way to understand the ergonomics of truthiness in python that might yield more insight into the language as a whole. edit: fixed a logic error above submitted by /u/jmole [link] [comments]

Hi everyone, I would like to share a small open-source project that brings uv-powered ephemeral environments to Jupyter. In short, whenever you start a notebook, an isolated venv is created with dependencies stored directly within the notebook itself (PEP 723). 🔗 GitHub: https://github.com/OKUA1/juvio (MIT License) What it does 💡 Inline Dependency Management Install packages right from the notebook: %juvio install numpy pandas Dependencies are saved directly in the notebook as metadata (PEP 723-style), like: # /// script # requires-python = "==3.10.17" # dependencies = [ # "numpy==2.2.5", # "pandas==2.2.3" # ] # /// ⚙️ Automatic Environment Setup When the notebook is opened, Juvio installs the dependencies automatically in an ephemeral virtual environment (using uv), ensuring that the notebook runs with the correct versions of the packages and Python. 📁 Git-Friendly Format Notebooks are converted on the fly to a script-style format using # %% markers, making diffs and version control painless: # %% %juvio install numpy # %% import numpy as np # %% arr = np.array([1, 2, 3]) print(arr) # %% Target audience Mostly data scientists frequently working with notebooks. Comparison There are several projects that provide similar features to juvio. juv also stores dependency metadata inside the notebook and uses uv for dependency management. marimo stores the notebooks as plain scripts and has the ability to include dependencies in PEP 723 format. However, to the best of my knowledge, juvio is the only project that creates an ephemeral environment on the kernel level. This allows you to have multiple notebooks within the same JupyterLab session, each with its own venv. submitted by /u/iryna_kondr [link] [comments]

What My Project Does: An AI-powered coder and debugger in one place Use LLM to drive debugger (debugpy) in VS Code Documentation: zentar.ai Github: github.com/Zentar-Ai/zentara-code/ VS Code Marketplace: marketplace.visualstudio.com/items/?itemName=ZentarAI.zentara-code Target Audience: Meant for production Comparison: First in kind comprehensive AI-powered debugger and code in one place For python tests: Drive pytests tests, catch assertion errors, walk the stack , inspect variables, stack tracing. submitted by /u/bn_from_zentara [link] [comments]

The datasets I'm working with would range from 100,000 rows to 2 million rows of data. With around 40 columns per row. I'm looking to write the fastest code possible and I assume a table valued parameter passed to sql server via pyodbc would be the fastest as its less network calls and trips to sql. I've looked for comparisons with using fast_executemany = True and cursor.executemany in pyodbc but cant seem to find any. Anyone ever tested or know if passing data via a TVP would be alot faster than using executemany? My assumption would be yes but thought I'd ask in case anyone has tested this themselves. submitted by /u/Particular-Battle513 [link] [comments]

🚦 Flowguard – A Python rate limiter for both synchronous and asynchronous code. 🔗 https://github.com/Tapanhaz/flowguard What it does: Flowguard lets you control how many operations are allowed within a time window. You can set optional burst limits and use it in both sync and async Python applications. Who it's for: Developers building APIs or services that need rate limiting with minimal overhead. Comparison with similar tools: Compared to aiolimiter (which is async-only and uses the leaky bucket algorithm), Flowguard supports both sync and async contexts, and allows bursting (e.g., sending all allowed requests at once). Planned: support for the leaky bucket algorithm. submitted by /u/DifficultZebra1553 [link] [comments]

Hi everyone! I made a small Python library to generate beautiful, customizable chessboard images from FEN strings. What is FEN string ? FEN (Forsyth–Edwards Notation) is a standard way to describe a chess position using a short text string. It captures piece placement, turn, castling rights, en passant targets, and move counts — everything needed to recreate the exact state of a game. 🔗 GitHub: chessboard-image pip install chessboard-image What My Project Does Convert FEN to high-quality chessboard images Support for white/black POV Optional rank/file coordinates Customizable themes (colors, fonts) Target Audience Developers building chess tools Content creators and educators Anyone needing clean board images from FEN It's lightweight, offline-friendly, and great for side projects or integrations Comparison python-chess supports FEN parsing and SVG rendering, but image customization is limited Most web tools aren’t Python-native or offline-friendly This fills a gap: a Python-native, customizable image generator for chessboards Feedback and contributions are welcome! 🙌 submitted by /u/Own_Piano9785 [link] [comments]

Ladies and gentleman! I've been trying to run a (very networking, computation and io heavy) script that is async in 90% of its functionality. so far i've been using uvloop for its claimed better performance. Now that python 3.13's free threading is supported by the majority of libraries (and the newest cpython release) the only library that is holding me back from using the free threaded python is uvloop, since it's still not updated (and hasn't been since October 2024). I'm considering falling back on asyncio's event loop for now, just because of this. Has anyone here ran some tests to see if uvloop is still faster than asyncio? if so, by what margin? submitted by /u/webshark_25 [link] [comments]

Weekly Thread: Beginner Questions 🐍 Welcome to our Beginner Questions thread! Whether you're new to Python or just looking to clarify some basics, this is the thread for you. How it Works: Ask Anything: Feel free to ask any Python-related question. There are no bad questions here! Community Support: Get answers and advice from the community. Resource Sharing: Discover tutorials, articles, and beginner-friendly resources. Guidelines: This thread is specifically for beginner questions. For more advanced queries, check out our Advanced Questions Thread. Recommended Resources: If you don't receive a response, consider exploring r/LearnPython or join the Python Discord Server for quicker assistance. Example Questions: What is the difference between a list and a tuple? How do I read a CSV file in Python? What are Python decorators and how do I use them? How do I install a Python package using pip? What is a virtual environment and why should I use one? Let's help each other learn Python! 🌟 submitted by /u/AutoModerator [link] [comments]

I'm about to switch jobs and have been required to use only python 3.9 for years in order to maintain consistency within my team. In my new role I'll responsible for leading the creation of our python based infrastructure. I never really know the best term for what I do, but let's say full-stack data analytics. So, the whole process from data collection, etl, through to analysis and reporting. I most often use pandas and duckdb in my pipelines. For folks who do stuff like that, what's your go to python version? Should I stick with 3.9? P.S. I know I can use different versions as needed in my virtual environments, but I'd rather have a standard and note the exception where needed. submitted by /u/donHormiga [link] [comments]

Hi, I've written a CLI for Streamlabs Desktop, you can use it with the Remote Control API. https://github.com/onyx-and-iris/slobs-cli With it you can switch scenes, start/stop stream|record + other things, check the README. submitted by /u/onyx_and_iris [link] [comments]

Is the repr for template strings intended not to work as "copy paste-able" code? I always thought this is the "desired" behavior of repr (if possible). I mean, I guess t-strings have a very finicky nature, but it still seems like something that could be done. Concretely, I can build a t-string and print a repr representation, >>> value = "this" >>> my_template = t"value is {value}" >>> print(repr(my_template) Template(strings=('value is ', ''), interpolations=(Interpolation('this', 'value', None, ''),)) but I can't reconstruct it from the repr representation: >>> from string.templatelib import Template, Interpolation >>> my_template = Template(strings=('value is ', ''), interpolations=(Interpolation('this', 'value', None, ''),)) Traceback (most recent call last): ... TypeError: Template.__new__ only accepts *args arguments It looks like it only needs a kwargs version of the constructor, or to output the repr as an interleaving input >>> my_template = Template('value is ', Interpolation('this', 'value', None, ''), '') # no error Or maybe just print as a t-string def _repr_interpolation(interpolation: Interpolation): match interpolation: case Interpolation(_, expr, None | "", None | ""): return f'{{{expr}}}' case Interpolation(_, expr, conv, None | ""): return f'{{{expr}!{conv}}}' case Interpolation(_, expr, None | "", fmt): return f'{{{expr}:{fmt}}}' case Interpolation(_, expr, conv, fmt): return f'{{{expr}!{conv}:{fmt}}}' def repr_template_as_t_string(template: Template) -> str: body = "".join( x if isinstance(x, str) else _repr_interpolation(x) for x in template ) return f't"{body}"' >>> repr_template_as_t_string(my_template) t"value is {value}" Here are some example of repr for other python types >>> print(repr(9)) 9 >>> print(repr(slice(1,2,'k'))) slice(1, 2, 'k') >>> print(repr('hello')) 'hello' >>> print(repr(lambda x: x)) # not really possible I guess <function <lambda> at 0x000001B717321BC0> >>> from dataclasses import dataclass >>> @dataclass class A: a: str >>> print(repr(A('hello'))) A(a='hello') submitted by /u/NoExpression1053 [link] [comments]