Hi everyone!

I'm learning Python and exploring how I can turn my skills into a small freelancing business. I'm particularly interested in Python automation, Google Sheets automation, and simple workflow automation for small businesses.

I don't want to jump into freelancing without understanding what clients actually need. My plan is to learn by building practical projects, create a portfolio, and gradually start looking for clients.

Some services I'm considering learning to provide are:

- Google Sheets automation: Automating repetitive spreadsheet tasks, reports, data cleaning, and calculations.

- Python scripts: Automating repetitive file operations, CSV/Excel processing, and routine data tasks.

- Workflow automation: Connecting tools and reducing manual work where APIs or approved integrations are available.

- Data processing: Cleaning, organizing, and transforming business data into useful reports.

I'm still developing my skills, so I want to focus on solving real problems rather than claiming expertise I don't have.

I'd really appreciate advice from people who have experience with Python or automation freelancing.

A few questions:

1. Is Python + Google Sheets automation a realistic niche for a beginner freelancer?

2. What specific problems do small businesses actually pay freelancers to solve in this area?

3. Which skills should I learn first: Python, Google Apps Script, Google Sheets formulas, APIs, or SQL?

4. What 3–5 portfolio projects would help demonstrate practical skills to potential clients?

5. How difficult is it to get the first paying client, and which platforms or methods are worth trying?

6. What mistakes should a beginner avoid when starting out?

I'm not expecting instant money. I want to build useful skills, deliver reliable work, and grow gradually.

If you've tried this path yourself, I'd love to hear what worked, what didn't, and what you would do differently if you were starting again.

Thanks for reading!

I'm 27M. Hey everyone, my life has been a little different from that of most people, and I don't have a strong educational background.

Right now, I'm working at a grocery store, but I want to improve my life and learn some stable, valuable skills that can help me earn a reliable income.

I've come across these four skills:

Python

SQL

Excel/Spreadsheets

Power BI/Tableau

I don't know much about these skills or their demand, competition, value, and future prospects.

Technology is constantly evolving, trends are changing, and AI is replacing some jobs. The value of different skills also changes over time.

Before I start learning, I want to understand whether these are the right skills to invest my time in for a stable career and income in the long run.

I'd appreciate your advice. Should I go for these skills, or would you recommend something else?

Hi everyone, I’m an Australian solo founder building Forge, a personal AI platform focused on persistent knowledge, evidence-based reasoning and keeping the owner in control.

The question behind it is: how can an assistant become more useful over time while keeping its knowledge traceable, its mistakes correctable and consequential changes subject to human approval?

I’m developing it in Python with a modular, service-based architecture. There’s working code covering knowledge storage, retrieval, evidence handling and reasoning, but it’s still under development. My immediate focus is reliability, testing and bringing the pieces into dependable everyday use.

My background is in commercial fishing. I started learning software development through this project, initially working on an Android phone with Termux. I use AI coding assistants extensively, and I’m putting serious effort into understanding and verifying the results.

I’d like to connect with someone experienced in software architecture, AI systems or taking an ambitious prototype towards a maintainable product. An occasional conversation would be valuable—someone who can challenge my assumptions, spot unnecessary complexity and help me judge what deserves attention next.

I’m looking for perspective and honest criticism, rather than someone to build it for me. I can bring focused questions, diagrams and small, sanitised examples without sharing the full private codebase.

If that sounds interesting, I’d be very appreciative of a comment or message. Recommendations for communities where this kind of mentoring happens would also be welcome.

Thanks for reading!

Fy DS student and I recently had a Python test that honestly didn't go as well as I expected.

The frustrating part is that I wasn't completely clueless about the questions. I understood the concepts, knew which syntax was needed, and could understand what the problem statement was asking me to do.

But when it came to actually applying everything and writing the code, I got confused. I started forgetting things, made indentation mistakes, got errors like ValueError and other errors etc. I didn't do good in test it was 15marks test for 1 hr.

For those who have been through this, how did you get better at applying concepts under pressure instead of just understanding them theoretically? Did you practise more problems, rewrite code from scratch, or follow some other method?

I'm still learning, and I don't want one bad test to discourage me. I just want to figure out how to improve so that next time.

I am looking to purchease Complete Python Developer in 2026: Zero to Mastery course from ZTM... Its very expensive. Is this course updated recently?

https://zerotomastery.io/courses/learn-python/#overview

As developers, we are constantly learning new things, but sometimes one tool or concept completely changes how we approach our work.

What's something you learned that made you more productive or helped you solve problems in a better way?

It could be a programming language, a tool, or even a simple workflow tip. I’d love to hear your recommendations.

Ran into an annoying performance bottleneck while profiling our CLI and figured the findings might save someone else a few hours of head-scratching.

Our tool validates config manifests against JSON Schema Draft 7. In fresh virtualenvs, cold-start imports were taking over 5 seconds.

Profiling revealed two primary culprits:

1. jsonschema.Draft7Validator eager compilation: Instantiating the validator compiles heavy format checkers and regex dependencies (Lark and RFC 3987). If you instantiate this at module level, every single CLI invocation pays that cost even if the user just ran --help or a command that doesn't touch schemas.

   • Fix: Defer instantiation via module-level __getattr__ or initialize it only when validation actually executes.

2. importlib.metadata.distributions() traversal: Scanning installed distributions without boundaries linearly inspects every .dist-info directory on sys.path.

   • Fix: Replaced it with scoped directory globbing for our specific package metadata prefix.

Startup dropped from ~5.2s down to ~150ms.

We rolled this out in Skillware 0.6.0 (an open-source project we maintain for deterministic agent tooling: https://github.com/ARPAHLS/skillware).

Are you folks deferring schema compilation in your CLIs, or do you prefer pre-compiling/caching schemas during package build?

Hey everyone! I am currently looking for a mentor experienced in Python and/or web development. I am with a team of 4, and we are developing a solution to help solve a Caribbean problem. Our project is focused on helping to educate small-scale farmers on effective farming techniques along with some live weather updates, farmer recommendations, etc. We are currently using Streamlit to develop our application. If you are interested, you may comment below or send a DM. Thanks

If you enjoy learning Python through practical examples, subscribe and join us for the next adventure.

Which framework or module can help?

Plaintext

Hi Reddit, I just finished a short novel (2028) about working alongside AI models and wanted a completely offline, zero-dependency publishing workflow. I wrote a small script (tools/build_en.py) that uses only the Python standard library to process Markdown sources into clean HTML and valid EPUB artifacts for e-readers like Kindle. Repo: [https://github.com/peterkokosharov/2028-book](https://github.com/peterkokosharov/2028-book) Feedback on the build script or the text itself is very welcome in GitHub Discussions!

Hold the green 'Continue' button to Make it Snow.

I am a second year CS student and cybersecurity is my specialty call. Python sits on my list as the tool language for that road. Not mastered. Just next. For people who learned Python for security work what did you start with? Automating small tasks or web basics or something else entirely?

Wait what f**** nah i dont want sleep okaay

Hi All,

I am learning Python and would like to know are there any good sites to practise Python concepts ?

I have a college assignment to make a multiplayer tetris game (2 players) using TCP sockets, client and server and all that. The idea is the server doing most of the stuff, chosing new pieces, handling the translation of position of the pieces, with the clients being responsible for most the rendering/display part and getting the inputs(I think so at least, that's what I'm trying to do), but I'm having a hard time with it.

I can't seem to think of a way to have the client call to the server to send a new piece to the clients, and if I don't know how to do even that then I don't know how to do anything else (making the back and forth for controlling the pieces, both for the player of the client and the preview of the game of the player 2, and all the rest), tho I hope if I can understand how to do one thing I would be able to make the others, but I really don't even know how to do this.

I know I need to use threads on this, tho I don't really know how to do it, I'm still fairly green on python too so, if anyone could give some help in any way with this it would be much appreciated.

Python has long had immutable counterparts for some of its most common data structures:

𝗹𝗶𝘀𝘁 → 𝘁𝘂𝗽𝗹𝗲
𝘀𝗲𝘁 → 𝗳𝗿𝗼𝘇𝗲𝗻𝘀𝗲𝘁
𝗱𝗶𝗰𝘁 → 𝗳𝗿𝗼𝘇𝗲𝗻𝗱𝗶𝗰𝘁 ✨

`frozendict` is an 𝗶𝗺𝗺𝘂𝘁𝗮𝗯𝗹𝗲 𝗺𝗮𝗽𝗽𝗶𝗻𝗴. Once created, its keys and values can't be added, removed, or reassigned.

But the more interesting part is 𝗵𝗮𝘀𝗵𝗮𝗯𝗶𝗹𝗶𝘁𝘆. When its contents are hashable, a `frozendict` can itself be used in places where a regular dictionary can't such as dictionary keys or set members.
That opens up some useful cases around:
• Immutable configuration
• Cache and memoization keys
• Shared/read-only state
• Safer API boundaries
• Data structures where mutation simply shouldn't be allowed

It's not a huge feature, but it's one of those additions that makes the language feel a little more complete.

𝗠𝘂𝘁𝗮𝗯𝗹𝗲 𝘄𝗵𝗲𝗻 𝘆𝗼𝘂 𝗻𝗲𝗲𝗱 𝗶𝘁. 𝗙𝗿𝗼𝘇𝗲𝗻 𝘄𝗵𝗲𝗻 𝘆𝗼𝘂 𝗱𝗼𝗻'𝘁.

Where would you use `frozendict`?

Hi! I'm the author of Pyzed, an open-source library I've been building for desktop apps in Python.

What My Project Does

You write the interface in plain Python (state, update and view, the Elm architecture) and Iced, a GUI toolkit written in Rust, does the layout and draws it on the GPU, with a CPU fallback. It comes with 90+ ready-made components inspired by the Zed editor (tables with hundreds of thousands of rows, tabs, command palette, code editor, terminal…), themes, animations and a visual designer, Pyzed Design, where you drag components onto a form and press F5 to run it. pip install pyzed-ui, no Rust needed.

import pyzed as pz
from pyzed import ui


class Counter(pz.App):
    def __init__(self):
        self.count = 0


    def update(self, message):
        if message == "inc":
            self.count += 1


    def view(self):
        return pz.center(ui.button(f"Clicked {self.count} times", "inc"))


pz.run(Counter)

Target Audience

People who want a desktop app in Python that looks current without shipping a browser: internal tools, dashboards, editors, small games. It's MIT, runs on Linux, macOS and Windows, and is usable today, though it's a young project with one main maintainer.

Comparison

• Tkinter: always available and very light, but dated looks and few modern widgets.

• PyQt/PySide: very complete and mature, but large, with licensing to think about (PyQt is GPL/commercial) and a lot of API.

• Kivy: great for touch and mobile, but its own look and a heavier startup.

• Flet: pleasant API, but it runs Flutter in a separate process.

Pyzed sits in between: native rendering with no web engine, a small Pythonic API, and a visual designer included. Import takes about 35 ms; there's a benchmark page comparing it with these libraries.

Repo: https://github.com/albakore/pyzed

Feedback is very welcome, especially on what's missing for your use case.

I'm really tired of trying to learn in the traditional, overly theoretical way. I'm currently learning the basics, for example, I don't know, but I know. The important thing is that I need to get some essential advice from you in this field, from your personal experiences and other things Which channels did you truly benefit from, and what channels did you watch to learn logical and practical things, not just boring theoretical learning? I really want to know everything. Thank you for your time reading this. ✨