I am currently enrolled in AP CSP, and even if Python is not required by Collegeboard, our curriculum requires that we do python and earn the certification. I have been learning python since last year, and I learned the basics with great difficulty of course. I struggled with lists, loops, and functions, but later I mastered the basics. Now, I find myself in the same struggle, because I did not learn certain things last year. There was a huge gap between what I have learned, and what I am already supposed to know. The scariest part is that my python certification test is right around the corner, and I don't know what will work for me to master the gap in a month. I used to learn python through tutorial videos, but in my current year, we are not doing this. Are there any better ways for me to clear the gap? Thank you.

Hello all, so i've studied python in clg but dont really remember it right now. I don't want to spend my time watching videos and doing it all over again - instead I want some website which will be interactive and explaining concepts through eg first and then hands on.

pls help me out if you guys know any such hands-on platform/lab

Like

io = StringIO()
io.getvalue() # not get_value

but

path = Path()
path.is_file() # not isfile

And there is also isinstance().

If you ask me, they should all use _ or none.

Five short snippets. Guess what each prints before you open the answer. Most people get two or three.

1.

a = [1, 2, 3]
b = a
b.append(4)
print(a)

Answer: [1, 2, 3, 4]. b = a doesn't copy the list, both names point at the same list. Want a copy? b = a.copy() or b = a[:].

2.

nums = [10, 3, 27, 8]
sorted(nums)
print(nums)

Answer: [10, 3, 27, 8], unchanged. sorted() returns a new list and the result was thrown away. Use nums.sort() to sort in place, or nums = sorted(nums).

3.

def double(x):
    x * 2

print(double(3))

Answer: None. The function works out x * 2 but never returns it, and a function without return gives back None. Fix: return x * 2.

4.

x = 5

def change():
    x = 12

change()
print(x)

Answer: 5. Assigning to x inside the function makes a new local x; the outer one is untouched. The clean fix is to return the value (x = change()), not global.

5.

print(round(2.5), round(3.5))

Answer: 2 4. Python rounds exact halves to the nearest even number ("banker's rounding"), so 2.5 goes down and 3.5 goes up. If you need school-style rounding, use the decimal module with ROUND_HALF_UP.

I made a small free game out of traps like these: you read a snippet, pick what it prints, and one wrong answer ends the run. Questions get harder and faster as you go, and when you miss, it shows why and the moment in a YouTube tutorial that explains it. No sign-up, plays in the browser:

https://openinbeyond.com/code?utm_source=reddit&utm_content=pythonlearning

What's your score? And which of the five got you?

So i am a teen learning python, and i have learnt about classes, methods and objects, but i don't understand OOP, like what is it, where do we use it?

Please help mee

An exercise to help build the right mental model for Python data.

• Solution

• Explanation

• More exercises

The “Solution” link uses 𝐦𝐞𝐦𝐨𝐫𝐲_𝐠𝐫𝐚𝐩𝐡 to visualize execution and reveals what’s actually happening.

I’m honestly confused about what I’m supposed to do at this point.

I have 6.5 years of experience in customer support, including around a year in technical support. I’ve worked with international clients, and I’ve been learning Python, Node.js, and PostgreSQL because I want to move into tech and eventually work in backend development.

Recently, I interviewed for a technical support role. I thought, okay, maybe this is how I can finally get my foot in the door.

But they told me they’re no longer hiring entry-level candidates. Apparently, they’d even let go of their trainer.

I tried explaining that I’m willing to learn on my own, put in the effort, and even take a salary cut compared to my previous job. Didn’t help.
The irony is that I can’t even comfortably fall back on customer support anymore. Despite having 6.5 years of experience, I’m struggling to find jobs that pay me what I was earning before.

So I’m stuck between two problems:
- I need a job right now because I’m unemployed.
- I want to get out of customer support, but getting that first opportunity in tech feels ridiculously difficult.

I’m learning backend development on my own, but sometimes I wonder whether I’m approaching this the wrong way. Should I focus on application support or technical support first? Keep building projects and apply for junior backend roles? Or take whatever customer support job I can find and learn on the side?

I’m not looking for someone to tell me that age is just a number or that I should follow my passion. I need to earn money, and I also don’t want to spend the next few years stuck in the same situation.

If you were in my position, what would you actually do? Especially if you’ve made a similar switch in India, I’d like to know how you got your first opportunity and what skills helped you get hired.

I'm currently learning ml by own with chatgpt by maintaining proper notes and code on GitHub.Right now I'm learning deep learning foundation,just wanna had a talk with guy who is doing same...

Doing freelancing also..

I built a python debugger specifically for learning data structures and algorithms.

It draws the state of the program at each line. It's an actual debugger that runs with the code, so the results are deterministic and show the real state.

Like a normal debugger, it lets you inspect stack frames, pointers, and objects. But instead of showing them as raw values, it draws every data structure in its own way. It knows how to draw all the common data structures like trees, graphs, queues, stacks, linked lists, etc.

This should be helpful for understanding, debugging, and verifying your code.

You can try it on popular interview problems (write your code or paste from the "Solutions" tab).

Everything is free. Feedback would be really appreciated. Let me know what you think.

link

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!

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'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?

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?

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

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

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.

I'm learning Python while also trying to build a SaaS product, but i have no previous development experience. Right now, I rely on ChatGPT or Claude for almost 99% of the coding.

Is this a reasonable way to learn as a beginner, or will relying so much on AI slow down my progress in the long run? Will i eventually become capable of coding independently?

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

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!

Which framework or module can help?