I've spent 4 years as a Python developer working on direct client projects inside a company — ERPNext, AI agents, FastAPI, Django, RAG systems. Real production work

I recently started freelance as a full time, to give a try. LinkedIn is my main focus right now, but I want one more platform to run alongside it.

I'm looking at Contra, Arc.dev, Gun.io, Upwork and skipping Toptal (not ready for that process yet).

For those who've used any of these — which one actually gets traction for a Python developer with my stack? And is there anything you wish you knew before starting?

Any honest experience appreciated.

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.

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How it Works:

1. Career Talk: Discuss using Python in your job, or the job market for Python roles.
2. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
3. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally.

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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.

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Example Topics:

1. Career Paths: What kinds of roles are out there for Python developers?
2. Certifications: Are Python certifications worth it?
3. Course Recommendations: Any good advanced Python courses to recommend?
4. Workplace Tools: What Python libraries are indispensable in your professional work?
5. Interview Tips: What types of Python questions are commonly asked in interviews?

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Let's help each other grow in our careers and education. Happy discussing! 🌟

Hey guys can you please suggest me python course i should by on sale 100 days python code by dr angela vs python course by ardit sulce? I just completed my first year i did c in my first and year i complete python basics from youtube

Hey, I am looking for some GitHub repo to contribute this summer, if you have any projects related to Python, Backend (FastAPI), AI agent, then I will be happy to contribute in the long term.

I am specifically looking for an active less crowded repos.

Should i buy the course in 2026 . I already know python basics till oops . I saw the course structure from outside it looked good. Is it still revelent? Please drop your reviews and guide me

I had seen python mentioned in some unix books and some of my old Linux books. I thought it was an ancient language spoken only by high priests now departed. All of my projects (commercial embedded real-time) were in ansi C. The really old stuff was k&r. I'm assuming it executes i-code. I have gigs in my historic projects that I have reuse frequently now archived.

But is Python for me learning now?

I don't have a formal degree in IT, but I've been diving deep into fields like RPA, AI agents, LLM fine-tuning, and Machine Learning. According to reports (like UiPath's), Python is pretty much the backbone for all of this.

If you were looking to land a Python Developer role starting from scratch today, would you prioritize certifications like the Python Institute’s PCAP, or would you take a different route?

I’d love to hear your personal stories and what worked for you!

I don't know where to start and how for backend role in python. I am stucked in watching youtube and then thinking is this right path i should follow or I have to move another things to learn first. Suggest some things

Suggestion:

We should call python 3.14 pithon.

For those who don't understand.

Pi (the math thing) is 3.14

Weekly Thread: Project Ideas 💡

Welcome to our weekly Project Ideas thread! Whether you're a newbie looking for a first project or an expert seeking a new challenge, this is the place for you.

How it Works:

1. Suggest a Project: Comment your project idea—be it beginner-friendly or advanced.
2. Build & Share: If you complete a project, reply to the original comment, share your experience, and attach your source code.
3. Explore: Looking for ideas? Check out Al Sweigart's "The Big Book of Small Python Projects" for inspiration.

Guidelines:

• Clearly state the difficulty level.
• Provide a brief description and, if possible, outline the tech stack.
• Feel free to link to tutorials or resources that might help.

Example Submissions:

Project Idea: Chatbot

Difficulty: Intermediate

Tech Stack: Python, NLP, Flask/FastAPI/Litestar

Description: Create a chatbot that can answer FAQs for a website.

Resources: Building a Chatbot with Python

Project Idea: Weather Dashboard

Difficulty: Beginner

Tech Stack: HTML, CSS, JavaScript, API

Description: Build a dashboard that displays real-time weather information using a weather API.

Resources: Weather API Tutorial

Project Idea: File Organizer

Difficulty: Beginner

Tech Stack: Python, File I/O

Description: Create a script that organizes files in a directory into sub-folders based on file type.

Resources: Automate the Boring Stuff: Organizing Files

Let's help each other grow. Happy coding! 🌟

I’m trying to use the clump_find function in yt on my Parthenon .rhdf file, but it crashes immediately when it tries to generate the first contours. Has anyone had this problem? If so, how did you fix it?

To get around it, I regridded the data and it works, but I lose resolution.

In Python, the actual app construction usually feels pretty straightforward. The hard part starts when you try to turn it into something real people can actually use.

Things like packaging, updates, installers, compatibility issues, access control, managing different systems etc. take a lot longer than I thought they would.

At first, I thought the hard part was finishing the code. But now it feels like everything afterwards is a whole new ball game.

Curious if anyone else who builds Python apps has felt the same.

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! 🌟

Hi guys hope everyone’s having a wonderful weekend.

Just wanted to ask the experts what’s the best and absolutely free website to train for Coding assessment interview on Python

I have an interview coming up!! ;)

Hej,

I've been working on a language called hica and Python has been one of its inspirations, especially working with lists. I have created a Hica vs. Python comparison at https://cladam.github.io/hica/docs/hica-vs-python and the verdict is ofc Python 🙂

From my conclusion:

>Python is the safe, proven choice with the largest ecosystem and lowest barrier to entry.

>hica emphasises foundations like immutability, type safety, pattern matching, and explicit error handling. Students who learn hica carry these patterns into Python, Rust, TypeScript, or whatever they use next.

>Why not both? Start with hica to build the foundations, then move to Python with a head start on the concepts that matter most.

What does this community think? My Python is a bit rusty, any feedback is welcome.

Disclaimer: I am not sure this post is appropriate for r/LearnPython since it's not a question of "how to do something in Python", rather I am looking for a lower-level discussion for why my Python application performs poorly on a significantly more powerful server. Hence I'm posting it here.

The problem:

I have a relatively complex data pipeline that is written in Polars. On my local machine with 12 cores, the pipeline finishes in about 1200ms. On my 128-core EC2, it takes 13000ms to complete. I have tried setting the POLARS_MAX_THREADS parameter to 12 on the EC2, and it's still slower.

I am using a TMPFS partition on both machines to read the data into the pipeline directly from RAM. Both my machine and the EC2 have DDR5 RAM so I think they should be comparable.

Anyone have any ideas why the pipeline would run much slower on the EC2?

I needed to send ~80 personalized emails to a list of GitHub users a few weeks ago. Different name in each one, different repo reference, written like a person wrote them. The kind of thing you do when you're cold-reaching for a side project.

Every guide I found told me to sign up for SendGrid, Postmark or Resend. Verify a domain, set up DKIM, get on a free tier, hope you don't trip a spam classifier. Half a day of setup for something I needed to do once.

Then I remembered Gmail does this natively. Google has been running an SMTP server at smtp.gmail.com for twenty years and any language with a sockets library can talk to it. The only thing standing between you and sending email from your own Gmail is one settings page most people never visit.
Here's the whole thing.

What you need

A Gmail account with 2-Step Verification turned on. If you don't have 2FA on, go to myaccount.google.com/security and switch it on first, otherwise the next step doesn't exist.

Then go to myaccount.google.com/apppasswords and generate a new app password. Google shows you the 16-character string once, looks like abcd efgh ijkl mnop. Copy it immediately. The spaces are optional, Gmail accepts it either way. Treat this like a password — don't commit it, don't paste it in chat, don't put it in a Notion doc your team can read. Google's scanners catch app passwords leaked in public repos and auto-revoke them, but the lag is unspecified and you really don't want to find out the hard way.

That's it for setup. Now you can send email.

The minimal version

Ten lines of Python. No libraries beyond the standard library.

python
import smtplib
from email.message import EmailMessage

msg = EmailMessage()
msg["From"] = "you@gmail.com"
msg["To"] = "recipient@example.com"
msg["Subject"] = "hello"
msg.set_content("Body goes here.")

with smtplib.SMTP("smtp.gmail.com", 587) as smtp:
smtp.starttls()
smtp.login("you@gmail.com", "abcd efgh ijkl mnop")
smtp.send_message(msg)
Run it. An email leaves your Gmail and shows up in the recipient's inbox a few seconds later, looking exactly like one you typed by hand. That's the whole protocol. Everything else is wrapping that in a workflow.

If port 587 is blocked on your network (corporate Wi-Fi, some hotels), switch to port 465 with smtplib.SMTP_SSL instead of STARTTLS. Same protocol, different transport, one line change.

The pattern for sending to a list

For real outreach you need three files: a .env for the Gmail address and app password, a recipients.csv with name and email columns, and a template.txt where the first line is the subject and the body uses {name} placeholders. The script reads all three, renders an email per recipient, has a dry-run flag that prints everything without sending, asks for a y confirmation if it's a live send, and then sends one at a time with a 4-second delay between each.

The dry-run flag matters more than it sounds. The number one mistake is a typo in your template — {nmae} instead of {name} — and Python's string formatter will quietly send the literal {nmae} to all 80 recipients. A dry-run that prints every rendered email to your terminal catches this in five seconds and saves you the apology email. Always dry-run first.

The whole script is about 120 lines of stdlib Python. I keep the working version saved as an npad here: https://npad.run/p/how-to-send-emails-using-gmail-programmatically-sgkbrkxaxs. If you have Claude Code or Cursor, paste that URL and tell your agent to set this up. It'll write the script, the env, the CSV format, and the template. One shot, no copy-pasting from this article.

Things to know before you live-send

A few things I learned the slightly painful way that aren't obvious from the docs.

Send one email per recipient, not one BCC'd to everyone. BCC blasts look like spam to filters, and some email clients reveal the BCC list anyway, which is how you accidentally show 50 strangers each other's addresses. Sending one at a time means each person sees only their own address and it looks like you actually wrote to them.

Put a real delay between sends. 4–5 seconds is the sweet spot. Faster and Gmail starts returning 421 4.7.0 errors that mean "you look like a bot, slow down." Don't try to be clever about parallelism — Gmail's free tier wants quiet, polite traffic, not a burst of fifty messages in three seconds.

Add a confirmation prompt before sending. "About to send to 80 recipients. Continue? [y/N]" is the cheapest insurance you'll ever write. The day you accidentally point the script at the wrong CSV, that prompt is what saves you.

Limits

Free Gmail will let you send around 500 emails per day before it starts pushing back. Workspace bumps that to 2,000. If you need more than that, you're at the volume where SendGrid or Postmark actually starts to make sense — they exist because at scale you do need bounce handling, deliverability monitoring, and a warmed-up sender reputation. But for under 500 emails a day of personalized outreach, Gmail is genuinely fine. Better than fine actually — it lands in inboxes more reliably than a cold ESP IP because Gmail has spent twenty years building sender trust on its own infrastructure.

btw if you really want to push past the daily cap, you can rotate keys across multiple Gmail accounts. hehe.