---
type: email
from: Tech With Tim <tim@techwithtim.net>
subject: The fastest way to become a python dev in 2025
received: 2026-03-05 10:12:25
date_header: Wed, 20 Aug 2025 12:09:42 +0000 (UTC)
priority: normal
status: awaiting_approval
uid: 28176
---

## Email Content

**From:** Tech With Tim <tim@techwithtim.net>
**Subject:** The fastest way to become a python dev in 2025
**Date:** Wed, 20 Aug 2025 12:09:42 +0000 (UTC)

### Body (preview)

Hey there,



Writing python code is like running it locally... it works on

your machine, but until you deploy, it doesn’t count.



I usually break down a CI/CD pipeline into 4 main stages: build,

verify, release, and deploy.



And the funny thing is...



Your developer career runs on the same pipeline...



You have to pass through every stage to land a job.



That's what I call the Deployment Pipeline Method: 4 stages to

turn code into a career...



token; ConvertKit strips classes, so we inline styles instead

-->



Stage 1: Build (Core Foundations)

---------------------------------



* Core syntax: Variables, loops, conditionals, lists, dicts,

sets, functions. Ship scripts end to end.

* OOP: Classes, inheritance, encapsulation. Build a BankAccount

or text adventure.

* Async and concurrency:

asyncio

and threads. Fetch multiple URLs without blocking.



* Advanced features: Decorators, generators, context managers,

comprehensions. Write concise, pythonic code.

* Modules and packages: Clean package layout and imports for

reuse.

* Stdlib and libs:

os,

pathlib,

json,

requests

for files, paths, and APIs.



In pipelines, a broken build stops everything. In your career,

weak foundations do the same.



Stage 2: Verify (Tools & Quality)

---------------------------------



* Git and GitHub: Branch, rebase, PR, review. Keep

main green.



* CLI: Navigate, chain commands, use pipes and

grep. Add a simple

Makefile

or script to speed routine tasks.



* HTTP and REST:

requests, headers, auth, pagination, JSON parsing.



* Virtual environments:

venv

or Conda. Pin dependencies in

requirements.txt

or

pyproject.toml.



* Debugging and testing: Breakpoints, read stack traces, write

pytest unit tests.



Tests are the gatekeeper in a pipeline and tools are the

gatekeeper in your career.



Stage 3: Release (Specialization & Proof)

-----------------------------------------



* Web: Django, Flask, or FastAPI with auth and Postgres. Expose

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