What Recent AI Layoffs Mean for Python Freshers

from collections import Counter
import re

# Paste the text of 20 Python job posts into posts.txt
text = open("posts.txt", encoding="utf-8").read().lower()

skills = ["fastapi", "django", "flask", "pandas", "sql",
          "pytest", "docker", "aws", "llm", "git"]
counts = Counter({s: len(re.findall(r"\b" + s + r"\b", text)) for s in skills})

for skill, n in counts.most_common():
    print(f"{skill:<8} {n}")

sql      18
git      15
pandas   12
django    9
pytest    8
docker    7
fastapi   6
aws       5
llm       4
flask     3

(Example output format only — your numbers will
 depend on the posts you collect.)

def normalise_phone(raw: str) -> str:
    """Return a 10-digit Indian mobile number or raise ValueError."""
    digits = "".join(ch for ch in raw if ch.isdigit())
    if digits.startswith("91") and len(digits) == 12:
        digits = digits[2:]
    if digits.startswith("0") and len(digits) == 11:
        digits = digits[1:]
    if len(digits) != 10 or digits[0] not in "6789":
        raise ValueError(f"invalid mobile number: {raw!r}")
    return digits

import pytest
from phone import normalise_phone

@pytest.mark.parametrize("raw, expected", [
    ("+91 98765 43210", "9876543210"),
    ("098765-43210", "9876543210"),
    ("9876543210", "9876543210"),
])
def test_valid_numbers(raw, expected):
    assert normalise_phone(raw) == expected

@pytest.mark.parametrize("raw", ["12345", "5876543210", "abc"])
def test_invalid_numbers(raw):
    with pytest.raises(ValueError):
        normalise_phone(raw)

Before committing any AI-assisted code:
[ ] I can explain every line in plain words
[ ] I ran it with normal, empty and wrong inputs
[ ] I added at least one test for an edge case
[ ] I checked for hard-coded secrets or paths
[ ] I removed code I do not understand
[ ] I noted in the README where I used a tool

Date:
Task:
Prompt I used:
What the tool suggested:
What was wrong or missing:
What I changed and why:
What I learned:

Week 1 — Foundations check
  Learn : functions, classes, exceptions, virtualenv
  Build : 10 small exercises with tests (pytest)
  Show  : push to GitHub with a clear README

Week 2 — Data with Python
  Learn : pandas basics, reading CSV, SQLite queries
  Build : clean one messy public dataset
  Show  : short LinkedIn post on one insight

Week 3 — APIs
  Learn : HTTP methods, status codes, JSON
  Build : FastAPI service with 3 endpoints
  Show  : add request examples to README

Week 4 — Testing and debugging
  Learn : pytest fixtures, pdb, logging
  Build : tests for the API, fix 2 real bugs
  Show  : write-up of one bug and its fix

Week 5 — Project 2
  Learn : Docker basics, environment variables
  Build : data pipeline that loads, cleans, stores
  Show  : architecture diagram in README

Week 6 — Job readiness
  Learn : common Python interview questions
  Build : polish both projects, add CI
  Show  : apply to 5 roles that match your stack