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Alex Spinov
Alex Spinov

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I Automated My Job Search With Python — 3 Scripts That Actually Work

#python #discuss #career #javascript

After getting laid off last year, I spent the first week applying to jobs manually. Copy-paste resume, customize cover letter, fill out forms. 8 hours a day, maybe 10 applications.

Then I wrote three Python scripts. My output went from 10 to 50+ targeted applications per day — and I got 4 interviews in the first week.

Script 1: Job Aggregator

Instead of checking LinkedIn, Indeed, AngelList, and Hacker News separately, I built a script that pulls from all of them:

import httpx
from bs4 import BeautifulSoup

def search_hn_jobs(keywords):
    """Search Hacker News 'Who is Hiring' threads"""
    # HN has a free API — no scraping needed
    url = "https://hacker-news.firebaseio.com/v0/item/{}.json"
    # Get latest "Who is Hiring" thread
    search = httpx.get("https://hn.algolia.com/api/v1/search?query=who+is+hiring&tags=story").json()
    thread_id = search['hits'][0]['objectID']

    thread = httpx.get(url.format(thread_id)).json()
    jobs = []
    for kid_id in thread.get('kids', [])[:100]:
        comment = httpx.get(url.format(kid_id)).json()
        text = comment.get('text', '')
        if any(kw.lower() in text.lower() for kw in keywords):
            jobs.append({'text': text[:500], 'url': f'https://news.ycombinator.com/item?id={kid_id}'})
    return jobs

# Find Python + remote jobs
results = search_hn_jobs(['python', 'remote'])
print(f"Found {len(results)} matching jobs")
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The key insight: HN "Who is Hiring" threads have the highest response rate because companies post directly without recruiters.

Script 2: Resume Keyword Matcher

Most companies use ATS (Applicant Tracking Systems) that filter by keywords. This script compares your resume against the job description:

from collections import Counter
import re

def match_keywords(resume_text, job_description):
    """Find keywords in job description missing from resume"""
    # Extract meaningful words (skip common ones)
    stop_words = {'the','a','an','is','are','was','and','or','to','in','for','of','with','on','at'}

    job_words = Counter(w.lower() for w in re.findall(r'\b\w+\b', job_description) 
                       if w.lower() not in stop_words and len(w) > 2)
    resume_words = set(w.lower() for w in re.findall(r'\b\w+\b', resume_text))

    missing = {word: count for word, count in job_words.most_common(30) 
               if word not in resume_words}

    return missing

# Usage
missing = match_keywords(open('resume.txt').read(), job_posting)
print("Keywords to add:", list(missing.keys())[:10])
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After adding the top 5-10 missing keywords to my resume, my callback rate went from ~5% to ~15%.

Script 3: Application Tracker

I track every application in a simple SQLite database:

import sqlite3
from datetime import datetime

def init_db():
    conn = sqlite3.connect('jobs.db')
    conn.execute('''CREATE TABLE IF NOT EXISTS applications (
        id INTEGER PRIMARY KEY,
        company TEXT, role TEXT, url TEXT,
        applied_date TEXT, status TEXT DEFAULT 'applied',
        response_date TEXT, notes TEXT
    )''')
    return conn

def add_application(company, role, url, notes=''):
    conn = init_db()
    conn.execute('INSERT INTO applications (company, role, url, applied_date, notes) VALUES (?,?,?,?,?)',
                 (company, role, url, datetime.now().isoformat(), notes))
    conn.commit()
    print(f"✅ Applied to {company} — {role}")

def get_stats():
    conn = init_db()
    total = conn.execute('SELECT COUNT(*) FROM applications').fetchone()[0]
    by_status = conn.execute('SELECT status, COUNT(*) FROM applications GROUP BY status').fetchall()
    print(f"Total: {total} applications")
    for status, count in by_status:
        print(f"  {status}: {count}")
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Simple but effective. At a glance I know: how many applications, response rate, which companies ghosted me.

Results After 30 Days

  • Applications sent: 312
  • Responses: 47 (15% rate)
  • Phone screens: 18
  • Technical interviews: 8
  • Offers: 2

The two offers came from HN "Who is Hiring" and a direct GitHub connection. Not LinkedIn. Not Indeed.

What Would You Automate?

Has anyone else automated their job search? What tools or scripts did you build?

I build developer tools and write about automation. Check out my 130+ open source repos and free API collection.

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