I've seen it too many times. Someone wants to build a simple price tracker or a folder organizer, and the first thing they do is install 47 different libraries. Pandas, numpy, matplotlib, scipy, tensorflow "just in case" — and half of them never even get imported.
Stop. You're making your life harder for no reason. Every dependency is a potential security vulnerability, a source of version conflicts, and a resource hog on your VPS. For 90% of automation tasks, you need exactly 5 external libraries (and a few built-ins). Everything else is optional until you hit a technical wall that these can't scale over.
Here are the only 5 I install on every new server before I even start coding.
1. requests (API Calls)
In 2025, there are faster libraries (httpx) and more modern ones (aiohttp). But for automation, requests is still the king. It is simple, reliable, and every Python developer on the planet knows how to read it. When you're debugging a bot at 2 AM, the last thing you want is to wrestle with complex async/await boilerplate if a simple synchronous call works fine.
import requests
# Fetching your crypto balance in 3 lines
response = requests.get('https://api.binance.com/api/v3/ticker/price?symbol=BTCUSDT')
price = response.json()['price']
print(f"Bitcoin is currently ${price}")When to use: Any time you need to talk to a website, an API, or download a file. If you aren't making 1,000+ concurrent requests per second, requests is all you need. It handles headers, cookies, and JSON parsing with zero friction.
2. schedule (Timing)
Crontab is great, but it's annoying to manage inside your terminal, and it's hard to version control. The schedule library allows you to define your bot's timing logic directly in your Python code using human-readable syntax that even a non-coder could understand.
import schedule
import time
def job():
print("Cleaning up downloads folder...")
# Elegant, readable, version-controlled
schedule.every().day.at("10:30").do(job)
schedule.every(10).minutes.do(job)
while True:
schedule.run_pending()
time.sleep(1)Pro Tip: By keeping your schedule in the code, your bot is completely portable. Move it from your laptop to a Linux VPS, run python main.py, and your timing logic is already active without you having to re-configure the server's crontab system.
3. python-dotenv (Secrets Management)
Never, ever hardcode API keys. I've accidentally pushed a Binance secret key to a public GitHub repo before, and within 30 seconds, it was scraped and used by an automated script. It is an expensive and embarrassing mistake. python-dotenv encourages the best practice of using environment variables, ensuring your sensitive data never touches your version control history.
from dotenv import load_dotenv
import os
load_dotenv() # Loads the .env file
API_KEY = os.getenv('BINANCE_KEY')
SECRET = os.getenv('BINANCE_SECRET')4. logging (The Black Box Recorder)
Technically, this is in the Standard Library, but most developers ignore it in favor of print(). Don't. If your bot crashes at 2 AM while you're asleep, a print statement is gone forever. You need a log file that survives crashes, terminal closures, and system reboots. Logging allows you to track the exact state of your bot before it failed.
import logging
logging.basicConfig(
filename='bot_errors.log',
level=logging.ERROR,
format='%(asctime)s - %(levelname)s - %(message)s'
)
try:
main_loop()
except Exception as e:
logging.error(f"Bot crashed: {e}")5. sqlite3 (Zero-Config Persistence)
You don't need a heavy database like PostgreSQL or MongoDB for a personal bot. If you're storing trade history, user settings, or scraped prices, sqlite3 is perfect. It's built into Python, requires zero installation, and stores everything in a single .db file that you can easily back up or move. It is the most reliable way to give your bot a long-term memory without the overhead of a dedicated database server.
The Hidden Power of the Standard Library
Before you Reach for pip install, remember that Python comes "batteries included." I often see people installing libraries for things that are already built-in. json for parsing, datetime for time zones, and pathlib for file management are world-class modules. If you master these 3 core modules plus the 5 libraries mentioned above, you are technically capable of building almost any professional-grade automation tool without ever bloating your dependency list.
Frequently Asked Questions
Why not use the built-in urllib instead of requests?
Technically, urllib is fine, but it's incredibly verbose and requires handling low-level details. requests turns a 10-line block of boilerplate into a 1-line command. The improved readability and time saved on debugging is worth the small overhead of an external dependency.
What about Selenium for browser tasks?
I avoid Selenium in 2025. It is slow, heavy, and notoriously difficult to set up on a headless Linux VPS. If you must automate a browser, use Playwright. It is faster, has a better API, and handles modern web elements (like shadow DOMs) much more reliably than Selenium ever could.
Is sqlite3 safe for concurrent access?
SQLite is great for one writer and many readers. If you have five different bots all trying to write to the same database at the exact same millisecond, you might run into "database is locked" errors. If you reach that level of scale, switch to PostgreSQL. But for a single bot? SQLite is flawless.
"Complexity is the enemy of reliability. A successful automation bot is one that you can forget about because it never breaks."
The Bottom Line
Stick to these 5 pillars, master the built-in modules, and your bots will be easier to maintain, faster to deploy, and significantly harder to break. Every line of code you don't write is a line you never have to debug. Stay minimalist, stay efficient, and happy coding!
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