A programmer’s growth isn’t just about writing code — it’s also about discovering and using the right tools.
Today, I’ll share 8 tools that dramatically improved my productivity — so while my teammates are still debugging late at night, I’m already home watching Netflix.
🧱 ServBay: The Foundation of My Local Development
Whatever you build, a stable, isolated, and manageable local environment is essential.
That’s where ServBay comes in — it’s the cornerstone of my local dev setup.
- Installing and Running Multiple Versions of Python: I can install and run multiple Python versions on one machine — Python 2.7 for legacy projects and Python 3.11 for modern ones — all isolated and switchable with a click. If you’re a full-stack developer, you can even install other languages like PHP or Node.js for testing and development just as easily.
- All-in-one Services: ServBay integrates databases (MySQL, MariaDB, PostgreSQL) and caching services (Redis) in one place. No more manually configuring each one — it’s all neatly managed in a single dashboard.
- Simple GUI Switching: Switching between Python, Rust, or other dev languages takes just a few clicks. Managing services visually saves tons of setup time.
- One-Click Local AI Setup: Want to run DeepSeek, Qwen 3, or Llama 3 locally? ServBay can install and run them with a single click — no messy environment configs.
In short: ServBay is my local dev hub — saving me from countless hours of configuration headaches.
🧪 Hypothesis: Never Guess Test Data Again
When writing tests, most people manually create test cases like:
assert add(2, 3) == 5
assert add(-1, -5) == -6
But it’s impossible to think of every edge case.
Hypothesis flips that process around. You define the rules, and it automatically generates hundreds of clever inputs — all trying to break your function.
Example:
You define a function called absolute_value(x), and then use Hypothesis to test it with all possible integers. The library ensures that every test result follows your rule — for instance, that the output is always greater than or equal to zero.
This way, you no longer have to manually write cases like test_absolute_value(5) or test_absolute_value(-10). Hypothesis handles all that automatically, and if it finds a counterexample, it reports it instantly.
💬 One-line summary: Hypothesis finds bugs your hand-written tests never will.
🐵 MonkeyType: Add Type Hints to Legacy Code Automatically
Working with old projects without type hints can be painful. Adding int, str, etc., manually is boring and error-prone.
MonkeyType, an open-source tool from Facebook, observes your code while it runs and automatically suggests type annotations.
My typical workflow:
- Run your test script with
monkeytype run my_script.py. - MonkeyType records every function call and return type during execution.
- After tests finish, apply the collected types back to your source with
monkeytype apply my_project.my_module.
💬 One-line summary: MonkeyType adds 80% of your missing type hints automatically — saving you time and mental energy.
🦆 DuckDuckGo Search: Lightweight Search Without API Keys
Sometimes, I just need to perform a quick programmatic web search.
Usually, that requires registering for Google or Bing API keys — annoying, right?
DuckDuckGo Search is refreshingly simple: no API key, just plug and play.
Example idea: You can search for “Python web scraping libraries” and directly access the title and link results, making it great for small tools that aggregate or fetch data online.
💬 One-line summary: Perfect for quick, API-free search scripts and data lookups.
🌍 Requests-HTML: The All-in-One Web Parser
Most developers use Requests to fetch HTML and BeautifulSoup to parse it.
But Requests-HTML combines both steps in one powerful library — by the same author as Requests.
Example: You fetch a webpage like https://python.org/, then directly query elements using CSS selectors such as #intro or get all links from the page object.
The syntax is much cleaner and the process feels smoother.
💬 One-line summary: For small-scale scraping, Requests-HTML beats the Requests + BeautifulSoup combo hands down.
🐘 PGQueuer: Task Queue Using Only PostgreSQL
For background tasks like sending emails or processing videos, people often use Celery + Redis.
But what if your project only uses PostgreSQL? Why introduce Redis just for queuing?
PGQueuer lets you create a lightweight task queue using your existing PostgreSQL database. It’s reliable and easy to implement.
Example: You can enqueue email-sending jobs into the database, and have a small worker script that continuously polls, processes, and marks tasks as done — all without any extra dependencies.
💬 One-line summary: A simple and solid task queue when PostgreSQL is all you need.
🧙 Snoop: The Magic Debugger That Beats print()
We’ve all used print() to debug — it works, but it’s messy.
Snoop is the next level of that idea.
Add a simple decorator like @snoop to your function, and it prints each step’s execution details, variable changes, and logic flow in real-time.
Example: Add @snoop on top of a factorial function, and you’ll instantly see how each recursive call behaves — no manual prints, no clutter.
💬 One-line summary: When you need to understand a function’s internal logic quickly, Snoop is cleaner than print and simpler than a debugger.
🪟 PyWebView: Build Desktop Apps with Python and Web Tech
Sometimes, I want to turn a web app into a desktop app — but Electron feels too heavy.
PyWebView is a lightweight solution. It creates a native window that displays your web app, whether it’s local HTML/CSS/JS or an online site.
Example: You can load a website like https://python.org into a window titled “My Desktop App” using just a few lines of Python. It even supports communication between Python and JavaScript.
💬 One-line summary: The fastest way to wrap your web project into a native desktop experience.
💭 Final Thoughts
Tools don’t write code — but they shape how you code.
These are the tools that genuinely made my daily workflow smoother and helped me avoid late nights fixing things manually.
The right tools won’t make you a great developer —
but a great developer always knows how to choose the right tools.
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