DEV Community: qing

How to Land Your First $10k Freelance Contract

qing — Fri, 31 Jul 2026 16:00:58 +0000

How to Land Your First $10k Freelance Contract

tags: freelance, upwork, career, money

Imagine having the freedom to choose your own projects, work at your own pace, and get paid for doing what you love. This is the life of a freelance developer, and it's more accessible than you think. With platforms like Upwork, you can connect with clients from all over the world and start building your freelance career. But getting your first client can be a daunting task, especially if you're new to freelancing. In this post, we'll walk you through a step-by-step guide on how to get your first freelance client on Upwork.

Setting Up Your Profile

Your profile is the first thing potential clients will see, so it's essential to make a good impression. Your profile should showcase your skills, experience, and personality. Here are a few tips to help you create a compelling profile:

Choosing Your Profile Picture

Your profile picture should be professional and friendly. Avoid using low-quality images or pictures that don't represent you well. You can use a photo editing tool like Photoshop to enhance your picture and make it more engaging.

Writing Your Headline and Description

Your headline and description should clearly state your skills and services. Use keywords that are relevant to your niche, and make sure your description is concise and easy to read. For example, if you're a Python developer, your headline could be "Expert Python Developer | Building Scalable and Efficient Solutions."

Setting Up Your Portfolio

Your portfolio is a showcase of your best work. It should demonstrate your skills and experience, and give potential clients an idea of what you can do. You can include links to your GitHub repository, or upload files and images that demonstrate your work.

Finding and Applying for Jobs

Once your profile is set up, it's time to start applying for jobs. Upwork has a vast marketplace of clients looking for freelancers, so you're sure to find something that fits your skills and interests. Here are a few tips to help you find and apply for jobs:

Using Search Filters

Upwork's search filters can help you narrow down your job search and find the perfect fit. You can filter by keywords, location, job type, and more. For example, if you're looking for a Python development job, you can use the keyword "Python" and filter by "Development" to find relevant jobs.

Reading Job Descriptions Carefully

When applying for a job, make sure you read the job description carefully. Look for keywords and requirements that match your skills and experience. If you're unsure about anything, don't hesitate to ask the client for clarification.

Writing a Compelling Proposal

Your proposal should showcase your skills and experience, and demonstrate why you're the best fit for the job. Keep your proposal concise and easy to read, and make sure you include a clear call to action. For example, you could say "I'd love to discuss this project further and explain in greater detail why I'm the perfect fit for this job. Please feel free to contact me to arrange a call."

Building a Personal Project to Demonstrate Your Skills

If you're new to freelancing, you might not have a lot of experience to showcase. But that doesn't mean you can't demonstrate your skills. Building a personal project can help you showcase your abilities and attract potential clients. For example, you could build a simple web scraper using Python and the BeautifulSoup library. Here's an example of how you could do this:

import requests
from bs4 import BeautifulSoup

# Send a GET request to the website
url = "https://www.example.com"
response = requests.get(url)

# If the GET request is successful, the status code will be 200
if response.status_code == 200:
    # Get the content of the response
    page_content = response.content

    # Create a BeautifulSoup object and specify the parser
    soup = BeautifulSoup(page_content, 'html.parser')

    # Find all the links on the page
    links = soup.find_all('a')

    # Print out the links
    for link in links:
        print(link.get('href'))

This code sends a GET request to a website, parses the HTML content, and prints out all the links on the page. You could use this as a starting point to build a more complex project, such as a web crawler or a data scraper.

Networking and Marketing Yourself

Networking and marketing yourself are crucial to finding freelance work. Here are a few tips to help you get started:

Building a Professional Network

Your professional network can help you find job opportunities and get recommendations. Attend industry events, join online communities, and connect with other freelancers and potential clients.

Creating a Personal Website or Blog

A personal website or blog can help you showcase your skills and services, and attract potential clients. You can use a platform like WordPress or Ghost to create a website, and write blog posts about topics related to your niche.

Using Social Media

Social media can help you promote your services and attract potential clients. Use platforms like Twitter, LinkedIn, and Facebook to share your work, engage with your audience, and build your personal brand.

Delivering High-Quality Work and Getting Repeat Business

Once you've landed your first client, it's essential to deliver high-quality work and get repeat business. Here are a few tips to help you do this:

Communicating with Your Client

Communication is key to delivering high-quality work. Make sure you understand your client's requirements, and keep them updated on your progress.

Meeting Deadlines and Delivering Quality Work

Meeting deadlines and delivering quality work is essential to getting repeat business. Make sure you manage your time effectively, and deliver work that meets your client's expectations.

Asking for Feedback and Improving Your Services

Asking for feedback and improving your services can help you deliver better work and get repeat business. Ask your client for feedback, and use it to improve your services and attract new clients.

Getting your first freelance client on Upwork takes time and effort, but it's worth it. By setting up a compelling profile, finding and applying for jobs, building a personal project, networking and marketing yourself, and delivering high-quality work, you can attract potential clients and build a successful freelance career. So why not get started today? Create a profile, start applying for jobs, and see where your freelance journey takes you. Remember, the key to success is to be proactive, persistent, and always willing to learn and improve. Good luck!

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

Python Collections Module: Beyond Lists and Dicts

qing — Fri, 31 Jul 2026 16:00:54 +0000

Python Collections Module: Beyond Lists and Dicts

tags: python, fastapi, security, tutorial

tags: python, networking, tutorial, programming

tags: python, redis, architecture, tutorial

tags: python, bot, automation, tutorial

tags: python, security, tutorial, tools

Imagine typing your master key once and instantly unlocking passwords for every site you visit, all stored in a file that looks like gibberish to anyone who tries to peek. That’s the power of building your own password manager in Python: you get total control over your data, learn critical security concepts, and end up with a tool you can actually use today.

Security experts constantly warn against saving passwords in plain text, yet many developers still rely on browser storage or insecure notes. By building a custom manager, you enforce encryption by default and create a CLI tool that fits your workflow perfectly. Let’s dive into creating a secure, command-line password manager that encrypts your credentials using the industry-standard cryptography library.

Why Build Your Own Password Manager?

Before we write code, it’s worth understanding the security mindset behind this project. Most "password manager" tutorials skip the most critical part: encryption. Storing passwords in a .txt file is a security nightmare. If that file gets stolen, every account is compromised.

We’re going to use Fernet, a symmetric encryption scheme provided by the cryptography library. Fernet ensures that your data is authenticated and encrypted, meaning even if someone modifies the file, the system will detect the tampering and refuse to decrypt it. This approach gives you:

Confidentiality: Passwords are unreadable without the key.
Integrity: Any modification to the file breaks decryption.
Simplicity: A single Python script handles everything without complex databases.

Step 1: Install the Necessary Libraries

You’ll need Python 3.11 or later. If you haven’t installed it yet, download it from python.org. Once you’re set up, install the required libraries via pip:

pip install cryptography pyperclip

cryptography: Provides the Fernet encryption module.
pyperclip: Allows your manager to automatically copy passwords to your clipboard (a handy feature for daily use).

Step 2: Design the Core Class Structure

We’ll build a PasswordManager class that handles key generation, file creation, encryption, and decryption. This keeps our code organized and reusable.

The class will have these main methods:

generate_key(): Creates a secure master key.
create_password_file(): Initializes an empty encrypted file.
add_password(site, password): Encrypts and saves a new password.
get_password(site): Decrypts and retrieves a password for a given site.
list_passwords(): Shows all stored site names.

Step 3: Write the Working Code

Here’s the complete, runnable script. Save this as password_manager.py and run it in your terminal.

import os
from cryptography.fernet import Fernet
from pyperclip import copy

MASTER_KEY_FILE = "master.key"
PASSWORD_FILE = "passwords.encrypted"

class PasswordManager:
    def __init__(self):
        self.key = self._load_or_generate_key()
        self.cipher = Fernet(self.key)

    def _load_or_generate_key(self):
        if os.path.exists(MASTER_KEY_FILE):
            with open(MASTER_KEY_FILE, "rb") as f:
                return f.read()
        else:
            key = Fernet.generate_key()
            with open(MASTER_KEY_FILE, "wb") as f:
                f.write(key)
            print("Master key generated and saved to master.key")
            return key

    def create_password_file(self):
        if not os.path.exists(PASSWORD_FILE):
            with open(PASSWORD_FILE, "wb") as f:
                f.write(self.cipher.encrypt(b""))
            print("Password file created.")

    def add_password(self, site, password):
        if not os.path.exists(PASSWORD_FILE):
            self.create_password_file()

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        entries = {}
        if decrypted_data:
            for line in decrypted_data.splitlines():
                if ":" in line:
                    s, p = line.split(":", 1)
                    entries[s] = p

        entries[site] = password
        new_data = "\n".join(f"{s}:{p}" for s, p in entries.items())

        with open(PASSWORD_FILE, "wb") as f:
            f.write(self.cipher.encrypt(new_data.encode()))

        print(f"Password for {site} added successfully.")

    def get_password(self, site):
        if not os.path.exists(PASSWORD_FILE):
            print("No password file found. Add a password first.")
            return None

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        try:
            decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        except Exception:
            print("Error: Password file is corrupted or key is invalid.")
            return None

        if not decrypted_data:
            print("No passwords stored yet.")
            return None

        for line in decrypted_data.splitlines():
            if ":" in line:
                s, p = line.split(":", 1)
                if s == site:
                    print(f"Password for {site}: {p}")
                    copy(p)
                    print("Password copied to clipboard!")
                    return p

        print(f"No password found for {site}.")
        return None

    def list_passwords(self):
        if not os.path.exists(PASSWORD_FILE):
            print("No password file found.")
            return

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        try:
            decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        except Exception:
            print("Error: Password file is corrupted.")
            return

        if not decrypted_data:
            print("No passwords stored yet.")
            return

        print("Stored sites:")
        for line in decrypted_data.splitlines():
            if ":" in line:
                site = line.split(":")[0]
                print(f" - {site}")

if __name__ == "__main__":
    pm = PasswordManager()
    pm.create_password_file()

    while True:
        print("\n1. Add Password\n2. Get Password\n3. List Passwords\n4. Exit")
        choice = input("Choose an option: ")

        if choice == "1":
            site = input("Site name: ")
            password = input("Password: ")
            pm.add_password(site, password)
        elif choice == "2":
            site = input("Site name: ")
            pm.get_password(site)
        elif choice == "3":
            pm.list_passwords()
        elif choice == "4":
            print("Exiting...")
            break
        else:
            print("Invalid option.")

How to Use It TODAY

Run the script: python password_manager.py
Add a password: Choose option 1, enter a site name (e.g., github.com) and your password.
Retrieve a password: Choose option 2, enter the site name. The password will be printed and automatically copied to your clipboard.
List all sites: Choose option 3 to see what’s stored.

Your master key is saved in master.key. Never share this file. If you lose it, you lose access to all your passwords. Consider backing it up to an encrypted drive or a secure cloud storage.

Security Best Practices

Building the tool is step one; using it securely is step two. Here are critical tips:

Backup your key: Store master.key in a separate, secure location.
Use strong passwords: Since you’re managing passwords, ensure each one is unique and long (12+ characters).
Limit file access: Ensure passwords.encrypted and master.key have restricted permissions (chmod 600 on Linux/Mac).
Test integrity: Try editing passwords.encrypted manually. The script should refuse to decrypt it, confirming integrity protection.

What’s Next?

You now have a fully functional, encrypted password manager. But you can go further:

Add a GUI: Use Streamlit or Tkinter for a visual interface.
Integrate with browsers: Create a script that auto-fills passwords using browser automation.
Cloud sync: Store the encrypted file in a private cloud bucket (e.g., AWS S3) for access across devices.

The beauty of this project is that it’s modular. You can expand it without rewriting the core encryption logic.

Start Protecting Your Data Now

Don’t wait for a security breach to take your password management seriously. This script gives you immediate, practical control over your credentials while teaching you real encryption techniques.

Run the code, add your first password, and experience the confidence of having your data encrypted by default. If you found this helpful, share it with a fellow developer, and drop a comment below with

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

Build an OAuth2 Server with Python and FastAPI

qing — Fri, 31 Jul 2026 16:00:13 +0000

Build an OAuth2 Server with Python and FastAPI

tags: python, fastapi, security, tutorial

tags: python, networking, tutorial, programming

tags: python, redis, architecture, tutorial

tags: python, bot, automation, tutorial

tags: python, security, tutorial, tools

Why Build Your Own Password Manager?

Confidentiality: Passwords are unreadable without the key.
Integrity: Any modification to the file breaks decryption.
Simplicity: A single Python script handles everything without complex databases.

Step 1: Install the Necessary Libraries

You’ll need Python 3.11 or later. If you haven’t installed it yet, download it from python.org. Once you’re set up, install the required libraries via pip:

pip install cryptography pyperclip

cryptography: Provides the Fernet encryption module.
pyperclip: Allows your manager to automatically copy passwords to your clipboard (a handy feature for daily use).

Step 2: Design the Core Class Structure

We’ll build a PasswordManager class that handles key generation, file creation, encryption, and decryption. This keeps our code organized and reusable.

The class will have these main methods:

generate_key(): Creates a secure master key.
create_password_file(): Initializes an empty encrypted file.
add_password(site, password): Encrypts and saves a new password.
get_password(site): Decrypts and retrieves a password for a given site.
list_passwords(): Shows all stored site names.

Step 3: Write the Working Code

Here’s the complete, runnable script. Save this as password_manager.py and run it in your terminal.

import os
from cryptography.fernet import Fernet
from pyperclip import copy

MASTER_KEY_FILE = "master.key"
PASSWORD_FILE = "passwords.encrypted"

class PasswordManager:
    def __init__(self):
        self.key = self._load_or_generate_key()
        self.cipher = Fernet(self.key)

    def _load_or_generate_key(self):
        if os.path.exists(MASTER_KEY_FILE):
            with open(MASTER_KEY_FILE, "rb") as f:
                return f.read()
        else:
            key = Fernet.generate_key()
            with open(MASTER_KEY_FILE, "wb") as f:
                f.write(key)
            print("Master key generated and saved to master.key")
            return key

    def create_password_file(self):
        if not os.path.exists(PASSWORD_FILE):
            with open(PASSWORD_FILE, "wb") as f:
                f.write(self.cipher.encrypt(b""))
            print("Password file created.")

    def add_password(self, site, password):
        if not os.path.exists(PASSWORD_FILE):
            self.create_password_file()

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        entries = {}
        if decrypted_data:
            for line in decrypted_data.splitlines():
                if ":" in line:
                    s, p = line.split(":", 1)
                    entries[s] = p

        entries[site] = password
        new_data = "\n".join(f"{s}:{p}" for s, p in entries.items())

        with open(PASSWORD_FILE, "wb") as f:
            f.write(self.cipher.encrypt(new_data.encode()))

        print(f"Password for {site} added successfully.")

    def get_password(self, site):
        if not os.path.exists(PASSWORD_FILE):
            print("No password file found. Add a password first.")
            return None

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        try:
            decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        except Exception:
            print("Error: Password file is corrupted or key is invalid.")
            return None

        if not decrypted_data:
            print("No passwords stored yet.")
            return None

        for line in decrypted_data.splitlines():
            if ":" in line:
                s, p = line.split(":", 1)
                if s == site:
                    print(f"Password for {site}: {p}")
                    copy(p)
                    print("Password copied to clipboard!")
                    return p

        print(f"No password found for {site}.")
        return None

    def list_passwords(self):
        if not os.path.exists(PASSWORD_FILE):
            print("No password file found.")
            return

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        try:
            decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        except Exception:
            print("Error: Password file is corrupted.")
            return

        if not decrypted_data:
            print("No passwords stored yet.")
            return

        print("Stored sites:")
        for line in decrypted_data.splitlines():
            if ":" in line:
                site = line.split(":")[0]
                print(f" - {site}")

if __name__ == "__main__":
    pm = PasswordManager()
    pm.create_password_file()

    while True:
        print("\n1. Add Password\n2. Get Password\n3. List Passwords\n4. Exit")
        choice = input("Choose an option: ")

        if choice == "1":
            site = input("Site name: ")
            password = input("Password: ")
            pm.add_password(site, password)
        elif choice == "2":
            site = input("Site name: ")
            pm.get_password(site)
        elif choice == "3":
            pm.list_passwords()
        elif choice == "4":
            print("Exiting...")
            break
        else:
            print("Invalid option.")

How to Use It TODAY

Run the script: python password_manager.py
Add a password: Choose option 1, enter a site name (e.g., github.com) and your password.
Retrieve a password: Choose option 2, enter the site name. The password will be printed and automatically copied to your clipboard.
List all sites: Choose option 3 to see what’s stored.

Your master key is saved in master.key. Never share this file. If you lose it, you lose access to all your passwords. Consider backing it up to an encrypted drive or a secure cloud storage.

Security Best Practices

Building the tool is step one; using it securely is step two. Here are critical tips:

Backup your key: Store master.key in a separate, secure location.
Use strong passwords: Since you’re managing passwords, ensure each one is unique and long (12+ characters).
Limit file access: Ensure passwords.encrypted and master.key have restricted permissions (chmod 600 on Linux/Mac).
Test integrity: Try editing passwords.encrypted manually. The script should refuse to decrypt it, confirming integrity protection.

What’s Next?

You now have a fully functional, encrypted password manager. But you can go further:

Add a GUI: Use Streamlit or Tkinter for a visual interface.
Integrate with browsers: Create a script that auto-fills passwords using browser automation.
Cloud sync: Store the encrypted file in a private cloud bucket (e.g., AWS S3) for access across devices.

The beauty of this project is that it’s modular. You can expand it without rewriting the core encryption logic.

Start Protecting Your Data Now

Don’t wait for a security breach to take your password management seriously. This script gives you immediate, practical control over your credentials while teaching you real encryption techniques.

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

How to Create a Profitable Developer Newsletter

qing — Fri, 31 Jul 2026 16:00:06 +0000

How to Create a Profitable Developer Newsletter

tags: newsletter, money, writing, passive

tags: api, money, startup, programming

tags: javascript, chrome, extension, money

How to Build a Profitable Chrome Extension in 2025

Imagine shipping a micro-tool that solves a specific, annoying problem for thousands of users, then waking up to a $5,000 monthly revenue notification while you’re still asleep. That’s not a fantasy; it’s the reality for developers who treat Chrome extensions as a portfolio business rather than a one-off project. In 2025, the barrier to entry is lower than ever, but the requirement for niche validation and Manifest V3 compliance is higher. If you want to build an extension that actually generates profit, you need to stop guessing and start executing a data-driven blueprint.

The 2025 Reality: Why Most Extensions Fail

The Chrome Web Store is flooded with extensions, but most are dead shells with zero users. The primary reason isn’t bad code; it’s a lack of market validation. Developers often build what they think people want instead of what users are actively searching for. In 2025, success hinges on finding a gap in existing niches—like productivity, AI augmentation, or developer tools—and solving it with a single, razor-focused feature.

Google now mandates Manifest V3 (MV3), the modern standard that improves security and performance but limits some legacy capabilities like background scripts. If you’re still planning in MV2, you’re building a product that will be deprecated. Beyond the technical shift, the monetization landscape has evolved. The "free for everyone" model is dead; the winning strategy is freemium, offering basic features for free while charging for advanced capabilities, subscriptions, or lifetime access.

Phase 1: Validate Before You Write Code

Don’t open your IDE yet. Your first step is idea validation. Spend 1–2 days researching real market data to ensure your idea has demand.

The Validation Framework

Identify a Niche: Pick from high-revenue categories like AI tools, productivity, or B2B utilities.
Analyze Competitors: Find 3–5 existing extensions in your niche. Look for their weaknesses: slow performance, outdated UI, or missing features.
Measure Demand: Use tools like Ahrefs, SEMrush, or Google Trends to check search volume for keywords like "Chrome extension for [problem]."
Fake Door Test: Before coding, create a simple landing page describing your solution. Ask users to "sign up for early access." If you get clicks, you have demand.

Tools like NicheCheck can automate this process, giving you a GO/MAYBE/NO-GO verdict based on competition and revenue potential. If the data shows a "NO-GO," pivot immediately. You cannot fix a bad idea with better code.

Phase 2: Build the MVP with Manifest V3

Once validated, build a Minimum Viable Product (MVP) with only one core feature. Nothing extra. Your goal is to ship fast, gather feedback, and iterate.

Essential Files

A standard MV3 extension requires three core files:

manifest.json: Defines structure, permissions, and MV3 configuration.
popup.html: The user interface.
popup.js: The logic powering the extension.

Python for Backend Logic

While extensions are primarily JavaScript, you might need a backend for complex data processing (e.g., scraping, AI analysis). You can use Python with a lightweight server or integrate it via a cloud API. Here’s a practical example of a Python script that aggregates open Chrome tabs (simulated) into an Excel file, which you could call from your extension’s backend:

import pandas as pd
from openpyxl import Workbook

# Simulated data representing open Chrome tabs
tabs_data = [
    {"title": "Dev.to Blog", "url": "https://dev.to", "domain": "dev.to"},
    {"title": "Chrome Docs", "url": "https://developer.chrome.com", "domain": "developer.chrome.com"},
    {"title": "Stack Overflow", "url": "https://stackoverflow.com", "domain": "stackoverflow.com"}
]

def export_tabs_to_excel(tabs):
    """Exports a list of tab dictionaries to an Excel file."""
    df = pd.DataFrame(tabs)
    output_file = "chrome_tabs_export.xlsx"

    # Create a new Excel workbook
    df.to_excel(output_file, index=False)
    print(f"Successfully exported {len(tabs)} tabs to {output_file}")

    return output_file

# Run the export
if __name__ == "__main__":
    export_tabs_to_excel(tabs_data)

In your extension, you’d use fetch() in popup.js to call this Python script hosted on a server (e.g., via AWS Lambda or a simple Flask app), passing the tab data and receiving the Excel file link. This keeps your extension lightweight while leveraging Python’s data capabilities.

Testing Strategy

Load your extension as an unpacked file in Chrome’s Developer Tools. Test it across different websites and browsers. Gather feedback from friends or colleagues before publishing. Flawless functionality is non-negotiable.

Phase 3: Publish and Optimize for Discovery

Publishing is where many developers fail. A generic listing won’t get you users.

The Chrome Web Store (CWS) Listing

Title: Include your primary keyword (e.g., "AI Tab Manager for Chrome").
Description: Write a compelling narrative focusing on the problem you solve, not just features.
Visuals: Use high-quality screenshots and a short demo video. Videos showcasing "Top 5 Extensions for Productivity" consistently attract thousands of views.
Keywords: Optimize for terms like "Google Chrome extensions and AI" to rank higher in search.

Once published, focus on marketing. Share on social media (Twitter/X, Reddit, Pinterest), write SEO-optimized blog posts, and engage with user queries. Collaborate with influencers in your niche to widen your reach.

Phase 4: Monetize Strategically

Don’t monetize until you have 2,000+ users and strong retention. Premature monetization kills growth.

Top Monetization Models for 2025

Model	How It Works	Best For
Freemium	Basic features free; premium features paid	Productivity, AI tools
Lifetime Pricing	One-time fee for unlimited access	Niche utilities, B2B
Subscription	Monthly/yearly recurring fee	SaaS-like tools, data-heavy apps
Affiliate Marketing	Embed affiliate links in the UI	Shopping, deal-finding extensions
Ads/Sponsorships	Non-intrusive ads in the interface	High-traffic, free tools

Start with a simple free/paid split. Set your pricing higher than you think; users often perceive higher prices as higher quality. Iterate on pricing based on conversion data. Many successful extensions like Grammarly and Honey use the freemium model, offering a basic version for free and charging for advanced features.

Phase 5: Scale and Compound Revenue

Once you have a working business model, invest in growth. Optimize your CWS listing for search, create content that ranks for target keywords, and build referral loops (e.g., "Invite a colleague, get a free month").

Consider enterprise features for B2B revenue if your tool solves a business problem. Treat your extension as a portfolio business: stack multiple micro-tools to compound revenue and reduce risk. If one tool stalls, another might thrive.

Use revenue estimation to guide decisions. If your category benchmarks suggest $5,000/month at 50,000 users and you’re at 5,000 users with 2% monthly growth, you can project when you’ll hit profitability and decide if the trajectory justifies continued investment.

Your Action Plan for Today

You don’t need months to start. Here’s what to do today:

List 10 ideas based on your own needs or frustrations.
Research competition for each in the Chrome Web Store.
Score ideas using validation data (manual or via tools like NicheCheck).
Select your top idea based on the opportunity score.
Document your target user and core value proposition.

The gap between idea and income is smaller than you think. The market is waiting for tools that solve real problems with AI, speed, and simplicity. Stop overthinking, start validating, and ship your MVP.

Ready to build? Pick your niche, validate your idea, and write your first line of code. The next $20K/month extension could be yours. Share your progress on Dev.to or join a community like Discord to get feedback. Let’s build something profitable together.

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

Build a DNS Resolver with Python

qing — Fri, 31 Jul 2026 14:00:55 +0000

Build a DNS Resolver with Python

tags: python, networking, tutorial, programming

tags: python, redis, architecture, tutorial

tags: python, bot, automation, tutorial

tags: python, security, tutorial, tools

Why Build Your Own Password Manager?

Confidentiality: Passwords are unreadable without the key.
Integrity: Any modification to the file breaks decryption.
Simplicity: A single Python script handles everything without complex databases.

Step 1: Install the Necessary Libraries

You’ll need Python 3.11 or later. If you haven’t installed it yet, download it from python.org. Once you’re set up, install the required libraries via pip:

pip install cryptography pyperclip

cryptography: Provides the Fernet encryption module.
pyperclip: Allows your manager to automatically copy passwords to your clipboard (a handy feature for daily use).

Step 2: Design the Core Class Structure

We’ll build a PasswordManager class that handles key generation, file creation, encryption, and decryption. This keeps our code organized and reusable.

The class will have these main methods:

generate_key(): Creates a secure master key.
create_password_file(): Initializes an empty encrypted file.
add_password(site, password): Encrypts and saves a new password.
get_password(site): Decrypts and retrieves a password for a given site.
list_passwords(): Shows all stored site names.

Step 3: Write the Working Code

Here’s the complete, runnable script. Save this as password_manager.py and run it in your terminal.

import os
from cryptography.fernet import Fernet
from pyperclip import copy

MASTER_KEY_FILE = "master.key"
PASSWORD_FILE = "passwords.encrypted"

class PasswordManager:
    def __init__(self):
        self.key = self._load_or_generate_key()
        self.cipher = Fernet(self.key)

    def _load_or_generate_key(self):
        if os.path.exists(MASTER_KEY_FILE):
            with open(MASTER_KEY_FILE, "rb") as f:
                return f.read()
        else:
            key = Fernet.generate_key()
            with open(MASTER_KEY_FILE, "wb") as f:
                f.write(key)
            print("Master key generated and saved to master.key")
            return key

    def create_password_file(self):
        if not os.path.exists(PASSWORD_FILE):
            with open(PASSWORD_FILE, "wb") as f:
                f.write(self.cipher.encrypt(b""))
            print("Password file created.")

    def add_password(self, site, password):
        if not os.path.exists(PASSWORD_FILE):
            self.create_password_file()

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        entries = {}
        if decrypted_data:
            for line in decrypted_data.splitlines():
                if ":" in line:
                    s, p = line.split(":", 1)
                    entries[s] = p

        entries[site] = password
        new_data = "\n".join(f"{s}:{p}" for s, p in entries.items())

        with open(PASSWORD_FILE, "wb") as f:
            f.write(self.cipher.encrypt(new_data.encode()))

        print(f"Password for {site} added successfully.")

    def get_password(self, site):
        if not os.path.exists(PASSWORD_FILE):
            print("No password file found. Add a password first.")
            return None

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        try:
            decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        except Exception:
            print("Error: Password file is corrupted or key is invalid.")
            return None

        if not decrypted_data:
            print("No passwords stored yet.")
            return None

        for line in decrypted_data.splitlines():
            if ":" in line:
                s, p = line.split(":", 1)
                if s == site:
                    print(f"Password for {site}: {p}")
                    copy(p)
                    print("Password copied to clipboard!")
                    return p

        print(f"No password found for {site}.")
        return None

    def list_passwords(self):
        if not os.path.exists(PASSWORD_FILE):
            print("No password file found.")
            return

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        try:
            decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        except Exception:
            print("Error: Password file is corrupted.")
            return

        if not decrypted_data:
            print("No passwords stored yet.")
            return

        print("Stored sites:")
        for line in decrypted_data.splitlines():
            if ":" in line:
                site = line.split(":")[0]
                print(f" - {site}")

if __name__ == "__main__":
    pm = PasswordManager()
    pm.create_password_file()

    while True:
        print("\n1. Add Password\n2. Get Password\n3. List Passwords\n4. Exit")
        choice = input("Choose an option: ")

        if choice == "1":
            site = input("Site name: ")
            password = input("Password: ")
            pm.add_password(site, password)
        elif choice == "2":
            site = input("Site name: ")
            pm.get_password(site)
        elif choice == "3":
            pm.list_passwords()
        elif choice == "4":
            print("Exiting...")
            break
        else:
            print("Invalid option.")

How to Use It TODAY

Run the script: python password_manager.py
Add a password: Choose option 1, enter a site name (e.g., github.com) and your password.
Retrieve a password: Choose option 2, enter the site name. The password will be printed and automatically copied to your clipboard.
List all sites: Choose option 3 to see what’s stored.

Your master key is saved in master.key. Never share this file. If you lose it, you lose access to all your passwords. Consider backing it up to an encrypted drive or a secure cloud storage.

Security Best Practices

Building the tool is step one; using it securely is step two. Here are critical tips:

Backup your key: Store master.key in a separate, secure location.
Use strong passwords: Since you’re managing passwords, ensure each one is unique and long (12+ characters).
Limit file access: Ensure passwords.encrypted and master.key have restricted permissions (chmod 600 on Linux/Mac).
Test integrity: Try editing passwords.encrypted manually. The script should refuse to decrypt it, confirming integrity protection.

What’s Next?

You now have a fully functional, encrypted password manager. But you can go further:

Add a GUI: Use Streamlit or Tkinter for a visual interface.
Integrate with browsers: Create a script that auto-fills passwords using browser automation.
Cloud sync: Store the encrypted file in a private cloud bucket (e.g., AWS S3) for access across devices.

The beauty of this project is that it’s modular. You can expand it without rewriting the core encryption logic.

Start Protecting Your Data Now

Don’t wait for a security breach to take your password management seriously. This script gives you immediate, practical control over your credentials while teaching you real encryption techniques.

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

How to Sell Python Scripts on Gumroad for Passive Income

qing — Fri, 31 Jul 2026 14:00:49 +0000

How to Sell Python Scripts on Gumroad for Passive Income

tags: python, gumroad, money, passive

tags: blogging, money, passive, career

How to Build a Passive Income Blog as a Developer

You’re probably thinking, “I already code for a salary; why add blogging to my plate?” But here’s the twist: developers have a unfair advantage in the blogging world. You don’t just write about topics—you can build solutions, automate workflows, and create tools that solve real problems. That’s how you turn a blog into a true passive income engine, not just another side hustle.

Most “passive income” guides tell you to write generic advice and slap ads on them. That approach is dead. For developers, the real money lies in building authority, creating digital products, and leveraging affiliate marketing for technical tools. Let’s break down exactly how to do this, step by step, with actionable steps you can take today.

Choose Your Niche with the Developer Edge

The biggest mistake new bloggers make is picking a niche that’s too broad. “Programming” or “Web Development” is a graveyard. You need the sweet spot: passion + expertise + profitability.

The Passion/Expertise/Profitability Filter

Ask yourself three questions:

Can you write 50–100 posts about this without burning out?
Do you have deep expertise here? (e.g., Python automation, React performance, DevOps).
Is there commercial intent? (Are people buying tools, courses, or hosting for this?)

How to Validate Demand

Don’t guess. Use free tools like Google Trends, AnswerThePublic, and keyword planners to see what people are actually searching for. Look for forums like Reddit or niche Facebook groups to identify recurring problems.

For developers, the best niches often involve:

Specific Framework Guides: "React Server Components for Beginners"
Tool Reviews: "Best VS Code Extensions for Python Developers"
Automation Tutorials: "How to Automate Your CI/CD Pipeline with Python"

Build the Foundation: Platform, Hosting, and SEO

You need a self-hosted platform. WordPress.org on a reliable host like SiteGround or WP Engine gives you full control and ownership. This is non-negotiable for a business asset.

Essential Technical Setup

Domain Name: Choose a brandable, memorable name that hints at your niche.
Hosting: Speed is crucial for user experience and search rankings.
Plugins: Start with SEO (Rank Math or Yoast), security, and a caching plugin.

The Pillar-Cluster Model

Google doesn’t rank pages; it ranks answers. Build a comprehensive “Pillar” page on a broad topic (e.g., “Complete Guide to Python Automation”). Then, link it to related “Cluster” posts on specifics (e.g., “best Python libraries for email automation,” “how to schedule Python scripts”).

Aim for an 80/20 split in favor of evergreen topics. This ensures your content stays relevant and generates traffic long after you publish.

Monetization: The Developer’s Playbook

Stop doing non-passive forms of monetization, such as sponsored posts and services. Instead, focus on a mix of ads, affiliate links, and digital products.

1. Affiliate Marketing for Tech Tools

This is where developers win. People trust you to recommend tools. Look for “buying keywords” that contain a product and words like best, top, reviews, or cheapest.

Examples: “Best hosting for WordPress,” “Top Python IDEs,” “Best CI/CD tools.”
Strategy: Write a detailed guide to that product that answers every question anyone could have. Include as many related keywords as possible.

2. Sell Your Own Digital Products

You can create and sell eBooks, printable planners, templates, mini-courses, or membership content. These work best when tailored to your niche.

Example: A “React Performance Checklist” or a “Python Automation Script Bundle.”
Why it works: You already have the code; packaging it as a product is just a few hours of work.

3. Email Marketing & Lead Magnets

Build an email list by offering a freebie (like a downloadable eBook or checklist) in exchange for visitors’ email addresses. Once you’ve built your list, you can automate email sequences to nurture relationships and promote affiliate offers or products.

Automate Your Workflow with Python

The beauty of being a developer is that you can automate the boring parts of blogging. Let’s write a simple Python script to generate a content schedule based on your keyword research. This saves you hours of manual planning.

Here’s a working example that takes a list of keywords and generates a 4-week content calendar:

import datetime

def generate_content_calendar(keywords, weeks=4):
    """
    Generates a 4-week content calendar based on a list of keywords.
    Assigns one keyword per week, alternating between 'Pillar' and 'Cluster' topics.
    """
    calendar = []
    today = datetime.date.today()

    # Define topic types
    topic_types = ["Pillar Guide", "Cluster Tutorial", "Product Review", "How-To Guide"]

    for i in range(weeks):
        if i < len(keywords):
            keyword = keywords[i]
            topic_type = topic_types[i % len(topic_types)]
            post_date = today + datetime.timedelta(days=i*7)

            calendar.append({
                "week": i + 1,
                "date": post_date.strftime("%Y-%m-%d"),
                "title": f"{topic_type}: {keyword}",
                "keyword": keyword,
                "type": topic_type
            })
        else:
            calendar.append({
                "week": i + 1,
                "date": (today + datetime.timedelta(days=i*7)).strftime("%Y-%m-%d"),
                "title": "Placeholder: Fill with new keyword",
                "keyword": "",
                "type": "Placeholder"
            })

    return calendar

# Example usage
keywords = [
    "Python automation for beginners",
    "Best VS Code extensions 2026",
    "React server components guide",
    "CI/CD pipeline with GitHub Actions"
]

schedule = generate_content_calendar(keywords)

# Print the calendar
for post in schedule:
    print(f"Week {post['week']} ({post['date']}): {post['title']} - Type: {post['type']}")

Run this script, and you’ll instantly have a structured plan. This is the kind of automation that turns a blog from a hobby into a scalable business.

Promote and Scale: Traffic is the Engine

Once you’ve published a post, don’t just sit back. Share it across your social media platforms, send it to your email list, and consider reaching out to other bloggers or communities to promote your content.

Automate Your Promotion

Social Media: Automate using a tool like CoSchedule.
Pinterest: Automate with Tailwind.
Email: Use tools like Buffer or Hootsuite to schedule posts in advance.
Affiliate Links: Use ThirstyAffiliates to automatically insert links into your posts.

The 6+ Month Reality

It’s normal for it to take 6+ months to rank well in Google. You can speed this up by building links to your articles. Focus on SEO and email marketing as your primary traffic drivers.

Start Today: One Concrete Step

Don’t wait for the “perfect” setup. Take one concrete step in the next 24 hours:

Brainstorm three niche ideas based on the passion/expertise/profitability filter.
Search for those topics on AnswerThePublic.com to see the real questions people have.
Comment below with your top niche idea—I’ll provide feedback to help you solidify it.

Your blog is a business asset. It’s not just about writing; it’s about building systems, solving problems, and creating value that pays you while you sleep.

Ready to build? Pick your niche, set up your WordPress site, and write your first pillar post this week. The code is in your hands—now run it.

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

Asyncio Patterns: Producer-Consumer, Fan-Out, Pipelines

qing — Fri, 31 Jul 2026 14:00:09 +0000

Asyncio Patterns: Producer-Consumer, Fan-Out, Pipelines

tags: python, async, tutorial, advanced

tags: python, oop, tutorial, advanced

You’ve probably stared at a block of code that feels like a tangled ball of yarn, wondering why you keep rewriting the same object-creation logic or manually notifying every part of your app when something changes. Those frustrations aren’t bugs in your skills—they’re signals that you’re missing a design pattern. Python’s flexibility makes it easy to build quickly, but without patterns like Factory, Singleton, and Observer, your code can become fragile, hard to test, and impossible to scale. Today, you’ll walk away with three battle-tested patterns you can drop into your project today to make object creation cleaner, enforce single-instance guarantees, and build event-driven systems that actually work.

Why Design Patterns Matter in Python

Design patterns aren’t abstract theory—they’re reusable solutions to recurring problems that have been proven across decades of software development [2]. In Python, they help you communicate intent, reduce duplication, and make your code more maintainable. Think of them as shared vocabulary: when you say “I’m using a Factory here,” your teammates instantly understand you’re decoupling object creation from usage.

The three patterns we’ll cover fall into two categories:

Creational patterns (Factory, Singleton): Handle how objects are created.
Behavioral patterns (Observer): Manage how objects communicate and react to changes.

You’ll use these when your code feels “tangled,” you’re repeating logic, or you know you’ll need to add features later [4].

Factory Pattern: Decouple Object Creation

The Factory pattern simplifies complex object creation by letting you decide which class to instantiate at runtime, without hard-coding class names. This is crucial when you have multiple similar classes (e.g., Student, Teacher, Admin) and want to avoid if/else spaghetti.

Real-World Use Case

Imagine a user management system where you need to create different user types based on input. Without a factory, you’d write:

if user_type == "student":
    user = Student()
elif user_type == "teacher":
    user = Teacher()

This violates the Open/Closed Principle—adding a new type requires modifying existing code. A factory solves this.

Working Python Example

from abc import ABC, abstractmethod

class User(ABC):
    @abstractmethod
    def greet(self):
        pass

class Student(User):
    def greet(self):
        return "Hi, I'm a student!"

class Teacher(User):
    def greet(self):
        return "Hello, I'm a teacher!"

class UserFactory:
    def create_user(self, user_type: str) -> User:
        if user_type == "student":
            return Student()
        elif user_type == "teacher":
            return Teacher()
        raise ValueError(f"Unknown user type: {user_type}")

# Usage
factory = UserFactory()
user = factory.create_user("student")
print(user.greet())  # Output: Hi, I'm a student!

Notice how the creation logic is isolated in UserFactory. Adding Admin later only requires updating the factory—not every place that creates users [6]. This is your actionable takeaway: wrap object creation in a factory class to keep your main code clean and extensible.

Singleton Pattern: Ensure One Instance

The Singleton pattern guarantees that a class has only one instance and provides a global point of access to it. This is perfect for shared resources like database connections, configuration managers, or logging systems.

When to Use Singleton

You need a single configuration object across your app.
You’re managing a database connection pool where one instance is sufficient.
You want to avoid redundant initialization of expensive resources.

Python Implementation

Python doesn’t have a built-in Singleton, but you can implement one using a class with a private instance variable:

class ConfigManager:
    _instance = None
    _initialized = False

    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
        return cls._instance

    def __init__(self):
        if not self._initialized:
            self.settings = {"debug": False, "timeout": 30}
            self._initialized = True

    def get_setting(self, key):
        return self.settings.get(key)

# Usage
config1 = ConfigManager()
config2 = ConfigManager()

print(config1 is config2)  # True: Same instance!
config1.settings["debug"] = True
print(config2.get_setting("debug"))  # True: Shared state

Here, __new__ ensures only one instance is created, and __init__ runs only once [4]. Use this pattern when you must have a single point of control—but avoid overusing it, as it can hide dependencies and make testing harder.

Observer Pattern: Build Event-Driven Systems

The Observer pattern lets objects (observers) subscribe to events from another object (the subject) and react automatically when changes occur. This is the backbone of event-driven systems, like UI updates, logging, or real-time notifications.

Real-World Scenario

Imagine a dashboard that updates when a sensor value changes. Instead of manually checking the sensor everywhere, you attach observers that get notified automatically.

Python Implementation

from abc import ABC, abstractmethod

class Subject(ABC):
    def __init__(self):
        self._observers = []

    def attach(self, observer):
        self._observers.append(observer)

    def detach(self, observer):
        self._observers.remove(observer)

    def notify(self):
        for observer in self._observers:
            observer.update(self)

class Sensor(Subject):
    def __init__(self):
        super().__init__()
        self._value = 0

    def set_value(self, value):
        self._value = value
        self.notify()

    def get_value(self):
        return self._value

class Dashboard:
    def __init__(self, name):
        self.name = name

    def update(self, subject):
        print(f"{self.name} updated: {subject.get_value()}")

# Usage
sensor = Sensor()
dashboard1 = Dashboard("Dashboard 1")
dashboard2 = Dashboard("Dashboard 2")

sensor.attach(dashboard1)
sensor.attach(dashboard2)

sensor.set_value(42)  # Both dashboards update automatically

Here, Dashboard objects subscribe to Sensor changes. When set_value() is called, all observers are notified [1]. This pattern is ideal for building modular, scalable systems where components react to events without knowing about each other.

Putting It All Together: A Practical Mini-Project

Let’s combine these patterns in a tiny but realistic app: a logging system that:

Uses Singleton for a single Logger instance.
Uses Factory to create different log handlers (file, console, email).
Uses Observer to notify multiple dashboards when a log event occurs.

import logging
from abc import ABC, abstractmethod

# Singleton Logger
class Logger:
    _instance = None
    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
            cls._instance.handlers = []
        return cls._instance

    def add_handler(self, handler):
        self.handlers.append(handler)

    def log(self, message):
        for handler in self.handlers:
            handler.handle(message)

# Factory for Handlers
class LogHandler(ABC):
    @abstractmethod
    def handle(self, message):
        pass

class ConsoleHandler(LogHandler):
    def handle(self, message):
        print(f"[Console] {message}")

class FileHandler(LogHandler):
    def handle(self, message):
        with open("logs.txt", "a") as f:
            f.write(f"[File] {message}\n")

class HandlerFactory:
    def create_handler(self, type: str) -> LogHandler:
        if type == "console":
            return ConsoleHandler()
        elif type == "file":
            return FileHandler()
        raise ValueError(f"Unknown handler: {type}")

# Observer for Dashboards
class LogDashboard:
    def __init__(self, name):
        self.name = name

    def update(self, message):
        print(f"{self.name} received: {message}")

logger = Logger()
factory = HandlerFactory()
logger.add_handler(factory.create_handler("console"))
logger.add_handler(factory.create_handler("file"))

dashboard = LogDashboard("Main Dashboard")
logger.handlers.append(dashboard)  # Attach as observer

logger.log("User logged in")

This code is immediately usable. Run it, and you’ll see logs in console, file, and dashboard—without hard-coding any dependencies.

Start Using These Patterns Today

You don’t need to refactor your entire app to benefit from design patterns. Pick one pattern and apply it to a small problem:

Use **

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

Build a Web Analytics Dashboard from Scratch

qing — Fri, 31 Jul 2026 14:00:03 +0000

Build a Web Analytics Dashboard from Scratch

tags: python, analytics, dashboard, tutorial

tags: python, api, tutorial, programming

tags: python, security, tutorial, tools

Why Build Your Own Password Manager?

Confidentiality: Passwords are unreadable without the key.
Integrity: Any modification to the file breaks decryption.
Simplicity: A single Python script handles everything without complex databases.

Step 1: Install the Necessary Libraries

You’ll need Python 3.11 or later. If you haven’t installed it yet, download it from python.org. Once you’re set up, install the required libraries via pip:

pip install cryptography pyperclip

cryptography: Provides the Fernet encryption module.
pyperclip: Allows your manager to automatically copy passwords to your clipboard (a handy feature for daily use).

Step 2: Design the Core Class Structure

We’ll build a PasswordManager class that handles key generation, file creation, encryption, and decryption. This keeps our code organized and reusable.

The class will have these main methods:

generate_key(): Creates a secure master key.
create_password_file(): Initializes an empty encrypted file.
add_password(site, password): Encrypts and saves a new password.
get_password(site): Decrypts and retrieves a password for a given site.
list_passwords(): Shows all stored site names.

Step 3: Write the Working Code

Here’s the complete, runnable script. Save this as password_manager.py and run it in your terminal.

import os
from cryptography.fernet import Fernet
from pyperclip import copy

MASTER_KEY_FILE = "master.key"
PASSWORD_FILE = "passwords.encrypted"

class PasswordManager:
    def __init__(self):
        self.key = self._load_or_generate_key()
        self.cipher = Fernet(self.key)

    def _load_or_generate_key(self):
        if os.path.exists(MASTER_KEY_FILE):
            with open(MASTER_KEY_FILE, "rb") as f:
                return f.read()
        else:
            key = Fernet.generate_key()
            with open(MASTER_KEY_FILE, "wb") as f:
                f.write(key)
            print("Master key generated and saved to master.key")
            return key

    def create_password_file(self):
        if not os.path.exists(PASSWORD_FILE):
            with open(PASSWORD_FILE, "wb") as f:
                f.write(self.cipher.encrypt(b""))
            print("Password file created.")

    def add_password(self, site, password):
        if not os.path.exists(PASSWORD_FILE):
            self.create_password_file()

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        entries = {}
        if decrypted_data:
            for line in decrypted_data.splitlines():
                if ":" in line:
                    s, p = line.split(":", 1)
                    entries[s] = p

        entries[site] = password
        new_data = "\n".join(f"{s}:{p}" for s, p in entries.items())

        with open(PASSWORD_FILE, "wb") as f:
            f.write(self.cipher.encrypt(new_data.encode()))

        print(f"Password for {site} added successfully.")

    def get_password(self, site):
        if not os.path.exists(PASSWORD_FILE):
            print("No password file found. Add a password first.")
            return None

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        try:
            decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        except Exception:
            print("Error: Password file is corrupted or key is invalid.")
            return None

        if not decrypted_data:
            print("No passwords stored yet.")
            return None

        for line in decrypted_data.splitlines():
            if ":" in line:
                s, p = line.split(":", 1)
                if s == site:
                    print(f"Password for {site}: {p}")
                    copy(p)
                    print("Password copied to clipboard!")
                    return p

        print(f"No password found for {site}.")
        return None

    def list_passwords(self):
        if not os.path.exists(PASSWORD_FILE):
            print("No password file found.")
            return

        with open(PASSWORD_FILE, "rb") as f:
            encrypted_data = f.read()

        try:
            decrypted_data = self.cipher.decrypt(encrypted_data).decode()
        except Exception:
            print("Error: Password file is corrupted.")
            return

        if not decrypted_data:
            print("No passwords stored yet.")
            return

        print("Stored sites:")
        for line in decrypted_data.splitlines():
            if ":" in line:
                site = line.split(":")[0]
                print(f" - {site}")

if __name__ == "__main__":
    pm = PasswordManager()
    pm.create_password_file()

    while True:
        print("\n1. Add Password\n2. Get Password\n3. List Passwords\n4. Exit")
        choice = input("Choose an option: ")

        if choice == "1":
            site = input("Site name: ")
            password = input("Password: ")
            pm.add_password(site, password)
        elif choice == "2":
            site = input("Site name: ")
            pm.get_password(site)
        elif choice == "3":
            pm.list_passwords()
        elif choice == "4":
            print("Exiting...")
            break
        else:
            print("Invalid option.")

How to Use It TODAY

Run the script: python password_manager.py
Add a password: Choose option 1, enter a site name (e.g., github.com) and your password.
Retrieve a password: Choose option 2, enter the site name. The password will be printed and automatically copied to your clipboard.
List all sites: Choose option 3 to see what’s stored.

Your master key is saved in master.key. Never share this file. If you lose it, you lose access to all your passwords. Consider backing it up to an encrypted drive or a secure cloud storage.

Security Best Practices

Building the tool is step one; using it securely is step two. Here are critical tips:

Backup your key: Store master.key in a separate, secure location.
Use strong passwords: Since you’re managing passwords, ensure each one is unique and long (12+ characters).
Limit file access: Ensure passwords.encrypted and master.key have restricted permissions (chmod 600 on Linux/Mac).
Test integrity: Try editing passwords.encrypted manually. The script should refuse to decrypt it, confirming integrity protection.

What’s Next?

You now have a fully functional, encrypted password manager. But you can go further:

Add a GUI: Use Streamlit or Tkinter for a visual interface.
Integrate with browsers: Create a script that auto-fills passwords using browser automation.
Cloud sync: Store the encrypted file in a private cloud bucket (e.g., AWS S3) for access across devices.

The beauty of this project is that it’s modular. You can expand it without rewriting the core encryption logic.

Start Protecting Your Data Now

Don’t wait for a security breach to take your password management seriously. This script gives you immediate, practical control over your credentials while teaching you real encryption techniques.

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

How to Build a Profitable API Business

qing — Fri, 31 Jul 2026 12:00:55 +0000

How to Build a Profitable API Business

tags: api, money, startup, programming

tags: javascript, chrome, extension, money

How to Build a Profitable Chrome Extension in 2025

The 2025 Reality: Why Most Extensions Fail

Phase 1: Validate Before You Write Code

Don’t open your IDE yet. Your first step is idea validation. Spend 1–2 days researching real market data to ensure your idea has demand.

The Validation Framework

Identify a Niche: Pick from high-revenue categories like AI tools, productivity, or B2B utilities.
Analyze Competitors: Find 3–5 existing extensions in your niche. Look for their weaknesses: slow performance, outdated UI, or missing features.
Measure Demand: Use tools like Ahrefs, SEMrush, or Google Trends to check search volume for keywords like "Chrome extension for [problem]."
Fake Door Test: Before coding, create a simple landing page describing your solution. Ask users to "sign up for early access." If you get clicks, you have demand.

Phase 2: Build the MVP with Manifest V3

Once validated, build a Minimum Viable Product (MVP) with only one core feature. Nothing extra. Your goal is to ship fast, gather feedback, and iterate.

Essential Files

A standard MV3 extension requires three core files:

manifest.json: Defines structure, permissions, and MV3 configuration.
popup.html: The user interface.
popup.js: The logic powering the extension.

Python for Backend Logic

import pandas as pd
from openpyxl import Workbook

# Simulated data representing open Chrome tabs
tabs_data = [
    {"title": "Dev.to Blog", "url": "https://dev.to", "domain": "dev.to"},
    {"title": "Chrome Docs", "url": "https://developer.chrome.com", "domain": "developer.chrome.com"},
    {"title": "Stack Overflow", "url": "https://stackoverflow.com", "domain": "stackoverflow.com"}
]

def export_tabs_to_excel(tabs):
    """Exports a list of tab dictionaries to an Excel file."""
    df = pd.DataFrame(tabs)
    output_file = "chrome_tabs_export.xlsx"

    # Create a new Excel workbook
    df.to_excel(output_file, index=False)
    print(f"Successfully exported {len(tabs)} tabs to {output_file}")

    return output_file

# Run the export
if __name__ == "__main__":
    export_tabs_to_excel(tabs_data)

Testing Strategy

Phase 3: Publish and Optimize for Discovery

Publishing is where many developers fail. A generic listing won’t get you users.

The Chrome Web Store (CWS) Listing

Title: Include your primary keyword (e.g., "AI Tab Manager for Chrome").
Description: Write a compelling narrative focusing on the problem you solve, not just features.
Visuals: Use high-quality screenshots and a short demo video. Videos showcasing "Top 5 Extensions for Productivity" consistently attract thousands of views.
Keywords: Optimize for terms like "Google Chrome extensions and AI" to rank higher in search.

Phase 4: Monetize Strategically

Don’t monetize until you have 2,000+ users and strong retention. Premature monetization kills growth.

Top Monetization Models for 2025

Model	How It Works	Best For
Freemium	Basic features free; premium features paid	Productivity, AI tools
Lifetime Pricing	One-time fee for unlimited access	Niche utilities, B2B
Subscription	Monthly/yearly recurring fee	SaaS-like tools, data-heavy apps
Affiliate Marketing	Embed affiliate links in the UI	Shopping, deal-finding extensions
Ads/Sponsorships	Non-intrusive ads in the interface	High-traffic, free tools

Phase 5: Scale and Compound Revenue

Your Action Plan for Today

You don’t need months to start. Here’s what to do today:

List 10 ideas based on your own needs or frustrations.
Research competition for each in the Chrome Web Store.
Score ideas using validation data (manual or via tools like NicheCheck).
Select your top idea based on the opportunity score.
Document your target user and core value proposition.

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

Python Typing: Advanced Type Hints and Generics

qing — Fri, 31 Jul 2026 12:00:50 +0000

Python Typing: Advanced Type Hints and Generics

tags: python, typing, tutorial, advanced

tags: python, typing, tutorial, programming

You’ve probably written code that says, “If it has a .quack() method, I don’t care what it is.” That’s duck typing in action—Python’s love of behavior over class names. But traditional duck typing leaves type checkers like mypy scratching their heads. Enter Python Protocols: the tool that gives you duck typing with static type safety.

Protocols let you define a shape of behavior without forcing inheritance. If your object has the right methods and attributes, it’s an instance of the protocol—even if it’s from a completely unrelated class. This is structural subtyping, or “static duck typing,” and it’s a game-changer for clean, flexible, and type-safe Python code.

Why Duck Typing Needs a Type Check

Duck typing is powerful. You can pass any object to a function that expects a .read() method, and Python will happily call it. But here’s the catch:

def process(reader):
    return reader.read()

process("not a reader")  # Runtime error!

Type checkers can’t verify this until you run the code. That’s where Protocols step in. They let you say, “I expect anything with a .read() method that returns a string,” and mypy will catch mistakes before you run anything.

What Is a Protocol?

A Protocol is a special base class from the typing module that describes a contract of methods and attributes. It’s not enforced at runtime (unless you decorate it with @runtime_checkable), but it’s fully respected by static type checkers.

Here’s the core idea:

If an object has the required methods/attributes, it satisfies the protocol.

No inheritance. No base class drama. Just behavior.

Building Your First Protocol

Let’s say you’re working with different data sources: files, APIs, and in-memory buffers. They all have a .read() method, but they’re unrelated classes. Without protocols, you’d either:

Force them to inherit from a common base (awkward), or
Use duck typing and hope type checkers don’t complain.

With protocols, you define the shape once:

from typing import Protocol

class Readable(Protocol):
    def read(self) -> str:
        ...

def process_source(source: Readable) -> None:
    data = source.read()
    print(f"Read {len(data)} characters")

class FileSource:
    def read(self) -> str:
        return "file content"

class ApiSource:
    def read(self) -> str:
        return "api response"

process_source(FileSource())  # ✅ mypy happy
process_source(ApiSource())   # ✅ mypy happy

Both FileSource and ApiSource satisfy Readable because they implement .read() returning a string. No inheritance. No shared base. Just behavior.

Adding Attributes and Multiple Methods

Protocols aren’t limited to methods. You can also specify attributes:

from typing import Protocol

class Configurable(Protocol):
    name: str
    timeout: int
    def load(self) -> dict:
        ...

class MyConfig:
    name = "app"
    timeout = 30
    def load(self) -> dict:
        return {"setting": "value"}

def apply_config(cfg: Configurable) -> None:
    print(f"Loading {cfg.name} with {cfg.timeout}s timeout")
    data = cfg.load()
    print(data)

apply_config(MyConfig())  # ✅

Now MyConfig must have name, timeout, and load(). If it misses any, mypy will flag it.

When to Use Protocols (and When Not To)

Use protocols when:

You want duck typing but with static type safety.
Your classes are unrelated but share behavior.
You’re defining function parameters or generic constraints based on shape, not class.

Don’t use protocols when:

You need runtime enforcement (unless you use @runtime_checkable, which has caveats).
You’re already using a shared base class and inheritance suits your design.
You’re writing simple scripts where type checking isn’t critical.

Making Protocols Runtime-Checkable (Optional)

By default, isinstance(obj, Protocol) always fails. But if you really need runtime checks:

from typing import Protocol, runtime_checkable

@runtime_checkable
class Runnable(Protocol):
    def run(self) -> None:
        ...

class Task:
    def run(self) -> None:
        print("Running...")

if isinstance(Task(), Runnable):
    print("It's runnable!")  # ✅

⚠️ Warning: @runtime_checkable only checks for the presence of methods/attributes, not their types or signatures. It’s a last resort, not a replacement for static checking.

Practical Tip: Use Protocols for Plugin Systems

One of the most powerful uses of protocols is plugin architecture. You define a protocol for what a plugin must do, and any class that matches becomes a valid plugin:

from typing import Protocol

class Plugin(Protocol):
    name: str
    def execute(self) -> None:
        ...

class LoggingPlugin:
    name = "logger"
    def execute(self) -> None:
        print("Logging...")

class MonitoringPlugin:
    name = "monitor"
    def execute(self) -> None:
        print("Monitoring...")

def run_plugin(p: Plugin) -> None:
    print(f"Running {p.name}")
    p.execute()

run_plugin(LoggingPlugin())
run_plugin(MonitoringPlugin())

Now you can add new plugins without touching the core system. Just implement Plugin, and you’re in.

Start Using Protocols Today

You don’t need to rewrite your entire codebase. Try this:

Find a function that accepts “anything with a .save() method.”
Define a Saveable protocol.
Add it as the type hint.
Run mypy and see what it catches.

from typing import Protocol

class Saveable(Protocol):
    def save(self, path: str) -> bool:
        ...

def backup(obj: Saveable, path: str) -> None:
    if obj.save(path):
        print("Backup complete!")

You’ll get immediate feedback on missing or mismatched methods. That’s the power of static duck typing.

Wrap Up

Protocols give you the flexibility of duck typing with the safety of static types. They let you write code that’s polymorphic by behavior, not by inheritance. And they’re already in your typing module—no extra installs needed.

So next time you’re tempted to say, “It’s duck-typed, I’ll just check at runtime,” stop. Define a protocol instead. Your future self (and your type checker) will thank you.

Try it now: Pick one function in your code that uses duck typing, define a protocol for it, and add the type hint. Run mypy. See what you find.

Share your protocol wins (or fails) in the comments—I’d love to see what you build with them!

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

Build a Database Migration Tool with Python

qing — Fri, 31 Jul 2026 12:00:09 +0000

Build a Database Migration Tool with Python

tags: python, database, devops, tutorial

tags: python, automation, tools, tutorial

Build a File Sync Tool with Python and Watchdog

Imagine you’re working on a project where you constantly edit files in one folder, but you need those changes instantly reflected in another location—maybe a backup drive, a cloud staging folder, or a deployment directory. Doing this manually is tedious, and relying on cron jobs introduces lag. What if you could build a tool that watches for changes and syncs them in real time? That’s exactly what we’re going to do today using Python and the powerful watchdog library.

Why Watchdog?

watchdog is a cross-platform Python library that lets you monitor file system events—like file creation, modification, and deletion—and trigger custom actions in response [1][8]. Unlike polling-based solutions, it’s event-driven, meaning it reacts immediately when a change happens. This makes it perfect for building real-time sync tools, automated testers, or even live documentation generators.

What You’ll Build

By the end of this post, you’ll have a working file sync tool that:

Watches a source directory for changes
Automatically copies new or modified files to a destination directory
Deletes files in the destination if they’re removed from the source
Runs continuously without blocking your main workflow

And yes, you can use this today to automate your own workflows.

Step 1: Set Up Your Environment

First, make sure you have Python 3 installed. Then, install watchdog:

pip install watchdog

You’ll also need Python’s built-in os and shutil modules for file operations, so no extra installs there [2][4].

Create a project folder and set up two directories: one for your source files and one for the synced destination.

mkdir file_sync_demo
cd file_sync_demo
mkdir source destination

Step 2: Build the Event Handler

The core of watchdog is the event handler—a class that defines what to do when specific file system events occur. We’ll create a custom handler that inherits from FileSystemEventHandler and overrides methods like on_created, on_modified, and on_deleted.

Here’s the full working code:

import os
import shutil
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler

class SyncHandler(FileSystemEventHandler):
    def __init__(self, source_dir, dest_dir):
        self.source_dir = source_dir
        self.dest_dir = dest_dir

    def on_created(self, event):
        if event.is_directory:
            return
        self.sync_file(event.src_path)

    def on_modified(self, event):
        if event.is_directory:
            return
        self.sync_file(event.src_path)

    def on_deleted(self, event):
        if event.is_directory:
            return
        dest_path = os.path.join(self.dest_dir, os.path.basename(event.src_path))
        if os.path.exists(dest_path):
            os.remove(dest_path)
            print(f"Deleted: {dest_path}")

    def sync_file(self, src_path):
        filename = os.path.basename(src_path)
        dest_path = os.path.join(self.dest_dir, filename)
        shutil.copy2(src_path, dest_path)
        print(f"Synced: {filename}")

if __name__ == "__main__":
    source = "source"
    destination = "destination"

    handler = SyncHandler(source, destination)
    observer = Observer()
    observer.schedule(handler, source, recursive=False)
    observer.start()

    print(f"Watching '{source}' for changes. Syncing to '{destination}'...")
    try:
        while True:
            pass
    except KeyboardInterrupt:
        observer.stop()
    observer.join()

Save this as sync.py in your project folder [2][8].

Step 3: How It Works

Let’s break down the key parts:

SyncHandler: Our custom event handler. It stores the source and destination paths and defines behavior for each event type.
on_created / on_modified: Both trigger the same sync_file method, which copies the file using shutil.copy2 (this preserves metadata like timestamps).
on_deleted: Removes the corresponding file from the destination if it exists.
Observer: The engine that watches the directory. We schedule it to watch the source folder with recursive=False to avoid watching subdirectories [3][7].
observer.start(): Begins monitoring in a background thread, so your script doesn’t block [7].

Step 4: Test It Out

Now, let’s see it in action.

Run the script:

   python sync.py

In another terminal, navigate to the source folder and create a file:

   cd source
   echo "Hello, sync!" > test.txt

Watch the output: you should see Synced: test.txt.
Check the destination folder—you’ll find test.txt there, identical to the source.

Try editing test.txt, moving it, or deleting it. The tool will react instantly [2].

Practical Tips & Enhancements

This is a minimal but functional sync tool. Here are a few ways to level it up:

Filter by file type: Add a patterns argument to observer.schedule() to watch only .txt or .py files [9].
Add logging: Use Python’s logging module instead of print() for production-ready output [4].
Handle race conditions: If a file is being written, on_modified might fire multiple times. You can add a small delay or check file size stability before syncing.
Make it recursive: Set recursive=True in schedule() if you want to sync subdirectories too [3].
Add CLI args: Use argparse to let users specify source/dest paths at runtime [1].

Why This Matters

Real-time file sync isn’t just convenient—it’s essential for modern development workflows. Whether you’re syncing config files to a server, mirroring assets for a website, or backing up critical data, having a lightweight, scriptable tool gives you full control without relying on third-party services.

And because it’s built in Python, you can extend it endlessly: add email notifications, integrate with cloud APIs, or even turn it into a web service.

Your Turn

Grab the code above, run it, and tweak it for your own needs. Try syncing a folder of your project files, or automate a backup for your documents. Once you see it working, you’ll never go back to manual copying.

If you build something cool with this, share it on Dev.to or tag me in your post. And if you hit any bugs or have ideas for improvements, drop a comment—let’s keep building better tools together.

Ready to sync? Run python sync.py and watch your files move in real time.

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.

How to Earn $3000/Month with Technical Consulting

qing — Fri, 31 Jul 2026 12:00:04 +0000

How to Earn $3000/Month with Technical Consulting

tags: freelance, money, career, consulting

tags: python, automation, money, freelance

$500/month from Python automation is not about building a “million-dollar app.” It’s about finding one repetitive business task, automating it reliably, and charging enough that a few clients or a small product hit your monthly target.

The fastest path: sell time savings, not code

If you want money quickly, don’t start with “what can I build?” Start with “what do people do manually every week that wastes time?” That framing is the core of Python automation as a side income model: businesses pay for saved labor, fewer mistakes, and faster turnaround. Practical opportunities include bots, scrapers, data cleanup scripts, report generators, and workflow automations.[2][3][6]

A realistic way to hit $500/month is one of these setups:

5 clients at $100/month for a small recurring automation
2 clients at $250/month for a higher-value workflow
1 setup fee of $500–$1,500 plus ongoing support or hosting
A small digital product sold to a narrow niche, such as a scraper, report generator, or template bundle[3][6]

The key is choosing work that is boring enough to be valuable and small enough to finish fast.

What to automate first

1) Repetitive data collection

Many businesses still copy-paste information from websites, spreadsheets, or dashboards. Python can automate scraping, crawling, and periodic data collection, then package the results into something useful like a spreadsheet, dashboard, or alert.[1][6]

Good targets:

Competitor price tracking
Lead lists from public directories
Real estate listings
Job boards
Product catalog monitoring

One YouTube example explicitly suggests building a web crawler that repeatedly collects data from specific pages and selling the resulting datasets or analysis to niche customers.[1] That’s a strong model because the value is not the script itself; it’s the ongoing data stream.

2) Report generation

A lot of people spend hours every week pulling numbers from different tools and formatting the same report. Python can take raw CSV files, APIs, or exports and turn them into clean weekly summaries.

Good targets:

Sales summaries
Inventory reports
Marketing performance reports
Finance reconciliations
Client status updates

This is easy to sell because it saves a visible chunk of time every single week.

3) Internal workflow automation

This is the classic “I pay you because my team hates doing this manually” use case. Python can rename files, move data between systems, send emails, schedule tasks, and trigger actions based on events.[2][6]

Good targets:

Email parsing and auto-tagging
Invoice processing
Form submission handling
File organization
Lead routing

A simple script you can sell today

Here’s a small but genuinely useful Python automation: monitor a webpage for changes and notify yourself when something updates. This can be adapted for price tracking, listing alerts, or content monitoring.

import hashlib
import time
from pathlib import Path

import requests

URL = "https://example.com"
CHECK_EVERY_SECONDS = 300
STATE_FILE = Path("page_hash.txt")


def get_page_hash(url: str) -> str:
    response = requests.get(url, timeout=15)
    response.raise_for_status()
    content = response.text.encode("utf-8")
    return hashlib.sha256(content).hexdigest()


def load_previous_hash() -> str | None:
    if STATE_FILE.exists():
        return STATE_FILE.read_text().strip()
    return None


def save_hash(page_hash: str) -> None:
    STATE_FILE.write_text(page_hash)


def main():
    previous_hash = load_previous_hash()

    while True:
        try:
            current_hash = get_page_hash(URL)

            if previous_hash and current_hash != previous_hash:
                print(f"Change detected on {URL}!")
            else:
                print(f"No change detected for {URL}.")

            save_hash(current_hash)
            previous_hash = current_hash

        except Exception as e:
            print(f"Error: {e}")

        time.sleep(CHECK_EVERY_SECONDS)


if __name__ == "__main__":
    main()

Why this matters commercially:

A local business can use it to watch competitors
A recruiter can track job posts
A vendor can monitor product availability
A marketer can monitor landing pages for changes

You can package this into a paid service by adding:

email alerts
CSV exports
a simple dashboard
scheduling with Docker or cron
deployment support

That turns a small script into a service worth charging for.

How to find your first paying customer

Start with people who already hate the manual work

The easiest clients are usually not “tech companies.” They are office managers, accountants, operations staff, recruiters, marketers, and small business owners who repeat the same task every day.[3][8]

Ask three simple questions:

What do you do manually every week?
What takes longer than it should?
What breaks when someone forgets it?

If they answer quickly, you may have a paid automation opportunity.

Offer a narrow, fixed-scope service

Don’t pitch “custom software.” Pitch one outcome.

Examples:

“I’ll automate your weekly competitor price report.”
“I’ll build a script that cleans and formats your CSV exports.”
“I’ll set up an alert when a listing changes.”
“I’ll move form submissions into your spreadsheet automatically.”

Side-income guides for Python developers repeatedly emphasize selling scoped deliverables rather than vague hourly work, because clients understand the value faster and you can close quicker.[3][4]

How to price it to reach $500/month

A lot of beginners undercharge because they price the script instead of the outcome. That’s backwards.

A good simple pricing structure:

Setup fee: $150–$500 for a basic automation
Monthly support: $50–$200 for monitoring, fixes, and updates
Premium tier: $250+ if the automation saves real business time or drives revenue

You do not need many customers. Two clients paying $250/month each gets you to the goal.

If you want to sell a product instead of services, you can also turn a script into a downloadable tool and sell it on platforms like Gumroad or similar marketplaces, which is a model recommended in Python side-income guides.[3]

Build once, sell many times

The most scalable strategy is to reuse the same automation pattern across multiple niches.

For example, a website change monitor can become:

a real estate monitor
a job alert monitor
a price tracker
a content monitoring tool

A report generator can become:

a payroll summary tool
a sales reporting tool
a marketing KPI tool
a client status dashboard

This is how you avoid building from scratch every time. You create one core system, then customize the input source, output format, and alerting layer.

What to do this week

If you want action, not theory, do this in the next 7 days:

Pick one repetitive task from your own life or a business you know
Build a tiny automation that solves only that one problem
Add logging, error handling, and clear output
Create a one-page demo with screenshots or a short video
Send it to 10 potential users and ask if they want it customized
Offer a fixed-price setup, not vague consulting

That is enough to start.

The real goal is not “make money with Python.” It’s to become the person who removes annoying work from someone else’s day. Once you can do that reliably, $500/month is a small target, not a big one. Pick one boring problem, automate it this week, and put it in front of real people.

If you found this helpful, consider buying me a coffee ☕ — it keeps these articles coming!

Also check out my AI tools collection: AI 次元世界 — free AI tools for developers.