webdev-pitfall-analyzer 2025.12.21133820
This package helps users identify and avoid common pitfalls in web and HTML development by analyzing text-based input—like code snippets, design descriptions, or technical discussions—and returning a
License: MIT
Requires Python: >=3.9

# webdev-pitfall-analyzer
[![PyPI version](https://badge.fury.io/py/webdev-pitfall-analyzer.svg)](https://badge.fury.io/py/webdev-pitfall-analyzer)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
[![Downloads](https://static.pepy.tech/badge/webdev-pitfall-analyzer)](https://pepy.tech/project/webdev-pitfall-analyzer)
[![LinkedIn](https://img.shields.io/badge/LinkedIn-blue)](https://www.linkedin.com/in/eugene-evstafev-716669181/)


**webdev-pitfall-analyzer** helps developers quickly spot common web‑development pitfalls—security issues, accessibility problems, performance bottlenecks, outdated patterns, and more—by analysing short text inputs such as code snippets, design questions, or discussion fragments. The package uses an LLM (by default **ChatLLM7** from `langchain_llm7`) to return a concise, structured list of warnings and best‑practice recommendations.

---

## 📦 Installation

```bash
pip install webdev_pitfall_analyzer
```

---

## 🚀 Quick start

```python
from webdev_pitfall_analyzer import webdev_pitfall_analyzer

# Example HTML/JS snippet
snippet = """
<input type="text" onblur="doBadThing()" />
<script>
  function doBadThing() {
    eval(userInput);   // <- unsafe!
  }
</script>
"""

warnings = webdev_pitfall_analyzer(user_input=snippet)
print(warnings)
```

**Output (example)**

```
[
  "⚠️ Use of `eval` can lead to XSS vulnerabilities. Consider safer alternatives.",
  "⚠️ Missing `label` element for the input; this hurts accessibility.",
  "⚠️ Inline event handlers (`onblur`) are discouraged; attach listeners via JavaScript instead."
]
```

---

## 🛠️ Function signature

```python
def webdev_pitfall_analyzer(
    user_input: str,
    api_key: Optional[str] = None,
    llm: Optional[BaseChatModel] = None,
) -> List[str]:
```

| Parameter | Type | Description |
|-----------|------|-------------|
| `user_input` | `str` | The text (code, question, description, etc.) you want analysed. |
| `api_key` | `Optional[str]` | API key for **ChatLLM7**. If omitted, the function will look for the `LLM7_API_KEY` environment variable; if still not found it falls back to an unauthenticated request (may be rate‑limited). |
| `llm` | `Optional[BaseChatModel]` | Any LangChain‑compatible LLM instance. If not supplied, the default `ChatLLM7` (from `langchain_llm7`) is used. |

The function returns a list of warning/recommendation strings. If the underlying LLM call fails, a `RuntimeError` is raised.

---

## 🔧 Using a custom LLM

You can pass any LangChain chat model that follows the `BaseChatModel` interface.

### OpenAI

```python
from langchain_openai import ChatOpenAI
from webdev_pitfall_analyzer import webdev_pitfall_analyzer

my_llm = ChatOpenAI(model="gpt-4o-mini")
result = webdev_pitfall_analyzer(user_input="...", llm=my_llm)
```

### Anthropic

```python
from langchain_anthropic import ChatAnthropic
from webdev_pitfall_analyzer import webdev_pitfall_analyzer

my_llm = ChatAnthropic(model="claude-3-haiku-20240307")
result = webdev_pitfall_analyzer(user_input="...", llm=my_llm)
```

### Google GenAI

```python
from langchain_google_genai import ChatGoogleGenerativeAI
from webdev_pitfall_analyzer import webdev_pitfall_analyzer

my_llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash")
result = webdev_pitfall_analyzer(user_input="...", llm=my_llm)
```

---

## 🔑 API key for ChatLLM7

*The default free tier of LLM7 is sufficient for most occasional analyses.*

- Set the key once in your environment:

```bash
export LLM7_API_KEY="your_llm7_key"
```

- Or pass it directly:

```python
result = webdev_pitfall_analyzer(user_input="...", api_key="your_llm7_key")
```

Obtain a free key by registering at <https://token.llm7.io/>.

---

## 📚 What the analyzer looks for

- **Security** – unsafe functions (`eval`, `innerHTML`, etc.), injection risks.
- **Accessibility** – missing ARIA attributes, improper heading structure, unlabeled form controls.
- **Performance** – blocking synchronous XHR, large inline assets, unnecessary reflows.
- **Modern best practices** – deprecated APIs, outdated HTML5 elements, inefficient CSS selectors.

The underlying prompt (`human_prompt`, `system_prompt`) can be customised by forking the repository.

---

## 📂 Repository

🛠️ Issues & feature requests: <https://github.com/chigwell/webdev_pitfall_analyzer/issues>

---

## 👤 Author

**Eugene Evstafev**  
Email: <hi@eugene.plus>  
GitHub: <https://github.com/chigwell>

---

## 📄 License

This project is licensed under the **MIT License**. See the `LICENSE` file for details.