Skip to main content

A Python package that generates complex Python projects and fixes errors in your code using OpenAI's GPT API.

Project description

ScriptMonkey 🐒

ScriptMonkey is an AI-powered Python package that reimagines how projects are built. It doesn’t just generate simple scripts or templates like traditional LLMs—it creates entire, multi-file, multi-directory projects with fully custom code. Complex Python projects can be generated in seconds based on your natural language descriptions, providing everything you need, from models and routes to templates and configuration files. With ScriptMonkey, you can instantly bootstrap new ideas or start complex projects without the tedious setup. And with built-in error detection and automatic fixes, ScriptMonkey keeps your development process smooth and stress-free, letting you focus on what matters most: building.

Features

  • Custom Project Generation: Create entire Python projects, not just boilerplate code. ScriptMonkey generates the specific files and directories you need based on your description.
  • Lightning-Fast Setup: Complex Python projects can be generated in seconds, saving you time and effort.
  • Automatic Error Detection: Captures errors during runtime.
  • AI-Powered Fixes: Uses OpenAI's GPT API to understand and resolve errors.
  • Code Auto-Correction: Automatically updates your Python files with the fixes.
  • Cross-IDE Compatibility: Works with any IDE or code editor.
  • Context-Aware Q&A: Ask questions directly to ChatGPT with or without providing files for context. Get detailed answers with code examples, explanations, and best practices tailored to your needs.

🚀 Watch the Demo

ScriptMonkey Demo

Click the image above or watch the video directly on YouTube.

Installation

To install ScriptMonkey, simply run:

pip install scriptmonkey

Usage

Project Generation with scriptmonkey

ScriptMonkey can generate a complete, custom-coded project structure based on a description you provide. This feature helps you quickly set up new projects with the necessary files and folders.

How to Use

  1. Run the following command in your terminal:

    scriptmonkey
    
  2. A text editor will open (e.g., nano, vim, or notepad depending on your environment). Follow the on-screen instructions to provide a detailed description of your project.

  3. Save and close the editor. ScriptMonkey will then:

    • Generate a complete project structure based on your description.
    • Create directories, code files, and templates.
    • Automatically generate a README.md with installation instructions and usage details.

Example Project Description Prompt

I need a Flask-based web application for managing a book library. The application should include:
- User authentication (login, registration, password reset).
- Models for Users, Books, and Authors using SQLAlchemy.
- A REST API with routes for adding, updating, and deleting books and authors.
- An admin dashboard for managing users and viewing statistics.
- HTML templates for user login, book list, and book detail views.
- The database should use PostgreSQL.
- Include environment-specific configurations for development and production.

ScriptMonkey will use this description to create a project structure and code files for you in a directory named generated_project.

Context-Aware Q&A with scriptmonkey --ask

ScriptMonkey can help answer your technical questions, whether or not you provide code files for context. This feature allows you to leverage the power of ChatGPT to ask questiona about files, clarify concepts, get code reviews, or understand best practices in various programming languages.

How to Use

  • Ask a question without files:

    scriptmonkey --ask "What are the best practices for database indexing?"
    
  • Ask a question with files:

    scriptmonkey --ask "Can you help me optimize this function?" --files ./path/to/file1.py ./path/to/file2.js
    

    ScriptMonkey will analyze your question and any provided files to give a detailed, markdown-formatted response with explanations and code suggestions, if applicable. This feature is great for in-depth guidance on code optimization, architecture, or general programming questions.

Error Handling with scriptmonkey.run()

ScriptMonkey doesn't just build projects; it also makes debugging a breeze.

  1. Import scriptmonkey in your Python script.
  2. Call scriptmonkey.run() to activate the error handler.
  3. Run your code, and let ScriptMonkey handle any errors that occur.

Example

import scriptmonkey

# Enable ScriptMonkey's error handler
scriptmonkey.run()

# Intentional error for testing
def add(a, b):
    return a + b  # This will fail if b is a string

print(add(2, "3"))  # ScriptMonkey will automatically fix this error and update the file.

Once an error occurs, ScriptMonkey will:

  1. Detect the error.
  2. Send the error and code to OpenAI for analysis.
  3. Provide a solution and automatically update the file with the corrected code.

Setting or Updating Your OpenAI API Key

If you haven't set your OpenAI API key yet or need to update it, you can do so with the following command:

python3 -m scriptmonkey --set-api-key your-api-key

This will store the API key in a config locally and use it for all future interactions with OpenAI.

Requirements

  • Python 3.6 or later
  • An OpenAI API key (follow the steps below if you don't have one)

Obtaining an OpenAI API Key

  1. Go to the OpenAI website: OpenAI Platform
  2. Sign up or log in to your account.
  3. Navigate to the API keys section in your account dashboard.
  4. Create a new API key and copy it.

Configuring the API Key for ScriptMonkey

  • Option 1: Environment Variable
    You can set up your API key as an environment variable:

    export OPENAI_API_KEY='your-api-key'
    
  • Option 2: Entering the API Key When Prompted
    If ScriptMonkey does not find an API key in your environment variables, it will prompt you to enter your key. Once entered, it will save the key to a configuration file for future use.

  • Option 3: Using the --set-api-key Command
    Use the --set-api-key command as shown above to set or update your API key easily.

Let ScriptMonkey take care of your Python errors and project setup so you can focus on building!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scriptmonkey-1.2.1.tar.gz (15.6 kB view details)

Uploaded Source

Built Distribution

scriptmonkey-1.2.1-py3-none-any.whl (19.5 kB view details)

Uploaded Python 3

File details

Details for the file scriptmonkey-1.2.1.tar.gz.

File metadata

  • Download URL: scriptmonkey-1.2.1.tar.gz
  • Upload date:
  • Size: 15.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for scriptmonkey-1.2.1.tar.gz
Algorithm Hash digest
SHA256 a679742928f9325cc173a44d19dd7446665a37e7636a040462d5774b4dde9be8
MD5 e0a34e3593662b805152f275d7b9ea08
BLAKE2b-256 d1c3711980bba04f3bad8a71ed3b3b857bc8978525ced629eb3881a0d62cc1b8

See more details on using hashes here.

File details

Details for the file scriptmonkey-1.2.1-py3-none-any.whl.

File metadata

File hashes

Hashes for scriptmonkey-1.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4e0543d70942656913626edd90e4c77fa16d3fbccb8102a467be77c8316f5ac7
MD5 068a3a798d4457cba95351feb0f5520c
BLAKE2b-256 1deeb52d741b3c077a721a7a95d896f3ba8f67706edefe8b27c0520aaae57cd7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page