async-rithmic

v1.6.2 safe
3.0
Low Risk

Python API Integration with Rithmic Protocol Buffer API

🤖 AI Analysis

Final verdict: SAFE

The package is assessed as safe with a low risk score due to the lack of suspicious activities such as shell execution, obfuscation, and credential harvesting. The network and metadata risks are slightly elevated but do not indicate any immediate threat.

  • Low network, shell, obfuscation, and credential risks.
  • Maintainer has only one package, indicating potential newcomer status.
Per-check LLM notes
  • Network: Network calls are expected if the package interacts with external services or APIs.
  • Shell: No shell execution patterns detected, indicating low risk of direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The maintainer has only one package, suggesting they may be new or less active, but no other red flags are present.

📦 Package Quality Overall: Medium (5.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2930 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 33 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 5 unique contributor(s) across 100 commits in rundef/async_rithmic
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • equest = self.request_manager.requests.get(request_id) self.request_manager.mar
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository rundef/async_rithmic appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Mickael Burguet" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with async-rithmic 
Your task is to develop a real-time financial data streaming application using the 'async-rithmic' Python package, which integrates with the Rithmic Protocol Buffer API. This application will allow users to subscribe to various financial markets and receive live market data updates. Here’s a detailed breakdown of the project requirements and steps to complete it:

1. **Project Setup**: Start by setting up your development environment. Ensure you have Python installed and create a virtual environment for your project. Install the 'async-rithmic' package and any other necessary libraries such as `protobuf` for handling protocol buffer messages.

2. **Application Design**: Design your application to include the following components:
   - A main module to handle user interactions and manage subscriptions.
   - Separate modules for each type of market data subscription (e.g., Stocks, Futures, Options).
   - An asynchronous event handler to process incoming data streams.

3. **User Interface**: Implement a simple command-line interface (CLI) for user interaction. Users should be able to:
   - List available market types they can subscribe to.
   - Subscribe to specific market data feeds.
   - View real-time updates of subscribed market data.
   - Unsubscribe from market data feeds.

4. **Market Data Subscription**: Utilize 'async-rithmic' to connect to the Rithmic API and subscribe to real-time market data. For each market type, implement functions to:
   - Authenticate the connection.
   - Request real-time data for specific symbols.
   - Handle authentication and connection errors gracefully.

5. **Data Handling**: Develop robust error handling and logging mechanisms to ensure that your application can recover from network issues and handle unexpected data formats. Use Python's built-in logging library to log important events and errors.

6. **Performance Optimization**: Since the application will be dealing with real-time data, focus on optimizing performance. Use asynchronous programming techniques provided by 'async-rithmic' to ensure the application can handle multiple concurrent data streams efficiently.

7. **Testing**: Write unit tests to verify that your application correctly subscribes to and unsubscribes from market data feeds. Additionally, test the application's ability to handle different types of input and edge cases, such as invalid market symbols or sudden disconnections.

8. **Documentation**: Provide clear documentation explaining how to install and run the application, including setup instructions and examples of how to interact with the CLI.

By the end of this project, you will have a fully functional, real-time financial data streaming application capable of subscribing to and displaying live market data from various financial markets. This project will not only demonstrate your skills in working with asynchronous APIs but also your ability to handle real-world data challenges.

💬 Discussion Feed

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