apache-airflow-providers-common-messaging

v2.0.3 safe
3.0
Low Risk

Provider package apache-airflow-providers-common-messaging for Apache Airflow

🤖 AI Analysis

Final verdict: SAFE

The package is considered safe as it shows no signs of network calls, shell executions, or credential harvesting. The obfuscation and metadata risks are low and do not suggest any malicious activities.

  • Low network and shell execution risks
  • No evidence of credential harvesting
Per-check LLM notes
  • Network: No network calls detected, which is normal for a library focused on common messaging abstractions.
  • Shell: No shell executions detected, aligning with the expected behavior of a non-executable library.
  • Obfuscation: The observed pattern is likely used for extending package paths and not indicative of malicious activity.
  • Credentials: No credential harvesting patterns detected.
  • Metadata: The package contains a non-secure external link and has an author with incomplete information, but no clear signs of malicious intent.

📦 Package Quality Overall: Medium (7.4/10)

✦ High Test Suite 9.0

Test suite present — 8 test file(s) found

  • Test runner config found: conftest.py
  • 8 test file(s) detected (e.g. conftest.py)
✦ High Documentation 9.0

Well-documented package

  • Documentation URL: "Documentation" -> https://airflow.apache.org/docs/apache-airflow-providers-com
  • 1 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (2635 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

  • Type checker (mypy / pyright / pytype) referenced in project
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 46 unique contributor(s) across 100 commits in apache/airflow
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • under the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # Licensed to the Apache S
✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: airflow.apache.org>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://www.apache.org/licenses/LICENSE-2.0
✓ Git Repository History

Repository apache/airflow appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 apache-airflow-providers-common-messaging 
Develop a small, yet comprehensive project using the 'apache-airflow-providers-common-messaging' package in conjunction with Apache Airflow. This project will serve as a messaging workflow orchestrator, designed to streamline communication between various services within a microservices architecture. Your goal is to create a robust system capable of handling real-time message passing, ensuring that messages are not only delivered but also tracked for successful processing.

**Project Overview:**
Your application will consist of three main components:
1. A producer service that generates messages based on certain triggers or events.
2. An Airflow DAG (Directed Acyclic Graph) that acts as the orchestrator, managing the flow of messages through different services.
3. Consumer services that receive messages from the DAG and process them according to predefined rules.

**Core Features to Implement:**
- **Message Generation:** The producer service should be able to generate messages based on user-defined parameters or external events (e.g., time-based, event-driven).
- **Orchestration with Airflow:** Utilize the 'apache-airflow-providers-common-messaging' package to set up tasks in your DAG that represent each step in the message passing process. These tasks could include sending messages to specific services, waiting for acknowledgments, retrying failed operations, etc.
- **Consumer Processing:** Each consumer service must be capable of receiving messages from the DAG, processing them according to its own logic, and then either acknowledging receipt or signaling failure.
- **Monitoring & Logging:** Implement a logging mechanism within your DAG to monitor the status of each message as it passes through the system. Logs should capture when a message was sent, received, processed, and any errors encountered during these processes.

**How to Use 'apache-airflow-providers-common-messaging':**
This package provides operators and hooks that enable seamless integration with messaging systems like Kafka, RabbitMQ, etc., which are commonly used in microservice architectures. Use these tools to define tasks in your DAG that correspond to sending and receiving messages. For instance, you might use a KafkaHook to send messages to a Kafka topic and a corresponding task to listen for incoming messages from another topic. Ensure that your implementation allows for flexibility in configuring which messaging system to use, making your application more versatile.

By completing this project, you'll gain hands-on experience with Apache Airflow and the 'apache-airflow-providers-common-messaging' package, while also building a practical tool that can be applied in real-world scenarios involving complex workflows and microservices.

💬 Discussion Feed

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