apache-airflow-providers-dingding

v3.9.4 safe
3.0
Low Risk

Provider package apache-airflow-providers-dingding for Apache Airflow

🤖 AI Analysis

Final verdict: SAFE

The package shows low risks across all assessed categories, indicating it is likely safe for use.

  • Low obfuscation risk
  • No detected credential harvesting
  • Minor metadata issues but not indicative of malicious activity
Per-check LLM notes
  • Obfuscation: The observed pattern is likely part of standard module handling and not malicious obfuscation.
  • Credentials: No credential harvesting patterns detected.
  • Metadata: The package has some minor issues but no clear signs of malicious intent.

📦 Package Quality Overall: Medium (7.8/10)

✦ High Test Suite 9.0

Test suite present — 10 test file(s) found

  • Test runner config found: conftest.py
  • 10 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-din
  • 1 documentation file(s) (e.g. conf.py)
  • Detailed PyPI description (3599 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 4 type-annotated function signatures (partial)
✦ 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 score 1.5

Found 1 network call pattern(s)

  • ngtalk.com" session = requests.Session() if headers: session.headers.update(hea
⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • under the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # Licensed to the Apache S
  • under the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # # Licensed to the Apache
✓ 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-dingding 
Your task is to create a mini-application using Apache Airflow that integrates with DingTalk, a popular enterprise communication platform in China, using the 'apache-airflow-providers-dingding' package. This application will serve as a notification system for your data pipelines, sending alerts via DingTalk when specific tasks are completed or if any issues arise during execution.

Here’s a step-by-step guide on how to build this application:
1. Set up your development environment with Python and Apache Airflow installed. Ensure you have the 'apache-airflow-providers-dingding' package installed as well.
2. Define a simple DAG (Directed Acyclic Graph) in Airflow that includes at least two tasks: one for processing data and another for sending notifications.
3. Use the 'apache-airflow-providers-dingding' package to configure a custom operator that sends messages to DingTalk. Customize this operator to include parameters like message content, DingTalk webhook URL, and recipient user IDs or group IDs.
4. Integrate this custom operator into your DAG so that it triggers after the completion of the data processing task. The message should indicate whether the task was successful or if there were any errors.
5. Extend your application by adding additional features such as logging errors to a file or database, scheduling the DAG to run at regular intervals, or even setting up retries for failed tasks.
6. Test your application thoroughly to ensure that all components work as expected. Verify that messages are sent correctly to DingTalk under various conditions.
7. Document your code and the setup process, including how to install dependencies and run the DAG.

Suggested Features:
- Implement different types of notifications based on the severity of the issue (e.g., informational, warning, critical).
- Allow users to customize the message templates used for notifications.
- Add support for attaching files or links to the DingTalk messages.
- Include an option to send notifications to multiple recipients or groups.
- Enable the configuration of multiple webhooks for redundancy and reliability.

💬 Discussion Feed

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