AI Analysis
The package shows no signs of malicious activity with low risks across all categories. The metadata risk is slightly elevated due to the maintainer's single package, but there are no other red flags.
- No network or shell risks detected
- Low metadata risk with only one package maintained
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communications.
- Shell: No shell execution patterns detected, indicating no immediate risk of executing system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which may indicate a new or less active account, but no other suspicious activities were detected.
Package Quality Overall: Low (3.4/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (4588 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Limited contributor diversity
2 unique contributor(s) across 99 commits in AlvaroCavalcante/airflow-calendar-pluginTwo distinct contributors found
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com
All external links appear legitimate
Repository AlvaroCavalcante/airflow-calendar-plugin appears legitimate
1 maintainer concern(s) found
Author "Alvaro Carneiro" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a fully functional mini-application that integrates the 'airflow-calendar' package to visualize and manage DAG schedules within Apache Airflow in a more interactive and user-friendly way. Your application should allow users to: 1. View a comprehensive calendar view of all DAGs and their scheduled tasks. 2. Filter and search through DAGs based on various criteria such as owner, last execution date, and status. 3. Highlight critical information such as upcoming DAG runs, failed executions, and overdue tasks. 4. Provide an overview of each DAG's schedule intervals and execution times. 5. Allow users to interactively adjust DAG schedules directly from the calendar interface. 6. Offer a feature to generate reports or summaries of the DAG activity over a selected time period. 7. Integrate with Apache Airflow's API to fetch real-time data about DAGs and their executions. 8. Ensure the application is responsive and accessible on both desktop and mobile devices. Utilize the 'airflow-calendar' package to create an engaging and modern calendar interface. This package should be leveraged to display the DAG schedules in a visually appealing manner, allowing users to easily navigate through different dates and view detailed information about each DAG run. Additionally, consider incorporating interactive elements such as tooltips, hover effects, and clickable events to enhance user experience.
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