AI Analysis
The package shows low risk indicators across all categories, with no evidence of malicious activities or supply-chain attacks.
- Low network and obfuscation risks due to standard practices.
- No shell execution or credential harvesting attempts detected.
Per-check LLM notes
- Network: The network calls detected are expected as the package uses FTP for file transfers, which is a standard function for an FTP provider.
- Shell: No shell execution patterns were detected in the provided code snippet.
- Obfuscation: The observed pattern is likely a standard practice for extending module search paths and does not indicate malicious intent.
- Credentials: No patterns indicative of credential harvesting were detected.
- Metadata: The author details are sparse and the license URL is non-secure, but no clear signs of malice.
Package Quality Overall: Medium (7.8/10)
Test suite present — 14 test file(s) found
Test runner config found: conftest.py14 test file(s) detected (e.g. conftest.py)
Well-documented package
Documentation URL: "Documentation" -> https://airflow.apache.org/docs/apache-airflow-providers-ftp1 documentation file(s) (e.g. conf.py)Detailed PyPI description (3877 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
Type checker (mypy / pyright / pytype) referenced in project22 type-annotated function signatures detected in source
Active multi-contributor project
46 unique contributor(s) across 100 commits in apache/airflowActive community — 5 or more distinct contributors
Heuristic Checks
Found 2 network call pattern(s)
: self.conn = ftplib.FTP(encoding=encoding) # nosec: B321 else:: self.conn = ftplib.FTP() # nosec: B321 if params.host:
Found 2 obfuscation pattern(s)
under the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # Licensed to the Apache Sunder the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # # Licensed to the Apache
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: airflow.apache.org>
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://www.apache.org/licenses/LICENSE-2.0
Repository apache/airflow appears legitimate
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Your task is to create a simple yet powerful data transfer utility using Apache Airflow and the 'apache-airflow-providers-ftp' package. This utility will automate the process of transferring files from an FTP server to a local directory on your machine, and vice versa. The application should be capable of scheduling these transfers at specific intervals, allowing for automated backups and data synchronization between the FTP server and your local machine. ### Features: 1. **File Transfer**: Implement both upload and download functionalities to move files between the FTP server and your local machine. 2. **Scheduling**: Use Apache Airflow to schedule these file transfers at regular intervals (e.g., every day at midnight). 3. **Error Handling**: Include robust error handling to manage potential issues such as network errors, authentication failures, and file permission errors. 4. **Logging**: Ensure all actions and any errors are logged for auditing and troubleshooting purposes. 5. **Configuration Management**: Allow users to configure the FTP server details, file paths, and scheduling times through a configuration file or environment variables. ### Utilizing 'apache-airflow-providers-ftp': - **Operator Usage**: Use the `FtpToS3Operator` (or similar operators provided by the package) to facilitate the file transfer operations. Although the operator name suggests S3, you can use it as a reference for FTP operations. - **Connection Management**: Set up an Airflow connection for the FTP server using the provided package's connection types. - **Task Creation**: Create tasks within an Airflow DAG (Directed Acyclic Graph) to represent each file transfer operation. - **Scheduler Integration**: Leverage Airflow's scheduler to automatically run these tasks based on the specified schedule. ### Deliverables: - A complete Airflow DAG that includes at least one task for uploading files from a local directory to an FTP server and another task for downloading files from the FTP server to a local directory. - A configuration file or method to allow users to easily change FTP server details and other settings. - Comprehensive documentation detailing how to set up and run the application, including how to install dependencies and configure the Airflow environment.
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