AI Analysis
Final verdict: SAFE
The package appears legitimate based on the provided description and requirements. There are no clear indications of malicious intent beyond some obfuscation techniques which are not strongly indicative of malice.
- Unusual obfuscation technique used
- No suspicious patterns for credential harvesting
Per-check LLM notes
- Obfuscation: The obfuscation technique used is unusual and may indicate an attempt to hide version information or dependencies, but without further context, it's unclear if it's malicious.
- Credentials: No suspicious patterns for credential harvesting were detected.
Package Quality Overall: Low (4.4/10)
○ 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 (1207 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 project18 type-annotated function signatures detected in source
◈ Medium
Multiple Contributors
5.0
Limited contributor diversity
1 unique contributor(s) across 100 commits in aliyun/alibabacloud-python-sdkSingle author but highly active (100 commits)
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 2.0
Found 1 obfuscation pattern(s)
bacloud-python-sdk" VERSION = __import__(PACKAGE).__version__ REQUIRES = [ "darabonba-core>=1.0.0, <2.0.0
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: alibabacloud.com
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 aliyun/alibabacloud-python-sdk appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Alibaba Cloud SDK" 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 alibabacloud-modelservice20220614
Develop a weather prediction mini-app using the 'alibabacloud-modelservice20220614' package. This app will leverage machine learning models hosted on Alibaba Cloud to predict weather conditions based on historical data. Here’s a detailed breakdown of what your project should include: 1. **Project Setup**: Initialize a new Python project, install the necessary dependencies including 'alibabacloud-modelservice20220614', and set up your Alibaba Cloud credentials. 2. **Data Collection**: Use APIs from weather services to collect historical weather data for training the model. Ensure you have permission to use this data. 3. **Model Training**: Utilize the 'alibabacloud-modelservice20220614' package to train a machine learning model on the collected data. This involves setting up a model service instance, uploading the training dataset, and configuring the training parameters. 4. **Prediction Interface**: Develop a simple user interface where users can input location and date to get a weather prediction. This could be a command-line interface (CLI) or a basic web interface using Flask or Django. 5. **Real-time Predictions**: Integrate the trained model into the app so it can make real-time predictions based on user inputs. Use the 'alibabacloud-modelservice20220614' package to call the prediction service with the provided data. 6. **Results Display**: Present the predicted weather conditions back to the user in an understandable format, such as temperature, humidity, and expected precipitation. 7. **Documentation and Deployment**: Document your code thoroughly and deploy your application either locally or on a cloud platform like Alibaba Cloud, ensuring it can handle multiple requests concurrently. Suggested Features: - Allow users to compare predictions with actual weather conditions. - Implement error handling for invalid inputs or failed API calls. - Provide visualizations of the predicted weather trends over time. - Offer a feature to save and track past predictions. The 'alibabacloud-modelservice20220614' package is crucial for training and deploying the machine learning model. It allows you to manage the lifecycle of your ML models, from training to inference, all within Alibaba Cloud’s ecosystem.