apify-client

v3.0.2 safe
3.0
Low Risk

Apify API client for Python

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with no signs of malicious intent. The low scores across all risk categories suggest it is safe to use.

  • No network calls or shell executions detected.
  • Maintainer's profile is incomplete but there are no suspicious activities.
Per-check LLM notes
  • Network: No network calls detected, which is not necessarily suspicious for a client library like apify-client.
  • Shell: No shell execution patterns detected, which is expected and safe.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has an incomplete profile and may be new or inactive, but no other suspicious activities were flagged.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.apify.com/api/client/python/docs/overview/intro
  • Detailed PyPI description (10915 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

  • 466 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 13 unique contributor(s) across 100 commits in apify/apify-client-python
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ 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: apify.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository apify/apify-client-python 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 apify-client 
Create a web scraping utility that leverages the Apify platform for efficient data extraction and storage. This utility will use the 'apify-client' Python package to interact with Apify's services. Here’s a detailed plan on how to build this application:

1. **Project Overview**: Develop a Python-based utility named 'ApifyScraper' that scrapes data from websites and stores it in a structured format using Apify's Actor and Dataset services.

2. **Setup Environment**: Ensure you have Python installed along with the 'apify-client' package. Use pip to install the package if not already installed.

3. **Define Target Websites**: Choose two websites as targets for scraping. One website could be a news site for article titles and dates, and another could be an e-commerce site for product information.

4. **Configure Apify Client**: Initialize the Apify client with your API token to authenticate and access Apify's services.

5. **Design Data Model**: Define the structure of the data to be scraped and stored. For example, for the news site, include fields like 'title', 'date', 'author', etc., and for the e-commerce site, include 'product_name', 'price', 'description', etc.

6. **Implement Scraping Logic**: Write Python functions to scrape the defined data points from the target websites. Utilize Apify's Actor service to run these scraping tasks efficiently.

7. **Data Storage**: Use Apify's Dataset service to store the scraped data. Ensure the data is properly formatted and saved in a readable JSON format within the dataset.

8. **Error Handling & Logging**: Implement error handling mechanisms to manage issues such as network errors or parsing failures. Also, log important actions and errors for debugging purposes.

9. **Testing**: Test the utility thoroughly on different pages of the chosen websites to ensure all functionalities work correctly.

10. **Deployment**: Deploy the utility in a cloud environment or locally, ensuring it runs periodically to keep the datasets updated.

Throughout the development process, utilize the 'apify-client' package to interact with Apify's APIs, manage actors, and handle datasets. This project aims to demonstrate the power and flexibility of the Apify platform combined with Python scripting.

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