appstorescraperpy

v0.1.2 suspicious
4.0
Medium Risk

Apple App Store Scraper written in Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package appears to be a legitimate tool for scraping data from the Apple App Store, but concerns over the metadata and author details suggest potential risks.

  • author has no identifiable information
  • repository has low engagement
Per-check LLM notes
  • Network: The detected network calls are consistent with the package's name and purpose, suggesting it may be scraping data from app stores.
  • Shell: No shell execution patterns were detected.
  • Metadata: The package shows some red flags such as an author with no name or history and a repository with low engagement, but there are no clear signs of typosquatting or other malicious intent.

📦 Package Quality Overall: Low (4.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_main.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (4101 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 5 type-annotated function signatures (partial)
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 8 commits in SpeakingStapler/appstorescraperpy
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • t, ) with requests.Session() as s: s.mount(AppleScraper.__base_request_url
  • y,app_id) result = requests.get(url=avail_url ,headers=headers,
✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 appstorescraperpy 
Create a Python-based application named 'AppRankTracker' that leverages the 'appstorescraperpy' package to monitor and track the ranking changes of specific apps on the Apple App Store over time. This tool will be particularly useful for developers and marketers who want to keep an eye on their app's performance relative to competitors. Here’s a detailed breakdown of what your application should do:

1. **User Interface**: Develop a simple command-line interface (CLI) that allows users to input the name of an app and the frequency of checks they wish to perform (e.g., every hour, daily).
2. **App Search**: Utilize the 'appstorescraperpy' package to search for the specified app by its name. Ensure that the search function can handle multiple pages if necessary.
3. **Ranking Fetch**: Once the correct app is identified, fetch its current ranking from the App Store. Your application should be able to parse this information accurately.
4. **Tracking Mechanism**: Implement a feature that logs the app's rank at each check interval into a local SQLite database. This database should store the date and time of each check alongside the rank.
5. **Visualization**: After collecting data over a period, provide a basic text-based visualization of the app's ranking trend within the CLI. Alternatively, you could export this data to a CSV file for further analysis using external tools like Excel or Google Sheets.
6. **Email Alerts**: Optionally, add functionality to send email alerts when there are significant changes in the app's ranking. This would require integrating an email sending service such as SendGrid or SMTP.
7. **Configuration File**: Allow users to configure settings such as the check interval and email notification preferences through a configuration file (e.g., JSON or YAML).
8. **Error Handling**: Implement robust error handling to manage cases where the app might not be found, network issues occur, or the API limits are hit.
9. **Testing**: Write unit tests for all major components of your application to ensure reliability and maintainability.

By completing this project, you will have built a powerful yet straightforward tool that demonstrates practical use of the 'appstorescraperpy' package while also showcasing your skills in Python programming, data handling, and user interaction.

💬 Discussion Feed

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