atmchile

v0.3.1 suspicious
5.0
Medium Risk

Python library to obtain climate and air quality data from monitoring stations in Chile

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate risk level due to the high shell risk and incomplete maintainer profile. These factors suggest potential vulnerabilities or malicious intent.

  • High shell risk due to executing shell commands based on user input.
  • Incomplete maintainer profile indicating possible lack of accountability.
Per-check LLM notes
  • Network: Network calls to external URLs are common but should be reviewed to ensure they align with the package's intended functionality.
  • Shell: Executing shell commands based on user input is risky and could indicate potential for unauthorized command execution, suggesting higher risk.
  • 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 seems to be new or inactive, which could indicate potential risk.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 7 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (7371 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

  • 173 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 67 commits in maigonzalezh/py-atmchile
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • l) response = requests.get(url, timeout=30) response.raise_for_status()
  • y: response = requests.get(url, timeout=30) response.raise_for_status()
  • ) try: response = requests.get(SINCA_STATIONS_URL, timeout=30) response.raise_for_s
  • eachable.""" try: requests.get(SINCA_CGI_PROBE, timeout=15) except requests.RequestExce
  • eachable.""" try: requests.get(SINCA_STATIONS_PROBE, timeout=10) except requests.Reques
  • eachable.""" try: requests.get(DMC_PROBE, timeout=15) except requests.RequestException:
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • ] + sys.argv[1:] sys.exit(subprocess.run(cmd).returncode) from __future__ import annotations from i
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository maigonzalezh/py-atmchile 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 atmchile 
Create a comprehensive Python-based desktop application that serves as a user-friendly dashboard for monitoring real-time climate and air quality conditions across various regions in Chile. This application will utilize the 'atmchile' Python package to fetch live data from monitoring stations. Here’s a detailed breakdown of the requirements and features:

1. **User Interface**: Design an intuitive GUI using libraries such as PyQt5 or Tkinter. The interface should display multiple panels for different types of data and locations.
2. **Data Fetching**: Implement functionality to automatically pull data from 'atmchile'. This includes temperature, humidity, air pressure, CO2 levels, particulate matter (PM2.5, PM10), and other relevant air quality metrics.
3. **Location Selection**: Allow users to select specific cities or regions within Chile to monitor their local conditions. Provide a dropdown menu or search bar for easy location selection.
4. **Real-Time Updates**: Ensure that the application updates data every 5 minutes or as frequently as possible based on the API limits provided by 'atmchile'.
5. **Data Visualization**: Integrate charts or graphs to visually represent trends over time. Use libraries like Matplotlib or Plotly to create dynamic visualizations of historical and current data.
6. **Alert System**: Implement an alert system that notifies users via email or push notifications when certain thresholds are exceeded for any monitored parameters (e.g., PM2.5 levels above a specified limit).
7. **Data Export**: Enable users to export data in CSV or Excel format for further analysis or record-keeping.
8. **User Accounts**: Optional feature - allow users to create accounts where they can save their preferred locations and settings. Use SQLite for local database storage.
9. **Help and Documentation**: Include a help section within the application that provides information about the monitored parameters, units of measurement, and how to interpret the data.

To achieve these goals, you will need to install and import the 'atmchile' package at the beginning of your Python scripts. Use its functions to query the latest data from the Chilean monitoring stations and integrate this into your application logic.

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