argentina

v0.2.0 suspicious
5.0
Medium Risk

Herramientas Python para datos públicos argentinos: provincias, departamentos, ciudades, geografía (IGN), economía (INDEC/BCRA), códigos postales, identificadores, EPH y más.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is moderately risky due to its network activity and the lack of a visible git repository, raising concerns about its origin and maintenance.

  • Network calls are made, which could potentially expose users to external risks.
  • The maintainer's git repository is not found, adding uncertainty about the package's development history.
Per-check LLM notes
  • Network: The package makes network calls which are typical for fetching data or updates, but the context and destination URLs should be verified to ensure legitimacy.
  • Shell: No shell execution patterns detected, indicating no immediate risk from this aspect.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
  • Metadata: The maintainer has only one package and the git repository is not found, which raises some concerns but does not definitively indicate malice.

📦 Package Quality Overall: Low (3.2/10)

○ 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 (28438 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

  • 121 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • th.suffix + ".part") with requests.get(url, stream=True, timeout=timeout) as r: r.raise_for
  • "] = end_date response = requests.get(BASE_URL, params=params, timeout=30) response.raise_for_
  • ire_requests() response = requests.get(url, params=params, timeout=timeout) response.raise_for_
  • t = int(anio) response = requests.get( API_URL.format(anio=anio_int), timeout=30,
  • lstrip('/')}" response = requests.get( url, params=params, timeout=timeout
  • return path response = requests.get(url, timeout=300) response.raise_for_status() path.
✓ 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Tobias Yatche" 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 argentina 
Create a Python-based mini-application named 'ArgentinaDataExplorer' that leverages the 'argentina' package to provide users with comprehensive geographical and economic data about Argentina. The application should allow users to explore various aspects of Argentine provinces, cities, and economic indicators interactively through a command-line interface.

Step 1: Set up the project environment. Install the 'argentina' package using pip.

Step 2: Design a user-friendly command-line interface that allows users to select different categories of data they wish to explore (e.g., provinces, cities, economic indicators).

Step 3: Implement functions within the application to fetch and display detailed information on selected categories. For example, when a user selects 'provinces', the application should display a list of all provinces along with their respective capitals, populations, and area sizes.

Step 4: Add advanced features such as filtering options based on specific criteria (e.g., population size, GDP, etc.), sorting functionalities, and the ability to export the displayed data into CSV format.

Step 5: Integrate real-time economic data from INDEC/BCRA, ensuring that the application updates regularly to reflect the latest available figures.

Throughout the development process, utilize the 'argentina' package's core features effectively to ensure accurate and up-to-date information is provided to users. The application should be designed with scalability in mind, allowing for future enhancements and additional data sources.

💬 Discussion Feed

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