arkindex-client

v1.3.0 safe
3.0
Low Risk

API client for the Arkindex project

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all categories with no evidence of malicious activity. The network risk is slightly elevated due to external API calls, but this is common for API client packages.

  • Network risk due to external API calls
  • Single package from maintainer
Per-check LLM notes
  • Network: Network calls to external URLs and APIs are common but need verification of their legitimacy and security practices.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating secure handling of sensitive information.
  • Metadata: The maintainer has only one package, which may indicate a new or less active account, but no other red flags are present.

📦 Package Quality Overall: Low (3.6/10)

✦ High Test Suite 9.0

Test suite present — 8 test file(s) found

  • 8 test file(s) detected (e.g. test_auth.py)
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ 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

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

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • ] self.session = requests.Session() if verify is None: verify = should_ve
  • body=payload) resp = requests.put( url=backend_part["url"], data=data
  • ith the s3 API resp = requests.put(url, data=f, verify=should_verify_cert(url), timeout=REQUEST
✓ 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

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Teklia <[email protected]>" 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 arkindex-client 
Create a financial data analysis tool using the 'arkindex-client' Python package. This tool will allow users to retrieve historical stock prices and other financial metrics from the Arkindex database, perform basic statistical analyses on the retrieved data, and visualize the results. Here are the key steps and features for building this application:

1. **Setup**: Install the necessary Python packages including 'arkindex-client', pandas for data manipulation, and matplotlib/seaborn for data visualization.
2. **Data Retrieval**: Utilize the 'arkindex-client' package to fetch historical stock price data for a user-specified ticker symbol over a specified date range. Ensure the data retrieval process includes handling potential errors such as invalid tickers or missing data periods gracefully.
3. **Data Analysis**: Implement functions to calculate basic statistics on the retrieved data such as mean, median, standard deviation, and more advanced metrics like moving averages.
4. **Visualization**: Create interactive visualizations of the stock price trends and calculated statistics using matplotlib or seaborn. Include options for the user to customize the plots, such as changing colors or selecting specific time frames.
5. **User Interface**: Develop a simple command-line interface (CLI) where users can input their desired stock ticker, date range, and select which analyses and visualizations they want to run. Alternatively, you could explore integrating a web-based UI if you're familiar with frameworks like Flask or Django.
6. **Documentation**: Write clear documentation explaining how to use your tool, including setup instructions, usage examples, and explanations of the available functionalities.

This project will not only demonstrate proficiency in utilizing the 'arkindex-client' package but also showcase skills in data analysis and visualization. It will be a valuable tool for anyone interested in analyzing historical stock performance.

💬 Discussion Feed

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