atoti-server-storage-gcp

v0.9.15 safe
3.0
Low Risk

Resources to load data from Google Cloud Storage

⚠ Tarball exceeded 25 MB — source code analysis was limited to package metadata only.

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network calls, shell executions, obfuscations, or credential harvesting attempts. The metadata risk slightly increases due to the maintainer having only one package, but this alone is insufficient to conclude malicious intent.

  • No network calls detected.
  • Single package maintained by the author.
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, which may indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (3.4/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

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

  • Classifier: Typing :: Typed
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in atoti/atoti
  • Two distinct contributors found

🔬 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: activeviam.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository atoti/atoti appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ActiveViam" 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 atoti-server-storage-gcp 
Create a mini-application called 'DataStreamer' which is designed to streamline the process of loading and analyzing datasets stored in Google Cloud Storage (GCS). This application will utilize the 'atoti-server-storage-gcp' Python package to efficiently manage data retrieval and storage operations from GCS buckets. Your task is to develop a user-friendly interface that allows users to specify a GCS bucket and file path, download the dataset, perform basic exploratory data analysis (EDA), and visualize key insights directly within the app.

The application should include the following features:
- User Interface: A simple web-based UI built using Flask or Streamlit where users can input their GCS credentials and specify the bucket name and file path.
- Data Retrieval: Use 'atoti-server-storage-gcp' to securely connect to the specified GCS bucket, download the dataset, and handle any authentication and authorization processes required for accessing the data.
- Data Analysis: Implement functions to perform EDA such as calculating summary statistics, identifying missing values, and detecting outliers.
- Visualization: Integrate a visualization library like Matplotlib or Seaborn to display key metrics and distributions from the dataset in real-time.
- Reporting: Provide options for users to generate and download reports summarizing the findings from the EDA phase.

Your goal is to create a seamless experience for users who need to quickly access, analyze, and understand their data stored in GCS without needing extensive technical knowledge about data retrieval or cloud storage systems.

💬 Discussion Feed

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