azure-mgmt-databricks

v2.0.0 safe
2.0
Low Risk

Microsoft Azure Data Bricks Management Client Library for Python

🤖 AI Analysis

Final verdict: SAFE

The package shows very low risk indicators across all categories checked, and there are no signs of malicious activity or supply-chain attacks.

  • No network calls detected
  • No shell execution patterns
  • No obfuscation or credential harvesting attempts
Per-check LLM notes
  • Network: No network calls detected, which is normal for many packages that don't require real-time interaction with external services.
  • Shell: No shell execution patterns detected, which is expected as Python packages typically do not execute system commands unless explicitly designed to do so.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author has only one package, which might indicate a new or less active account, but no other red flags were raised.

📦 Package Quality Overall: Medium (5.0/10)

○ 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 (7426 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

  • Type checker (mypy / pyright / pytype) referenced in project
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 35 unique contributor(s) across 100 commits in Azure/azure-sdk-for-python
  • Active community — 5 or more distinct contributors

🔬 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: microsoft.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Azure/azure-sdk-for-python appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Microsoft Corporation" 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 azure-mgmt-databricks 
Develop a Python-based utility that leverages the 'azure-mgmt-databricks' package to manage Azure Databricks workspaces and resources. This utility should provide functionalities such as creating, updating, and deleting Databricks workspaces, managing access control lists (ACLs), and handling Databricks clusters. Additionally, include features like logging actions performed on the Databricks resources and integrating with Azure Active Directory (AAD) for authentication.

Step 1: Set up your development environment with Python and install necessary packages including 'azure-mgmt-databricks', 'adal' for AAD integration, and 'logging' for tracking actions.

Step 2: Authenticate the utility with Azure using AAD credentials. Implement functions to create, update, and delete Databricks workspaces.

Step 3: Develop functionality to manage ACLs for Databricks workspaces, allowing users to specify permissions for different users and groups.

Step 4: Add features to handle Databricks clusters within the workspace. Users should be able to start, stop, resize, and delete clusters.

Step 5: Integrate logging into the utility to record all operations performed on Databricks resources, ensuring a history of changes is available.

Step 6: Enhance user experience by adding command-line interface (CLI) options and help documentation for each feature provided.

The 'azure-mgmt-databricks' package will be central to this utility, enabling interaction with Azure Databricks services through its comprehensive API. Your task is to design a robust, user-friendly tool that simplifies management of Azure Databricks resources.

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