altimate-datapilot-cli

v0.3.0 safe
2.0
Low Risk

Assistant for Data Teams

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of obfuscation or credential harvesting, and it is released under a permissive MIT license. The installation instructions provided are standard.

  • No obfuscation patterns detected
  • No credential harvesting patterns detected
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.

📦 Package Quality Overall: Medium (6.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_coverage.py)
✦ High Documentation 9.0

Well-documented package

  • Documentation URL: "Changelog" -> https://datapilot.readthedocs.io/en/latest/changelog.html
  • 1 documentation file(s) (e.g. conf.py)
  • Brief PyPI description (793 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

  • 88 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 11 unique contributor(s) across 100 commits in AltimateAI/datapilot-cli
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • url}") response = requests.get(url, headers=headers, params=params, timeout=timeout)
  • l: {url}") response = requests.post(url, headers=headers, json=data, timeout=timeout) se
  • l: {url}") response = requests.put(url, data=data, timeout=timeout) self.logger.debug(f
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • s): print("+", *args) subprocess.check_call(args) def exec_in_env(): env_path = base_path / ".tox"
  • y itself. for line in subprocess.check_output([sys.executable, "-m", "tox", "--listenvs"], universal_newli
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: altimate.ai

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository AltimateAI/datapilot-cli appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Altimate Inc" 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 altimate-datapilot-cli 
Create a data visualization and analysis mini-app using the 'altimate-datapilot-cli' Python package. Your app will serve as a tool for data teams to quickly visualize datasets, perform basic statistical analyses, and generate reports. Here are the steps and features to include:

1. **Setup**: Begin by installing the 'altimate-datapilot-cli' package. Ensure your environment supports Python 3.8 or higher.
2. **Data Import**: Allow users to upload CSV files directly into the app via a simple UI. The app should automatically detect the file format and parse it accordingly.
3. **Data Exploration**: Implement interactive visualizations of the imported data using 'altimate-datapilot-cli'. Include options for bar charts, line graphs, scatter plots, and histograms.
4. **Statistical Analysis**: Provide tools within the app to conduct basic statistical analyses such as mean, median, mode, standard deviation, and correlation coefficients.
5. **Report Generation**: Enable users to create and download PDF reports summarizing their data exploration and analysis findings. These reports should include charts and key statistics.
6. **Customization Options**: Offer customization options for visualizations like color schemes, chart types, and axes labels.
7. **Real-time Updates**: As users interact with the data (e.g., filtering, sorting), ensure the visualizations update in real-time.

Utilize 'altimate-datapilot-cli' to streamline the data processing and visualization workflow. The package's CLI should be integrated into your app to handle tasks such as importing data, generating visualizations, and performing statistical calculations. Additionally, explore how 'altimate-datapilot-cli' can facilitate the creation of dynamic and interactive dashboards for a more engaging user experience.

💬 Discussion Feed

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