AI Analysis
The package shows some network-related risks due to its ability to bypass local environment settings, which may indicate it communicates with external services without clear documentation. However, other risks like shell execution, obfuscation, and credential harvesting are low.
- network risk due to session.trust_env=False
- lack of clear documentation for external service communication
Per-check LLM notes
- Network: The use of session.trust_env=False and specific API calls may indicate the package is designed to bypass local environment settings and communicate with external services, which could be risky if not properly documented.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows some signs of being new or less active, but no clear indicators of malicious intent.
Package Quality Overall: Low (4.2/10)
Partial test coverage signals detected
1 test file(s) detected (e.g. __init__.py)
Some documentation present
Detailed PyPI description (10307 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
46 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Found 2 network call pattern(s)
session = requests.Session() session.trust_env = Falseself): self.session = requests.Session() self.base_url = "https://push2.eastmoney.com/api/q
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://www.numpy.org/
No GitHub repository linked
No GitHub repository link found
1 maintainer concern(s) found
Author "AIShareTxt Team" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
你正在开发一个名为 'StockInsight' 的迷你应用程序，该程序利用了名为 'aishare-txt' 的Python包。这个应用程序的目标是帮助投资者通过分析股票的技术指标来做出更明智的投资决策。使用'aishare-txt'，你可以生成关于特定股票的详细技术指标描述，这些描述可以被用于构建更加丰富和上下文相关的金融分析报告。 ### 应用程序的主要功能包括： - **用户界面**：设计一个简洁直观的UI，允许用户输入他们感兴趣的股票代码或名称。 - **技术指标生成**：当用户提交请求后，应用程序将调用'aishare-txt'包的功能来获取该股票的技术指标描述。这包括但不限于移动平均线、相对强弱指数（RSI）、布林带等。 - **可视化展示**：除了文字描述，应用程序还将生成图表以直观地展示所选股票的技术指标数据。 - **历史数据分析**：用户可以选择查看过去一段时间内的技术指标趋势，以便更好地理解市场动态。 - **个性化建议**：基于提供的技术指标描述和图表，应用程序能够给出简短的买入、卖出或持有建议。 ### 如何使用 'aishare-txt' 包： - 使用 'aishare-txt' 包中的函数来检索特定股票的技术指标描述。例如，如果用户查询了某个股票，你的应用需要调用相应的函数来获得该股票的相关技术指标描述。 - 利用返回的数据来填充应用程序的用户界面，确保信息准确且易于理解。 通过这个项目，你将创建一个既实用又有趣的工具，帮助投资者理解和分析复杂的金融市场数据。
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