tavily-ai/tavily-python
Dec 2025 – Dec 2025
1 Month active
Languages Used
Python
Technical Skills
Code formattingCode readabilityPython developmentpackage managementversion control
yashwanth-alapati
PROFILE
Yashwanth-alapati
Yash Alap contributed to the tavily-ai/tavily-python repository by delivering a targeted bug fix and a packaging update during December 2025. He addressed an indentation issue in the AsyncTavilyClient’s include_usage parameter, improving both code correctness and readability. This adjustment ensured proper syntax and reduced the risk of integration errors for downstream users. Yash also managed the release process by updating the package version in setup.py, enabling the distribution of version 0.7.15 via PyPI. His work involved Python development, code formatting, and version control, supporting parallel asynchronous usage and streamlining upgrade paths for developers integrating Tavily into their applications.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
4
Activity Months1
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Maitar AsherMember
maya-sivanMember
Work History
December 2025
2 Commits • 1 Features
Dec 1, 2025December 2025 — Tavily-python (tavily-ai/tavily-python) delivered a targeted bug fix and a packaging release, reinforcing stability and ease of adoption. Key outcomes include a correctness and readability improvement in AsyncTavilyClient include_usage parameter, and a formal package release (0.7.15) to publish via PyPI, enabling downstream consumers to rely on a tracked version. These changes reduce integration errors, support parallel async usage, and streamline upgrade paths for users integrating Tavily into their applications.
2 Commits • 1 Features
Dec 1, 2025December 2025 — Tavily-python (tavily-ai/tavily-python) delivered a targeted bug fix and a packaging release, reinforcing stability and ease of adoption. Key outcomes include a correctness and readability improvement in AsyncTavilyClient include_usage parameter, and a formal package release (0.7.15) to publish via PyPI, enabling downstream consumers to rely on a tracked version. These changes reduce integration errors, support parallel async usage, and streamline upgrade paths for users integrating Tavily into their applications.
December 2025
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Code formattingCode readabilityPython developmentpackage managementversion control
Repositories Contributed To
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