The result is based on ratio of number of commits and code additions from initial and final time ranges.
Initial time range – from 5 Jul, 2023 to 5 Oct, 2023
Final time range – from 5 Apr, 2024 to 5 Jul, 2024
It is basically a number of most active contributors responsible for 80% of contributions.
Bus factor tries to assess "What happens if a key member of the team is hit by a bus?". The more there are key members, the lower the risk.
The goldmansachs/gs-quant repository has a bus factor of 5.
Medium risk, some knowledge concentrated in a few people
Bus factor was measured on 14 Aug 2024
The goldmansachs/gs-quant
repository on GitHub is a Goldman Sachs Python toolkit that is designed to be used by quantitative developers and data scientists. The toolkit, abbreviated as gs-quant
, is designed to super-charge desktop Python development and allow users to express complex ideas, tackle big data and interact with a powerful, cross-asset portfolio and risk management platform.
It allows individuals to represent trading ideas, construct trades, and fetch historical and real-time risk. As gs-quant
interacts with Goldman Sachs Marquee APIs, the toolkit can interact with both desktop and cloud functionality to perform tasks that would otherwise require manual steps or custom scripting.
Here are some example tasks you can perform directly:
To use gs-quant
in a project, it first needs to be installed. This can be done directly through pip:
pip install gs-quant
The API key also needs to be set up.
Please note that gs-quant
is a toolkit aimed at professional developers and investors, and potential users are advised to read through all terms and conditions.
Remember, this information can change as the developers update the toolkit. You should always refer to the official Goldman Sachs gs-quant
GitHub page for the most recent information.
For a more detailed overview of capabilities, refer to the Goldman Sachs gs-quant guide
Contributor | Commits |
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100 | |
69 | |
44 | |
17 | |
15 |