fix: return DataFrame without resetting index in _normalize_data method

[LouisLetcher]

Summary

Briefly describe the change and the motivation.

Changes

• What was added/changed?
• Any breaking changes?

How to Test

• Commands or steps to validate locally (Docker/Poetry)
• Relevant config or environment variables

Checklist (KISS)

• Pre-commit passes locally (pre-commit run --all-files)
• Tests added/updated where it makes sense (80% cov gate)
• Docs/README updated if needed
• No secrets committed; .env values are excluded
• Backward compatibility considered (configs, CLI flags)

Related Issues/Links

• Closes #
• References #

[gemini-code-assist]

Summary of Changes

Hello @LouisLetcher, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request refines the data preparation logic by removing an extraneous reset_index call from a DataFrame return. This adjustment prevents an unnecessary modification of the DataFrame's index, which can lead to more efficient data handling and maintain the integrity of the index for subsequent operations.

Highlights

• DataFrame Index Management: The _prepare_pybroker_frame method in src/backtest/runner.py has been updated to remove the reset_index(drop=True) call when returning the processed DataFrame. This change ensures that the DataFrame's index is preserved as it is, avoiding an unnecessary reset operation.

Changelog

• src/backtest/runner.py
  • Removed the reset_index(drop=True) method call from the DataFrame returned by the _prepare_pybroker_frame function.

Activity

• The pull request was created by LouisLetcher.
• No specific review comments or other activities have been recorded in the provided context.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature	Command	Description
Code Review	/gemini review	Performs a code review for the current pull request in its current state.
Pull Request Summary	/gemini summary	Provides a summary of the current pull request in its current state.
Comment	@gemini-code-assist	Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help	/gemini help	Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩

[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud

[gemini-code-assist]

Code Review

This pull request removes a redundant .reset_index(drop=True) call within the _prepare_pybroker_frame method. The ordered DataFrame is created from a dictionary of NumPy arrays, which already results in a DataFrame with a default RangeIndex. Consequently, the call to reset_index was a no-op. This change is correct and improves code clarity. No issues found.