[pre-commit.ci] pre-commit autoupdate #107

pre-commit-ci · 2024-08-12T20:26:12Z

Comprehensive Code Quality and Formatting Improvements

Purpose:
Enhance code quality and readability across the project through linter updates and consistent formatting practices.
Key Changes:
- Updated the Ruff pre-commit hook from v0.5.6 to v0.9.4 for improved linting.
- Fixed string formatting issues in astradb_import.py.
- Standardized string quotes from single to double quotes in Jupyter notebooks.
- Removed unnecessary line breaks and whitespace for cleaner code.
- Consolidated multi-line statements into single lines where appropriate.
- Improved variable assignments and print statements for clarity.
- Removed unused imports and commented-out code to reduce clutter.
Impact:
These changes significantly enhance code maintainability and readability, facilitating easier collaboration and future development.

Original Description

# Update Ruff Linter to v0.9.4

**Purpose:
**
Upgrade the Ruff linter to the latest version.
Key Changes:
- Updated the Ruff pre-commit hook to version 0.9.4.
- Ruff is a fast, powerful, and extensible Python linter.
**Impact:
**
This update will ensure the codebase is checked against the latest Ruff rules and best practices.

Original Description

# Comprehensive Code Quality Enhancements

****Purpose:
**
**
Consolidate improvements in code quality, readability, and linter updates across multiple PRs.
Key Changes:
- Upgraded the Ruff pre-commit hook from v0.5.6 to v0.9.3 for enhanced linting capabilities.
- Updated SQL query formatting to utilize f-strings, improving performance and readability.
- Standardized string quotes from single to double for consistency across the codebase.
- Removed unnecessary whitespace and blank lines to enhance clarity.
- Simplified multi-line statements into single lines where appropriate.
- Improved comments for better understanding and clarity.
- Consolidated import statements and eliminated unused imports.
- Enhanced overall formatting and readability of the code in various files.
****Impact:
**
**
These changes collectively enhance code quality, maintainability, and developer experience, ensuring a more consistent and efficient codebase.

Original Description

# Update Ruff Pre-Commit Hook Version

******Purpose:
**
**
**
Upgrade the Ruff pre-commit hook to the latest version for improved linting capabilities.
Key Changes:
- Updated Ruff version from v0.5.6 to v0.9.3.
******Impact:
**
**
**
Enhances code quality checks by incorporating the latest linting features and bug fixes.

Original Description

# Comprehensive Update on Linter and Vertex AI Notebook

********Purpose:
**
**
**
**
Consolidate improvements in code quality and usability across the Ruff linter and Vertex AI notebook.
Key Changes:
- Upgraded the Ruff linter from v0.5.6 to v0.8.4 for enhanced code quality.
- Optimized parallelism in the flush_batch_to_db function using a context manager.
- Simplified context manager usage in the qdrant_import.py file.
- Refactored Vertex AI notebook for consistent formatting and variable naming.
- Removed unnecessary imports and simplified code blocks in the notebook.
- Enhanced readability and organization of the notebook content.
- Added detailed comments and documentation to improve user understanding.
********Impact:
**
**
**
**
These updates collectively enhance code performance, maintainability, and usability for data processing and machine learning tasks.

Original Description

# Update Ruff Linter Version

**********Purpose:
**
**
**
**
**
Update the Ruff linter version used in the pre-commit configuration.
Key Changes:
- Bump Ruff version from v0.5.6 to v0.8.4.
- The Ruff linter is used as a pre-commit hook to enforce code style and quality.
**********Impact:
**
**
**
**
**
This update will bring in the latest features and bug fixes from the Ruff linter, improving the overall code quality and consistency.

Original Description

# Comprehensive Code Improvements and Dependency Updates

************Purpose:
**
**
**
**
**
**
Update dependencies, refactor code for improved readability, and enhance maintainability across multiple files and notebooks.
Key Changes:
- Updated Ruff pre-commit hook version from v0.5.6 to v0.8.3.
- Refactored with statements in astradb_import.py and qdrant_import.py for better readability.
- Standardized string formatting and spacing in multiple Jupyter notebooks for consistency.
- Removed unnecessary imports and cleaned up commented code in various notebooks.
- Enhanced code clarity by restructuring list definitions and function calls.
- Refactored code to use more descriptive variable names and improve readability.
- Simplified and consolidated some code blocks, removing unnecessary imports and formatting.
- Improved error handling and added more detailed logging and status updates.
- Optimized the process of creating and deploying the Vertex AI index and endpoint.
************Impact:
**
**
**
**
**
**
These changes improve code maintainability and readability, ensure the latest linting standards are applied, and optimize the Vertex AI index creation and deployment process.

Original Description

# Comprehensive Code Refactor and Dependency Update

**************Purpose:
**
**
**
**
**
**
**
Update dependencies and improve code readability across multiple files.
Key Changes:
- Updated Ruff pre-commit hook version from v0.5.6 to v0.8.2.
- Refactored context managers for ThreadPoolExecutor and tqdm for better readability.
- Standardized string formatting and spacing in various Jupyter notebooks.
- Improved code consistency by replacing single quotes with double quotes in JSON-like structures.
- Removed unnecessary imports and comments to streamline notebook files.
- Refactored imports and formatting for better readability.
- Optimized BigQuery data retrieval using a generator function to fetch data in chunks.
- Implemented batched text embedding generation using the Vertex AI TextEmbeddingModel.
- Added functionality to save the generated embeddings to local files and upload them to a GCS bucket.
- Streamlined the process of creating a new Vertex AI index and index endpoint, or using existing ones.
- Deployed the index to the index endpoint and tested the public endpoint URL.
**************Impact:
**
**
**
**
**
**
**
The changes enhance code maintainability and readability, improve efficiency and modularity, and enable better handling of large datasets and deployment of Vertex AI indexes.

Original Description

# Update Ruff Pre-Commit Hook Version

****************Purpose:
**
**
**
**
**
**
**
**
Upgrade the Ruff pre-commit hook to a newer version.
Key Changes:
- Updated Ruff version from v0.5.6 to v0.8.2.
****************Impact:
**
**
**
**
**
**
**
**
Enhances linting capabilities and may introduce new features or fixes from the updated version.

Original Description

# Comprehensive Codebase Enhancements

******************Purpose:
**
**
**
**
**
**
**
**
**
Consolidate improvements across linting, database operations, and notebook formatting for enhanced performance and readability.
Key Changes:
- Upgraded Ruff linter from v0.5.6 to v0.8.1, improving code quality and bug detection.
- Optimized batch flushing to the database using a context manager for better resource management.
- Enhanced batch uploading to the Qdrant vector database with similar optimizations.
- Improved formatting and readability of Jupyter notebooks by adding newlines and adjusting code structure.
- Removed unnecessary whitespace and streamlined import statements in notebooks.
- Consolidated multiple lines into single lines where applicable for clarity.
- Ensured consistent use of double quotes for strings across notebooks.
- Eliminated commented-out code and redundant lines to enhance maintainability.
******************Impact:
**
**
**
**
**
**
**
**
**
These enhancements lead to a more efficient codebase, improved user experience in notebooks, and easier maintenance for future developers.

Original Description

# Update Ruff Linter to v0.8.1

********************Purpose:
**
**
**
**
**
**
**
**
**
**
Update the Ruff linter to the latest version.
Key Changes:
- Upgraded Ruff linter from v0.5.6 to v0.8.1.
- The Ruff linter is a tool used for static code analysis and style enforcement.
********************Impact:
**
**
**
**
**
**
**
**
**
**
This update will apply the latest Ruff linter rules and improvements to the codebase, helping to maintain code quality and consistency.

Original Description

# Comprehensive Update on Linter and Vertex AI Integration

**********************Purpose:
**
**
**
**
**
**
**
**
**
**
**
Integrate the latest Ruff linter version and demonstrate the use of Vertex AI for creating a scalable vector search system with BigQuery datasets.
Key Changes:
- Upgraded the Ruff pre-commit hook from v0.5.6 to v0.8.0, enhancing code quality checks.
- Updated Ruff configuration in the .pre-commit-config.yaml for improved linter performance.
- Enhanced concurrent batch handling in astradb_import.py and qdrant_import.py for better database import efficiency.
- Developed a function for chunked querying of BigQuery data and conversion to text embeddings.
- Implemented functionality to write embeddings to JSON, upload to GCS, and convert to Parquet format.
- Configured and deployed an approximate nearest neighbor (ANN) index as an endpoint using Vertex AI.
**********************Impact:
**
**
**
**
**
**
**
**
**
**
**
These updates improve code quality and performance while enabling a robust, production-ready vector search capability leveraging Vertex AI and BigQuery.

Original Description

# Update Ruff Pre-commit Hook Version

************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
Upgrade the Ruff pre-commit hook to a newer version for improved linting capabilities.
Key Changes:
- Updated Ruff version from v0.5.6 to v0.8.0.
************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
This change may enhance code quality checks by incorporating the latest linting features and bug fixes.

Original Description

# Comprehensive Code Quality and Readability Improvements in Jupyter Notebooks

**************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhance code quality, readability, and maintainability across Jupyter notebooks.
Key Changes:
- Upgraded the Ruff pre-commit hook from v0.5.6 to v0.7.4 and updated its configuration.
- Improved formatting by removing unnecessary blank lines and extra whitespace in multiple notebooks.
- Refactored the Cassandra connection code for better structure and readability.
- Standardized formatting of Chroma function calls and parameters.
- Adjusted import statements for clarity and removed unused imports.
- Simplified list and dictionary definitions for better readability.
- Consolidated multiple lines of code into single statements where appropriate.
- Enhanced the formatting of code blocks and data structures across notebooks.
**************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
These changes will significantly improve the overall readability and maintainability of the notebooks, facilitating easier understanding and modifications for future developers.

Original Description

# Update Ruff Pre-Commit Hook Version

****************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Upgrade the Ruff pre-commit hook to a newer version for improved linting capabilities.
Key Changes:
- Updated Ruff version from v0.5.6 to v0.7.4.
****************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This change may enhance code quality by incorporating the latest linting features and fixes.

Original Description

# Comprehensive Code Quality Enhancements Across Notebooks

******************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Consolidate improvements in code quality, readability, and maintainability across multiple Jupyter notebooks.
Key Changes:
- Upgraded the Ruff linter from v0.5.6 to v0.7.3, incorporating bug fixes and new linting rules.
- Enhanced formatting by removing unnecessary blank lines, extra whitespace, and standardizing code block presentations.
- Refined Cassandra connection logic with improved SSL options and simplified URI parsing.
- Optimized MongoDB queries by streamlining dictionary access and eliminating redundant comments.
- Standardized import statements and string formatting using f-strings for consistency.
- Consolidated multiple lines into single lines where appropriate for better readability.
- Removed redundant comments and empty lines to clean up the codebase.
******************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
These enhancements collectively improve code quality, readability, and maintainability, facilitating easier understanding and modifications for developers.

Original Description

# Update Ruff Pre-Commit Hook Version

********************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Upgrade the Ruff pre-commit hook to a newer version for improved linting.
Key Changes:
- Updated Ruff version from v0.5.6 to v0.7.3.
********************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhances code quality checks by incorporating the latest linting features and bug fixes.

Original Description

# Comprehensive Code Improvements

**********************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Upgrade dependencies, standardize code formatting, and optimize notebook content for improved readability and maintainability.
Key Changes:
- Upgraded Ruff pre-commit hook from version v0.5.6 to v0.7.2.
- Standardized code formatting, including replacing single quotes with double quotes and reformatting multiline statements, across multiple Jupyter notebooks.
- Removed unnecessary imports, cleaned up commented-out code, and streamlined print statements and comments in the notebooks.
- Consolidated multi-line property definitions into single lines for better clarity.
**********************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
These changes enhance code maintainability and readability, ensuring the codebase adheres to best practices and is easier for future developers to understand and work with.

Original Description

# Update Ruff Pre-Commit Hook Version

************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Upgrade the Ruff linter to a newer version for improved functionality.
Key Changes:
- Updated Ruff version from v0.5.6 to v0.7.2 in the pre-commit configuration.
************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhances linting capabilities and may introduce new features or fixes from the updated version.

Original Description

# Unified PR Summary: Code Cleanup and Vertex AI Quickstart

**************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Update code formatting and dependencies across multiple Jupyter notebooks, and refactor a Vertex AI quickstart notebook for improved readability, performance, and maintainability.
Key Changes:
- Updated Ruff pre-commit hook version from v0.5.6 to v0.7.1.
- Standardized string formatting and spacing in various code cells.
- Improved readability by restructuring long lines and adding line breaks.
- Replaced single quotes with double quotes for consistency in string literals.
- Removed unnecessary imports and comments to streamline the code.
- Refactored code to use more descriptive variable names and improve readability.
- Simplified imports and removed unused imports.
- Optimized BigQuery data retrieval by using a generator function to fetch data in chunks.
- Improved error handling and logging for the text embedding process.
- Restructured the file and index creation logic to make it more modular and reusable.
- Added support for using an existing Vertex AI index and index endpoint.
**************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The changes enhance code maintainability and readability, improve performance, and increase the flexibility of the Vertex AI quickstart notebook.

Original Description

# Update Ruff Linter to v0.7.1

****************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Update the Ruff linter to the latest version.
Key Changes:
- Upgraded Ruff linter from v0.5.6 to v0.7.1.
- Ruff is a fast, powerful Python linter that helps maintain code quality.
****************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The updated linter version will provide improved linting capabilities and bug fixes, helping to ensure consistent code style and quality.

Original Description

# Comprehensive Code Quality Improvements

******************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhance code quality, readability, and maintainability across various components.
Key Changes:
- Upgraded the Ruff linter from v0.5.6 to v0.7.0 for improved linting capabilities.
- Enhanced formatting of Jupyter notebooks by removing unnecessary whitespace and improving variable naming.
- Improved Cassandra connection configuration by organizing SSL options and using descriptive variable names.
- Streamlined Chroma collection handling with more concise syntax and better code organization.
- Standardized import statements and simplified data structure definitions in notebooks.
- Consolidated multi-line statements and enhanced string formatting for consistency.
- Removed unused imports and code segments to declutter the codebase.
******************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
These changes collectively lead to a more robust, maintainable, and user-friendly codebase, facilitating future development and collaboration.

Original Description

# Update Ruff Linter to v0.7.0

********************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Upgrade the Ruff linter to the latest version.
Key Changes:
- Updated the Ruff pre-commit hook to version 0.7.0.
- Ruff is a fast, powerful Python linter that helps maintain code quality.
********************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This upgrade will bring the latest linting improvements and bug fixes to the codebase.

Original Description

# Upgrade Ruff Linter Version

**********************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Update the Ruff pre-commit hook to the latest version (v0.6.9).
Key Changes:
- Updated the Ruff pre-commit hook version from v0.5.6 to v0.6.9.
- Improved the formatting of the Cassandra connection code in the aiven-qs.ipynb notebook.
- Fixed minor formatting issues in the astra_usage.ipynb notebook.
**********************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The upgrade to the latest Ruff linter version will ensure the codebase adheres to the latest linting standards and best practices.

Notebook Improvements

**********************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhance the readability and maintainability of the Jupyter notebooks.
Key Changes:
- Improved the formatting and code organization in the aiven-qs.ipynb, astra_usage.ipynb, chroma-qs.ipynb, and jsonl_to_parquet.ipynb notebooks.
- Removed unused imports and unnecessary code in the chroma-qs.ipynb and jsonltgz_to_parquet.ipynb notebooks.
- Simplified the code in the lance-qs.ipynb and medium-articles.ipynb notebooks.
**********************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The changes improve the overall code quality and make the notebooks more readable and maintainable for future reference and collaboration.

Vertex AI Quickstart with BigQuery Datasets

**********************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This notebook demonstrates how to use Vertex AI to create an approximate nearest neighbor (ANN) index from data stored in BigQuery, and deploy it as an index endpoint.
Key Changes:
- Refactored code to use more descriptive variable names and improve readability.
- Simplified imports and removed unused imports.
- Optimized BigQuery data retrieval by using a generator function to fetch data in chunks.
- Improved error handling and logging for the text embedding process.
- Streamlined the process of creating and deploying the Vertex AI index endpoint.
**********************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The changes improve the overall code quality, maintainability, and efficiency of the notebook, making it easier to understand and use.

Vespa Trial

**********************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This notebook explores the use of the Vespa search engine for text-based search and retrieval.
Key Changes:
- Removed unused imports and code related to the VespaQueryResponse and VespaError classes.
- Simplified the Vespa application initialization.
**********************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The changes make the notebook more concise and focused on the core Vespa functionality.

Weaviate Fill

**********************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This notebook demonstrates how to use the Weaviate client library to create a new class, insert data, and perform basic operations.
Key Changes:
- Simplified the creation of the Weaviate class using a more concise syntax.
- Streamlined the data insertion process by using a single insert_many call.
**********************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The changes make the notebook more readable and easier to understand.

WIT ResNet

**********************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This notebook explores the use of the Hugging Face Transformers library to load and use a pre-trained ResNet-50 model for image classification.
Key Changes:
- Removed an unused import for the requests library.
- Simplified the code for loading and processing the image.
**********************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The changes make the notebook more focused and remove unnecessary complexity.

Overall, the changes across these notebooks improve the code quality, readability, and maintainability, making the notebooks more accessible for future reference and collaboration.

Original Description

# Update Ruff Linter Version

************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Update the Ruff linter version used in the project's pre-commit hooks.
Key Changes:
- Upgrade Ruff linter from v0.5.6 to v0.6.9.
- The Ruff linter is a fast, powerful, and configurable Python linter.
************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This update will bring the latest improvements and bug fixes from the Ruff linter, helping to maintain code quality and consistency.

Original Description

# Comprehensive Code Enhancements and Updates

**************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Improve overall code quality and readability across multiple Jupyter notebooks.
Key Changes:
- Upgraded the Ruff linter from v0.5.6 to v0.6.8 for better linting capabilities.
- Enhanced formatting and readability of Jupyter notebooks by removing unnecessary blank lines and whitespace.
- Standardized the use of quotation marks and indentation for consistency.
- Improved formatting for long lines and complex data structures.
- Refactored Cassandra connection setup for clarity and explicitness.
- Expanded SSL options configuration for better readability.
- Improved the Astra usage notebook with more descriptive variable names.
- Added missing imports and enhanced formatting in the Astra usage notebook.
- Refined the formatting and structure of the Chrome notebook for clarity.
- Implemented error handling and logging improvements for robustness.
**************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
These changes will enhance the maintainability, readability, and overall quality of the codebase, making it easier for developers to work with the Jupyter notebooks.

Original Description

# Update Ruff Pre-Commit Hook Version

****************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Upgrade the Ruff linter to a newer version for improved functionality.
Key Changes:
- Updated Ruff version from v0.5.6 to v0.6.8 in the pre-commit configuration.
****************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhances linting capabilities and potentially resolves existing issues with the previous version.

Original Description

# Upgrade Ruff Linter Version

******************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Update the Ruff pre-commit hook to the latest version (v0.6.7).
Key Changes:
- Upgraded the Ruff pre-commit hook from v0.5.6 to v0.6.7.
- Updated the Ruff configuration in the .pre-commit-config.yaml file.
******************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This change will ensure the codebase is linted with the latest version of the Ruff linter, which includes bug fixes and new linting rules.

Improve Notebook Formatting

******************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhance the formatting and readability of the Jupyter notebooks.
Key Changes:
- Removed unnecessary blank lines and extra whitespace.
- Improved the formatting of code blocks and variable assignments.
- Standardized the use of double quotes for string literals.
******************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The improved formatting will make the notebooks more readable and maintainable for developers working on the codebase.

Enhance Cassandra and Astra Usage

******************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Optimize the code for interacting with Cassandra and Astra databases.
Key Changes:
- Reformatted the Cassandra connection code to improve readability.
- Updated the Astra database query syntax to use more consistent and idiomatic Python.
******************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
These changes will make the database interaction code more robust and easier to understand for future contributors.

Refactor Chroma Usage

******************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Simplify and streamline the usage of the Chroma vector database.
Key Changes:
- Removed unnecessary blank lines and extra whitespace in the Chroma code.
- Standardized the formatting of Chroma function calls and arguments.
******************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The refactored Chroma code will be more concise and easier to read, improving the overall maintainability of the codebase.

Miscellaneous Improvements

******************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Address various minor issues and improve the overall code quality.
Key Changes:
- Fixed formatting and style issues in several Jupyter notebooks.
- Removed unused imports and variables.
- Improved the consistency of variable naming and code structure.
******************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
These changes will make the codebase more readable, maintainable, and adhere to best practices.

Vertex AI Quickstart with BigQuery Datasets

******************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This notebook demonstrates how to use Vertex AI to create an approximate nearest neighbor (ANN) index from text data stored in BigQuery, and deploy the index as an endpoint.
Key Changes:
- Refactored imports and formatting for improved readability.
- Optimized BigQuery data retrieval by using a generator function to fetch data in chunks.
- Implemented batched text embedding generation using the Vertex AI TextEmbeddingModel.
- Added support for creating and deploying a new Vertex AI index, or using an existing one.
- Streamlined the process of saving embeddings to Parquet files and uploading them to Google Cloud Storage.
******************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The changes improve the efficiency and flexibility of the notebook, allowing users to work with larger datasets and customize the index creation process to their needs.

Original Description

# Update Ruff Linter to v0.6.7

********************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Update the Ruff linter to the latest version.
Key Changes:
- Upgraded Ruff linter from v0.5.6 to v0.6.7.
- The Ruff linter is a Python code linter that helps maintain code quality and consistency.
********************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This update will bring the latest bug fixes, improvements, and new features of the Ruff linter to the codebase.

Original Description

# Upgrade Ruff Linter Version

**********************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Update the Ruff pre-commit hook to the latest version.
Key Changes:
- Upgrade the Ruff pre-commit hook from v0.5.6 to v0.6.5.
- Update the Ruff configuration in the .pre-commit-config.yaml file.
**********************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This change will ensure the codebase is linted with the latest version of the Ruff linter, which includes bug fixes and new linting rules.

Improve Notebook Formatting

**********************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhance the formatting and readability of the Jupyter notebooks.
Key Changes:
- Remove unnecessary blank lines and extra whitespace.
- Standardize the use of quotation marks and indentation.
- Improve the formatting of long lines and complex data structures.
**********************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The improved formatting will make the notebooks more readable and maintainable for developers working on the project.

Optimize Cassandra Connection

**********************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Enhance the Cassandra connection configuration in the aiven-qs.ipynb notebook.
Key Changes:
- Separate the Cassandra URI and port into individual variables.
- Expand the SSL options configuration to use multiple lines for better readability.
**********************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The updated Cassandra connection setup will provide a more robust and maintainable configuration for interacting with the Cassandra database.

Enhance Astra Usage Notebook

**********************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
Improve the code quality and readability of the astra_usage.ipynb notebook.
Key Changes:
- Standardize the use of square brackets for dictionary access.
- Remove unnecessary blank lines and improve formatting.
- Simplify the code for writing data to a Parquet file.
**********************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
The changes will make the notebook more concise, easier to understand, and better aligned with the project's coding standards.

Vertex AI Quickstart with BigQuery Datasets

**********************************************************Purpose:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
This Jupyter notebook demonstrates how to use the Vertex AI SDK to create and manage a vector search index using data from BigQuery.
Key Changes:
- Refactored imports and formatting for better readability.
- Simplified and optimized the query_bigquery_chunks function.
- Improved error handling and logging for the text embedding process.
- Restructured the create_emb_vector_files function for better modularity and performance.
- Added more detailed configuration options for the Vertex AI index and endpoint.
- Streamlined the index and endpoint creation/deployment process.
**********************************************************Impact:
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
**
These changes should improve the overall reliability, efficiency, and maintainability of the Vertex AI integration with BigQuery data.

Original Description

kaizen-bot · 2024-08-26T20:45:37Z

src/vdf_io/notebooks/aiven-qs.ipynb

+    "ssl_options = {\n",
+    "    \"ca_certs\": \"/Users/dhruvanand/Code/vector-io/aiven.pem\",\n",
+    "    \"cert_reqs\": ssl.CERT_REQUIRED,\n",
+    "}\n",
    "CASSANDRA_URI = os.environ.get(\"CASSANDRA_URI\")\n",


Comment: Hardcoded paths for SSL certificates can lead to security vulnerabilities.

Solution: Use environment variables or configuration files to manage sensitive paths.

Reason For Comment: Using hardcoded paths exposes sensitive information and reduces portability.

Suggested change

"CASSANDRA_URI = os.environ.get(\"CASSANDRA_URI\")\n",

"ca_certs": os.environ.get('CA_CERTS_PATH'),

kaizen-bot · 2024-08-26T20:45:37Z

src/vdf_io/notebooks/astra_usage.ipynb

@@ -325,6 +325,7 @@
   "source": [
    "# convert list of dicts to pd.DataFrame\n",
    "import pandas as pd\n",
+    "\n",
    "df = pd.DataFrame(table)\n",


Comment: Missing error handling for database operations.

Solution: Implement try-except blocks around database calls.

Reason For Comment: Database operations can fail, and without error handling, this can lead to unhandled exceptions.

Suggested change

"df = pd.DataFrame(table)\n",

try:

df = pd.DataFrame(table)

except Exception as e:

print(f'Error creating DataFrame:{e}')

kaizen-bot · 2024-08-26T20:45:38Z

src/vdf_io/notebooks/lance-qs.ipynb

@@ -78,6 +78,7 @@
   "outputs": [],
   "source": [
    "import lancedb\n",
+    "\n",
    "uri = \"~/.lancedb\"\n",
    "db = lancedb.connect(uri)"
   ]


Comment: Missing error handling when connecting to the database.

Solution: Implement try-except blocks around database connection code.

Reason For Comment: Failure to handle exceptions can lead to crashes and unhandled states.

Suggested change

]

try:

db = lancedb.connect(uri)

except Exception as e:

print(f'Error connecting to database:{e}')

kaizen-bot · 2024-08-26T20:45:38Z

src/vdf_io/notebooks/qdrant-big.ipynb

  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
-    "\n",
    "ds = load_dataset(\"somewheresystems/dataclysm-pubmed\", split=\"train\", streaming=True)"


Comment: Lack of error handling for dataset loading.

Solution: Implement error handling when loading datasets to improve robustness.

Reason For Comment: Loading datasets can fail for various reasons (e.g., network issues, missing files), and should be wrapped in try-except blocks.

Suggested change

"ds = load_dataset(\"somewheresystems/dataclysm-pubmed\", split=\"train\", streaming=True)"

try:

ds = load_dataset("somewheresystems/dataclysm-pubmed", split="train", streaming=True)

except Exception as e:

print(f'Error loading dataset:{e}')

kaizen-bot · 2024-08-26T20:45:38Z

src/vdf_io/notebooks/vertex_quickstart_w_bq_datasets.ipynb

    ") -> Generator[pd.DataFrame, Any, None]:\n",
-    "    \n",
    "    for offset in range(start_chunk, max_rows, rows_per_chunk):\n",
    "        query = QUERY_TEMPLATE.format(limit=rows_per_chunk, offset=offset)\n",
    "        query_job = bq_client.query(query)\n",


Comment: Lack of error handling in critical sections.

Solution: Implement try-except blocks around critical operations, especially those involving external resources.

Reason For Comment: Not handling potential exceptions can lead to crashes or undefined behavior.

Suggested change

" query_job = bq_client.query(query)\n",

try:

query_job = bq_client.query(query)

except Exception as e:

print(f"Error querying BigQuery:{e}")

kaizen-bot · 2024-08-26T20:45:38Z

src/vdf_io/notebooks/jsonl_to_parquet.ipynb

@@ -35,7 +33,7 @@
   "outputs": [],
   "source": [


Comment: Avoid hardcoded file paths in the code.

Solution: Use configuration files or environment variables to manage paths.

Reason For Comment: This can lead to issues when the code is run in different environments.

Suggested change

"source": [

jsonl_file = os.getenv('JSONL_FILE_PATH')

kaizen-bot · 2024-08-26T20:45:38Z

src/vdf_io/notebooks/medium-articles.ipynb

+    "    embeddings,\n",
+    "    text_column=\"title\",\n",
+    "    model_id=\"openai-text-embedding-3-small\",\n",
+    ")"
   ]
  },


Comment: Potential security risk with unvalidated input in database operations.

Solution: Ensure all inputs are validated and sanitized before use.

Reason For Comment: Unvalidated input can lead to SQL injection or other vulnerabilities.

Suggested change

},

model_id=sanitize_input("openai-text-embedding-3-small")

kaizen-bot · 2024-08-26T20:45:39Z

src/vdf_io/notebooks/vertex_import_sample.ipynb

@@ -73,8 +73,8 @@
   ],
   "source": [
    "# naming convention for all cloud resources\n",
-    "VERSION        = \"pubv3\"                     # TODO\n",


Comment: Avoid hardcoding values directly in the code.

Solution: Define constants for values like 'pubv3' and 'vvs-vectorio' to improve maintainability.

Reason For Comment: Hardcoded values can lead to maintenance issues and lack flexibility.

Suggested change

"VERSION = \"pubv3\" # TODO\n",

VERSION = os.getenv('VERSION', 'pubv3') # Use environment variable with fallback

kaizen-bot · 2025-02-03T21:26:43Z

🔍 Code Review Summary

❗ Attention Required: This push has potential issues. 🚨

Overview

Total Feedbacks: 4 (Critical: 4, Refinements: 0)
Files Affected: 4
Code Quality: [█████████████████░░░] 85% (Good)

🚨 Critical Issues

security (4 issues)

1. Potential SQL Injection vulnerability in dynamic SQL queries.

📁 File: src/vdf_io/import_vdf/astradb_import.py
🔍 Reasoning:
Dynamic SQL queries constructed using string interpolation can lead to SQL injection attacks if user input is not properly sanitized.

💡 Solution:
Use parameterized queries to prevent SQL injection vulnerabilities.

Current Code:

self.session.execute(
                          f"CREATE TABLE IF NOT EXISTS{self.args['keyspace']}.{new_index_name}"
                          f' (id text PRIMARY KEY, "$vector" vector<float,{namespace_meta["dimensions"]}>)'
                      )

Suggested Code:

                     self.session.execute(
                                               "CREATE TABLE IF NOT EXISTS ?.? (id text PRIMARY KEY, "$vector" vector<float,?>)" , (self.args['keyspace'], new_index_name, namespace_meta["dimensions"])
                                           )

2. Use of hardcoded paths and lack of configuration management.

📁 File: src/vdf_io/notebooks/similar-words.ipynb
🔍 Reasoning:
Hardcoded paths can lead to issues when the code is run in different environments. Using configuration management can improve portability and maintainability.

💡 Solution:
Use environment variables or configuration files to manage paths.

Current Code:

scope_df = pd.read_parquet(
    "/Users/dhruvanand/Code/latent-scope/latentscope-working/homophones2/scopes/scopes-001.parquet"
)

Suggested Code:

    scope_df = pd.read_parquet(
        os.path.join(os.getenv('SCOPE_DATA_PATH', '/default/path'), 'scopes-001.parquet')
    )

3. Potential inefficiency in data processing loops.

📁 File: src/vdf_io/notebooks/tpuf-qs.ipynb
🔍 Reasoning:
Using a loop with a large number of iterations without optimization can lead to performance bottlenecks.

💡 Solution:
Consider using vectorized operations with pandas or optimizing the loop logic.

Current Code:

for i in tqdm(range(100)):
    # 10k random unique ids without replacement

Suggested Code:

     for i, row in tqdm(enumerate(ns.vectors()), total=20000):
         if i > 10000:
             break
         ns.delete(row.id)

4. Use of hardcoded values for configuration.

📁 File: src/vdf_io/notebooks/vespa-trial.ipynb
🔍 Reasoning:
Hardcoding values like URLs and tokens can lead to security vulnerabilities and makes the code less flexible and harder to maintain.

💡 Solution:
Consider using environment variables or configuration files to manage sensitive information and configuration settings.

Current Code:

app = Vespa(url="https://api.cord19.vespa.ai", cert=None, vespa_cloud_secret_token=None)

Suggested Code:

url = os.getenv('VESPA_URL', 'https://api.cord19.vespa.ai')
app = Vespa(url=url, cert=None, vespa_cloud_secret_token=os.getenv('VESPA_SECRET_TOKEN'))

Useful Commands

Feedback: Share feedback on kaizens performance with !feedback [your message]
Ask PR: Reply with !ask-pr [your question]
Review: Reply with !review
Update Tests: Reply with !unittest to create a PR with test changes

updates: - [github.com/astral-sh/ruff-pre-commit: v0.5.6 → v0.9.6](astral-sh/ruff-pre-commit@v0.5.6...v0.9.6)

for more information, see https://pre-commit.ci

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from dbc4a2f to 334d14d Compare August 19, 2024 20:31

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from 865a858 to 3e959a9 Compare August 26, 2024 20:41

kaizen-bot bot requested changes Aug 26, 2024

View reviewed changes

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from ea3ff4a to 6e664cc Compare September 2, 2024 20:29

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch 2 times, most recently from fb817ec to be0e27a Compare September 16, 2024 20:33

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from 2982ba9 to 4c72b95 Compare September 23, 2024 20:36

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from a492175 to 2626838 Compare September 30, 2024 20:48

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from f5b0dc5 to e1ce27e Compare October 7, 2024 21:48

kaizen-bot bot requested a review from dhruv-anand-aintech October 7, 2024 21:48

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from 86a2955 to 7aabee6 Compare October 21, 2024 20:53

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch 2 times, most recently from 27dde4b to bc990b8 Compare November 4, 2024 21:02

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from f5b2ae7 to 750799d Compare November 11, 2024 20:47

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch 2 times, most recently from ff00928 to 653e9b3 Compare November 25, 2024 20:47

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch 2 times, most recently from b217fe3 to c912d92 Compare December 9, 2024 20:48

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from 607d94b to 96d247f Compare December 16, 2024 20:46

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from 28d8d9a to 35d20c7 Compare December 23, 2024 20:56

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch 2 times, most recently from e24a2ed to 3b05fc7 Compare January 13, 2025 20:48

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from e61a16a to 43e5723 Compare January 20, 2025 20:42

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from 34e8924 to 99f3e7a Compare January 27, 2025 20:52

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from d352095 to 788a3cc Compare February 3, 2025 21:24

[pre-commit.ci] pre-commit autoupdate

b109b1f

updates: - [github.com/astral-sh/ruff-pre-commit: v0.5.6 → v0.9.6](astral-sh/ruff-pre-commit@v0.5.6...v0.9.6)

pre-commit-ci bot force-pushed the pre-commit-ci-update-config branch from 8782953 to b109b1f Compare February 10, 2025 20:56

[pre-commit.ci] auto fixes from pre-commit.com hooks

d7002e4

for more information, see https://pre-commit.ci

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

[pre-commit.ci] pre-commit autoupdate #107

[pre-commit.ci] pre-commit autoupdate #107

pre-commit-ci bot commented Aug 12, 2024 •

edited by kaizen-bot bot

Loading

Notebook Improvements

Vertex AI Quickstart with BigQuery Datasets

Vespa Trial

Weaviate Fill

WIT ResNet

Improve Notebook Formatting

Enhance Cassandra and Astra Usage

Refactor Chroma Usage

Miscellaneous Improvements

Vertex AI Quickstart with BigQuery Datasets

Improve Notebook Formatting

Optimize Cassandra Connection

Enhance Astra Usage Notebook

Vertex AI Quickstart with BigQuery Datasets

kaizen-bot bot Aug 26, 2024

kaizen-bot bot Aug 26, 2024

kaizen-bot bot Aug 26, 2024

kaizen-bot bot Aug 26, 2024

kaizen-bot bot Aug 26, 2024

kaizen-bot bot Aug 26, 2024

kaizen-bot bot Aug 26, 2024

kaizen-bot bot Aug 26, 2024

kaizen-bot bot commented Feb 3, 2025

	"CASSANDRA_URI = os.environ.get(\"CASSANDRA_URI\")\n",
	"ca_certs": os.environ.get('CA_CERTS_PATH'),

-   ]
+try:
+    db = lancedb.connect(uri)
+except Exception as e:
+    print(f'Error connecting to database:{e}')

	"VERSION = \"pubv3\" # TODO\n",
	VERSION = os.getenv('VERSION', 'pubv3') # Use environment variable with fallback

[pre-commit.ci] pre-commit autoupdate #107

Are you sure you want to change the base?

[pre-commit.ci] pre-commit autoupdate #107

Conversation

pre-commit-ci bot commented Aug 12, 2024 • edited by kaizen-bot bot Loading

Comprehensive Code Quality and Formatting Improvements

Notebook Improvements

Vertex AI Quickstart with BigQuery Datasets

Vespa Trial

Weaviate Fill

WIT ResNet

Improve Notebook Formatting

Enhance Cassandra and Astra Usage

Refactor Chroma Usage

Miscellaneous Improvements

Vertex AI Quickstart with BigQuery Datasets

Improve Notebook Formatting

Optimize Cassandra Connection

Enhance Astra Usage Notebook

Vertex AI Quickstart with BigQuery Datasets

kaizen-bot bot Aug 26, 2024

Choose a reason for hiding this comment

kaizen-bot bot Aug 26, 2024

Choose a reason for hiding this comment

kaizen-bot bot Aug 26, 2024

Choose a reason for hiding this comment

kaizen-bot bot Aug 26, 2024

Choose a reason for hiding this comment

kaizen-bot bot Aug 26, 2024

Choose a reason for hiding this comment

kaizen-bot bot Aug 26, 2024

Choose a reason for hiding this comment

kaizen-bot bot Aug 26, 2024

Choose a reason for hiding this comment

kaizen-bot bot Aug 26, 2024

Choose a reason for hiding this comment

kaizen-bot bot commented Feb 3, 2025

🔍 Code Review Summary

Overview

🚨 Critical Issues

pre-commit-ci bot commented Aug 12, 2024 •

edited by kaizen-bot bot

Loading