refactor: prepare_sample_dataset updated

[AwaisKamran]

Description

This PR corresponds to the following Refactor-Prepare-Sample-Database-Script
This PR refactors the existing script based on its cyclomatic complexity score and violation of SRP principles.

Before Refactor

./preprocess/prepare_sample_dataset.py
    F 15:0 get_train_file_path - A
    F 47:0 add_schema_used - A
    F 39:0 make_sqlite_connection - A

3 blocks (classes, functions, methods) analyzed.
Average complexity: A (3.0)

After Refactor

./preprocess/prepare_sample_dataset.py
    F 34:0 create_train_file - A
    F 71:0 add_schema_used - A
    F 25:0 get_train_file_path - A
    F 58:0 add_question_id_for_bird_train - A
    F 53:0 copy_bird_train_file - A
    F 116:0 write_train_data_to_file - A

6 blocks (classes, functions, methods) analyzed.
Average complexity: A (2.6666666666666665)

After Review

./preprocess/prepare_sample_dataset.py
    F 56:0 create_train_file - A
    F 147:0 add_schema_used - A
    F 121:0 fetch_database - A
    F 43:0 get_train_file_path - A
    F 92:0 create_database_connection - A
    F 81:0 copy_bird_train_file - A

6 blocks (classes, functions, methods) analyzed.
Average complexity: A (3.0)

For Reviewers

@fi5421 I you are requested to please run and test this script before merging

[Copilot]

Pull Request Overview

This PR refactors the sample dataset preparation script for text-to-SQL tasks, aiming to reduce cyclomatic complexity and better adhere to single-responsibility principles. Key changes include enhanced error handling and logging, improved documentation, and reorganized functions for creating and processing the train file.

Reviewed Changes

Copilot reviewed 8 out of 8 changed files in this pull request and generated 3 comments.

Show a summary per file

File	Description
server/utilities/constants/preprocess/prepare_sample_dataset/response_messages.py	Added standardized response message constants.
server/utilities/constants/preprocess/prepare_sample_dataset/indexing_constants.py	Introduced indexing constants for dataset preparation.
server/utilities/constants/common/error_messages.py	Provided common error message templates.
server/utilities/connections/sqlite.py	Implemented in-memory SQLite connection using backup.
server/utilities/connections/common.py	Added utility for safely closing connections.
server/scripts/train_test_split_bird.py	Enhanced functions and added detailed documentation for JSON processing and splitting.
server/scripts/mask_bird.py	Improved masking functionality with detailed documentation and refined file operations.
server/preprocess/prepare_sample_dataset.py	Refactored the main dataset preparation script with improved logging, error handling, and function reorganization.