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tessl/pypi-connectorx

Load data from databases to dataframes, the fastest way.

86

1.04x

Quality

Pending

Does it follow best practices?

Impact

86%

1.04x

Average score across 10 eval scenarios

Overview
Eval results
Files

task.mdevals/scenario-9/

Database Query Performance Optimizer

Build a database query performance optimizer that executes queries with optimized database session settings. The system should configure database session parameters before running queries to improve execution performance.

Requirements

Your implementation should:

  1. Accept a database connection string and a SQL query to execute
  2. Configure database session parameters before executing the main query to optimize performance
  3. Support setting multiple session configuration parameters
  4. Load the query results into a dataframe
  5. Return both the query results and confirmation that the configuration was applied

Functional Specifications

Input Parameters

  • Database connection string (PostgreSQL or MySQL format)
  • Main SQL query to execute
  • List of session configuration statements to run before the query

Configuration Types to Support

  • Memory allocation settings (e.g., work_mem for PostgreSQL)
  • Parallel execution settings (e.g., max_parallel_workers_per_gather for PostgreSQL)
  • Session behavior settings (e.g., sql_mode for MySQL)

Output

  • Query results loaded into a dataframe
  • Success indicator showing configuration was applied

Test Cases { .tests }

Test 1: PostgreSQL Memory Configuration { .test }

Input:

  • Connection: PostgreSQL database connection string
  • Configuration: ["SET work_mem = '256MB'"]
  • Query: "SELECT id, name, value FROM test_table WHERE value > 100"

Expected Output:

  • Dataframe containing query results with columns: id, name, value
  • Configuration successfully applied before query execution

Test 2: PostgreSQL Parallel Workers Configuration { .test }

Input:

  • Connection: PostgreSQL database connection string
  • Configuration: ["SET max_parallel_workers_per_gather = 4", "SET parallel_setup_cost = 100"]
  • Query: "SELECT category, COUNT(*) as count, AVG(amount) as avg_amount FROM transactions GROUP BY category"

Expected Output:

  • Dataframe containing aggregated results with columns: category, count, avg_amount
  • Both configuration statements applied before query execution

Test 3: MySQL Session Mode Configuration { .test }

Input:

  • Connection: MySQL database connection string
  • Configuration: ["SET SESSION sql_mode = 'STRICT_ALL_TABLES'"]
  • Query: "SELECT product_id, product_name, price FROM products WHERE price > 50.0"

Expected Output:

  • Dataframe containing query results with columns: product_id, product_name, price
  • Session mode configured before query execution

Implementation Files

  • src/query_optimizer.py - Main implementation module
  • tests/test_query_optimizer.py - Test suite

Dependencies { .dependencies }

connectorx { .dependency }

Provides fast database-to-dataframe data loading with configuration support.

Install with Tessl CLI

npx tessl i tessl/pypi-connectorx

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