pgbenchmark 0.0.4

A Python package to benchmark query performance and comparison on PostgreSQL Database

pgbenchmark

pgbenchmark is a Python package to benchmark query performance on a PostgreSQL database. It allows you to measure the execution time of queries over multiple runs, providing detailed metrics about each run's performance.

⚠️ This library is under HEAVY development ⚠️
I'll try to keep everything backwards compatible...

Getting Started

pip install pgbenchmark

---

Extremely simple setup.

import psycopg2
from pgbenchmark import Benchmark

conn = psycopg2.connect(
    "<< YOUR CONNECTION >>"
)

benchmark = Benchmark(db_connection=conn, number_of_runs=1000)
benchmark.set_sql("./test.sql")

for result in benchmark:
    # {'run': X, 'sent_at': <DATETIME WITH MS>, 'duration': '0.000064'}
    pass

""" View Summary """
print(benchmark.get_execution_results())
# {'runs': 1000, 'min_time': '0.00005', 'max_time': '0.000287', 'avg_time': '0.000072'}

You can also pass raw SQL as a String, instead of file

benchmark.set_sql("SELECT 1;")

It also supports SQLAlchemy connection engine

engine = create_engine("postgresql+psycopg2://.......")
conn = engine.connect()

# Set up benchmark class
benchmark = Benchmark(db_connection=conn, number_of_runs=5)