ParSEval considers the specific behaviors of each query operator and covers all possible execution branches of the logical query plan by adapting the notion of branch coverage to query plans.
The repo contains following supplemental materials:
- source code of ParSEval
- Source code of query parser
├── src # Source code of ParSEval
├── requirements.txt # pip requirements
└── README.md
Please download and set up the query parser from the repository.
- Please use conda or venv to create a virtual environment. Run following command to install requirements.
# Example with venv
python -m venv venv
source venv/bin/activate
# Or with conda
conda create -n parseval-dev python=3.8
conda activate parseval-dev- Install the required dependencies:
poetry installNormally, one invoke the tool as
from parseval import instantiate_db
instantiate_db(workspace, schema, sql, dialect, **kwargs):to generate test database instances for input query SQL1. To test the equivalence of two queries:
from parseval import disprove_queries
disprove_queries(schema, gold, pred, dialect, **kwargs)One can enhance the readability of generated data for common column types by customizing the data generation strategy in the register_default_generators function.
# Integer generator
def int_generator(existing_values: Optional[Set[Any]] = None, is_unique: bool = False) -> int:
"""
Generate a random integer value.
Args:
existing_values: Set of existing values to avoid duplicates if is_unique is True
is_unique: Whether the value should be unique
Returns:
int: A random integer value
"""
value = random.randint(1, 100)
if is_unique and existing_values:
while value in existing_values:
value = random.randint(1, 100)
return value
from .registry import ValueGeneratorRegistry
ValueGeneratorRegistry.register('int', int_generator)- adapting MySQL/SQLite dialect processing code
- Handling special functions from SQLite/MySQL
- Install Docker
- Dataset