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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,144 @@ | ||
| """ | ||
| Generate random SQL statements | ||
| These are pretty basic statements but this has still found bugs. | ||
| """ | ||
|
|
||
| import os | ||
| import sys | ||
|
|
||
| sys.path.insert(1, os.path.join(sys.path[0], "../..")) | ||
|
|
||
| import datetime | ||
| import random | ||
| import time | ||
|
|
||
| import pytest | ||
| from orso.tools import random_int, random_string | ||
| from orso.types import OrsoTypes | ||
|
|
||
| import opteryx | ||
| from opteryx.utils.formatter import format_sql | ||
|
|
||
|
|
||
| def random_value(t): | ||
| if t == OrsoTypes.VARCHAR: | ||
| return f"'{random_string(4)}'" | ||
| if t in (OrsoTypes.DATE, OrsoTypes.TIMESTAMP): | ||
| return f"'{datetime.datetime.now() + datetime.timedelta(seconds=random_int())}'" | ||
| if random.random() < 0.5: | ||
| return random_int() | ||
| return random_int() / 1000 | ||
|
|
||
|
|
||
| def generate_condition(columns): | ||
| where_column = columns[random.choice(range(len(columns)))] | ||
| while where_column.type in (OrsoTypes.ARRAY, OrsoTypes.STRUCT): | ||
| where_column = columns[random.choice(range(len(columns)))] | ||
| if random.random() < 0.1: | ||
| where_operator = random.choice(["IS", "IS NOT"]) | ||
| where_value = random.choice(["TRUE", "FALSE", "NULL"]) | ||
| elif where_column.type == OrsoTypes.VARCHAR and random.random() < 0.5: | ||
| where_operator = random.choice( | ||
| ["LIKE", "ILIKE", "NOT LIKE", "NOT ILIKE", "RLIKE", "NOT RLIKE"] | ||
| ) | ||
| where_value = ( | ||
| "'" + random_string(8).replace("1", "%").replace("A", "%").replace("6", "_") + "'" | ||
| ) | ||
| else: | ||
| where_operator = random.choice(["=", "!=", "<", "<=", ">", ">="]) | ||
| where_value = f"{str(random_value(where_column.type))}" | ||
| return f"{where_column.name} {where_operator} {where_value}" | ||
|
|
||
| def generate_random_sql_join(columns1, table1, columns2, table2) -> str: | ||
| join_type = random.choice(["INNER JOIN", "LEFT JOIN", "RIGHT JOIN", "FULL OUTER JOIN"]) | ||
|
|
||
| left_column = columns1[random.choice(range(len(columns1)))] | ||
| right_column = columns2[random.choice(range(len(columns2)))] | ||
| while left_column.type != right_column.type: | ||
| left_column = columns1[random.choice(range(len(columns1)))] | ||
| right_column = columns2[random.choice(range(len(columns2)))] | ||
|
|
||
| join_condition = f"{table1}.{left_column.name} = {table2}.{right_column.name}" | ||
| selected_columns = [f"{table1}.{col.name}" for col in columns1 if random.random() < 0.2] + [f"{table2}.{col.name}" for col in columns2 if random.random() < 0.2] | ||
| if len(selected_columns) == 0: | ||
| selected_columns = ["*"] | ||
| select_clause = "SELECT " + ", ".join(selected_columns) | ||
|
|
||
| query = f"{select_clause} FROM {table1} {join_type} {table2} ON {join_condition}" | ||
|
|
||
| return query | ||
|
|
||
| from opteryx import virtual_datasets | ||
|
|
||
| TABLES = [ | ||
| { | ||
| "name": virtual_datasets.planets.schema().name, | ||
| "fields": virtual_datasets.planets.schema().columns, | ||
| }, | ||
| { | ||
| "name": virtual_datasets.satellites.schema().name, | ||
| "fields": virtual_datasets.satellites.schema().columns, | ||
| }, | ||
| { | ||
| "name": virtual_datasets.astronauts.schema().name, | ||
| "fields": virtual_datasets.astronauts.schema().columns, | ||
| }, | ||
| { | ||
| "name": virtual_datasets.missions.schema().name, | ||
| "fields": virtual_datasets.missions.schema().columns, | ||
| }, | ||
| { | ||
| "name": "testdata.planets", | ||
| "fields": virtual_datasets.planets.schema().columns, | ||
| }, | ||
| { | ||
| "name": "testdata.satellites", | ||
| "fields": virtual_datasets.satellites.schema().columns, | ||
| }, | ||
| { | ||
| "name": "testdata.missions", | ||
| "fields": virtual_datasets.missions.schema().columns, | ||
| }, | ||
| ] | ||
|
|
||
| TEST_CYCLES: int = 250 | ||
|
|
||
|
|
||
| @pytest.mark.parametrize("i", range(TEST_CYCLES)) | ||
| def test_sql_fuzzing_join(i): | ||
| seed = random_int() | ||
| random.seed(seed) | ||
| print(f"Seed: {seed}") | ||
|
|
||
| table1 = TABLES[random.choice(range(len(TABLES)))] | ||
| table2 = TABLES[random.choice(range(len(TABLES)))] | ||
| while table1 == table2: | ||
| table2 = TABLES[random.choice(range(len(TABLES)))] | ||
| statement = generate_random_sql_join(table1["fields"], table1["name"], table2["fields"], table2["name"]) | ||
| formatted_statement = format_sql(statement) | ||
|
|
||
| print(formatted_statement) | ||
|
|
||
| start_time = time.time() # Start timing the query execution | ||
| try: | ||
| res = opteryx.query(statement) | ||
| execution_time = time.time() - start_time # Measure execution time | ||
| print(f"Shape: {res.shape}, Execution Time: {execution_time:.2f} seconds") | ||
| # Additional success criteria checks can be added here | ||
| except Exception as e: | ||
| import traceback | ||
|
|
||
| print(f"\033[0;31mError in Test Cycle {i+1}\033[0m: {e}") | ||
| print(traceback.print_exc()) | ||
| # Log failing statement and error for analysis | ||
| raise e | ||
| print() | ||
|
|
||
|
|
||
| if __name__ == "__main__": # pragma: no cover | ||
|
|
||
| for i in range(TEST_CYCLES): | ||
| test_sql_fuzzing_join(i) | ||
|
|
||
| print("✅ okay") |
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