qtrex

Query template rendering and execution library


Keywords
google-bigquery, python, sql, yaml
License
Apache-2.0
Install
pip install qtrex==0.1.0

Documentation

qtrex

CI

PyPI version

Query template rendering and execution library written in Python.

The goal of qtrex is to provide a simple API that supports loading .sql files that can be templated with jinja, and provide extensible configuration options to either compile the files, and execute the rendered templates against various databases.

Getting Started

qtrex is installable at https://pypi.org/project/qtrex/ via pip using:

We currently only support bigquery, but plan on adding other DB support as optional dependencies.

pip install 'qtrex[bigquery]==0.0.5'

Examples

Here is a brief example usage of qtrex.

Assuming you have query templates in a directory on a local filesystem, using our test suite as an example:

|tests
    |--test_*.py
    |--testdata
        |--mytemplate.sql
        |--ingest
            |--another_file_ext.j2
            |--another_query.sql

Where ./tests/testdata/mytemplate.sql has the following contents:

SELECT SUM(x)
FROM UNNEST({{ params.test_array }}) AS x

and ./tests/testdata/ingest/another_query.sql has:

SELECT
    *
FROM
    `{{ params.my_project_id }}.{{ params.my_dataset }}.{{ params.my_table }}`

and lastly, ./tests/testdata/nested_params.sql has:

SELECT
    {{ params.test_dict_key.one }} + {{ params.test_dict_key.two }}

Next, we want to have our .yaml config (or extend qtrex.config.BaseConfig) to implement your own config mechanism.

Our ./tests/example.yaml will look like:

params:
  - key: test_string_key
    value: "string_value"
  - key: test_array_key
    value: [1, 2, 3]
  - key: test_dict_key
    value:
      one: 1
      two: 2
      three: 3

We can now run the following script (./tests/example.py) after changing into the ./tests directory

from qtrex.executor import BigQueryExecutor
from qtrex.store import Store
from qtrex.config import YAMLConfig


def main():
    with open("./example.yaml", "r") as f:
        cfg = YAMLConfig(f)

    store = Store.from_path(cfg, "./testdata")
    ex = BigQueryExecutor()
    for query_ref in store:
        print(f"{query_ref.name}: {query_ref.template}\n")
        res = ex.execute(query_ref, dry_run=True)
        print(f"results: {res}")


if __name__ == "__main__":
    main()

When we run this script:

cd ./tests
python example.py

we should see the following in stdout

mytemplate.sql: SELECT SUM(x)
FROM UNNEST([1, 2, 3]) AS x

results: QueryResult(query_ref=QueryRef(filename='./testdata\\mytemplate.sql', template='SELECT SUM(x)\nFROM UNNEST([1, 2, 3]) AS x', name='mytemplate.sql'), df=None, error=None)
nested_params.sql: SELECT
    1 + 2

results: QueryResult(query_ref=QueryRef(filename='./testdata\\nested_params.sql', template='SELECT\n    1 + 2', name='nested_params.sql'), df=None, error=None)