clickhouse query
Project description
ClickHouse Query
ClickHouse Query is a Python library that functions as a powerful SQL generator for ClickHouse. It simplifies the construction of complex queries by offering a fluent, Pythonic API and a comprehensive set of helper functions.
Features
- Fluent and intuitive API for building ClickHouse queries.
- Comprehensive set of functions for data manipulation and aggregation.
- Support for PREWHERE, GROUP BY, ORDER BY, LIMIT, and other ClickHouse clauses.
- Easy integration with your existing ClickHouse client.
- Automatic generation of parameterized SQL queries to prevent SQL injection.
Installation
You can install the ClickHouse Query library using pip. Run the following command in your terminal:
pip install clickhouse-query
Usage
Here's an example of how to use the ClickHouse Query library:
import clickhouse_query as ch
from clickhouse_query import functions as chf
# Create a QuerySet instance for your table.
# Replace "my_table" with the actual name of your table.
# The `clickhouse_client` parameter should be your configured ClickHouse client instance.
q = (
ch.QuerySet("my_table", clickhouse_client=...)
# Filters rows before reading data from disk, improving query performance.
# This example filters for records where the year of the 'date' column is 2020 or later.
.prewhere(date__year__gte=2020)
# Groups the data by the 'status' column.
.group_by("status")
# Selects the 'status' column and calculates the sum of the 'price' column, aliasing it as 's'.
.select("status", s=chf.sum("price"))
# Orders the results by the sum of 'price' ('s') in descending order.
.order_by("-s")
# Limits the number of returned rows to 10.
.limit(10)
)
# Get the generated SQL query and its parameters.
# This is useful for debugging or understanding the underlying query.
sql, sql_params = ch.get_sql(q)
# Example output:
# sql = 'SELECT status, sum(price) AS s FROM my_table PREWHERE (greaterOrEquals(toYear(date), %(__U_1)f)) GROUP BY status ORDER BY s DESC LIMIT %(__U_2)f'
# sql_params = {'__U_1': 2020, '__U_2': 10}
# Execute the query against your ClickHouse database.
# The `execute()` method returns a list of dictionaries, where each dictionary represents a row.
data = q.execute()
# Example output:
# data = [{"status": "status1", "s": 200}, {"status": "status2", "s": 100}, ...]
In this example, sql will contain the generated SQL query and sql_params will contain its parameters. The execute method will execute the query and return the data.
Docs
For more detailed information on how to use the ClickHouse Query library, please refer to the documentation in the docs directory.
Contributing
Contributions are welcome! If you'd like to contribute, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make your changes and commit them with clear messages.
- Push your changes to your fork.
- Submit a pull request.
Tests
To run the tests for this library, you can use your preferred test runner (e.g., pytest). Make sure you have the necessary dependencies installed.
# Example using pytest
pytest
License
This project is licensed under the MIT License - see the LICENSE file for details
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