filequery 0.1.1

Query CSV and Parquet files using SQL

filequery

Query CSV and Parquet files using SQL

installation

$ pip install filequery

CLI usage

Run filequery --help to see what options are available.

usage: __main__.py [-h] --filename FILENAME [--query QUERY] [--query_file QUERY_FILE] [--out_file OUT_FILE] [--out_file_format OUT_FILE_FORMAT]

options:
  -h, --help            show this help message and exit
  --filename FILENAME   path to CSV or Parquet file
  --query QUERY         SQL query to execute against file
  --query_file QUERY_FILE
                        path to file with query to execute
  --out_file OUT_FILE   file to write results to instead of printing to standard output
  --out_file_format OUT_FILE_FORMAT
                        either csv or parquet, defaults to csv

For basic usage, provide a path to a CSV or Parquet file and a query to execute against it. The table name will be the file name without the extension.

$ filequery --filename sample_data/test.csv --query 'select * from test'

library usage

You can also use filequery in your own programs. See the example below.

from filequery.filedb import FileDb

query = 'select * from test'

# read test.csv into a table called "test"
fdb = FileDb('sample_data/test.csv')

# return QueryResult object
res = fdb.exec_query(query)

# formats result as csv
print(str(res))

# saves query result to result.csv
res.save_to_file('result.csv')

# saves query result as parquet file
fdb.export_query(query, 'result.parquet', FileType.PARQUET)

development

Packages required for distribution should go in requirements.txt.

To build the wheel: $ pip install -r requirements-dev.txt
$ python -m build

testing

To test the CLI, cd into the src directory and run filequery as a module.

$ python -m filequery <args>

To run unit tests, stay in the root of the project. The unit tests add src to the path so filequery can be imported properly.

$ python tests/<test file>