abstra-json-sql

abstra-json-sql

abstra-json-sql is a Python library that allows you to run SQL queries on JSON data. It is designed to be simple and easy to use, while providing powerful features for querying and manipulating JSON data.

[!WARNING]
This project is in its early stages and is not yet ready for production use. The API may change, and there may be bugs. Use at your own risk.

Installation

You can install abstra-json-sql using pip:

pip install abstra-json-sql

Usage

Command Line Interface

Assuming you have a directory structure like this:

.
├── organizations.json
├── projects.json
└── users.json

Querying Data

You can query the JSON files using SQL syntax. For example, to get all users from the users file, you can run:

abstra-json-sql "select * from users"

Or using the explicit query subcommand:

abstra-json-sql query --code "select * from users"

This will return all the users in the users.json file.

Interactive Mode

You can also run the CLI in interactive mode:

abstra-json-sql

This will start an interactive SQL prompt where you can type queries and see results immediately.

Creating Tables

You can create new tables interactively using the create table command:

abstra-json-sql create table --interactive

This will guide you through the process of creating a new table by asking for:

• Table name
• Column names and types (int, string, float, bool)
• Primary key designation
• Default values

The interactive table creation supports:

• Column types: int, string, float, bool
• Primary keys: Mark columns as primary keys during creation
• Default values: Set default values for columns
• Validation: Prevents duplicate table/column names and validates data types

Output Formats

You can specify the output format using the --format option:

abstra-json-sql "select * from users" --format csv
abstra-json-sql "select * from users" --format json

Python API

You can also use abstra-json-sql in your Python code. Here's an example:

from abstra_json_sql.eval import eval_sql
from abstra_json_sql.tables import InMemoryTables, Table, Column

code = "\n".join(
    [
        "select foo, count(*)",
        "from bar as baz",
        "where foo is not null",
        "group by foo",
        "having foo <> 2",
        "order by foo",
        "limit 1 offset 1",
    ]
)
tables = InMemoryTables(
    tables=[
        Table(
            name="bar",
            columns=[Column(name="foo", type="text")],
            data=[
                {"foo": 1},
                {"foo": 2},
                {"foo": 3},
                {"foo": 2},
                {"foo": None},
                {"foo": 3},
                {"foo": 1},
            ],
        )
    ],
)
ctx = {}
result = eval_sql(code=code, tables=tables, ctx=ctx)

print(result) # [{"foo": 3, "count": 2}]

CLI Examples

Basic Query

# Query all records from a table
abstra-json-sql "SELECT * FROM users"

# Query with conditions
abstra-json-sql "SELECT name, email FROM users WHERE age > 25"

Interactive Table Creation

# Start interactive table creation
abstra-json-sql create table --interactive

# Example interaction:
# Table name: employees
# Column name: id
# Column type for 'id' (int/string/float/bool): int
# Is 'id' a primary key? (y/N): y
# Column name: name
# Column type for 'name' (int/string/float/bool): string
# Column name: salary
# Column type for 'salary' (int/string/float/bool): float
# Does 'salary' have a default value? (y/N): y
# Default value for 'salary': 0.0
# Column name: (press Enter to finish)

Output Formats

# JSON output (default)
abstra-json-sql "SELECT * FROM users" --format json

# CSV output
abstra-json-sql "SELECT * FROM users" --format csv

Working Directory

# Specify a different working directory
abstra-json-sql "SELECT * FROM users" --workdir /path/to/json/files

Features

• SQL Queries on JSON: Run SQL queries directly on JSON files
• Command Line Interface: Easy-to-use CLI with multiple output formats
• Interactive Mode: Interactive SQL prompt for exploratory queries
• Table Management: Create and manage tables interactively
• Multiple Output Formats: Support for JSON and CSV output
• Python API: Use the library programmatically in your Python projects

Supported SQL Syntax

• WITH

  • RECURSIVE

• SELECT

  • ALL
  • DISTINCT
  • *
  • FROM
    • JOIN
      • INNER JOIN
      • LEFT JOIN
      • RIGHT JOIN
      • FULL JOIN
      • CROSS JOIN
  • WHERE
  • GROUP BY
  • HAVING
  • WINDOW
  • ORDER BY
  • LIMIT
  • OFFSET
  • FETCH
  • FOR

• INSERT

  • INTO
  • VALUES
  • DEFAULT
  • SELECT
  • RETURNING

• UPDATE

• DELETE

• CREATE

  • TABLE (via interactive CLI)

• DROP

• ALTER