json-ops 0.1.2

This is the `json-ops` package, intended to provide a collection of utilities for working with JSON data.

json-ops

json-ops package, intended to provide a collection of utilities for working with JSON data. Currently, it includes functionality to convert CSV and Excel files and strings to JSON format. More features will be added in the future.

Installation

No specific installation is required. Ensure you have Python and the pandas library installed. If you intend to run the tests, you will also need pytest and openpyxl:

pip install pandas openpyxl pytest

Modules

csv_to_json.py

This script provides functionality to convert CSV (Comma Separated Values) files and strings to JSON (JavaScript Object Notation) format.

Features

• Converts CSV files to JSON files.
• Converts CSV strings to JSON strings.
• Handles basic data type conversions (integer, float, boolean).

Usage

Converting a CSV file to JSON

from json_converter.csv_to_json import convert_csv_file

input_file = 'path/to/your/input.csv'
output_file = 'path/to/your/output.json'

success = convert_csv_file(input_file, output_file)

if success:
    print(f"Successfully converted {input_file} to {output_file}")
else:
    print(f"Failed to convert {input_file}")

Converting a CSV string to JSON

from json_converter.csv_to_json import convert_csv_string

csv_string = "Name,Age,City\\nAlice,30,New York\\nBob,25,London"
json_string = convert_csv_string(csv_string)

if json_string:
    print(json_string)
else:
    print("Failed to convert CSV string")

Limitations

• No support for nested input files: This converter is designed to work with flat CSV files. It does not support CSV files with nested structures or hierarchical data.

excel_to_json.py

This script provides functionality to convert Excel files and strings to nested JSON format based on column names.

Features

• Converts Excel files to nested JSON files.
• Converts Excel file content (bytes) to nested JSON strings.
• Uses column names with dot notation (e.g., address.city) to create nested JSON structures.

Usage

Converting an Excel file to nested JSON

from json_converter.excel_to_json import convert_excel_file

input_file = 'path/to/your/input.xlsx'
output_file = 'path/to/your/output.json'

success = convert_excel_file(input_file, output_file)

if success:
    print(f"Successfully converted {input_file} to {output_file}")
else:
    print(f"Failed to convert {input_file}")

Converting Excel file content (bytes) to nested JSON

from json_converter.excel_to_json import convert_excel_string
import pandas as pd
import io

data = {'address.city': ['New York', 'London'], 'name': ['Alice', 'Bob']}
df = pd.DataFrame(data)
buffer = io.BytesIO()
df.to_excel(buffer, index=False)
excel_content_bytes = buffer.getvalue()

json_string = convert_excel_string(excel_content_bytes)

if json_string:
    print(json_string)
else:
    print("Failed to convert Excel content")

Limitations

• Requires column names to follow a dot notation convention for creating nested structures.
• Handles basic data types as inferred by pandas.

Running Tests

To run the tests for the modules:

pytest tests/test_csv_to_json.py
pytest tests/test_excel_to_json.py

License

This project is licensed under the MIT License - see the LICENSE file for details.