ctj

A command-line tool to convert CSV files to JSON format, supporting both file input and piped stdin.

Features

• Convert CSV files to JSON with automatic type detection
• Support for piped stdin input (e.g., cat file.csv | ctj)
• Support for numbers, booleans, and strings
• Pretty print JSON output
• Output to file or stdout
• Command-line interface with helpful options

Installation

Option 1: Install from crates.io (recommended)

cargo install ctj

This will install the latest version from crates.io. After installation, you can use ctj command directly from anywhere.

Option 2: Install from source

Clone the repository and install locally:

git clone https://github.com/lef237/ctj.git
cd ctj
cargo install --path .

Option 3: Build from source

git clone https://github.com/lef237/ctj.git
cd ctj
cargo build --release

This creates an executable at ./target/release/ctj.

Usage

Basic Usage

Convert CSV to JSON and output to stdout:

ctj input.csv

Or using the explicit flag:

ctj -i input.csv

Piped Input

You can also pipe CSV data directly to ctj:

cat input.csv | ctj
echo "name,age\nJohn,30" | ctj
curl https://example.com/data.csv | ctj

Pretty Print

Format JSON output with indentation:

ctj input.csv -p

Output to File

Save JSON output to a file:

ctj input.csv -o output.json

Command Line Options

• -i, --input <FILE>: Input CSV file (optional, can also be provided as positional argument; if not provided, reads from stdin)
• -o, --output <FILE>: Output JSON file (optional, defaults to stdout)
• -p, --pretty: Pretty print JSON output
• -n, --no-header: Treat the first row as data, not headers (generates column_0, column_1, etc.)
• -h, --help: Show help message
• -V, --version: Show version information

Examples

Given a CSV file sample.csv:

name,age,city,active
John,25,Tokyo,true
Alice,30,Osaka,false
Bob,35,Kyoto,true

Example 1: Basic conversion

ctj sample.csv

Output:

[{"name":"John","age":25,"city":"Tokyo","active":true},{"name":"Alice","age":30,"city":"Osaka","active":false},{"name":"Bob","age":35,"city":"Kyoto","active":true}]

Example 2: Pretty printed output

ctj sample.csv -p

Output:

[
  {
    "name": "John",
    "age": 25,
    "city": "Tokyo",
    "active": true
  },
  {
    "name": "Alice",
    "age": 30,
    "city": "Osaka",
    "active": false
  },
  {
    "name": "Bob",
    "age": 35,
    "city": "Kyoto",
    "active": true
  }
]

Example 3: CSV without headers

For CSV files without header rows, use the -n option to generate default column names:

ctj sample-no-header.csv -n -p

Given a CSV file sample-no-header.csv without headers:

,,
,,FALSE
,55.5,

Output:

[
  {
    "column_0": "",
    "column_1": "",
    "column_2": ""
  },
  {
    "column_0": "",
    "column_1": "",
    "column_2": false
  },
  {
    "column_0": "",
    "column_1": 55.5,
    "column_2": ""
  }
]

Example 4: Using piped input

You can pipe CSV data directly into ctj:

# Basic piped input
cat sample.csv | ctj -p

# Processing data from a URL
curl -s https://example.com/data.csv | ctj --pretty

# Process data and save to file
echo "name,score\nAlice,95.5\nBob,87" | ctj > results.json

# Process without headers and pretty print
echo "John,30,Tokyo\nJane,25,Osaka" | ctj --no-header --pretty

Output for the last command:

[
  {
    "column_0": "John",
    "column_1": 30,
    "column_2": "Tokyo"
  },
  {
    "column_0": "Jane",
    "column_1": 25,
    "column_2": "Osaka"
  }
]

Type Detection

The tool automatically detects and converts data types:

• Integers: Whole numbers (e.g., 25, 100) are detected as integers
• Floating-point numbers: Numbers with decimal points (e.g., 95.5, 87.2) are detected as floats
• Booleans: true, false, TRUE, FALSE, True, False are converted to JSON booleans (case-insensitive)
• Strings: All other values are treated as strings

License

This project is available under the MIT License.