json-to-multicsv 0.1.2

Convert hierarchical JSON data into multiple related CSV files

json-to-multicsv

Split a JSON file with hierarchical data into multiple CSV files.

A Python rewrite of jsnell/json-to-multicsv. See Juho Snellman's 2016 blog post for motivation and design.

Installation

pip install json-to-multicsv

Usage

$ json-to-multicsv --help
Usage: json-to-multicsv [OPTIONS]

  Split a JSON file with hierarchical data to multiple CSV files.

Options:
  --file FILENAME  JSON input file (default: stdin)
  --path TEXT      pathspec:handler[:name[:key_name]]
  --table TEXT     Top-level table name
  --no-prefix      Use only the last component of the table name for output
                   filenames.
  --help           Show this message and exit.

Examples

Nested objects and arrays

Given this input:

{
    "item 1": {
        "title": "The First Item",
        "genres": ["sci-fi", "adventure"],
        "rating": {
            "mean": 9.5,
            "votes": 190
        }
    },
    "item 2": {
        "title": "The Second Item",
        "genres": ["history", "economics"],
        "rating": {
            "mean": 7.4,
            "votes": 865
        },
        "sales": [
            { "count": 76, "country": "us" },
            { "count": 13, "country": "de" },
            { "count": 4, "country": "fi" }
        ]
    }
}

json-to-multicsv --file input.json \
    --path '/:table:item' \
    --path '/*/rating:column' \
    --path '/*/sales:table:sales' \
    --path '/*/genres:table:genres'

Produces three CSV files, joinable on the *._key columns:

item.csv:

item._key,rating.mean,rating.votes,title
item 1,9.5,190,The First Item
item 2,7.4,865,The Second Item

item.genres.csv:

item._key,item.genres._key,genres
item 1,0,sci-fi
item 1,1,adventure
item 2,0,history
item 2,1,economics

item.sales.csv:

item._key,item.sales._key,count,country
item 2,0,76,us
item 2,1,13,de
item 2,2,4,fi

Row handler, custom key names, and ignore

When the top-level JSON value is a single object (not a collection), use /:row with --table to name the output table. Custom key column names can be set with an extra :KEY_NAME argument on table handlers. Use :ignore to skip parts of the data.

{
    "name": "Summer Championship",
    "year": 2024,
    "games": {
        "game-1": {
            "home": "Eagles",
            "away": "Hawks",
            "score": { "home": 3, "away": 1 }
        },
        "game-2": {
            "home": "Bears",
            "away": "Lions",
            "score": { "home": 2, "away": 2 }
        }
    },
    "sponsors": ["Acme Corp", "Globex"]
}

json-to-multicsv --file tournament.json \
    --path '/:row' \
    --path '/games:table:game:gameId' \
    --path '/games/*/score:column' \
    --path '/sponsors:ignore' \
    --table main

main.csv:

name,year
Summer Championship,2024

main.game.csv:

gameId,away,home,score.away,score.home
game-1,Hawks,Eagles,1,3
game-2,Lions,Bears,2,2

Note that gameId replaces the default game._key column name, and sponsors are omitted entirely.

Top-level array

When the input is a JSON array, a single table handler at the root is all you need:

[
    {"title": "Dune", "author": "Frank Herbert", "year": 1965},
    {"title": "Neuromancer", "author": "William Gibson", "year": 1984},
    {"title": "Snow Crash", "author": "Neal Stephenson", "year": 1992}
]

json-to-multicsv --file books.json --path '/:table:book'

book.csv:

book._key,author,title,year
0,Frank Herbert,Dune,1965
1,William Gibson,Neuromancer,1984
2,Neal Stephenson,Snow Crash,1992

Options

--file INPUT

Read JSON input from a file. Defaults to stdin.

--path PATHSPEC:table:NAME[:KEY_NAME]

Values matching the pathspec open a new table with the given name. The value should be an object or array. For objects, each field produces a row, with the field name stored in the NAME._key column. For arrays, each element produces a row, with the 0-based index stored in the NAME._key column.

When tables are nested, key columns from all outer tables are included in inner tables.

An optional key name can be provided to customize the key column name (e.g., /:table:item:itemId produces an itemId column instead of item._key).

--path PATHSPEC:column

Values matching the pathspec are emitted as columns in the current table's row. If the value is a scalar, it becomes a single column. If the value is an object, its fields are flattened into multiple columns with dotted names.

--path PATHSPEC:row

Values matching the pathspec are emitted as new rows in the current table. The value must be an object. This is generally only useful for the top-level JSON value, combined with --table.

--path PATHSPEC:ignore

Values matching the pathspec (and all their children) are skipped.

--table NAME

Name the top-level table. Use this with a row handler on the root element.

--no-prefix

Use only the last component of the table name for output filenames. For example, item.sales.csv becomes sales.csv.

Paths and pathspecs

The path to a JSON value is determined by:

• The root element's path is /
• For values inside an object: parent path + / + field name
• For values inside an array: parent path + / + 0-based index

In a pathspec, any path component can be replaced with *, which matches any single component. For example, /a/*/c matches /a/b/c but not /a/b/b/c.

License

MIT. Based on json-to-multicsv by Juho Snellman.