flatterer 0.9.0

Opinionated JSON to CSV converter

Flatterer. Making JSON flatterer

Full Doucmentation

Introduction

An opinionated JSON to CSV/XLSX converter which tries to make a useful relational output for data analysis.

It aims to be fast and memory efficient.

Install

pip install flatterer

Flatterer requires Python 3.6 or greater. It is written as a python extension in Rust but has binaries (wheels) for linux (x64), macos (x64 and universal) and windows (x64, x86). On other platforms a rust toolchain will need to be installed.

Example JSON

Say you have a JSON data like this named games.json:

[
  {
    "id": 1,
    "title": "A Game",
    "releaseDate": "2015-01-01",
    "platforms": [
      {"name":"Xbox"},
      {"name":"Playstation"}
    ],
    "rating": {
      "code": "E",
      "name": "Everyone"
    }
  },
  {
    "id": 2,
    "title": "B Game",
    "releaseDate": "2016-01-01",
    "platforms": [
      {"name":"PC"}
    ],
    "rating": {
      "code": "E",
      "name": "Everyone"
    }
  }
]

Running Flatterer

Run the above file with flatterer.

flatterer games.json games_dir

Output Files

By running the above you will get the following files:

tree games_dir

games_dir/
├── csv
│   ├── games.csv
│   └── platforms.csv
├── data_package.json
├── fields.csv
└── ...

Main Table

games.csv contains:

_link	_link_games	id	rating_code	rating_name	releaseDate	title
1	1	1	E	Everyone	2015-01-01	A Game
2	2	2	E	Everyone	2016-01-01	B Game

Special columns _link and _link_games are generated. _link is the primary key there unique per game.

Also the rating sub-object is promoted to this table it has a one-to-one relationship with games. Sub-object properties are separated by '_'.

One To Many Table

platforms is an array so is a one-to-many with games therefore needs its own table:

platforms.csv contains:

_link	_link_games	name
1.platforms.0	1	Xbox
1.platforms.1	1	Playstation
2.platforms.0	2	PC

Link Fields

_link is the primary key for the platforms table too. Every table contains a _link_games field to easily join to the main games table.

If there was a sub-array of platforms then that would have _link, _link_games and _link_platforms fields.

To generalize this the _link__<table_name> fields joins to the _link field of <table_name> i.e the _link__<table_name> are the foreign keys refrencing <table_name>._link.

Fields CSV

fields.csv contains some metadata about the output tables:

table_name	field_name	field_type	count	field_title
platforms	_link	text	3	_link
platforms	_link_games	text	3	_link_games
platforms	name	text	3	name
games	_link	text	2	_link
games	_link_games	text	2	_link_games
games	id	number	2	id
games	rating_code	text	2	rating_code
games	rating_name	text	2	rating_name
games	releaseDate	date	2	releaseDate
games	title	text	2	title

The field_type column contains a type guess useful for inserting into a database. The field_title is the column heading in the CSV file or XLSX tab, which is initally the same as the field_name. After editing this file then you can rerun the transform:

flatterer games.json new_games_dir -f myfields.csv --only-fields

This can be useful for renameing columns, rearranging the field order or if you want to remove some fields the --only-fields flag will only include the fields in the edited file.

data_package.json contains metadata in the Tabular Datapackge Spec