csv2json

README

csv2json

csv2json is a simple program for converting CSV files to JSON. Each CSV file given to csv2json will be written to a corresponding JSON file. It is expected for the first line in each CSV file to be the column names for that file. If any records cannot be converted to JSON for any reason, then these will simply be skipped over.

• Quick start
• Schema file

Quick start

Assume we have a file users.csv,

$ cat users.csv
id,username,password,created_at
1,andrew,secret,07/12/2021
2,sam,terces,08/12/2021

when given to csv2json, would produce a corresponding users.json file.

$ csv2json users.csv
users.json
$ cat users.json
{"created_at":"07/12/2021","id":1,"password":"secret","username":"andrew"}
{"created_at":"08/12/2021","id":2,"password":"terces","username":"sam"}

The above example demonstrats how csv2json works in simple scenarios where you want a 1-to-1 mapping of CSV to JSON. However, there may be instances where you would prefer to validate, and perhaps transform the data you're converting. This is possible with csv2json via schema files.

A schema file simply describes the type for each column, the pattern that column's value should adhere to, and how the column's value should be output to JSON. In the above example the users.csv file has a created_at column in the format of dd/mm/yyyy, with a schema file we can tell csv2json to take this field, treat it as a time, and convert it to an appropriate format.

$ cat schema
# Column    Type  Pattern     Format
created_at  time  02/01/2006  2006-01-02T15:04:05Z

With the above schema file we can rerun csv2json, and give it a schema to use via the -s flag.

$ csv2json -s schema users.csv
users.json
$ cat users.json
{"created_at":"2021-12-07T00:00:00Z","id":1,"password":"secret","username":"andrew"}
{"created_at":"2021-12-08T00:00:00Z","id":2,"password":"terces","username":"sam"}

As you can see, with the schema file csv2json was able to convert the initial time value in the CSV file into a more appropiate file. With the above schema in place, an error would occur if any of the CSV records have a created_at column that do not match the specified pattern. The schema file can be used for some simple validation on the CSV data to ensure only the correct data is converted to JSON.

Schema file

The schema file defines the types for each column being convered in a CSV file, along with the patterns the column's values should adhere to, and the output format for the corresponding JSON value. The schema file is made up of space delimited lines in the following format,

# Comment line
column  type  pattern  format  destination

column - required

The column field describes the name of the column in the CSV File. This is required.

type - required

This describes the type of the column's value in the CSV file. This is required and should be one of string, bool, int, float, or time.

pattern

This describes the input pattern of the column's value in the CSV file. This will vary depending on the type of the column. Detailed below are the different patterns that can be used for each type.

• string - The pattern for a string is a regular expression. This will be applied to the input strings to the CSV file. Any strings that do not match the given pattern will be rejected, and an error will be reported.

• int - The base for the integer being parsed. This can be either 0, 2, 8, 10, or 16. By default numbers are parsed as base 10. When set to 0, the base is implied by the prefix of the string, for example, 0b for binary, 0o for octal, etc.

• time - The layout of the time in the CSV file. This uses the reference date Mon Jan 2 15:04:05 MST 2006 from the standard library. For more information on how to use different date layouts see the Go documentation for the time package.

format

This describes the output format of the column's value when written to JSON. This will vary depending on the column's type.

destination

This describes the name of the field that should be written to in the output JSON. If not given, then the original CSV column name is used.