Property-Based Testing with PropEr in Erlang/

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CSV Parsing: The CSV Parser

CSV Parsing: The CSV Parser

Take a look at the implementation of the CSV parser in our example application.

We'll cover the following...

The CSV parser

We can now move on to implementing a CSV parser. Here is a possible implementation:

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-module(bday_csv).
-export([encode/1, decode/1]).
%% @doc Take a list of maps with the same keys and transform them
%% into a string that is valid CSV, with a header.
-spec encode([map()]) -> string().
encode([]) -> "";
encode(Maps) ->
    Keys = lists:join(",", [escape(Name) || Name <- maps:keys(hd(Maps))]),
    Vals = [lists:join(",", [escape(Field) || Field <- maps:values(Map)])
            || Map <- Maps],
    lists:flatten([Keys, "\r\n", lists:join("\r\n", Vals)]).
%% @doc Take a string that represents a valid CSV data dump
%% and turn it into a list of maps with the header entries as keys
-spec decode(string()) -> list(map()).
decode("") -> [];
decode(CSV) ->
    {Headers, Rest} = decode_header(CSV, []),
    Rows = decode_rows(Rest),
    [maps:from_list(lists:zip(Headers, Row)) || Row <- Rows].

Note: Decoding is done by fetching the headers, then fetching all of the rows. A header line is parsed by reading each column name one at a time, and a row is parsed by reading each field one at a time.

First, there’s the public interface with two functions:

  1. encode/1
  2. decode/1.

The functions are fairly straightforward, delegating the more complex operations to private ...

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