csv.pl -- Process CSV (Comma-Separated Values) data
This library parses and generates CSV data. CSV data is represented in Prolog as a list of rows. Each row is a compound term, where all rows have the same name and arity.
- csv_read_file(+File, -Rows) is det
- csv_read_file(+File, -Rows, +Options) is det
- Read a CSV file into a list of rows. Each row is a Prolog term
with the same arity. Options is handed to csv//2. Remaining
options are processed by phrase_from_file/3. The default
separator depends on the file name extension and is
\t
for.tsv
files and,
otherwise.Suppose we want to create a predicate table/6 from a CSV file that we know contains 6 fields per record. This can be done using the code below. Without the option
arity(6)
, this would generate a predicate table/N, where N is the number of fields per record in the data.?- csv_read_file(File, Rows, [functor(table), arity(6)]), maplist(assert, Rows).
- csv(?Rows)// is det
- csv(?Rows, +Options)// is det
- Prolog DCG to `read/write' CSV data. Options:
- separator(+Code)
- The comma-separator. Must be a character code. Default is
(of course) the comma. Character codes can be specified
using the 0' notion. E.g., using
separator(0';)
parses a semicolon separated file. - ignore_quotes(+Boolean)
- If
true
(default false), threat double quotes as a normal character. - strip(+Boolean)
- If
true
(defaultfalse
), strip leading and trailing blank space. RFC4180 says that blank space is part of the data. - convert(+Boolean)
- If
true
(default), use name/2 on the field data. This translates the field into a number if possible. - case(+Action)
- If
down
, downcase atomic values. Ifup
, upcase them and ifpreserve
(default), do not change the case. - functor(+Atom)
- Functor to use for creating row terms. Default is
row
. - arity(?Arity)
- Number of fields in each row. This predicate raises
a
domain_error(row_arity(Expected), Found)
if a row is found with different arity. - match_arity(+Boolean)
- If
false
(defaulttrue
), do not reject CSV files where lines provide a varying number of fields (columns). This can be a work-around to use some incorrect CSV files.
- string_codes(-Codes)[private]
- Process a double-quotes string where the quote is escaped by doubling it. Eats the terminating double-quote.
- make_value(+Codes, -Value, +Options) is det[private]
- Convert a list of character codes to the actual value, depending on Options.
- csv_read_file_row(+File, -Row, +Options) is nondet
- True when Row is a row in File. First unifies Row with the first
row in File. Backtracking yields the second, ... row. This
interface is an alternative to csv_read_file/3 that avoids
loading all rows in memory. Note that this interface does not
guarantee that all rows in File have the same arity.
In addition to the options of csv_read_file/3, this predicate processes the option:
- line(-Line)
- Line is unified with the 1-based line-number from which Row is read. Note that Line is not the physical line, but rather the logical record number.
- csv_read_row(+Stream, -Row, +CompiledOptions) is det
- Read the next CSV record from Stream and unify the result with Row.
CompiledOptions is created from options defined for csv//2 using
csv_options/2. Row is unified with
end_of_file
upon reaching the end of the input. - csv_options(-Compiled, +Options) is det
- Compiled is the compiled representation of the CSV processing options as they may be passed into csv//2, etc. This predicate is used in combination with csv_read_row/3 to avoid repeated processing of the options.
- csv_write_file(+File, +Data) is det
- csv_write_file(+File, +Data, +Options) is det
- Write a list of Prolog terms to a CSV file. Options are given
to csv//2. Remaining options are given to open/4. The default
separator depends on the file name extension and is
\t
for.tsv
files and,
otherwise. - csv_write_stream(+Stream, +Data, +Options) is det
- Write the rows in Data to Stream. This is similar to
csv_write_file/3, but can deal with data that is produced
incrementally. The example below saves all answers from the
predicate data/3 to File.
save_data(File) :- setup_call_cleanup( open(File, write, Out), forall(data(C1,C2,C3), csv_write_stream(Out, [row(C1,C2,C3)], [])), close(Out)),