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![]() | Pack logtalk -- logtalk-3.81.0/manuals/_sources/libraries/csv.rst.txt |
.. _library_csv:
csv
The csv
library provides predicates for reading and writing CSV
files and streams:
https://www.rfc-editor.org/rfc/rfc4180.txt
The main object, csv/3, is a parametric object allowing passing
options for the handling of the header of the file, the fields
separator, and the handling of double-quoted fields. The cvs
object
extends the csv/3 parametric object using default option values.
The library also include predicates to guess the separator and guess the number of columns in a given CSV file.
Files and streams can be read into a list of rows (with each row being
represented by a list of fields) or asserted using a user-defined
dynamic predicate. Reading can be done by first loading the whole file
(using the read_file/2-3
predicates) into memory or line by line
(using the read_file_by_line/2-3
predicates). Reading line by line
is usually the best option for parsing large CSV files.
Data can be saved to a CSV file or stream by providing the object and predicate for accessing the data plus the name of the destination file or the stream handle or alias.
Open the `../../docs/library_index.html#csv <../../docs/library_index.html#csv>`__ link in a web browser.
To load all entities in this library, load the loader.lgt
file:
::
| ?- logtalk_load(csv(loader))
.
To test this library predicates, load the tester.lgt
file:
::
| ?- logtalk_load(csv(tester))
.
The csv(Header, Separator, IgnoreQuotes)
parametric object allows
passing the following options:
Header
: possible values are missing
, skip
, and keep
.Separator
: possible values are comma
, tab
, semicolon
,
and colon
.IgnoreQuotes
: possible values are true
to ignore double
quotes surrounding field data and false
to preserve the double
quotes.
The csv
object uses the default values keep
, comma
, and
false
.
When writing CSV files or streams, set the quoted fields option to
false
to write all non-numeric fields double-quoted (i.e. escaped).
The library objects can also be used to guess the separator used in a CSV file if necessary. For example:
::
| ?- csv::guess_separator('test_files/crlf_ending.csv', Separator)
.
Is this the proper reading of a line of this file (y/n)? [aaa,bb,ccc]
|> y.
Separator = comma ?
This information can then be used to read the CSV file returning a list of rows:
::
| ?- csv(keep, comma, true)
::read_file('test_files/crlf_ending.csv', Rows)
.
Rows = [[aaa,bbb,ccc],[zzz,yyy,xxx]] ?
Alternatively, The CSV data can be saved using a public and dynamic object predicate (that must be previously declared). For example:
::
| ?- assertz(p(_,_,_))
, retractall(p(_,_,_))
.
yes
| ?- csv(keep, comma, true)
::read_file('test_files/crlf_ending.csv', user, p/3)
.
yes
| ?- p(A,B,C)
.
A = aaa B = bbb C = ccc ? ;
A = zzz B = yyy C = xxx
Given a predicate representing a table, the predicate data can be written to a file or stream. For example:
::
| ?- csv(keep, comma, true)
::write_file('output.csv', user, p/3)
.
yes
leaving the content just as the original file thanks to the use of
true
for the IgnoreQuotes
option:
::
aaa,bbb,ccc zzz,yyy,xxx
Otherwise:
::
| ?- csv(keep, comma, false)
::write_file('output.csv', user, p/3)
.
yes
results in the following file content:
::
"aaa","bbb","ccc" "zzz","yyy","xxx"
The guess_arity/2 method, to identify the arity, i. e. the number of fields or columns per record in a given CSV file, for example:
::
| ?- csv(keep, comma, false)
::guess_arity('test_files/crlf_ending.csv', Arity)
.
Is this the proper reading of a line of this file (y/n)? [aaa,bbb,ccc]
|> y.
Arity = 3