csv
— CSV File Reading and Writing¶
Source code: Lib/csv.py
The so-called CSV (Comma Separated Values) format is the most common import and export format for spreadsheets and databases. CSV format was used for many years prior to attempts to describe the format in a standardized way in RFC 4180. The lack of a well-defined standard means that subtle differences often exist in the data produced and consumed by different applications. These differences can make it annoying to process CSV files from multiple sources. Still, while the delimiters and quoting characters vary, the overall format is similar enough that it is possible to write a single module which can efficiently manipulate such data, hiding the details of reading and writing the data from the programmer.
The csv
module implements classes to read and write tabular data in CSV
format. It allows programmers to say, „write this data in the format preferred
by Excel,” or „read data from this file which was generated by Excel,” without
knowing the precise details of the CSV format used by Excel. Programmers can
also describe the CSV formats understood by other applications or define their
own special-purpose CSV formats.
The csv
module’s reader
and writer
objects read and
write sequences. Programmers can also read and write data in dictionary form
using the DictReader
and DictWriter
classes.
Zobacz także
- PEP 305 - CSV File API
The Python Enhancement Proposal which proposed this addition to Python.
Module Contents¶
The csv
module defines the following functions:
- csv.reader(csvfile, dialect='excel', **fmtparams)¶
Return a reader object that will process lines from the given csvfile. A csvfile must be an iterable of strings, each in the reader’s defined csv format. A csvfile is most commonly a file-like object or list. If csvfile is a file object, it should be opened with
newline=''
. [1] An optional dialect parameter can be given which is used to define a set of parameters specific to a particular CSV dialect. It may be an instance of a subclass of theDialect
class or one of the strings returned by thelist_dialects()
function. The other optional fmtparams keyword arguments can be given to override individual formatting parameters in the current dialect. For full details about the dialect and formatting parameters, see section Dialects and Formatting Parameters.Each row read from the csv file is returned as a list of strings. No automatic data type conversion is performed unless the
QUOTE_NONNUMERIC
format option is specified (in which case unquoted fields are transformed into floats).A short usage example:
>>> import csv >>> with open('eggs.csv', newline='') as csvfile: ... spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|') ... for row in spamreader: ... print(', '.join(row)) Spam, Spam, Spam, Spam, Spam, Baked Beans Spam, Lovely Spam, Wonderful Spam
- csv.writer(csvfile, dialect='excel', **fmtparams)¶
Return a writer object responsible for converting the user’s data into delimited strings on the given file-like object. csvfile can be any object with a
write()
method. If csvfile is a file object, it should be opened withnewline=''
[1]. An optional dialect parameter can be given which is used to define a set of parameters specific to a particular CSV dialect. It may be an instance of a subclass of theDialect
class or one of the strings returned by thelist_dialects()
function. The other optional fmtparams keyword arguments can be given to override individual formatting parameters in the current dialect. For full details about dialects and formatting parameters, see the Dialects and Formatting Parameters section. To make it as easy as possible to interface with modules which implement the DB API, the valueNone
is written as the empty string. While this isn’t a reversible transformation, it makes it easier to dump SQL NULL data values to CSV files without preprocessing the data returned from acursor.fetch*
call. All other non-string data are stringified withstr()
before being written.A short usage example:
import csv with open('eggs.csv', 'w', newline='') as csvfile: spamwriter = csv.writer(csvfile, delimiter=' ', quotechar='|', quoting=csv.QUOTE_MINIMAL) spamwriter.writerow(['Spam'] * 5 + ['Baked Beans']) spamwriter.writerow(['Spam', 'Lovely Spam', 'Wonderful Spam'])
- csv.register_dialect(name[, dialect[, **fmtparams]])¶
Associate dialect with name. name must be a string. The dialect can be specified either by passing a sub-class of
Dialect
, or by fmtparams keyword arguments, or both, with keyword arguments overriding parameters of the dialect. For full details about dialects and formatting parameters, see section Dialects and Formatting Parameters.
- csv.unregister_dialect(name)¶
Delete the dialect associated with name from the dialect registry. An
Error
is raised if name is not a registered dialect name.
- csv.get_dialect(name)¶
Return the dialect associated with name. An
Error
is raised if name is not a registered dialect name. This function returns an immutableDialect
.
- csv.list_dialects()¶
Return the names of all registered dialects.
- csv.field_size_limit([new_limit])¶
Returns the current maximum field size allowed by the parser. If new_limit is given, this becomes the new limit.
The csv
module defines the following classes:
- class csv.DictReader(f, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds)¶
Create an object that operates like a regular reader but maps the information in each row to a
dict
whose keys are given by the optional fieldnames parameter.The fieldnames parameter is a sequence. If fieldnames is omitted, the values in the first row of file f will be used as the fieldnames and will be omitted from the results. If fieldnames is provided, they will be used and the first row will be included in the results. Regardless of how the fieldnames are determined, the dictionary preserves their original ordering.
If a row has more fields than fieldnames, the remaining data is put in a list and stored with the fieldname specified by restkey (which defaults to
None
). If a non-blank row has fewer fields than fieldnames, the missing values are filled-in with the value of restval (which defaults toNone
).All other optional or keyword arguments are passed to the underlying
reader
instance.If the argument passed to fieldnames is an iterator, it will be coerced to a
list
.Zmienione w wersji 3.6: Returned rows are now of type
OrderedDict
.Zmienione w wersji 3.8: Returned rows are now of type
dict
.A short usage example:
>>> import csv >>> with open('names.csv', newline='') as csvfile: ... reader = csv.DictReader(csvfile) ... for row in reader: ... print(row['first_name'], row['last_name']) ... Eric Idle John Cleese >>> print(row) {'first_name': 'John', 'last_name': 'Cleese'}
- class csv.DictWriter(f, fieldnames, restval='', extrasaction='raise', dialect='excel', *args, **kwds)¶
Create an object which operates like a regular writer but maps dictionaries onto output rows. The fieldnames parameter is a
sequence
of keys that identify the order in which values in the dictionary passed to thewriterow()
method are written to file f. The optional restval parameter specifies the value to be written if the dictionary is missing a key in fieldnames. If the dictionary passed to thewriterow()
method contains a key not found in fieldnames, the optional extrasaction parameter indicates what action to take. If it is set to'raise'
, the default value, aValueError
is raised. If it is set to'ignore'
, extra values in the dictionary are ignored. Any other optional or keyword arguments are passed to the underlyingwriter
instance.Note that unlike the
DictReader
class, the fieldnames parameter of theDictWriter
class is not optional.If the argument passed to fieldnames is an iterator, it will be coerced to a
list
.A short usage example:
import csv with open('names.csv', 'w', newline='') as csvfile: fieldnames = ['first_name', 'last_name'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() writer.writerow({'first_name': 'Baked', 'last_name': 'Beans'}) writer.writerow({'first_name': 'Lovely', 'last_name': 'Spam'}) writer.writerow({'first_name': 'Wonderful', 'last_name': 'Spam'})
- class csv.Dialect¶
The
Dialect
class is a container class whose attributes contain information for how to handle doublequotes, whitespace, delimiters, etc. Due to the lack of a strict CSV specification, different applications produce subtly different CSV data.Dialect
instances define howreader
andwriter
instances behave.All available
Dialect
names are returned bylist_dialects()
, and they can be registered with specificreader
andwriter
classes through their initializer (__init__
) functions like this:import csv with open('students.csv', 'w', newline='') as csvfile: writer = csv.writer(csvfile, dialect='unix')
- class csv.excel¶
The
excel
class defines the usual properties of an Excel-generated CSV file. It is registered with the dialect name'excel'
.
- class csv.excel_tab¶
The
excel_tab
class defines the usual properties of an Excel-generated TAB-delimited file. It is registered with the dialect name'excel-tab'
.
- class csv.unix_dialect¶
The
unix_dialect
class defines the usual properties of a CSV file generated on UNIX systems, i.e. using'\n'
as line terminator and quoting all fields. It is registered with the dialect name'unix'
.Added in version 3.2.
- class csv.Sniffer¶
The
Sniffer
class is used to deduce the format of a CSV file.The
Sniffer
class provides two methods:- sniff(sample, delimiters=None)¶
Analyze the given sample and return a
Dialect
subclass reflecting the parameters found. If the optional delimiters parameter is given, it is interpreted as a string containing possible valid delimiter characters.
- has_header(sample)¶
Analyze the sample text (presumed to be in CSV format) and return
True
if the first row appears to be a series of column headers. Inspecting each column, one of two key criteria will be considered to estimate if the sample contains a header:the second through n-th rows contain numeric values
the second through n-th rows contain strings where at least one value’s length differs from that of the putative header of that column.
Twenty rows after the first row are sampled; if more than half of columns + rows meet the criteria,
True
is returned.
Informacja
This method is a rough heuristic and may produce both false positives and negatives.
An example for Sniffer
use:
with open('example.csv', newline='') as csvfile:
dialect = csv.Sniffer().sniff(csvfile.read(1024))
csvfile.seek(0)
reader = csv.reader(csvfile, dialect)
# ... process CSV file contents here ...
The csv
module defines the following constants:
- csv.QUOTE_MINIMAL¶
Instructs
writer
objects to only quote those fields which contain special characters such as delimiter, quotechar or any of the characters in lineterminator.
- csv.QUOTE_NONNUMERIC¶
Instructs
writer
objects to quote all non-numeric fields.Instructs
reader
objects to convert all non-quoted fields to type float.
- csv.QUOTE_NONE¶
Instructs
writer
objects to never quote fields. When the current delimiter occurs in output data it is preceded by the current escapechar character. If escapechar is not set, the writer will raiseError
if any characters that require escaping are encountered.Instructs
reader
objects to perform no special processing of quote characters.
- csv.QUOTE_NOTNULL¶
Instructs
writer
objects to quote all fields which are notNone
. This is similar toQUOTE_ALL
, except that if a field value isNone
an empty (unquoted) string is written.Instructs
reader
objects to interpret an empty (unquoted) field asNone
and to otherwise behave asQUOTE_ALL
.Added in version 3.12.
- csv.QUOTE_STRINGS¶
Instructs
writer
objects to always place quotes around fields which are strings. This is similar toQUOTE_NONNUMERIC
, except that if a field value isNone
an empty (unquoted) string is written.Instructs
reader
objects to interpret an empty (unquoted) string asNone
and to otherwise behave asQUOTE_NONNUMERIC
.Added in version 3.12.
Informacja
Due to a bug, constants QUOTE_NOTNULL
and QUOTE_STRINGS
do not affect behaviour of reader
objects.
This bug is fixed in Python 3.13.
The csv
module defines the following exception:
- exception csv.Error¶
Raised by any of the functions when an error is detected.
Dialects and Formatting Parameters¶
To make it easier to specify the format of input and output records, specific
formatting parameters are grouped together into dialects. A dialect is a
subclass of the Dialect
class containing various attributes
describing the format of the CSV file. When creating reader
or
writer
objects, the programmer can specify a string or a subclass of
the Dialect
class as the dialect parameter. In addition to, or instead
of, the dialect parameter, the programmer can also specify individual
formatting parameters, which have the same names as the attributes defined below
for the Dialect
class.
Dialects support the following attributes:
- Dialect.delimiter¶
A one-character string used to separate fields. It defaults to
','
.
- Dialect.doublequote¶
Controls how instances of quotechar appearing inside a field should themselves be quoted. When
True
, the character is doubled. WhenFalse
, the escapechar is used as a prefix to the quotechar. It defaults toTrue
.On output, if doublequote is
False
and no escapechar is set,Error
is raised if a quotechar is found in a field.
- Dialect.escapechar¶
A one-character string used by the writer to escape the delimiter if quoting is set to
QUOTE_NONE
and the quotechar if doublequote isFalse
. On reading, the escapechar removes any special meaning from the following character. It defaults toNone
, which disables escaping.Zmienione w wersji 3.11: An empty escapechar is not allowed.
- Dialect.lineterminator¶
The string used to terminate lines produced by the
writer
. It defaults to'\r\n'
.Informacja
The
reader
is hard-coded to recognise either'\r'
or'\n'
as end-of-line, and ignores lineterminator. This behavior may change in the future.
- Dialect.quotechar¶
A one-character string used to quote fields containing special characters, such as the delimiter or quotechar, or which contain new-line characters. It defaults to
'"'
.Zmienione w wersji 3.11: An empty quotechar is not allowed.
- Dialect.quoting¶
Controls when quotes should be generated by the writer and recognised by the reader. It can take on any of the QUOTE_* constants and defaults to
QUOTE_MINIMAL
.
Reader Objects¶
Reader objects (DictReader
instances and objects returned by the
reader()
function) have the following public methods:
- csvreader.__next__()¶
Return the next row of the reader’s iterable object as a list (if the object was returned from
reader()
) or a dict (if it is aDictReader
instance), parsed according to the currentDialect
. Usually you should call this asnext(reader)
.
Reader objects have the following public attributes:
- csvreader.dialect¶
A read-only description of the dialect in use by the parser.
- csvreader.line_num¶
The number of lines read from the source iterator. This is not the same as the number of records returned, as records can span multiple lines.
DictReader objects have the following public attribute:
- DictReader.fieldnames¶
If not passed as a parameter when creating the object, this attribute is initialized upon first access or when the first record is read from the file.
Writer Objects¶
writer
objects (DictWriter
instances and objects returned by
the writer()
function) have the following public methods. A row must be
an iterable of strings or numbers for writer
objects and a dictionary
mapping fieldnames to strings or numbers (by passing them through str()
first) for DictWriter
objects. Note that complex numbers are written
out surrounded by parens. This may cause some problems for other programs which
read CSV files (assuming they support complex numbers at all).
- csvwriter.writerow(row)¶
Write the row parameter to the writer’s file object, formatted according to the current
Dialect
. Return the return value of the call to the write method of the underlying file object.Zmienione w wersji 3.5: Added support of arbitrary iterables.
- csvwriter.writerows(rows)¶
Write all elements in rows (an iterable of row objects as described above) to the writer’s file object, formatted according to the current dialect.
Writer objects have the following public attribute:
- csvwriter.dialect¶
A read-only description of the dialect in use by the writer.
DictWriter objects have the following public method:
- DictWriter.writeheader()¶
Write a row with the field names (as specified in the constructor) to the writer’s file object, formatted according to the current dialect. Return the return value of the
csvwriter.writerow()
call used internally.Added in version 3.2.
Zmienione w wersji 3.8:
writeheader()
now also returns the value returned by thecsvwriter.writerow()
method it uses internally.
Przykłady¶
The simplest example of reading a CSV file:
import csv
with open('some.csv', newline='') as f:
reader = csv.reader(f)
for row in reader:
print(row)
Reading a file with an alternate format:
import csv
with open('passwd', newline='') as f:
reader = csv.reader(f, delimiter=':', quoting=csv.QUOTE_NONE)
for row in reader:
print(row)
The corresponding simplest possible writing example is:
import csv
with open('some.csv', 'w', newline='') as f:
writer = csv.writer(f)
writer.writerows(someiterable)
Since open()
is used to open a CSV file for reading, the file
will by default be decoded into unicode using the system default
encoding (see locale.getencoding()
). To decode a file
using a different encoding, use the encoding
argument of open:
import csv
with open('some.csv', newline='', encoding='utf-8') as f:
reader = csv.reader(f)
for row in reader:
print(row)
The same applies to writing in something other than the system default encoding: specify the encoding argument when opening the output file.
Registering a new dialect:
import csv
csv.register_dialect('unixpwd', delimiter=':', quoting=csv.QUOTE_NONE)
with open('passwd', newline='') as f:
reader = csv.reader(f, 'unixpwd')
A slightly more advanced use of the reader — catching and reporting errors:
import csv, sys
filename = 'some.csv'
with open(filename, newline='') as f:
reader = csv.reader(f)
try:
for row in reader:
print(row)
except csv.Error as e:
sys.exit('file {}, line {}: {}'.format(filename, reader.line_num, e))
And while the module doesn’t directly support parsing strings, it can easily be done:
import csv
for row in csv.reader(['one,two,three']):
print(row)
Przypisy