csv — CSV File Reading and Writing
New in version 2.3.
The so-called CSV (Comma Separated Values) format is the most common import and
export format for spreadsheets and databases. There is no “CSV standard”, so
the format is operationally defined by the many applications which read and
write it. The lack of a 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.
Note
This version of the csv module doesn’t support Unicode input. Also,
there are currently some issues regarding ASCII NUL characters. Accordingly,
all input should be UTF-8 or printable ASCII to be safe; see the examples in
section Examples. These restrictions will be removed in the future.
See also
- 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'][, fmtparam])
Return a reader object which will iterate over lines in the given csvfile.
csvfile can be any object which supports the iterator protocol and returns a
string each time its next() method is called — file objects and list
objects are both suitable. If csvfile is a file object, it must be opened
with the ‘b’ flag on platforms where that makes a difference. 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
the Dialect class or one of the strings returned by the
list_dialects() function. The other optional fmtparam 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.
All data read are returned as strings. No automatic data type conversion is
performed.
A short usage example:
>>> import csv
>>> spamReader = csv.reader(open('eggs.csv'), delimiter=' ', quotechar='|')
>>> for row in spamReader:
... print ', '.join(row)
Spam, Spam, Spam, Spam, Spam, Baked Beans
Spam, Lovely Spam, Wonderful Spam
Changed in version 2.5: The parser is now stricter with respect to multi-line quoted fields. Previously,
if a line ended within a quoted field without a terminating newline character, a
newline would be inserted into the returned field. This behavior caused problems
when reading files which contained carriage return characters within fields.
The behavior was changed to return the field without inserting newlines. As a
consequence, if newlines embedded within fields are important, the input should
be split into lines in a manner which preserves the newline characters.
-
csv.writer(csvfile[, dialect='excel'][, fmtparam])
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 must be opened with the
‘b’ flag on platforms where that makes a difference. 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 the
Dialect class or one of the strings returned by the
list_dialects() function. The other optional fmtparam 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. To make it
as easy as possible to interface with modules which implement the DB API, the
value None 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 a cursor.fetch* call.
All other non-string data are stringified with str() before being written.
A short usage example:
>>> import csv
>>> spamWriter = csv.writer(open('eggs.csv', 'w'), delimiter=' ',
... quotechar='|', quoting=QUOTE_MINIMAL)
>>> spamWriter.writerow(['Spam'] * 5 + ['Baked Beans'])
>>> spamWriter.writerow(['Spam', 'Lovely Spam', 'Wonderful Spam'])
-
csv.register_dialect(name[, dialect][, fmtparam])
- Associate dialect with name. name must be a string or Unicode object. The
dialect can be specified either by passing a sub-class of Dialect, or
by fmtparam keyword arguments, or both, with keyword arguments overriding
parameters of the dialect. For full details about the dialect 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.
Changed in version 2.5: This function now returns an immutable Dialect. Previously an
instance of the requested dialect was returned. Users could modify the
underlying class, changing the behavior of active readers and writers.
-
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.
New in version 2.5.
The csv module defines the following classes:
-
class csv.DictReader(csvfile[, fieldnames=None[, restkey=None[, restval=None[, dialect='excel'[, *args, **kwds]]]]])
- Create an object which operates like a regular reader but maps the information
read into a dict whose keys are given by the optional fieldnames parameter.
If the fieldnames parameter is omitted, the values in the first row of the
csvfile will be used as the fieldnames. If the row read has fewer fields than
the fieldnames sequence, the value of restval will be used as the default
value. If the row read has more fields than the fieldnames sequence, the
remaining data is added as a sequence keyed by the value of restkey. If the
row read has fewer fields than the fieldnames sequence, the remaining keys take
the value of the optional restval parameter. Any other optional or keyword
arguments are passed to the underlying reader instance.
-
class csv.DictWriter(csvfile, 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 identifies the order in which values in
the dictionary passed to the writerow() method are written to the
csvfile. The optional restval parameter specifies the value to be written
if the dictionary is missing a key in fieldnames. If the dictionary passed to
the writerow() method contains a key not found in fieldnames, the
optional extrasaction parameter indicates what action to take. If it is set
to 'raise' a ValueError 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 underlying writer instance.
Note that unlike the DictReader class, the fieldnames parameter of
the DictWriter is not optional. Since Python’s dict objects
are not ordered, there is not enough information available to deduce the order
in which the row should be written to the csvfile.
-
class csv.Dialect
- The Dialect class is a container class relied on primarily for its
attributes, which are used to define the parameters for a specific
reader or writer instance.
-
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.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.
- 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.
An example for Sniffer use:
csvfile = open("example.csv")
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_ALL
- Instructs writer objects to quote all fields.
-
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 the reader 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 raise Error if
any characters that require escaping are encountered.
Instructs reader to perform no special processing of quote characters.
The csv module defines the following exception:
-
exception csv.Error
- Raised by any of the functions when an error is detected.
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, parsed according
to the current dialect.
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.
New in version 2.5.
DictReader objects have the following public attribute:
-
csvreader.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.
Changed in version 2.6.
Writer Objects
Writer objects (DictWriter instances and objects returned by
the writer() function) have the following public methods. A row must be
a sequence 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.
-
csvwriter.writerows(rows)
- Write all the rows parameters (a list 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.
Examples
The simplest example of reading a CSV file:
import csv
reader = csv.reader(open("some.csv", "rb"))
for row in reader:
print row
Reading a file with an alternate format:
import csv
reader = csv.reader(open("passwd", "rb"), delimiter=':', quoting=csv.QUOTE_NONE)
for row in reader:
print row
The corresponding simplest possible writing example is:
import csv
writer = csv.writer(open("some.csv", "wb"))
writer.writerows(someiterable)
Registering a new dialect:
import csv
csv.register_dialect('unixpwd', delimiter=':', quoting=csv.QUOTE_NONE)
reader = csv.reader(open("passwd", "rb"), 'unixpwd')
A slightly more advanced use of the reader — catching and reporting errors:
import csv, sys
filename = "some.csv"
reader = csv.reader(open(filename, "rb"))
try:
for row in reader:
print row
except csv.Error, e:
sys.exit('file %s, line %d: %s' % (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
The csv module doesn’t directly support reading and writing Unicode, but
it is 8-bit-clean save for some problems with ASCII NUL characters. So you can
write functions or classes that handle the encoding and decoding for you as long
as you avoid encodings like UTF-16 that use NULs. UTF-8 is recommended.
unicode_csv_reader() below is a generator that wraps csv.reader
to handle Unicode CSV data (a list of Unicode strings). utf_8_encoder()
is a generator that encodes the Unicode strings as UTF-8, one string (or row) at
a time. The encoded strings are parsed by the CSV reader, and
unicode_csv_reader() decodes the UTF-8-encoded cells back into Unicode:
import csv
def unicode_csv_reader(unicode_csv_data, dialect=csv.excel, **kwargs):
# csv.py doesn't do Unicode; encode temporarily as UTF-8:
csv_reader = csv.reader(utf_8_encoder(unicode_csv_data),
dialect=dialect, **kwargs)
for row in csv_reader:
# decode UTF-8 back to Unicode, cell by cell:
yield [unicode(cell, 'utf-8') for cell in row]
def utf_8_encoder(unicode_csv_data):
for line in unicode_csv_data:
yield line.encode('utf-8')
For all other encodings the following UnicodeReader and
UnicodeWriter classes can be used. They take an additional encoding
parameter in their constructor and make sure that the data passes the real
reader or writer encoded as UTF-8:
import csv, codecs, cStringIO
class UTF8Recoder:
"""
Iterator that reads an encoded stream and reencodes the input to UTF-8
"""
def __init__(self, f, encoding):
self.reader = codecs.getreader(encoding)(f)
def __iter__(self):
return self
def next(self):
return self.reader.next().encode("utf-8")
class UnicodeReader:
"""
A CSV reader which will iterate over lines in the CSV file "f",
which is encoded in the given encoding.
"""
def __init__(self, f, dialect=csv.excel, encoding="utf-8", **kwds):
f = UTF8Recoder(f, encoding)
self.reader = csv.reader(f, dialect=dialect, **kwds)
def next(self):
row = self.reader.next()
return [unicode(s, "utf-8") for s in row]
def __iter__(self):
return self
class UnicodeWriter:
"""
A CSV writer which will write rows to CSV file "f",
which is encoded in the given encoding.
"""
def __init__(self, f, dialect=csv.excel, encoding="utf-8", **kwds):
# Redirect output to a queue
self.queue = cStringIO.StringIO()
self.writer = csv.writer(self.queue, dialect=dialect, **kwds)
self.stream = f
self.encoder = codecs.getincrementalencoder(encoding)()
def writerow(self, row):
self.writer.writerow([s.encode("utf-8") for s in row])
# Fetch UTF-8 output from the queue ...
data = self.queue.getvalue()
data = data.decode("utf-8")
# ... and reencode it into the target encoding
data = self.encoder.encode(data)
# write to the target stream
self.stream.write(data)
# empty queue
self.queue.truncate(0)
def writerows(self, rows):
for row in rows:
self.writerow(row)
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