13.1. csv — CSV File Reading and Writing — Python 2.7.2 documentation (2024)

New in version 2.3.

The so-called CSV (Comma Separated Values) format is the most common import andexport format for spreadsheets and databases. There is no “CSV standard”, sothe format is operationally defined by the many applications which read andwrite it. The lack of a standard means that subtle differences often exist inthe data produced and consumed by different applications. These differences canmake it annoying to process CSV files from multiple sources. Still, while thedelimiters and quoting characters vary, the overall format is similar enoughthat it is possible to write a single module which can efficiently manipulatesuch data, hiding the details of reading and writing the data from theprogrammer.

The csv module implements classes to read and write tabular data in CSVformat. It allows programmers to say, “write this data in the format preferredby Excel,” or “read data from this file which was generated by Excel,” withoutknowing the precise details of the CSV format used by Excel. Programmers canalso describe the CSV formats understood by other applications or define theirown special-purpose CSV formats.

The csv module’s reader and writer objects read andwrite sequences. Programmers can also read and write data in dictionary formusing 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 insection Examples. These restrictions will be removed in the future.

13.1.1. 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 astring each time its next() method is called — file objects and listobjects are both suitable. If csvfile is a file object, it must be openedwith the ‘b’ flag on platforms where that makes a difference. An optionaldialect parameter can be given which is used to define a set of parametersspecific to a particular CSV dialect. It may be an instance of a subclass ofthe Dialect class or one of the strings returned by thelist_dialects() function. The other optional fmtparam keyword argumentscan be given to override individual formatting parameters in the currentdialect. For full details about the dialect and formatting parameters, seesection Dialects and Formatting Parameters.

Each row read from the csv file is returned as a list of strings. Noautomatic data type conversion is performed.

A short usage example:

>>> import csv>>> spamReader = csv.reader(open('eggs.csv', 'rb'), delimiter=' ', quotechar='|')>>> for row in spamReader:...  print ', '.join(row)Spam, Spam, Spam, Spam, Spam, Baked BeansSpam, 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, anewline would be inserted into the returned field. This behavior caused problemswhen reading files which contained carriage return characters within fields.The behavior was changed to return the field without inserting newlines. As aconsequence, if newlines embedded within fields are important, the input shouldbe 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 delimitedstrings on the given file-like object. csvfile can be any object with awrite() method. If csvfile is a file object, it must be opened with the‘b’ flag on platforms where that makes a difference. An optional dialectparameter can be given which is used to define a set of parameters specific to aparticular 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 fmtparam keyword argumentscan be given to override individual formatting parameters in the currentdialect. For full details about the dialect and formatting parameters, seesection Dialects and Formatting Parameters. To make itas easy as possible to interface with modules which implement the DB API, thevalue None is written as the empty string. While this isn’t areversible transformation, it makes it easier to dump SQL NULL data values toCSV 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', 'wb'), delimiter=' ',...  quotechar='|', quoting=csv.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. Thedialect can be specified either by passing a sub-class of Dialect, orby fmtparam keyword arguments, or both, with keyword arguments overridingparameters of the dialect. For full details about the dialect and formattingparameters, see section Dialects and Formatting Parameters.

csv.unregister_dialect(name)¶: Delete the dialect associated with name from the dialect registry. AnError 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 nameis not a registered dialect name.

Changed in version 2.5: This function now returns an immutable Dialect. Previously aninstance of the requested dialect was returned. Users could modify theunderlying 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 isgiven, 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 informationread 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 thecsvfile will be used as the fieldnames. If the row read has more fieldsthan the fieldnames sequence, the remaining data is added as a sequencekeyed by the value of restkey. If the row read has fewer fields than thefieldnames sequence, the remaining keys take the value of the optionalrestval parameter. Any other optional or keyword arguments are passed tothe 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 ontooutput rows. The fieldnames parameter identifies the order in which values inthe dictionary passed to the writerow() method are written to thecsvfile. The optional restval parameter specifies the value to be writtenif the dictionary is missing a key in fieldnames. If the dictionary passed tothe writerow() method contains a key not found in fieldnames, theoptional extrasaction parameter indicates what action to take. If it is setto 'raise' a ValueError is raised. If it is set to 'ignore',extra values in the dictionary are ignored. Any other optional or keywordarguments are passed to the underlying writer instance.

Note that unlike the DictReader class, the fieldnames parameter ofthe DictWriter is not optional. Since Python’s dict objectsare not ordered, there is not enough information available to deduce the orderin which the row should be written to the csvfile.

class csv.Dialect¶: The Dialect class is a container class relied on primarily for itsattributes, which are used to define the parameters for a specificreader or writer instance.

class csv.excel¶: The excel class defines the usual properties of an Excel-generated CSVfile. It is registered with the dialect name 'excel'.

class csv.excel_tab¶: The excel_tab class defines the usual properties of an Excel-generatedTAB-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 subclassreflecting the parameters found. If the optional delimiters parameteris given, it is interpreted as a string containing possible validdelimiter characters.

has_header(sample)¶: Analyze the sample text (presumed to be in CSV format) and returnTrue if the first row appears to be a series of column headers.

An example for Sniffer use:

csvfile = open("example.csv", "rb")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 containspecial characters such as delimiter, quotechar or any of the characters inlineterminator.

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 currentdelimiter occurs in output data it is preceded by the current escapecharcharacter. If escapechar is not set, the writer will raise Error ifany 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.

13.1.2. Dialects and Formatting Parameters¶

To make it easier to specify the format of input and output records, specificformatting parameters are grouped together into dialects. A dialect is asubclass of the Dialect class having a set of specific methods and asingle validate() method. When creating reader orwriter objects, the programmer can specify a string or a subclass ofthe Dialect class as the dialect parameter. In addition to, or insteadof, the dialect parameter, the programmer can also specify individualformatting parameters, which have the same names as the attributes defined belowfor the Dialect class.

13.1.3. Reader Objects¶

Reader objects (DictReader instances and objects returned by thereader() function) have the following public methods:

csvreader.next()¶: Return the next row of the reader’s iterable object as a list, parsed accordingto 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 thenumber 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 isinitialized upon first access or when the first record is read from thefile.

Changed in version 2.6.

13.1.4. Writer Objects¶

Writer objects (DictWriter instances and objects returned bythe writer() function) have the following public methods. A row must bea sequence of strings or numbers for Writer objects and a dictionarymapping fieldnames to strings or numbers (by passing them through str()first) for DictWriter objects. Note that complex numbers are writtenout surrounded by parens. This may cause some problems for other programs whichread CSV files (assuming they support complex numbers at all).

csvwriter.writerow(row)¶: Write the row parameter to the writer’s file object, formatted according tothe current dialect.

csvwriter.writerows(rows)¶: Write all the rows parameters (a list of row objects as described above) tothe 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).

New in version 2.7.

13.1.5. Examples¶

The simplest example of reading a CSV file:

import csvwith open('some.csv', 'rb') as f: reader = csv.reader(f) for row in reader: print row

Reading a file with an alternate format:

import csvwith open('passwd', 'rb') 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 csvwith open('some.csv', 'wb') as f: writer = csv.writer(f) writer.writerows(someiterable)

Registering a new dialect:

import csvcsv.register_dialect('unixpwd', delimiter=':', quoting=csv.QUOTE_NONE)with open('passwd', 'rb') as f: reader = csv.reader(f, 'unixpwd')

A slightly more advanced use of the reader — catching and reporting errors:

import csv, sysfilename = 'some.csv'with open(filename, 'rb') as f: reader = csv.reader(f) 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 bedone:

import csvfor row in csv.reader(['one,two,three']): print row

The csv module doesn’t directly support reading and writing Unicode, butit is 8-bit-clean save for some problems with ASCII NUL characters. So you canwrite functions or classes that handle the encoding and decoding for you as longas you avoid encodings like UTF-16 that use NULs. UTF-8 is recommended.

unicode_csv_reader() below is a generator that wraps csv.readerto 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) ata time. The encoded strings are parsed by the CSV reader, andunicode_csv_reader() decodes the UTF-8-encoded cells back into Unicode:

import csvdef 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 andUnicodeWriter classes can be used. They take an additional encodingparameter in their constructor and make sure that the data passes the realreader or writer encoded as UTF-8:

import csv, codecs, cStringIOclass 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 selfclass 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)