# `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.

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', **fmtparams)

  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 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 the `Dialect` class or one of the strings returned by the `list_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 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 the `Dialect` class or one of the strings returned by the `list_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 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
      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 immutable `Dialect`.

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. 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 to `None`).

  All other optional or keyword arguments are passed to the underlying `reader` instance.

  Changed in version 3.6: Returned rows are now of type `OrderedDict`.

  Changed in version 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 the `writerow()` 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 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'`, the default value, 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` class is not optional.

  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 how `reader` and `writer` instances behave.

  All available `Dialect` names are returned by `list_dialects()`, and they can be registered with specific `reader` and `writer` 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'`.

  New 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.

  Note

  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_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.

## 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 having a set of specific methods and a single `validate()` method. 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. When `False`, the escapechar is used as a prefix to the quotechar. It defaults to `True`.

  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 is `False`. On reading, the escapechar removes any special meaning from the following character. It defaults to `None`, which disables escaping.

  Changed in version 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'`.

  Note

  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 `'"'`.

  Changed in version 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 (see section Module Contents) and defaults to `QUOTE_MINIMAL`.

Dialect.skipinitialspace

  When `True`, spaces immediately following the delimiter are ignored. The default is `False`.

Dialect.strict

  When `True`, raise exception `Error` on bad CSV input. The default is `False`.

## 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 a `DictReader` instance), parsed according to the current `Dialect`. Usually you should call this as `next(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.

  Changed in version 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.

  New in version 3.2.

  Changed in version 3.8: `writeheader()` now also returns the value returned by the `csvwriter.writerow()` method it uses internally.

## Examples

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)

Footnotes

1(1,2)

  If `newline=''` is not specified, newlines embedded inside quoted fields will not be interpreted correctly, and on platforms that use `\r\n` linendings on write an extra `\r` will be added. It should always be safe to specify `newline=''`, since the csv module does its own (universal) newline handling.