Field Types

Supported Field Types

: Field type Converted to
+ autoincrement int
@ time datetime.datetime
0 flags byte string (int before 2.0)
B double float (Visual FoxPro)
B binary memo byte string (other versions)
C text unicode string
D date datetime.date or None
F float float
G OLE object byte string
I integer int
L logical True, False or None
M memo unicode string (memo), byte string (picture or object) or None
N numeric int, float or None
O double float (floats are doubles in Python)
P picture byte string
T time datetime.datetime
V varchar unicode string
Y currency decimal.Decimal

Text values (‘C’) can be up to 65535 bytes long. DBF was originally limited to 255 bytes but some vendors have reused the decimal_count field to get another byte for field length.

The ‘B’ field type is used to store double precision (64 bit) floats in Visual FoxPro databases and binary memos in other versions. dbfread will look at the database version to parse and return the correct data type.

The ‘0’ field type is used for ‘_NullFlags’ in Visual FoxPro. It was mistakenly though to always be one byte long and was interpreted as an integer. From 2.0.1 on it is returned as a byte string.

The ‘V’ field is an alternative character field used by Visual FoxPro. The binary version of this field is not yet supported. (See https://msdn.microsoft.com/en-us/library/st4a0s68%28VS.80%29.aspx for more.)

Adding Custom Field Types

You can add new field types by subclassing FieldParser. For example:

"""
Add custom field parsing by subclassing FieldParser.
"""

from dbfread import DBF, FieldParser

class CustomFieldParser(FieldParser):
    def parseC(self, field, data):
        # Return strings reversed.
        return data.rstrip(b' 0').decode()[::-1]

for record in DBF('files/people.dbf', parserclass=CustomFieldParser):
    print(record['NAME'])

The FieldParser object has the following attributes:

self.table
A reference to the DBF objects. This can be used to get the headers to find dbversion and other things.
self.encoding
The character encoding. (A a shortcut for self.table.encoding to speed things up a bit.)
self.char_decode_errors
Error handling scheme to use while decoding. (A shortcut for self.table.char_decode_errors.)
self.dbversion
The database version as an integer. (A shortcut for self.table.header.dbversion.)
self.get_memo(index)

Returns a memo from the memo file using the index stored in the field data.

This returns a byte string (bytes) which you can then decode.

For Visual FoxPro (.FPT) files it will return TextMemo, PictureMemo and ObjectMemo objects depending on the type of memo. These are all subclasses of bytes so the type is only used to annotate the memo type without breaking code elsewhere. The full class tree:

bytes
  VFPMemo
    TextMemo
    BinaryMemo
      PictureMemo
      ObjectMemo

These are all found in dbfread.memo.

self.decode_text(text)

This will decode the text using the correct encoding and the user supplied char_decode_errors option.

Special Characters in Field Type Names

For a field type like ‘+’ (autoincrement) the method would be named parse+(). Since this is not allowed in Python you can instead use its ASCII value in hexadecimal. For example, the ‘+’ parser is called parse3F().

You can name your method with:

>>> 'parse' + format(ord('?'), 'x').upper()
'parse3F'

Just replace '?' with your field type.

InvalidValue

The field parser will normally raise ValueError when invalid values are encountered. If instead you want them returned as raw data you can do this:

"""
A field parser that returns invalid values as InvalidValue objects
instead of raising ValueError.
"""
from dbfread import DBF, FieldParser, InvalidValue

class MyFieldParser(FieldParser):
    def parse(self, field, data):
        try:
            return FieldParser.parse(self, field, data)
        except ValueError:
            return InvalidValue(data)

table = DBF('files/invalid_value.dbf', parserclass=MyFieldParser)
for i, record in enumerate(table):
    for name, value in record.items():
        if isinstance(value, InvalidValue):
            print('records[{}][{!r}] == {!r}'.format(i, name, value))

InvalidValue is a subclass of bytes, and allows you to tell invalid data apart from valid data that happens to be byte strings. You can test for this with:

isinstance(value, InvalidData)

You can also tell from the repr() string:

>>> value
InvalidData(b'not a number')