dbf

dbf (also known as python dbase) is a module for reading/writing dBase III, FP, VFP, and Clipper .dbf database files. It's an ancient format that still finds lots of use (the most common I'm aware of is retrieving legacy data so it can be stored in a newer database system; other uses include GIS, stand-alone programs such as Family History, Personal Finance, etc.).

Highlights

Table -- represents a single .dbf/.dbt (or .fpt) file combination and provides access to records; supports the sequence access and 'with' protocols. Temporary tables can also live entirely in memory.

Record -- represents a single record/row in the table, with field access returning native or custom data types; supports the sequence, mapping, attribute access (with the field names as the attributes), and 'with' protocols. Updates to a record object are reflected on disk either immediately (using gather() or write()), or at the end of a 'with' statement.

Index -- nonpersistent index for a table.

Fields::

dBase III (Null not supported)

    Character --> unicode
    Date      --> datetime.date or None
    Logical   --> bool or None
    Memo      --> unicode or None
    Numeric   --> int/float depending on field definition or None

    Float     --> same as numeric

Clipper (Null not supported)

    Character --> unicode  (character fields can be up to 65,519)

Foxpro (Null supported)

    General   --> str (treated as binary)
    Picture   --> str (treated as binary)

Visual Foxpro (Null supported)

    Currency  --> decimal.Decimal
    douBle    --> float
    Integer   --> int
    dateTime  --> datetime.datetime

If a field is uninitialized (Date, Logical, Numeric, Memo, General,
Picture) then None is returned for the value.

Custom data types::

Null     -->  used to support Null values

Char     -->  unicode type that auto-trims trailing whitespace, and
              ignores trailing whitespace for comparisons

Date     -->  date object that allows for no date

DateTime -->  datetime object that allows for no datetime

Time     -->  time object that allows for no time

Logical  -->  adds Unknown state to bool's: instead of True/False/None,
              values are Truth, Falsth, and Unknown, with appropriate
              tri-state logic; just as bool(None) is False, bool(Unknown)
              is also False;  the numerical values of Falsth, Truth, and
              Unknown is 0, 1, 2

Quantum  -->  similar to Logical, but implements boolean algebra (I think).
              Has states of Off, On, and Other.  Other has no boolean nor
              numerical value, and attempts to use it as such will raise
              an exception

Whirlwind Tour

Reading a DBF:

import dbf

dbf_filename = "some-file.dbf"
encoding = "utf8"
table = dbf.Table(dbf_filename, codepage=encoding, on_disk=True)
field_names = table.field_names
table.open()
for record in table:
    row = {field_name: record[field_name] for field_name in field_names}
    print(row)  # You can use row.field_name to get each field's data also

Creating/writing a DBF:

import datetime
import dbf

# create an in-memory table
table = dbf.Table(
        filename='test',
        field_specs='name C(25); age N(3,0); birth D; qualified L',
        on_disk=False,
        )
table.open(dbf.READ_WRITE)

# add some records to it
for datum in (
        ('Spanky', 7, dbf.Date.fromymd('20010315'), False),
        ('Spunky', 23, dbf.Date(1989, 7, 23), True),
        ('Sparky', 99, dbf.Date(), dbf.Unknown),
        ):
    table.append(datum)

# iterate over the table, and print the records
for record in table:
    print(record)
    print('--------')
    print(record[0:3])
    print([record.name, record.age, record.birth])
    print('--------')

# make a copy of the test table (structure, not data)
custom = table.new(
        filename='test_on_disk.dbf',
        default_data_types=dict(C=dbf.Char, D=dbf.Date, L=dbf.Logical),
        )

# automatically opened and closed
with custom:
    # copy records from test to custom
    for record in table:
        custom.append(record)
    # modify each record in custom (could have done this in prior step)
    for record in custom:
        dbf.write(record, name=record.name.upper())
        # and print the modified record
        print(record)
        print('--------')
        print(record[0:3])
        print([record.name, record.age, record.birth])
        print('--------')

table.close()