ANN: dbf.py 0.94.003

Thu Jul 26 15:31:01 EDT 2012

A few more bug fixes, and I actually included the documentation this 
time. :) It can be found at http://python.org/pypi/dbf, and has been 
tested on CPythons 2.4 - 2.7, and PyPy 1.8.
dbf v0.94.003
=============
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; suports the sequence access and 'with'
protocols. Temporary tables can also live entirely in memory.
Record -- repesents 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.
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; while bool(None) is False, bool(Unknown)
 raises a TypeError; __index__ of Unknown is 2
 Quantum --> similar to Logical, but implements boolean algebra (I 
think)
Whirlwind Tour
--------------
import datetime
import dbf
table = dbf.Table(':test:', 'name C(25); age N(3,0); birth D; qualified L')
table.open()
for datum in (
 ('Spanky', 7, dbf.Date.fromymd('20010315'), False),
 ('Spunky', 23, dbf.Date(1989, 07, 23), True),
 ('Sparky', 99, dbf.Date(), dbf.Unknown),
 ):
 table.append(datum)
for record in table:
 print record
 print '--------'
 print record[0:3]
 print record['name':'birth']
 print [record.name, record.age, record.birth]
 print '--------'
custom = table.new(
 filename='test_on_disk',
 default_data_types=dict(C=dbf.Char, D=dbf.Date, L=dbf.Logical),
 )
with custom: # automatically opened and closed
 for record in table:
 custom.append(record)
 for record in custom:
 dbf.write(record, name=record.name.upper())
 print record
 print '--------'
 print record[0:3]
 print record['name':'birth']
 print [record.name, record.age, record.birth]
 print '--------'
table.close()