Thuban/Model/table.py

# Copyright (c) 2001, 2002, 2003 by Intevation GmbH
# Authors:
# Bernhard Herzog <[email protected]>
#
# This program is free software under the GPL (>=v2)
# Read the file COPYING coming with Thuban for details.

"""
Classes for handling tables of data.
"""

__version__ = "$Revision$"

import dbflib

# the field types supported by a Table instance.
FIELDTYPE_INT = "int"
FIELDTYPE_STRING = "string"
FIELDTYPE_DOUBLE = "double"


# map the dbflib constants for the field types to our constants
dbflib_fieldtypes = {dbflib.FTString: FIELDTYPE_STRING,
                     dbflib.FTInteger: FIELDTYPE_INT,
                     dbflib.FTDouble: FIELDTYPE_DOUBLE}

class DBFTable:

    """
    Table interface for the data in a DBF file
    """

    # Implementation strategy regarding writing to a DBF file:
    #
    # Most of the time Thuban only needs to read from a table and it is
    # important that Thuban can work with read-only files. Therefore the
    # DBF file is opened only for reading initially. Only when
    # write_record is called we try to open the DBF file for writing as
    # well. If that succeeds the read/write DBF file will be used for
    # all IO afterwards.
    #
    # It's important to use the same DBF file object for both reading
    # and writing to make sure that reading a records after writing
    # returns the new values. With two separate objects this wouldn't
    # work because a DBF file object buffers some data

    def __init__(self, filename):
        self.filename = filename
        self.dbf = dbflib.DBFFile(filename)

        # If true, self.dbf is open for writing.
        self._writable = 0

    def Destroy(self):
        self.dbf.close()
        self.dbf = None

    def record_count(self):
        """Return the number of records"""
        return self.dbf.record_count()

    def field_count(self):
        """Return the number of fields in a record"""
        return self.dbf.field_count()

    def field_info(self, field):
        """Return a tuple (type, name, width, prec) for the field no. field

        type is the data type of the field, name the name, width the
        field width in characters and prec the decimal precision.
        """
        type, name, width, prec = self.dbf.field_info(field)
        type = dbflib_fieldtypes[type]
        return type, name, width, prec

    def field_info_by_name(self, fieldName):
        count = self.field_count()

        for i in range(count):
            info = self.field_info(i)
            if info[1] == fieldName:
                return info

        return None

    def field_range(self, fieldName):
        """Finds the first occurences of the minimum and maximum values 
        in the table for the given field.

        This assumes that the standard comparison operators (<, >, etc.)
        will work for the given data.

        Returns a tuple ((min, rec), (max, rec)) where:
            min is the minimum value
            max is the maximum value
            rec is the record number where the value was found. One
                should check that the record number of min is not
                the same as the record number of max.

        Returns None if there are no records

        """


        count = self.record_count()

        if count == 0:
            return None

        rec = self.read_record(0)

        min = rec[fieldName]
        min_rec = 0

        max = rec[fieldName]
        max_rec = 0

        for i in range(1, count):
            rec = self.read_record(i)
            data = rec[fieldName]

            if data < min: 
                min = data
                min_rec = rec
            elif data > max: 
                max = data
                max_rec = rec

        return ((min, min_rec), (max, max_rec))

    def GetUniqueValues(self, fieldName):
        """Return a list of all unique entries in the table for the given
        field name.
        """

        dict = {}

        for i in range(0, self.record_count()):
            rec = self.read_record(i)
            data = rec[fieldName]

            if not dict.has_key(data):
                dict[data] = 0

        return dict.keys()

    def read_record(self, record):
        """Return the record no. record as a dict mapping field names to values
        """
        return self.dbf.read_record(record)

    def write_record(self, record, values):
        """Write the values into the record

        The values parameter may either be a dictionary or a sequence.

        If it's a dictionary the keys must be the names of the fields
        and their value must have a suitable type. Only the fields
        actually contained in the dictionary are written. Fields for
        which there's no item in the dict are not modified.

        If it's a sequence, all fields must be present in the right
        order.
        """
        if not self._writable:
            new_dbf = dbflib.DBFFile(self.filename, "r+b")
            self.dbf.close()
            self.dbf = new_dbf
            self._writable = 1
        self.dbf.write_record(record, values)
        self.dbf.commit()


# Temporary backwards compatibility
Table = DBFTable
1	# Copyright (c) 2001, 2002, 2003 by Intevation GmbH
2	# Authors:
3	# Bernhard Herzog <[email protected]>
4	#
5	# This program is free software under the GPL (>=v2)
6	# Read the file COPYING coming with Thuban for details.
7
8	"""
9	Classes for handling tables of data.
10	"""
11
12	__version__ = "$Revision$"
13
14	import dbflib
15
16	# the field types supported by a Table instance.
17	FIELDTYPE_INT = "int"
18	FIELDTYPE_STRING = "string"
19	FIELDTYPE_DOUBLE = "double"
20
21
22	# map the dbflib constants for the field types to our constants
23	dbflib_fieldtypes = {dbflib.FTString: FIELDTYPE_STRING,
24	dbflib.FTInteger: FIELDTYPE_INT,
25	dbflib.FTDouble: FIELDTYPE_DOUBLE}
26
27	class DBFTable:
28
29	"""
30	Table interface for the data in a DBF file
31	"""
32
33	# Implementation strategy regarding writing to a DBF file:
34	#
35	# Most of the time Thuban only needs to read from a table and it is
36	# important that Thuban can work with read-only files. Therefore the
37	# DBF file is opened only for reading initially. Only when
38	# write_record is called we try to open the DBF file for writing as
39	# well. If that succeeds the read/write DBF file will be used for
40	# all IO afterwards.
41	#
42	# It's important to use the same DBF file object for both reading
43	# and writing to make sure that reading a records after writing
44	# returns the new values. With two separate objects this wouldn't
45	# work because a DBF file object buffers some data
46
47	def __init__(self, filename):
48	self.filename = filename
49	self.dbf = dbflib.DBFFile(filename)
50
51	# If true, self.dbf is open for writing.
52	self._writable = 0
53
54	def Destroy(self):
55	self.dbf.close()
56	self.dbf = None
57
58	def record_count(self):
59	"""Return the number of records"""
60	return self.dbf.record_count()
61
62	def field_count(self):
63	"""Return the number of fields in a record"""
64	return self.dbf.field_count()
65
66	def field_info(self, field):
67	"""Return a tuple (type, name, width, prec) for the field no. field
68
69	type is the data type of the field, name the name, width the
70	field width in characters and prec the decimal precision.
71	"""
72	type, name, width, prec = self.dbf.field_info(field)
73	type = dbflib_fieldtypes[type]
74	return type, name, width, prec
75
76	def field_info_by_name(self, fieldName):
77	count = self.field_count()
78
79	for i in range(count):
80	info = self.field_info(i)
81	if info[1] == fieldName:
82	return info
83
84	return None
85
86	def field_range(self, fieldName):
87	"""Finds the first occurences of the minimum and maximum values
88	in the table for the given field.
89
90	This assumes that the standard comparison operators (<, >, etc.)
91	will work for the given data.
92
93	Returns a tuple ((min, rec), (max, rec)) where:
94	min is the minimum value
95	max is the maximum value
96	rec is the record number where the value was found. One
97	should check that the record number of min is not
98	the same as the record number of max.
99
100	Returns None if there are no records
101
102	"""
103
104
105	count = self.record_count()
106
107	if count == 0:
108	return None
109
110	rec = self.read_record(0)
111
112	min = rec[fieldName]
113	min_rec = 0
114
115	max = rec[fieldName]
116	max_rec = 0
117
118	for i in range(1, count):
119	rec = self.read_record(i)
120	data = rec[fieldName]
121
122	if data < min:
123	min = data
124	min_rec = rec
125	elif data > max:
126	max = data
127	max_rec = rec
128
129	return ((min, min_rec), (max, max_rec))
130
131	def GetUniqueValues(self, fieldName):
132	"""Return a list of all unique entries in the table for the given
133	field name.
134	"""
135
136	dict = {}
137
138	for i in range(0, self.record_count()):
139	rec = self.read_record(i)
140	data = rec[fieldName]
141
142	if not dict.has_key(data):
143	dict[data] = 0
144
145	return dict.keys()
146
147	def read_record(self, record):
148	"""Return the record no. record as a dict mapping field names to values
149	"""
150	return self.dbf.read_record(record)
151
152	def write_record(self, record, values):
153	"""Write the values into the record
154
155	The values parameter may either be a dictionary or a sequence.
156
157	If it's a dictionary the keys must be the names of the fields
158	and their value must have a suitable type. Only the fields
159	actually contained in the dictionary are written. Fields for
160	which there's no item in the dict are not modified.
161
162	If it's a sequence, all fields must be present in the right
163	order.
164	"""
165	if not self._writable:
166	new_dbf = dbflib.DBFFile(self.filename, "r+b")
167	self.dbf.close()
168	self.dbf = new_dbf
169	self._writable = 1
170	self.dbf.write_record(record, values)
171	self.dbf.commit()
172
173
174
175	# Temporary backwards compatibility
176	Table = DBFTable
Name	Value
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svn:keywords	Author Date Id Revision