def from_xlrdcell(xlrd_cell, sheet, col, row):
value = xlrd_cell.value
cell_type = XLS_TYPES.get(xlrd_cell.ctype, StringType())
if cell_type == DateType(None):
if value == 0:
raise InvalidDateError
year, month, day, hour, minute, second = \
xlrd.xldate_as_tuple(value, sheet.book.datemode)
value = datetime(year, month, day, hour, minute, second)
messy_cell = XLSCell(value, type=cell_type)
messy_cell.sheet = sheet
messy_cell.xlrd_cell = xlrd_cell
messy_cell.xlrd_pos = (row, col
) # necessary for properties, note not (x,y)
return messy_cell
def raw(self, sample=False):
""" Iterate over all rows in this sheet. Types are automatically
converted according to the excel data types specified, including
conversion of excel dates, which are notoriously buggy. """
num_rows = self.sheet.get_highest_row()
for i in xrange(min(self.window, num_rows) if sample else num_rows):
row = []
for cell in self.sheet.rows[i]:
value = cell.value
if cell.is_date():
type = DateType(None)
elif cell.data_type == 'n':
type = IntegerType()
else:
type = StringType()
row.append(Cell(value, type=type))
yield row
def raw(self, sample=False):
""" Iterate over all rows in this sheet. Types are automatically
converted according to the excel data types specified, including
conversion of excel dates, which are notoriously buggy. """
num_rows = self.sheet.nrows
for i in xrange(min(self.window, num_rows) if sample else num_rows):
row = []
for j, cell in enumerate(self.sheet.row(i)):
value = cell.value
type = XLS_TYPES.get(cell.ctype, StringType())
if type == DateType(None):
if value == 0:
raise ValueError('Invalid date at "%s":%d,%d' %
(self.sheet.name, j + 1, i + 1))
year, month, day, hour, minute, second = \
xlrd.xldate_as_tuple(value, self.sheet.book.datemode)
value = datetime(year, month, day, hour, minute, second)
row.append(Cell(value, type=type))
yield row
from datetime import datetime
import xlrd
from messytables.core import RowSet, TableSet, Cell
from messytables.types import StringType, IntegerType, \
DateType, FloatType
XLS_TYPES = {
1: StringType(),
# NB: Excel does not distinguish floats from integers so we use floats
# We could try actual type detection between floats and ints later
# or use the excel format string info - see
# https://groups.google.com/forum/?fromgroups=#!topic/
# python-excel/cAQ1ndsCVxk
2: FloatType(),
3: DateType(None),
# this is actually boolean but we do not have a boolean type yet
4: IntegerType()
}
class XLSTableSet(TableSet):
"""An excel workbook wrapper object.
"""
def __init__(self,
fileobj=None,
filename=None,
window=None,
encoding=None):
'''Initilize the tableset.
from lxml import etree
from messytables.core import RowSet, TableSet, Cell
from messytables.types import (StringType, DecimalType, DateType)
ODS_NAMESPACES_TAG_MATCH = re.compile("(<office:document-content[^>]*>)",
re.MULTILINE)
ODS_TABLE_MATCH = re.compile(".*?(<table:table.*?<\/.*?:table>).*?",
re.MULTILINE)
ODS_TABLE_NAME = re.compile('.*?table:name=\"(.*?)\".*?')
ODS_ROW_MATCH = re.compile(".*?(<table:table-row.*?<\/.*?:table-row>).*?",
re.MULTILINE)
ODS_TYPES = {
'float': DecimalType(),
'date': DateType(None),
}
class ODSTableSet(TableSet):
"""
A wrapper around ODS files. Because they are zipped and the info we want
is in the zipped file as content.xml we must ensure that we either have
a seekable object (local file) or that we retrieve all of the content from
the remote URL.
"""
def __init__(self, fileobj, window=None):
'''Initialize the object.
:param fileobj: may be a file path or a file-like object. Note the
file-like object *must* be in binary mode and must be seekable (it will
VALUE_TYPE = 'value-type'
COLUMN_REPEAT = 'number-columns-repeated'
EMPTY_CELL_VALUE = ''
ODS_VALUE_TOKEN = {
"float": "value",
"date": "date-value",
"time": "time-value",
"boolean": "boolean-value",
"percentage": "value",
"currency": "value"
}
ODS_TYPES = {
'float': DecimalType(),
'date': DateType('%Y-%m-%d'),
'boolean': BoolType(),
'percentage': PercentageType(),
'time': TimeType()
}
class ODSTableSet(TableSet):
"""
A wrapper around ODS files. Because they are zipped and the info we want
is in the zipped file as content.xml we must ensure that we either have
a seekable object (local file) or that we retrieve all of the content from
the remote URL.
"""
def __init__(self, fileobj, window=None, **kw):
'''Initialize the object.
