1042 lines
28 KiB
Python
1042 lines
28 KiB
Python
# -*- coding: utf-8 -*-
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"""
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tablib.core
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~~~~~~~~~~~
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This module implements the central Tablib objects.
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:copyright: (c) 2011 by Kenneth Reitz.
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:license: MIT, see LICENSE for more details.
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"""
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from copy import copy
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from operator import itemgetter
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from tablib import formats
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from tablib.compat import OrderedDict, unicode
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__title__ = 'tablib'
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__version__ = '0.9.11'
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__build__ = 0x000911
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__author__ = 'Kenneth Reitz'
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__license__ = 'MIT'
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__copyright__ = 'Copyright 2011 Kenneth Reitz'
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__docformat__ = 'restructuredtext'
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class Row(object):
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"""Internal Row object. Mainly used for filtering."""
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__slots__ = ['_row', 'tags']
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def __init__(self, row=list(), tags=list()):
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self._row = list(row)
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self.tags = list(tags)
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def __iter__(self):
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return (col for col in self._row)
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def __len__(self):
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return len(self._row)
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def __repr__(self):
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return repr(self._row)
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def __getslice__(self, i, j):
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return self._row[i,j]
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def __getitem__(self, i):
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return self._row[i]
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def __setitem__(self, i, value):
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self._row[i] = value
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def __delitem__(self, i):
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del self._row[i]
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def __getstate__(self):
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slots = dict()
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for slot in self.__slots__:
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attribute = getattr(self, slot)
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slots[slot] = attribute
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return slots
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def __setstate__(self, state):
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for (k, v) in list(state.items()): setattr(self, k, v)
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def rpush(self, value):
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self.insert(0, value)
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def lpush(self, value):
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self.insert(len(value), value)
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def append(self, value):
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self.rpush(value)
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def insert(self, index, value):
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self._row.insert(index, value)
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def __contains__(self, item):
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return (item in self._row)
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@property
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def tuple(self):
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"""Tuple representation of :class:`Row`."""
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return tuple(self._row)
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@property
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def list(self):
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"""List representation of :class:`Row`."""
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return list(self._row)
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def has_tag(self, tag):
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"""Returns true if current row contains tag."""
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if tag == None:
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return False
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elif isinstance(tag, str):
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return (tag in self.tags)
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else:
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return bool(len(set(tag) & set(self.tags)))
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class Dataset(object):
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"""The :class:`Dataset` object is the heart of Tablib. It provides all core
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functionality.
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Usually you create a :class:`Dataset` instance in your main module, and append
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rows as you collect data. ::
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data = tablib.Dataset()
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data.headers = ('name', 'age')
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for (name, age) in some_collector():
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data.append((name, age))
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Setting columns is similar. The column data length must equal the
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current height of the data and headers must be set ::
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data = tablib.Dataset()
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data.headers = ('first_name', 'last_name')
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data.append(('John', 'Adams'))
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data.append(('George', 'Washington'))
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data.append_col((90, 67), header='age')
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You can also set rows and headers upon instantiation. This is useful if
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dealing with dozens or hundreds of :class:`Dataset` objects. ::
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headers = ('first_name', 'last_name')
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data = [('John', 'Adams'), ('George', 'Washington')]
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data = tablib.Dataset(*data, headers=headers)
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:param \*args: (optional) list of rows to populate Dataset
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:param headers: (optional) list strings for Dataset header row
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.. admonition:: Format Attributes Definition
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If you look at the code, the various output/import formats are not
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defined within the :class:`Dataset` object. To add support for a new format, see
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:ref:`Adding New Formats <newformats>`.
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"""
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def __init__(self, *args, **kwargs):
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self._data = list(Row(arg) for arg in args)
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self.__headers = None
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# ('title', index) tuples
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self._separators = []
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# (column, callback) tuples
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self._formatters = []
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try:
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self.headers = kwargs['headers']
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except KeyError:
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self.headers = None
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try:
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self.title = kwargs['title']
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except KeyError:
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self.title = None
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self._register_formats()
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def __len__(self):
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return self.height
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def __getitem__(self, key):
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if isinstance(key, str) or isinstance(key, unicode):
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if key in self.headers:
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pos = self.headers.index(key) # get 'key' index from each data
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return [row[pos] for row in self._data]
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else:
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raise KeyError
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else:
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_results = self._data[key]
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if isinstance(_results, Row):
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return _results.tuple
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else:
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return [result.tuple for result in _results]
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def __setitem__(self, key, value):
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self._validate(value)
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self._data[key] = Row(value)
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def __delitem__(self, key):
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if isinstance(key, str) or isinstance(key, unicode):
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if key in self.headers:
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pos = self.headers.index(key)
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del self.headers[pos]
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for i, row in enumerate(self._data):
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del row[pos]
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self._data[i] = row
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else:
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raise KeyError
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else:
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del self._data[key]
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def __repr__(self):
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try:
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return '<%s dataset>' % (self.title.lower())
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except AttributeError:
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return '<dataset object>'
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def __unicode__(self):
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result = [self.__headers]
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result.extend(list(map(unicode, row)) for row in self._data)
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# here, we calculate max width for each column
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lens = (list(map(len, row)) for row in result)
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field_lens = list(map(max, zip(*lens)))
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# delimiter between header and data
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result.insert(1, ['-' * length for length in field_lens])
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format_string = '|'.join('{%s:%s}' % item for item in enumerate(field_lens))
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return '\n'.join(format_string.format(*row) for row in result)
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def __str__(self):
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return self.__unicode__()
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# ---------
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# Internals
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# ---------
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@classmethod
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def _register_formats(cls):
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"""Adds format properties."""
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for fmt in formats.available:
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try:
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try:
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setattr(cls, fmt.title, property(fmt.export_set, fmt.import_set))
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except AttributeError:
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setattr(cls, fmt.title, property(fmt.export_set))
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except AttributeError:
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pass
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def _validate(self, row=None, col=None, safety=False):
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"""Assures size of every row in dataset is of proper proportions."""
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if row:
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is_valid = (len(row) == self.width) if self.width else True
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elif col:
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if len(col) < 1:
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is_valid = True
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else:
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is_valid = (len(col) == self.height) if self.height else True
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else:
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is_valid = all((len(x) == self.width for x in self._data))
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if is_valid:
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return True
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else:
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if not safety:
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raise InvalidDimensions
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return False
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def _package(self, dicts=True, ordered=True):
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"""Packages Dataset into lists of dictionaries for transmission."""
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# TODO: Dicts default to false?
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_data = list(self._data)
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if ordered:
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dict_pack = OrderedDict
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else:
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dict_pack = dict
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# Execute formatters
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if self._formatters:
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for row_i, row in enumerate(_data):
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for col, callback in self._formatters:
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try:
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if col is None:
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for j, c in enumerate(row):
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_data[row_i][j] = callback(c)
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else:
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_data[row_i][col] = callback(row[col])
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except IndexError:
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raise InvalidDatasetIndex
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if self.headers:
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if dicts:
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data = [dict_pack(list(zip(self.headers, data_row))) for data_row in _data]
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else:
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data = [list(self.headers)] + list(_data)
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else:
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data = [list(row) for row in _data]
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return data
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def _get_headers(self):
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"""An *optional* list of strings to be used for header rows and attribute names.
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This must be set manually. The given list length must equal :class:`Dataset.width`.
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"""
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return self.__headers
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def _set_headers(self, collection):
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"""Validating headers setter."""
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self._validate(collection)
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if collection:
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try:
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self.__headers = list(collection)
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except TypeError:
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raise TypeError
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else:
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self.__headers = None
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headers = property(_get_headers, _set_headers)
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def _get_dict(self):
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"""A native Python representation of the :class:`Dataset` object. If headers have
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been set, a list of Python dictionaries will be returned. If no headers have been set,
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a list of tuples (rows) will be returned instead.
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A dataset object can also be imported by setting the `Dataset.dict` attribute: ::
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data = tablib.Dataset()
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data.json = '[{"last_name": "Adams","age": 90,"first_name": "John"}]'
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"""
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return self._package()
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def _set_dict(self, pickle):
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"""A native Python representation of the Dataset object. If headers have been
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set, a list of Python dictionaries will be returned. If no headers have been
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set, a list of tuples (rows) will be returned instead.
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A dataset object can also be imported by setting the :class:`Dataset.dict` attribute. ::
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data = tablib.Dataset()
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data.dict = [{'age': 90, 'first_name': 'Kenneth', 'last_name': 'Reitz'}]
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"""
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if not len(pickle):
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return
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# if list of rows
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if isinstance(pickle[0], list):
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self.wipe()
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for row in pickle:
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self.append(Row(row))
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# if list of objects
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elif isinstance(pickle[0], dict):
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self.wipe()
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self.headers = list(pickle[0].keys())
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for row in pickle:
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self.append(Row(list(row.values())))
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else:
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raise UnsupportedFormat
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dict = property(_get_dict, _set_dict)
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def _clean_col(self, col):
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"""Prepares the given column for insert/append."""
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col = list(col)
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if self.headers:
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header = [col.pop(0)]
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else:
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header = []
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if len(col) == 1 and hasattr(col[0], '__call__'):
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col = list(map(col[0], self._data))
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col = tuple(header + col)
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return col
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@property
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def height(self):
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"""The number of rows currently in the :class:`Dataset`.
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Cannot be directly modified.
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"""
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return len(self._data)
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@property
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def width(self):
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"""The number of columns currently in the :class:`Dataset`.
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Cannot be directly modified.
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"""
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try:
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return len(self._data[0])
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except IndexError:
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try:
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return len(self.headers)
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except TypeError:
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return 0
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# -------
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# Formats
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# -------
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@property
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def xls():
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"""A Legacy Excel Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.
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.. note::
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XLS files are limited to a maximum of 65,000 rows. Use :class:`Dataset.xlsx` to avoid this limitation.
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.. admonition:: Binary Warning
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:class:`Dataset.xls` contains binary data, so make sure to write in binary mode::
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with open('output.xls', 'wb') as f:
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f.write(data.xls)'
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"""
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pass
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@property
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def xlsx():
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"""An Excel '07+ Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.
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.. admonition:: Binary Warning
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:class:`Dataset.xlsx` contains binary data, so make sure to write in binary mode::
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with open('output.xlsx', 'wb') as f:
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f.write(data.xlsx)'
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"""
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pass
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@property
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def ods():
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"""An OpenDocument Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.
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.. admonition:: Binary Warning
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:class:`Dataset.ods` contains binary data, so make sure to write in binary mode::
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with open('output.ods', 'wb') as f:
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f.write(data.ods)'
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"""
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pass
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@property
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def csv():
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"""A CSV representation of the :class:`Dataset` object. The top row will contain
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headers, if they have been set. Otherwise, the top row will contain
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the first row of the dataset.
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A dataset object can also be imported by setting the :class:`Dataset.csv` attribute. ::
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data = tablib.Dataset()
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data.csv = 'age, first_name, last_name\\n90, John, Adams'
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Import assumes (for now) that headers exist.
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.. admonition:: Binary Warning
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:class:`Dataset.csv` uses \\r\\n line endings by default, so make
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sure to write in binary mode::
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with open('output.csv', 'wb') as f:
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f.write(data.csv)'
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If you do not do this, and you export the file on Windows, your
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CSV file will open in Excel with a blank line between each row.
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"""
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pass
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@property
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def tsv():
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"""A TSV representation of the :class:`Dataset` object. The top row will contain
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headers, if they have been set. Otherwise, the top row will contain
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the first row of the dataset.
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A dataset object can also be imported by setting the :class:`Dataset.tsv` attribute. ::
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data = tablib.Dataset()
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data.tsv = 'age\tfirst_name\tlast_name\\n90\tJohn\tAdams'
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Import assumes (for now) that headers exist.
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"""
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pass
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@property
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def yaml():
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"""A YAML representation of the :class:`Dataset` object. If headers have been
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set, a YAML list of objects will be returned. If no headers have
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been set, a YAML list of lists (rows) will be returned instead.
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A dataset object can also be imported by setting the :class:`Dataset.yaml` attribute: ::
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data = tablib.Dataset()
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data.yaml = '- {age: 90, first_name: John, last_name: Adams}'
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Import assumes (for now) that headers exist.
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"""
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pass
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@property
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def json():
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"""A JSON representation of the :class:`Dataset` object. If headers have been
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set, a JSON list of objects will be returned. If no headers have
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been set, a JSON list of lists (rows) will be returned instead.
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A dataset object can also be imported by setting the :class:`Dataset.json` attribute: ::
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data = tablib.Dataset()
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data.json = '[{age: 90, first_name: "John", liast_name: "Adams"}]'
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Import assumes (for now) that headers exist.
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"""
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pass
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@property
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def html():
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"""A HTML table representation of the :class:`Dataset` object. If
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headers have been set, they will be used as table headers.
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..notice:: This method can be used for export only.
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"""
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pass
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# ----
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# Rows
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# ----
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def insert(self, index, row, tags=list()):
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"""Inserts a row to the :class:`Dataset` at the given index.
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Rows inserted must be the correct size (height or width).
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The default behaviour is to insert the given row to the :class:`Dataset`
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object at the given index.
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"""
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self._validate(row)
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self._data.insert(index, Row(row, tags=tags))
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def rpush(self, row, tags=list()):
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"""Adds a row to the end of the :class:`Dataset`.
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See :class:`Dataset.insert` for additional documentation.
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"""
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self.insert(self.height, row=row, tags=tags)
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def lpush(self, row, tags=list()):
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"""Adds a row to the top of the :class:`Dataset`.
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See :class:`Dataset.insert` for additional documentation.
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"""
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self.insert(0, row=row, tags=tags)
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def append(self, row, tags=list()):
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"""Adds a row to the :class:`Dataset`.
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See :class:`Dataset.insert` for additional documentation.
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"""
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self.rpush(row, tags)
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def extend(self, rows, tags=list()):
|
|
"""Adds a list of rows to the :class:`Dataset` using
|
|
:class:`Dataset.append`
|
|
"""
|
|
|
|
for row in rows:
|
|
self.append(row, tags)
|
|
|
|
|
|
def lpop(self):
|
|
"""Removes and returns the first row of the :class:`Dataset`."""
|
|
|
|
cache = self[0]
|
|
del self[0]
|
|
|
|
return cache
|
|
|
|
|
|
def rpop(self):
|
|
"""Removes and returns the last row of the :class:`Dataset`."""
|
|
|
|
cache = self[-1]
|
|
del self[-1]
|
|
|
|
return cache
|
|
|
|
|
|
def pop(self):
|
|
"""Removes and returns the last row of the :class:`Dataset`."""
|
|
|
|
return self.rpop()
|
|
|
|
|
|
# -------
|
|
# Columns
|
|
# -------
|
|
|
|
def insert_col(self, index, col=None, header=None):
|
|
"""Inserts a column to the :class:`Dataset` at the given index.
|
|
|
|
Columns inserted must be the correct height.
|
|
|
|
You can also insert a column of a single callable object, which will
|
|
add a new column with the return values of the callable each as an
|
|
item in the column. ::
|
|
|
|
data.append_col(col=random.randint)
|
|
|
|
If inserting a column, and :class:`Dataset.headers` is set, the
|
|
header attribute must be set, and will be considered the header for
|
|
that row.
|
|
|
|
See :ref:`dyncols` for an in-depth example.
|
|
|
|
.. versionchanged:: 0.9.0
|
|
If inserting a column, and :class:`Dataset.headers` is set, the
|
|
header attribute must be set, and will be considered the header for
|
|
that row.
|
|
|
|
.. versionadded:: 0.9.0
|
|
If inserting a row, you can add :ref:`tags <tags>` to the row you are inserting.
|
|
This gives you the ability to :class:`filter <Dataset.filter>` your
|
|
:class:`Dataset` later.
|
|
|
|
"""
|
|
|
|
if col is None:
|
|
col = []
|
|
|
|
# Callable Columns...
|
|
if hasattr(col, '__call__'):
|
|
col = list(map(col, self._data))
|
|
|
|
col = self._clean_col(col)
|
|
self._validate(col=col)
|
|
|
|
if self.headers:
|
|
# pop the first item off, add to headers
|
|
if not header:
|
|
raise HeadersNeeded()
|
|
|
|
# corner case - if header is set without data
|
|
elif header and self.height == 0 and len(col):
|
|
raise InvalidDimensions
|
|
|
|
self.headers.insert(index, header)
|
|
|
|
|
|
if self.height and self.width:
|
|
|
|
for i, row in enumerate(self._data):
|
|
|
|
row.insert(index, col[i])
|
|
self._data[i] = row
|
|
else:
|
|
self._data = [Row([row]) for row in col]
|
|
|
|
|
|
|
|
def rpush_col(self, col, header=None):
|
|
"""Adds a column to the end of the :class:`Dataset`.
|
|
See :class:`Dataset.insert` for additional documentation.
|
|
"""
|
|
|
|
self.insert_col(self.width, col, header=header)
|
|
|
|
|
|
def lpush_col(self, col, header=None):
|
|
"""Adds a column to the top of the :class:`Dataset`.
|
|
See :class:`Dataset.insert` for additional documentation.
|
|
"""
|
|
|
|
self.insert_col(0, col, header=header)
|
|
|
|
|
|
def insert_separator(self, index, text='-'):
|
|
"""Adds a separator to :class:`Dataset` at given index."""
|
|
|
|
sep = (index, text)
|
|
self._separators.append(sep)
|
|
|
|
|
|
def append_separator(self, text='-'):
|
|
"""Adds a :ref:`separator <separators>` to the :class:`Dataset`."""
|
|
|
|
# change offsets if headers are or aren't defined
|
|
if not self.headers:
|
|
index = self.height if self.height else 0
|
|
else:
|
|
index = (self.height + 1) if self.height else 1
|
|
|
|
self.insert_separator(index, text)
|
|
|
|
|
|
def append_col(self, col, header=None):
|
|
"""Adds a column to the :class:`Dataset`.
|
|
See :class:`Dataset.insert_col` for additional documentation.
|
|
"""
|
|
|
|
self.rpush_col(col, header)
|
|
|
|
|
|
def get_col(self, index):
|
|
"""Returns the column from the :class:`Dataset` at the given index."""
|
|
|
|
return [row[index] for row in self._data]
|
|
|
|
|
|
# ----
|
|
# Misc
|
|
# ----
|
|
|
|
def add_formatter(self, col, handler):
|
|
"""Adds a :ref:`formatter` to the :class:`Dataset`.
|
|
|
|
.. versionadded:: 0.9.5
|
|
:param col: column to. Accepts index int or header str.
|
|
:param handler: reference to callback function to execute
|
|
against each cell value.
|
|
"""
|
|
|
|
if isinstance(col, str):
|
|
if col in self.headers:
|
|
col = self.headers.index(col) # get 'key' index from each data
|
|
else:
|
|
raise KeyError
|
|
|
|
if not col > self.width:
|
|
self._formatters.append((col, handler))
|
|
else:
|
|
raise InvalidDatasetIndex
|
|
|
|
return True
|
|
|
|
|
|
def filter(self, tag):
|
|
"""Returns a new instance of the :class:`Dataset`, excluding any rows
|
|
that do not contain the given :ref:`tags <tags>`.
|
|
"""
|
|
_dset = copy(self)
|
|
_dset._data = [row for row in _dset._data if row.has_tag(tag)]
|
|
|
|
return _dset
|
|
|
|
|
|
def sort(self, col, reverse=False):
|
|
"""Sort a :class:`Dataset` by a specific column, given string (for
|
|
header) or integer (for column index). The order can be reversed by
|
|
setting ``reverse`` to ``True``.
|
|
|
|
Returns a new :class:`Dataset` instance where columns have been
|
|
sorted.
|
|
"""
|
|
|
|
if isinstance(col, str) or isinstance(col, unicode):
|
|
|
|
if not self.headers:
|
|
raise HeadersNeeded
|
|
|
|
_sorted = sorted(self.dict, key=itemgetter(col), reverse=reverse)
|
|
_dset = Dataset(headers=self.headers)
|
|
|
|
for item in _sorted:
|
|
row = [item[key] for key in self.headers]
|
|
_dset.append(row=row)
|
|
|
|
else:
|
|
if self.headers:
|
|
col = self.headers[col]
|
|
|
|
_sorted = sorted(self.dict, key=itemgetter(col), reverse=reverse)
|
|
_dset = Dataset(headers=self.headers)
|
|
|
|
for item in _sorted:
|
|
if self.headers:
|
|
row = [item[key] for key in self.headers]
|
|
else:
|
|
row = item
|
|
_dset.append(row=row)
|
|
|
|
|
|
return _dset
|
|
|
|
|
|
def transpose(self):
|
|
"""Transpose a :class:`Dataset`, turning rows into columns and vice
|
|
versa, returning a new ``Dataset`` instance. The first row of the
|
|
original instance becomes the new header row."""
|
|
|
|
# Don't transpose if there is no data
|
|
if not self:
|
|
return
|
|
|
|
_dset = Dataset()
|
|
# The first element of the headers stays in the headers,
|
|
# it is our "hinge" on which we rotate the data
|
|
new_headers = [self.headers[0]] + self[self.headers[0]]
|
|
|
|
_dset.headers = new_headers
|
|
for column in self.headers:
|
|
|
|
if column == self.headers[0]:
|
|
# It's in the headers, so skip it
|
|
continue
|
|
|
|
# Adding the column name as now they're a regular column
|
|
row_data = [column] + self[column]
|
|
row_data = Row(row_data)
|
|
_dset.append(row=row_data)
|
|
|
|
return _dset
|
|
|
|
|
|
def stack(self, other):
|
|
"""Stack two :class:`Dataset` instances together by
|
|
joining at the row level, and return new combined
|
|
``Dataset`` instance."""
|
|
|
|
if not isinstance(other, Dataset):
|
|
return
|
|
|
|
if self.width != other.width:
|
|
raise InvalidDimensions
|
|
|
|
# Copy the source data
|
|
_dset = copy(self)
|
|
|
|
rows_to_stack = [row for row in _dset._data]
|
|
other_rows = [row for row in other._data]
|
|
|
|
rows_to_stack.extend(other_rows)
|
|
_dset._data = rows_to_stack
|
|
|
|
return _dset
|
|
|
|
|
|
def stack_cols(self, other):
|
|
"""Stack two :class:`Dataset` instances together by
|
|
joining at the column level, and return a new
|
|
combined ``Dataset`` instance. If either ``Dataset``
|
|
has headers set, than the other must as well."""
|
|
|
|
if not isinstance(other, Dataset):
|
|
return
|
|
|
|
if self.headers or other.headers:
|
|
if not self.headers or not other.headers:
|
|
raise HeadersNeeded
|
|
|
|
if self.height != other.height:
|
|
raise InvalidDimensions
|
|
|
|
try:
|
|
new_headers = self.headers + other.headers
|
|
except TypeError:
|
|
new_headers = None
|
|
|
|
_dset = Dataset()
|
|
|
|
for column in self.headers:
|
|
_dset.append_col(col=self[column])
|
|
|
|
for column in other.headers:
|
|
_dset.append_col(col=other[column])
|
|
|
|
_dset.headers = new_headers
|
|
|
|
return _dset
|
|
|
|
|
|
def wipe(self):
|
|
"""Removes all content and headers from the :class:`Dataset` object."""
|
|
self._data = list()
|
|
self.__headers = None
|
|
|
|
|
|
|
|
class Databook(object):
|
|
"""A book of :class:`Dataset` objects.
|
|
"""
|
|
|
|
def __init__(self, sets=None):
|
|
|
|
if sets is None:
|
|
self._datasets = list()
|
|
else:
|
|
self._datasets = sets
|
|
|
|
self._register_formats()
|
|
|
|
def __repr__(self):
|
|
try:
|
|
return '<%s databook>' % (self.title.lower())
|
|
except AttributeError:
|
|
return '<databook object>'
|
|
|
|
|
|
def wipe(self):
|
|
"""Removes all :class:`Dataset` objects from the :class:`Databook`."""
|
|
self._datasets = []
|
|
|
|
|
|
@classmethod
|
|
def _register_formats(cls):
|
|
"""Adds format properties."""
|
|
for fmt in formats.available:
|
|
try:
|
|
try:
|
|
setattr(cls, fmt.title, property(fmt.export_book, fmt.import_book))
|
|
except AttributeError:
|
|
setattr(cls, fmt.title, property(fmt.export_book))
|
|
|
|
except AttributeError:
|
|
pass
|
|
|
|
|
|
def add_sheet(self, dataset):
|
|
"""Adds given :class:`Dataset` to the :class:`Databook`."""
|
|
if isinstance(dataset, Dataset):
|
|
self._datasets.append(dataset)
|
|
else:
|
|
raise InvalidDatasetType
|
|
|
|
|
|
def _package(self, ordered=True):
|
|
"""Packages :class:`Databook` for delivery."""
|
|
collector = []
|
|
|
|
if ordered:
|
|
dict_pack = OrderedDict
|
|
else:
|
|
dict_pack = dict
|
|
|
|
for dset in self._datasets:
|
|
collector.append(dict_pack(
|
|
title = dset.title,
|
|
data = dset._package(ordered=ordered)
|
|
))
|
|
return collector
|
|
|
|
|
|
@property
|
|
def size(self):
|
|
"""The number of the :class:`Dataset` objects within :class:`Databook`."""
|
|
return len(self._datasets)
|
|
|
|
|
|
def detect(stream):
|
|
"""Return (format, stream) of given stream."""
|
|
for fmt in formats.available:
|
|
try:
|
|
if fmt.detect(stream):
|
|
return (fmt, stream)
|
|
except AttributeError:
|
|
pass
|
|
return (None, stream)
|
|
|
|
|
|
def import_set(stream):
|
|
"""Return dataset of given stream."""
|
|
(format, stream) = detect(stream)
|
|
|
|
try:
|
|
data = Dataset()
|
|
format.import_set(data, stream)
|
|
return data
|
|
|
|
except AttributeError:
|
|
return None
|
|
|
|
|
|
def import_book(stream):
|
|
"""Return dataset of given stream."""
|
|
(format, stream) = detect(stream)
|
|
|
|
try:
|
|
databook = Databook()
|
|
format.import_book(databook, stream)
|
|
return databook
|
|
|
|
except AttributeError:
|
|
return None
|
|
|
|
|
|
class InvalidDatasetType(Exception):
|
|
"Only Datasets can be added to a DataBook"
|
|
|
|
|
|
class InvalidDimensions(Exception):
|
|
"Invalid size"
|
|
|
|
class InvalidDatasetIndex(Exception):
|
|
"Outside of Dataset size"
|
|
|
|
class HeadersNeeded(Exception):
|
|
"Header parameter must be given when appending a column in this Dataset."
|
|
|
|
class UnsupportedFormat(NotImplementedError):
|
|
"Format is not supported"
|