# -*- coding: utf-8 -*-
"""
    tablib.core
    ~~~~~~~~~~~

    This module implements the central Tablib objects.

    :copyright: (c) 2016 by Kenneth Reitz.
    :license: MIT, see LICENSE for more details.
"""

from collections import OrderedDict
from copy import copy
from operator import itemgetter

from tablib import formats

from tablib.compat import unicode


__title__ = 'tablib'
__version__ = '0.13.0'
__build__ = 0x001201
__author__ = 'Kenneth Reitz'
__license__ = 'MIT'
__copyright__ = 'Copyright 2017 Kenneth Reitz'
__docformat__ = 'restructuredtext'


class Row(object):
    """Internal Row object. Mainly used for filtering."""

    __slots__ = ['_row', 'tags']

    def __init__(self, row=list(), tags=list()):
        self._row = list(row)
        self.tags = list(tags)

    def __iter__(self):
        return (col for col in self._row)

    def __len__(self):
        return len(self._row)

    def __repr__(self):
        return repr(self._row)

    def __getslice__(self, i, j):
        return self._row[i:j]

    def __getitem__(self, i):
        return self._row[i]

    def __setitem__(self, i, value):
        self._row[i] = value

    def __delitem__(self, i):
        del self._row[i]

    def __getstate__(self):

        slots = dict()

        for slot in self.__slots__:
            attribute = getattr(self, slot)
            slots[slot] = attribute

        return slots

    def __setstate__(self, state):
        for (k, v) in list(state.items()): setattr(self, k, v)

    def rpush(self, value):
        self.insert(0, value)

    def lpush(self, value):
        self.insert(len(value), value)

    def append(self, value):
        self.rpush(value)

    def insert(self, index, value):
        self._row.insert(index, value)

    def __contains__(self, item):
        return (item in self._row)

    @property
    def tuple(self):
        """Tuple representation of :class:`Row`."""
        return tuple(self._row)

    @property
    def list(self):
        """List representation of :class:`Row`."""
        return list(self._row)

    def has_tag(self, tag):
        """Returns true if current row contains tag."""

        if tag == None:
            return False
        elif isinstance(tag, str):
            return (tag in self.tags)
        else:
            return bool(len(set(tag) & set(self.tags)))




class Dataset(object):
    """The :class:`Dataset` object is the heart of Tablib. It provides all core
    functionality.

    Usually you create a :class:`Dataset` instance in your main module, and append
    rows as you collect data. ::

        data = tablib.Dataset()
        data.headers = ('name', 'age')

        for (name, age) in some_collector():
            data.append((name, age))


    Setting columns is similar. The column data length must equal the
    current height of the data and headers must be set ::

        data = tablib.Dataset()
        data.headers = ('first_name', 'last_name')

        data.append(('John', 'Adams'))
        data.append(('George', 'Washington'))

        data.append_col((90, 67), header='age')


    You can also set rows and headers upon instantiation. This is useful if
    dealing with dozens or hundreds of :class:`Dataset` objects. ::

        headers = ('first_name', 'last_name')
        data = [('John', 'Adams'), ('George', 'Washington')]

        data = tablib.Dataset(*data, headers=headers)

    :param \*args: (optional) list of rows to populate Dataset
    :param headers: (optional) list strings for Dataset header row
    :param title: (optional) string to use as title of the Dataset


    .. admonition:: Format Attributes Definition

     If you look at the code, the various output/import formats are not
     defined within the :class:`Dataset` object. To add support for a new format, see
     :ref:`Adding New Formats <newformats>`.

    """

    _formats = {}

    def __init__(self, *args, **kwargs):
        self._data = list(Row(arg) for arg in args)
        self.__headers = None

        # ('title', index) tuples
        self._separators = []

        # (column, callback) tuples
        self._formatters = []

        self.headers = kwargs.get('headers')

        self.title = kwargs.get('title')

        self._register_formats()


    def __len__(self):
        return self.height


    def __getitem__(self, key):
        if isinstance(key, (str, unicode)):
            if key in self.headers:
                pos = self.headers.index(key) # get 'key' index from each data
                return [row[pos] for row in self._data]
            else:
                raise KeyError
        else:
            _results = self._data[key]
            if isinstance(_results, Row):
                return _results.tuple
            else:
                return [result.tuple for result in _results]

    def __setitem__(self, key, value):
        self._validate(value)
        self._data[key] = Row(value)


    def __delitem__(self, key):
        if isinstance(key, (str, unicode)):

            if key in self.headers:

                pos = self.headers.index(key)
                del self.headers[pos]

                for i, row in enumerate(self._data):

                    del row[pos]
                    self._data[i] = row
            else:
                raise KeyError
        else:
            del self._data[key]


    def __repr__(self):
        try:
            return '<%s dataset>' % (self.title.lower())
        except AttributeError:
            return '<dataset object>'

    def __unicode__(self):
        result = []

        # Add unicode representation of headers.
        if self.__headers:
            result.append([unicode(h) for h in self.__headers])

        # Add unicode representation of rows.
        result.extend(list(map(unicode, row)) for row in self._data)

        lens = [list(map(len, row)) for row in result]
        field_lens = list(map(max, zip(*lens)))

        # delimiter between header and data
        if self.__headers:
            result.insert(1, ['-' * length for length in field_lens])

        format_string = '|'.join('{%s:%s}' % item for item in enumerate(field_lens))

        return '\n'.join(format_string.format(*row) for row in result)

    def __str__(self):
        return self.__unicode__()

    # ---------
    # Internals
    # ---------

    @classmethod
    def _register_formats(cls):
        """Adds format properties."""
        for fmt in formats.available:
            try:
                try:
                    setattr(cls, fmt.title, property(fmt.export_set, fmt.import_set))
                    setattr(cls, 'get_%s' % fmt.title, fmt.export_set)
                    setattr(cls, 'set_%s' % fmt.title, fmt.import_set)
                    cls._formats[fmt.title] = (fmt.export_set, fmt.import_set)
                except AttributeError:
                    setattr(cls, fmt.title, property(fmt.export_set))
                    setattr(cls, 'get_%s' % fmt.title, fmt.export_set)
                    cls._formats[fmt.title] = (fmt.export_set, None)

            except AttributeError:
                cls._formats[fmt.title] = (None, None)


    def _validate(self, row=None, col=None, safety=False):
        """Assures size of every row in dataset is of proper proportions."""
        if row:
            is_valid = (len(row) == self.width) if self.width else True
        elif col:
            if len(col) < 1:
                is_valid = True
            else:
                is_valid = (len(col) == self.height) if self.height else True
        else:
            is_valid = all((len(x) == self.width for x in self._data))

        if is_valid:
            return True
        else:
            if not safety:
                raise InvalidDimensions
            return False


    def _package(self, dicts=True, ordered=True):
        """Packages Dataset into lists of dictionaries for transmission."""
        # TODO: Dicts default to false?

        _data = list(self._data)

        if ordered:
            dict_pack = OrderedDict
        else:
            dict_pack = dict

        # Execute formatters
        if self._formatters:
            for row_i, row in enumerate(_data):
                for col, callback in self._formatters:
                    try:
                        if col is None:
                            for j, c in enumerate(row):
                                _data[row_i][j] = callback(c)
                        else:
                            _data[row_i][col] = callback(row[col])
                    except IndexError:
                        raise InvalidDatasetIndex


        if self.headers:
            if dicts:
                data = [dict_pack(list(zip(self.headers, data_row))) for data_row in _data]
            else:
                data = [list(self.headers)] + list(_data)
        else:
            data = [list(row) for row in _data]

        return data



    def _get_headers(self):
        """An *optional* list of strings to be used for header rows and attribute names.

        This must be set manually. The given list length must equal :class:`Dataset.width`.

        """
        return self.__headers


    def _set_headers(self, collection):
        """Validating headers setter."""
        self._validate(collection)
        if collection:
            try:
                self.__headers = list(collection)
            except TypeError:
                raise TypeError
        else:
            self.__headers = None

    headers = property(_get_headers, _set_headers)


    def _get_dict(self):
        """A native Python representation of the :class:`Dataset` object. If headers have
        been set, a list of Python dictionaries will be returned. If no headers have been set,
        a list of tuples (rows) will be returned instead.

        A dataset object can also be imported by setting the `Dataset.dict` attribute: ::

            data = tablib.Dataset()
            data.dict = [{'age': 90, 'first_name': 'Kenneth', 'last_name': 'Reitz'}]

        """
        return self._package()


    def _set_dict(self, pickle):
        """A native Python representation of the Dataset object. If headers have been
        set, a list of Python dictionaries will be returned. If no headers have been
        set, a list of tuples (rows) will be returned instead.

        A dataset object can also be imported by setting the :class:`Dataset.dict` attribute. ::

            data = tablib.Dataset()
            data.dict = [{'age': 90, 'first_name': 'Kenneth', 'last_name': 'Reitz'}]

        """

        if not len(pickle):
            return

        # if list of rows
        if isinstance(pickle[0], list):
            self.wipe()
            for row in pickle:
                self.append(Row(row))

        # if list of objects
        elif isinstance(pickle[0], dict):
            self.wipe()
            self.headers = list(pickle[0].keys())
            for row in pickle:
                self.append(Row(list(row.values())))
        else:
            raise UnsupportedFormat

    dict = property(_get_dict, _set_dict)


    def _clean_col(self, col):
        """Prepares the given column for insert/append."""

        col = list(col)

        if self.headers:
            header = [col.pop(0)]
        else:
            header = []

        if len(col) == 1 and hasattr(col[0], '__call__'):

            col = list(map(col[0], self._data))
        col = tuple(header + col)

        return col


    @property
    def height(self):
        """The number of rows currently in the :class:`Dataset`.
           Cannot be directly modified.
        """
        return len(self._data)


    @property
    def width(self):
        """The number of columns currently in the :class:`Dataset`.
           Cannot be directly modified.
        """

        try:
            return len(self._data[0])
        except IndexError:
            try:
                return len(self.headers)
            except TypeError:
                return 0


    def load(self, in_stream, format=None, **kwargs):
        """
        Import `in_stream` to the :class:`Dataset` object using the `format`.

        :param \*\*kwargs: (optional) custom configuration to the format `import_set`.
        """

        if not format:
            format = detect_format(in_stream)

        export_set, import_set = self._formats.get(format, (None, None))
        if not import_set:
            raise UnsupportedFormat('Format {0} cannot be imported.'.format(format))

        import_set(self, in_stream, **kwargs)
        return self



    def export(self, format, **kwargs):
        """
        Export :class:`Dataset` object to `format`.

        :param \*\*kwargs: (optional) custom configuration to the format `export_set`.
        """
        export_set, import_set = self._formats.get(format, (None, None))
        if not export_set:
            raise UnsupportedFormat('Format {0} cannot be exported.'.format(format))

        return export_set(self, **kwargs)

    # -------
    # Formats
    # -------

    @property
    def xls():
        """A Legacy Excel Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.

        .. note::

            XLS files are limited to a maximum of 65,000 rows. Use :class:`Dataset.xlsx` to avoid this limitation.

         .. admonition:: Binary Warning

             :class:`Dataset.xls` contains binary data, so make sure to write in binary mode::

                with open('output.xls', 'wb') as f:
                    f.write(data.xls)
        """
        pass

    @property
    def xlsx():
        """An Excel '07+ Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.

         .. admonition:: Binary Warning

             :class:`Dataset.xlsx` contains binary data, so make sure to write in binary mode::

                with open('output.xlsx', 'wb') as f:
                    f.write(data.xlsx)
        """
        pass

    @property
    def ods():
        """An OpenDocument Spreadsheet representation of the :class:`Dataset` object, with :ref:`separators`. Cannot be set.

         .. admonition:: Binary Warning

             :class:`Dataset.ods` contains binary data, so make sure to write in binary mode::

                with open('output.ods', 'wb') as f:
                    f.write(data.ods)
        """
        pass

    @property
    def csv():
        """A CSV representation of the :class:`Dataset` object. The top row will contain
        headers, if they have been set. Otherwise, the top row will contain
        the first row of the dataset.

        A dataset object can also be imported by setting the :class:`Dataset.csv` attribute. ::

            data = tablib.Dataset()
            data.csv = 'age, first_name, last_name\\n90, John, Adams'

        Import assumes (for now) that headers exist.

        .. admonition:: Binary Warning for Python 2

             :class:`Dataset.csv` uses \\r\\n line endings by default so, in Python 2, make
             sure to write in binary mode::

                 with open('output.csv', 'wb') as f:
                     f.write(data.csv)

             If you do not do this, and you export the file on Windows, your
             CSV file will open in Excel with a blank line between each row.

        .. admonition:: Line endings for Python 3

             :class:`Dataset.csv` uses \\r\\n line endings by default so, in Python 3, make
             sure to include newline='' otherwise you will get a blank line between each row
             when you open the file in Excel::

                 with open('output.csv', 'w', newline='') as f:
                     f.write(data.csv)

             If you do not do this, and you export the file on Windows, your
             CSV file will open in Excel with a blank line between each row.
        """
        pass


    @property
    def tsv():
        """A TSV representation of the :class:`Dataset` object. The top row will contain
        headers, if they have been set. Otherwise, the top row will contain
        the first row of the dataset.

        A dataset object can also be imported by setting the :class:`Dataset.tsv` attribute. ::

            data = tablib.Dataset()
            data.tsv = 'age\tfirst_name\tlast_name\\n90\tJohn\tAdams'

        Import assumes (for now) that headers exist.
        """
        pass

    @property
    def yaml():
        """A YAML representation of the :class:`Dataset` object. If headers have been
        set, a YAML list of objects will be returned. If no headers have
        been set, a YAML list of lists (rows) will be returned instead.

        A dataset object can also be imported by setting the :class:`Dataset.yaml` attribute: ::

            data = tablib.Dataset()
            data.yaml = '- {age: 90, first_name: John, last_name: Adams}'

        Import assumes (for now) that headers exist.
        """
        pass

    @property
    def df():
        """A DataFrame representation of the :class:`Dataset` object.

        A dataset object can also be imported by setting the :class:`Dataset.df` attribute: ::

            data = tablib.Dataset()
            data.df = DataFrame(np.random.randn(6,4))

        Import assumes (for now) that headers exist.
        """
        pass

    @property
    def json():
        """A JSON representation of the :class:`Dataset` object. If headers have been
        set, a JSON list of objects will be returned. If no headers have
        been set, a JSON list of lists (rows) will be returned instead.

        A dataset object can also be imported by setting the :class:`Dataset.json` attribute: ::

            data = tablib.Dataset()
            data.json = '[{"age": 90, "first_name": "John", "last_name": "Adams"}]'

        Import assumes (for now) that headers exist.
        """
        pass

    @property
    def html():
        """A HTML table representation of the :class:`Dataset` object. If
        headers have been set, they will be used as table headers.

        ..notice:: This method can be used for export only.
        """
        pass

    @property
    def dbf():
        """A dBASE representation of the :class:`Dataset` object.

        A dataset object can also be imported by setting the
        :class:`Dataset.dbf` attribute. ::

            # To import data from an existing DBF file:
            data = tablib.Dataset()
            data.dbf = open('existing_table.dbf').read()

            # to import data from an ASCII-encoded bytestring:
            data = tablib.Dataset()
            data.dbf = '<bytestring of tabular data>'

        .. admonition:: Binary Warning

            :class:`Dataset.dbf` contains binary data, so make sure to write in binary mode::

                with open('output.dbf', 'wb') as f:
                    f.write(data.dbf)
        """
        pass

    @property
    def latex():
        """A LaTeX booktabs representation of the :class:`Dataset` object. If a
        title has been set, it will be exported as the table caption.

        .. note:: This method can be used for export only.
        """
        pass

    @property
    def jira():
        """A Jira table representation of the :class:`Dataset` object.

        .. note:: This method can be used for export only.
        """
        pass

    # ----
    # Rows
    # ----

    def insert(self, index, row, tags=list()):
        """Inserts a row to the :class:`Dataset` at the given index.

        Rows inserted must be the correct size (height or width).

        The default behaviour is to insert the given row to the :class:`Dataset`
        object at the given index.
       """

        self._validate(row)
        self._data.insert(index, Row(row, tags=tags))


    def rpush(self, row, tags=list()):
        """Adds a row to the end of the :class:`Dataset`.
        See :class:`Dataset.insert` for additional documentation.
        """

        self.insert(self.height, row=row, tags=tags)


    def lpush(self, row, tags=list()):
        """Adds a row to the top of the :class:`Dataset`.
        See :class:`Dataset.insert` for additional documentation.
        """

        self.insert(0, row=row, tags=tags)


    def append(self, row, tags=list()):
        """Adds a row to the :class:`Dataset`.
        See :class:`Dataset.insert` for additional documentation.
        """

        self.rpush(row, tags)

    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, unicode):
            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, unicode)):

            if not self.headers:
                raise HeadersNeeded

            _sorted = sorted(self.dict, key=itemgetter(col), reverse=reverse)
            _dset = Dataset(headers=self.headers, title=self.title)

            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, title=self.title)

            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 index, column in enumerate(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
            # Use `get_col(index)` in case there are repeated values
            row_data = [column] + self.get_col(index)
            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 remove_duplicates(self):
        """Removes all duplicate rows from the :class:`Dataset` object
        while maintaining the original order."""
        seen = set()
        self._data[:] = [row for row in self._data if not (tuple(row) in seen or seen.add(tuple(row)))]


    def wipe(self):
        """Removes all content and headers from the :class:`Dataset` object."""
        self._data = list()
        self.__headers = None


    def subset(self, rows=None, cols=None):
        """Returns a new instance of the :class:`Dataset`,
        including only specified rows and columns.
        """

        # Don't return if no data
        if not self:
            return

        if rows is None:
            rows = list(range(self.height))

        if cols is None:
            cols = list(self.headers)

        #filter out impossible rows and columns
        rows = [row for row in rows if row in range(self.height)]
        cols = [header for header in cols if header in self.headers]

        _dset = Dataset()

        #filtering rows and columns
        _dset.headers = list(cols)

        _dset._data = []
        for row_no, row in enumerate(self._data):
            data_row = []
            for key in _dset.headers:
                if key in self.headers:
                    pos = self.headers.index(key)
                    data_row.append(row[pos])
                else:
                    raise KeyError

            if row_no in rows:
                _dset.append(row=Row(data_row))

        return _dset



class Databook(object):
    """A book of :class:`Dataset` objects.
    """

    _formats = {}

    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))
                    cls._formats[fmt.title] = (fmt.export_book, fmt.import_book)
                except AttributeError:
                    setattr(cls, fmt.title, property(fmt.export_book))
                    cls._formats[fmt.title] = (fmt.export_book, None)

            except AttributeError:
                cls._formats[fmt.title] = (None, None)

    def sheets(self):
        return self._datasets

    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 load(self, format, in_stream, **kwargs):
        """
        Import `in_stream` to the :class:`Databook` object using the `format`.

        :param \*\*kwargs: (optional) custom configuration to the format `import_book`.
        """

        if not format:
            format = detect_format(in_stream)

        export_book, import_book = self._formats.get(format, (None, None))
        if not import_book:
            raise UnsupportedFormat('Format {0} cannot be loaded.'.format(format))

        import_book(self, in_stream, **kwargs)
        return self

    def export(self, format, **kwargs):
        """
        Export :class:`Databook` object to `format`.

        :param \*\*kwargs: (optional) custom configuration to the format `export_book`.
        """
        export_book, import_book = self._formats.get(format, (None, None))
        if not export_book:
            raise UnsupportedFormat('Format {0} cannot be exported.'.format(format))

        return export_book(self, **kwargs)


def detect_format(stream):
    """Return format name of given stream."""
    for fmt in formats.available:
        try:
            if fmt.detect(stream):
                return fmt.title
        except AttributeError:
            pass

def import_set(stream, format=None, **kwargs):
    """Return dataset of given stream."""

    return Dataset().load(stream, format, **kwargs)


def import_book(stream, format=None, **kwargs):
    """Return dataset of given stream."""

    return Databook().load(stream, format, **kwargs)


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"