コード例 #1
0
ファイル: html.py プロジェクト: masayas/pandas
def _parse(flavor, io, match, attrs, encoding, **kwargs):
    flavor = _validate_flavor(flavor)
    compiled_match = re.compile(match)  # you can pass a compiled regex here

    # hack around python 3 deleting the exception variable
    retained = None
    for flav in flavor:
        parser = _parser_dispatch(flav)
        p = parser(io, compiled_match, attrs, encoding)

        try:
            tables = p.parse_tables()
        except Exception as caught:
            retained = caught
        else:
            break
    else:
        raise_with_traceback(retained)

    ret = []
    for table in tables:
        try:
            ret.append(_data_to_frame(data=table, **kwargs))
        except EmptyDataError:  # empty table
            continue
    return ret
コード例 #2
0
ファイル: html.py プロジェクト: pardusnimr/adelscrapper
def _parse(
    flavor, io, match, header, index_col, skiprows, infer_types, parse_dates, tupleize_cols, thousands, attrs, encoding
):
    flavor = _validate_flavor(flavor)
    compiled_match = re.compile(match)  # you can pass a compiled regex here

    # hack around python 3 deleting the exception variable
    retained = None
    for flav in flavor:
        parser = _parser_dispatch(flav)
        p = parser(io, compiled_match, attrs, encoding)

        try:
            tables = p.parse_tables()
        except Exception as caught:
            retained = caught
        else:
            break
    else:
        raise_with_traceback(retained)

    ret = []
    for table in tables:
        try:
            ret.append(
                _data_to_frame(table, header, index_col, skiprows, infer_types, parse_dates, tupleize_cols, thousands)
            )
        except StopIteration:  # empty table
            continue
    return ret
コード例 #3
0
ファイル: html.py プロジェクト: Sakampavankumar/pandas-1
def _parse(flavor, io, match, header, index_col, skiprows, parse_dates,
           tupleize_cols, thousands, attrs, encoding):
    flavor = _validate_flavor(flavor)
    compiled_match = re.compile(match)  # you can pass a compiled regex here

    # hack around python 3 deleting the exception variable
    retained = None
    for flav in flavor:
        parser = _parser_dispatch(flav)
        p = parser(io, compiled_match, attrs, encoding)

        try:
            tables = p.parse_tables()
        except Exception as caught:
            retained = caught
        else:
            break
    else:
        raise_with_traceback(retained)

    ret = []
    for table in tables:
        try:
            ret.append(
                _data_to_frame(data=table,
                               header=header,
                               index_col=index_col,
                               skiprows=skiprows,
                               parse_dates=parse_dates,
                               tupleize_cols=tupleize_cols,
                               thousands=thousands))
        except StopIteration:  # empty table
            continue
    return ret
コード例 #4
0
ファイル: html.py プロジェクト: AlexisMignon/pandas
def _parse(flavor, io, match, attrs, encoding, **kwargs):
    flavor = _validate_flavor(flavor)
    compiled_match = re.compile(match)  # you can pass a compiled regex here

    # hack around python 3 deleting the exception variable
    retained = None
    for flav in flavor:
        parser = _parser_dispatch(flav)
        p = parser(io, compiled_match, attrs, encoding)

        try:
            tables = p.parse_tables()
        except Exception as caught:
            retained = caught
        else:
            break
    else:
        raise_with_traceback(retained)

    ret = []
    for table in tables:
        try:
            ret.append(_data_to_frame(data=table, **kwargs))
        except EmptyDataError:  # empty table
            continue
    return ret
コード例 #5
0
ファイル: html.py プロジェクト: pedros/pandas
def _parse(flavor, io, match, header, index_col, skiprows, infer_types,
           parse_dates, tupleize_cols, thousands, attrs, encoding):
    flavor = _validate_flavor(flavor)
    compiled_match = re.compile(match)  # you can pass a compiled regex here

    # hack around python 3 deleting the exception variable
    retained = None
    for flav in flavor:
        parser = _parser_dispatch(flav)
        p = parser(io, compiled_match, attrs, encoding)

        try:
            tables = p.parse_tables()
        except Exception as caught:
            retained = caught
        else:
            break
    else:
        raise_with_traceback(retained)

    return [
        _data_to_frame(table, header, index_col, skiprows, infer_types,
                       parse_dates, tupleize_cols, thousands)
        for table in tables
    ]
コード例 #6
0
ファイル: testing.py プロジェクト: khairy/pandas
 def handle_success(self, exc_type, exc_value, traceback):
     if self.regexp is not None:
         val = str(exc_value)
         if not self.regexp.search(val):
             e = AssertionError('"%s" does not match "%s"' % (self.regexp.pattern, str(val)))
             raise_with_traceback(e, traceback)
     return True
コード例 #7
0
 def handle_success(self, exc_type, exc_value, traceback):
     if self.regexp is not None:
         val = str(exc_value)
         if not self.regexp.search(val):
             e = AssertionError('"%s" does not match "%s"' %
                                (self.regexp.pattern, str(val)))
             raise_with_traceback(e, traceback)
     return True
コード例 #8
0
ファイル: construction.py プロジェクト: PaulGureghian1/Pandas
def init_ndarray(values, index, columns, dtype=None, copy=False):
    # input must be a ndarray, list, Series, index

    if isinstance(values, ABCSeries):
        if columns is None:
            if values.name is not None:
                columns = [values.name]
        if index is None:
            index = values.index
        else:
            values = values.reindex(index)

        # zero len case (GH #2234)
        if not len(values) and columns is not None and len(columns):
            values = np.empty((0, 1), dtype=object)

    # we could have a categorical type passed or coerced to 'category'
    # recast this to an arrays_to_mgr
    if (is_categorical_dtype(getattr(values, 'dtype', None))
            or is_categorical_dtype(dtype)):

        if not hasattr(values, 'dtype'):
            values = prep_ndarray(values, copy=copy)
            values = values.ravel()
        elif copy:
            values = values.copy()

        index, columns = _get_axes(len(values), 1, index, columns)
        return arrays_to_mgr([values], columns, index, columns, dtype=dtype)
    elif (is_datetime64tz_dtype(values) or is_extension_array_dtype(values)):
        # GH#19157
        if columns is None:
            columns = [0]
        return arrays_to_mgr([values], columns, index, columns, dtype=dtype)

    # by definition an array here
    # the dtypes will be coerced to a single dtype
    values = prep_ndarray(values, copy=copy)

    if dtype is not None:
        if not is_dtype_equal(values.dtype, dtype):
            try:
                values = values.astype(dtype)
            except Exception as orig:
                e = ValueError("failed to cast to '{dtype}' (Exception "
                               "was: {orig})".format(dtype=dtype, orig=orig))
                raise_with_traceback(e)

    index, columns = _get_axes(*values.shape, index=index, columns=columns)
    values = values.T

    # if we don't have a dtype specified, then try to convert objects
    # on the entire block; this is to convert if we have datetimelike's
    # embedded in an object type
    if dtype is None and is_object_dtype(values):
        values = maybe_infer_to_datetimelike(values)

    return create_block_manager_from_blocks([values], [columns, index])
コード例 #9
0
ファイル: test_testing.py プロジェクト: christlc/pandas
 def test_raise_with_traceback(self):
     with pytest.raises(LookupError, match="error_text"):
         try:
             raise ValueError("THIS IS AN ERROR")
         except ValueError as e:
             e = LookupError("error_text")
             raise_with_traceback(e)
     with pytest.raises(LookupError, match="error_text"):
         try:
             raise ValueError("This is another error")
         except ValueError:
             e = LookupError("error_text")
             _, _, traceback = sys.exc_info()
             raise_with_traceback(e, traceback)
コード例 #10
0
 def test_raise_with_traceback(self):
     with pytest.raises(LookupError, match="error_text"):
         try:
             raise ValueError("THIS IS AN ERROR")
         except ValueError as e:
             e = LookupError("error_text")
             raise_with_traceback(e)
     with pytest.raises(LookupError, match="error_text"):
         try:
             raise ValueError("This is another error")
         except ValueError:
             e = LookupError("error_text")
             _, _, traceback = sys.exc_info()
             raise_with_traceback(e, traceback)
コード例 #11
0
ファイル: sql.py プロジェクト: hussainsultan/pandas
    def execute(self, *args, **kwargs):
        try:
            cur = self.con.cursor()
            if kwargs:
                cur.execute(*args, **kwargs)
            else:
                cur.execute(*args)
            return cur
        except Exception as e:
            try:
                self.con.rollback()
            except Exception:  # pragma: no cover
                ex = DatabaseError("Execution failed on sql: %s\n%s\nunable to rollback" % (args[0], e))
                raise_with_traceback(ex)

            ex = DatabaseError("Execution failed on sql: %s" % args[0])
            raise_with_traceback(ex)
コード例 #12
0
ファイル: sql.py プロジェクト: mindw/pandas
    def execute(self, *args, **kwargs):
        try:
            cur = self.con.cursor()
            if kwargs:
                cur.execute(*args, **kwargs)
            else:
                cur.execute(*args)
            return cur
        except Exception as e:
            try:
                self.con.rollback()
            except Exception:  # pragma: no cover
                ex = DatabaseError(
                    "Execution failed on sql: %s\n%s\nunable to rollback" %
                    (args[0], e))
                raise_with_traceback(ex)

            ex = DatabaseError("Execution failed on sql: %s" % args[0])
            raise_with_traceback(ex)
コード例 #13
0
def _parse(flavor, io, match, attrs, encoding, displayed_only, **kwargs):
    flavor = _validate_flavor(flavor)
    compiled_match = re.compile(match)  # you can pass a compiled regex here

    # hack around python 3 deleting the exception variable
    retained = None
    for flav in flavor:
        parser = _parser_dispatch(flav)
        p = parser(io, compiled_match, attrs, encoding, displayed_only)

        try:
            tables = p.parse_tables()
        except Exception as caught:
            # if `io` is an io-like object, check if it's seekable
            # and try to rewind it before trying the next parser
            if hasattr(io, "seekable") and io.seekable():
                io.seek(0)
            elif hasattr(io, "seekable") and not io.seekable():
                # if we couldn't rewind it, let the user know
                raise ValueError(
                    "The flavor {} failed to parse your input. "
                    "Since you passed a non-rewindable file "
                    "object, we can't rewind it to try "
                    "another parser. Try read_html() with a "
                    "different flavor.".format(flav)
                )

            retained = caught
        else:
            break
    else:
        raise_with_traceback(retained)

    ret = []
    for table in tables:
        try:
            ret.append(_data_to_frame(data=table, **kwargs))
        except EmptyDataError:  # empty table
            continue
    return ret
コード例 #14
0
ファイル: html.py プロジェクト: MasonGallo/pandas
def _parse(flavor, io, match, attrs, encoding, displayed_only, **kwargs):
    flavor = _validate_flavor(flavor)
    compiled_match = re.compile(match)  # you can pass a compiled regex here

    # hack around python 3 deleting the exception variable
    retained = None
    for flav in flavor:
        parser = _parser_dispatch(flav)
        p = parser(io, compiled_match, attrs, encoding, displayed_only)

        try:
            tables = p.parse_tables()
        except Exception as caught:
            # if `io` is an io-like object, check if it's seekable
            # and try to rewind it before trying the next parser
            if hasattr(io, 'seekable') and io.seekable():
                io.seek(0)
            elif hasattr(io, 'seekable') and not io.seekable():
                # if we couldn't rewind it, let the user know
                raise ValueError('The flavor {} failed to parse your input. '
                                 'Since you passed a non-rewindable file '
                                 'object, we can\'t rewind it to try '
                                 'another parser. Try read_html() with a '
                                 'different flavor.'.format(flav))

            retained = caught
        else:
            break
    else:
        raise_with_traceback(retained)

    ret = []
    for table in tables:
        try:
            ret.append(_data_to_frame(data=table, **kwargs))
        except EmptyDataError:  # empty table
            continue
    return ret
コード例 #15
0
ファイル: construction.py プロジェクト: phdnguyen/pandas
def init_ndarray(values, index, columns, dtype=None, copy=False):
    # input must be a ndarray, list, Series, index

    if isinstance(values, ABCSeries):
        if columns is None:
            if values.name is not None:
                columns = [values.name]
        if index is None:
            index = values.index
        else:
            values = values.reindex(index)

        # zero len case (GH #2234)
        if not len(values) and columns is not None and len(columns):
            values = np.empty((0, 1), dtype=object)

    # we could have a categorical type passed or coerced to 'category'
    # recast this to an arrays_to_mgr
    if (is_categorical_dtype(getattr(values, 'dtype', None))
            or is_categorical_dtype(dtype)):

        if not hasattr(values, 'dtype'):
            values = prep_ndarray(values, copy=copy)
            values = values.ravel()
        elif copy:
            values = values.copy()

        index, columns = _get_axes(len(values), 1, index, columns)
        return arrays_to_mgr([values], columns, index, columns, dtype=dtype)
    elif is_extension_array_dtype(values):
        # GH#19157
        if columns is None:
            columns = [0]
        return arrays_to_mgr([values], columns, index, columns, dtype=dtype)

    # by definition an array here
    # the dtypes will be coerced to a single dtype
    values = prep_ndarray(values, copy=copy)

    if dtype is not None:
        if not is_dtype_equal(values.dtype, dtype):
            try:
                values = values.astype(dtype)
            except Exception as orig:
                e = ValueError("failed to cast to '{dtype}' (Exception "
                               "was: {orig})".format(dtype=dtype, orig=orig))
                raise_with_traceback(e)

    index, columns = _get_axes(*values.shape, index=index, columns=columns)
    values = values.T

    # if we don't have a dtype specified, then try to convert objects
    # on the entire block; this is to convert if we have datetimelike's
    # embedded in an object type
    if dtype is None and is_object_dtype(values):

        if values.ndim == 2 and values.shape[0] != 1:
            # transpose and separate blocks

            dvals_list = [maybe_infer_to_datetimelike(row) for row in values]
            for n in range(len(dvals_list)):
                if isinstance(dvals_list[n], np.ndarray):
                    dvals_list[n] = dvals_list[n].reshape(1, -1)

            from pandas.core.internals.blocks import make_block

            # TODO: What about re-joining object columns?
            block_values = [
                make_block(dvals_list[n], placement=[n])
                for n in range(len(dvals_list))
            ]

        else:
            datelike_vals = maybe_infer_to_datetimelike(values)
            block_values = [datelike_vals]
    else:
        block_values = [values]

    return create_block_manager_from_blocks(block_values, [columns, index])
コード例 #16
0
ファイル: construction.py プロジェクト: Itay4/pandas
def init_ndarray(values, index, columns, dtype=None, copy=False):
    # input must be a ndarray, list, Series, index

    if isinstance(values, ABCSeries):
        if columns is None:
            if values.name is not None:
                columns = [values.name]
        if index is None:
            index = values.index
        else:
            values = values.reindex(index)

        # zero len case (GH #2234)
        if not len(values) and columns is not None and len(columns):
            values = np.empty((0, 1), dtype=object)

    # we could have a categorical type passed or coerced to 'category'
    # recast this to an arrays_to_mgr
    if (is_categorical_dtype(getattr(values, 'dtype', None)) or
            is_categorical_dtype(dtype)):

        if not hasattr(values, 'dtype'):
            values = prep_ndarray(values, copy=copy)
            values = values.ravel()
        elif copy:
            values = values.copy()

        index, columns = _get_axes(len(values), 1, index, columns)
        return arrays_to_mgr([values], columns, index, columns,
                             dtype=dtype)
    elif (is_datetime64tz_dtype(values) or
          is_extension_array_dtype(values)):
        # GH#19157
        if columns is None:
            columns = [0]
        return arrays_to_mgr([values], columns, index, columns,
                             dtype=dtype)

    # by definition an array here
    # the dtypes will be coerced to a single dtype
    values = prep_ndarray(values, copy=copy)

    if dtype is not None:
        if not is_dtype_equal(values.dtype, dtype):
            try:
                values = values.astype(dtype)
            except Exception as orig:
                e = ValueError("failed to cast to '{dtype}' (Exception "
                               "was: {orig})".format(dtype=dtype,
                                                     orig=orig))
                raise_with_traceback(e)

    index, columns = _get_axes(*values.shape, index=index, columns=columns)
    values = values.T

    # if we don't have a dtype specified, then try to convert objects
    # on the entire block; this is to convert if we have datetimelike's
    # embedded in an object type
    if dtype is None and is_object_dtype(values):
        values = maybe_infer_to_datetimelike(values)

    return create_block_manager_from_blocks([values], [columns, index])