408 lines
12 KiB
Python
408 lines
12 KiB
Python
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# Copyright 2018-2022 Streamlit Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from collections.abc import Iterable
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from typing import Any, Dict, List, Mapping, Optional, Union, cast, TYPE_CHECKING
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from typing import TypeVar
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from numpy import ndarray
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from pandas import DataFrame
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from pandas.io.formats.style import Styler
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import pyarrow as pa
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from streamlit import type_util
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from streamlit.proto.Arrow_pb2 import Arrow as ArrowProto
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if TYPE_CHECKING:
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from streamlit.delta_generator import DeltaGenerator
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Data = Union[DataFrame, Styler, pa.Table, ndarray, Iterable, Dict[str, List[Any]], None]
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class ArrowMixin:
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def _arrow_dataframe(
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self,
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data: Data = None,
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width: Optional[int] = None,
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height: Optional[int] = None,
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) -> "DeltaGenerator":
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"""Display a dataframe as an interactive table.
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Parameters
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----------
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data : pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, Iterable, dict, or None
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The data to display.
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If 'data' is a pandas.Styler, it will be used to style its
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underlying DataFrame.
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width : int or None
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Desired width of the UI element expressed in pixels. If None, a
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default width based on the page width is used.
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height : int or None
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Desired height of the UI element expressed in pixels. If None, a
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default height is used.
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Examples
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--------
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>>> df = pd.DataFrame(
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... np.random.randn(50, 20),
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... columns=('col %d' % i for i in range(20)))
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...
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>>> st._arrow_dataframe(df)
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>>> st._arrow_dataframe(df, 200, 100)
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You can also pass a Pandas Styler object to change the style of
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the rendered DataFrame:
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>>> df = pd.DataFrame(
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... np.random.randn(10, 20),
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... columns=('col %d' % i for i in range(20)))
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...
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>>> st._arrow_dataframe(df.style.highlight_max(axis=0))
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"""
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# If pandas.Styler uuid is not provided, a hash of the position
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# of the element will be used. This will cause a rerender of the table
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# when the position of the element is changed.
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delta_path = self.dg._get_delta_path_str()
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default_uuid = str(hash(delta_path))
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proto = ArrowProto()
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marshall(proto, data, default_uuid)
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return self.dg._enqueue(
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delta_type="arrow_data_frame",
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element_proto=proto,
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element_width=width,
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element_height=height,
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)
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def _arrow_table(self, data: Data = None) -> "DeltaGenerator":
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"""Display a static table.
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This differs from `st._arrow_dataframe` in that the table in this case is
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static: its entire contents are laid out directly on the page.
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Parameters
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----------
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data : pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, Iterable, dict, or None
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The table data.
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Example
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-------
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>>> df = pd.DataFrame(
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... np.random.randn(10, 5),
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... columns=("col %d" % i for i in range(5)))
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...
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>>> st._arrow_table(df)
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"""
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# If pandas.Styler uuid is not provided, a hash of the position
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# of the element will be used. This will cause a rerender of the table
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# when the position of the element is changed.
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delta_path = self.dg._get_delta_path_str()
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default_uuid = str(hash(delta_path))
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proto = ArrowProto()
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marshall(proto, data, default_uuid)
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return self.dg._enqueue("arrow_table", proto)
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@property
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def dg(self) -> "DeltaGenerator":
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"""Get our DeltaGenerator."""
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return cast("DeltaGenerator", self)
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def marshall(proto: ArrowProto, data: Data, default_uuid: Optional[str] = None) -> None:
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"""Marshall pandas.DataFrame into an Arrow proto.
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Parameters
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----------
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proto : proto.Arrow
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Output. The protobuf for Streamlit Arrow proto.
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data : pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, Iterable, dict, or None
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Something that is or can be converted to a dataframe.
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default_uuid : Optional[str]
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If pandas.Styler UUID is not provided, this value will be used.
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This attribute is optional and only used for pandas.Styler, other elements
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(e.g. charts) can ignore it.
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"""
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if type_util.is_pandas_styler(data):
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# default_uuid is a string only if the data is a `Styler`,
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# and `None` otherwise.
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assert isinstance(
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default_uuid, str
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), "Default UUID must be a string for Styler data."
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_marshall_styler(proto, data, default_uuid)
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if isinstance(data, pa.Table):
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proto.data = type_util.pyarrow_table_to_bytes(data)
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else:
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df = type_util.convert_anything_to_df(data)
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proto.data = type_util.data_frame_to_bytes(df)
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def _marshall_styler(proto: ArrowProto, styler: Styler, default_uuid: str) -> None:
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"""Marshall pandas.Styler into an Arrow proto.
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Parameters
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----------
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proto : proto.Arrow
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Output. The protobuf for Streamlit Arrow proto.
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styler : pandas.Styler
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Helps style a DataFrame or Series according to the data with HTML and CSS.
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default_uuid : str
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If pandas.Styler uuid is not provided, this value will be used.
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"""
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# pandas.Styler uuid should be set before _compute is called.
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_marshall_uuid(proto, styler, default_uuid)
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# We're using protected members of pandas.Styler to get styles,
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# which is not ideal and could break if the interface changes.
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styler._compute()
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# In Pandas 1.3.0, styler._translate() signature was changed.
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# 2 arguments were added: sparse_index and sparse_columns.
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# The functionality that they provide is not yet supported.
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if type_util.is_pandas_version_less_than("1.3.0"):
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pandas_styles = styler._translate()
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else:
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pandas_styles = styler._translate(False, False)
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_marshall_caption(proto, styler)
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_marshall_styles(proto, styler, pandas_styles)
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_marshall_display_values(proto, styler.data, pandas_styles)
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def _marshall_uuid(proto: ArrowProto, styler: Styler, default_uuid: str) -> None:
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"""Marshall pandas.Styler uuid into an Arrow proto.
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Parameters
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----------
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proto : proto.Arrow
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Output. The protobuf for Streamlit Arrow proto.
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styler : pandas.Styler
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Helps style a DataFrame or Series according to the data with HTML and CSS.
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default_uuid : str
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If pandas.Styler uuid is not provided, this value will be used.
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"""
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if styler.uuid is None:
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styler.set_uuid(default_uuid)
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proto.styler.uuid = str(styler.uuid)
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def _marshall_caption(proto: ArrowProto, styler: Styler) -> None:
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"""Marshall pandas.Styler caption into an Arrow proto.
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Parameters
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----------
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proto : proto.Arrow
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Output. The protobuf for Streamlit Arrow proto.
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styler : pandas.Styler
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Helps style a DataFrame or Series according to the data with HTML and CSS.
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"""
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if styler.caption is not None:
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proto.styler.caption = styler.caption
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def _marshall_styles(
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proto: ArrowProto, styler: Styler, styles: Mapping[str, Any]
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) -> None:
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"""Marshall pandas.Styler styles into an Arrow proto.
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Parameters
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----------
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proto : proto.Arrow
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Output. The protobuf for Streamlit Arrow proto.
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styler : pandas.Styler
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Helps style a DataFrame or Series according to the data with HTML and CSS.
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styles : dict
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pandas.Styler translated styles.
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"""
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css_rules = []
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if "table_styles" in styles:
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table_styles = styles["table_styles"]
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table_styles = _trim_pandas_styles(table_styles)
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for style in table_styles:
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# styles in "table_styles" have a space
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# between the uuid and selector.
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rule = _pandas_style_to_css(
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"table_styles", style, styler.uuid, separator=" "
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)
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css_rules.append(rule)
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if "cellstyle" in styles:
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cellstyle = styles["cellstyle"]
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cellstyle = _trim_pandas_styles(cellstyle)
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for style in cellstyle:
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rule = _pandas_style_to_css("cell_style", style, styler.uuid)
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css_rules.append(rule)
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if len(css_rules) > 0:
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proto.styler.styles = "\n".join(css_rules)
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M = TypeVar("M", bound=Mapping[str, Any])
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def _trim_pandas_styles(styles: List[M]) -> List[M]:
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"""Filter out empty styles.
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Every cell will have a class, but the list of props
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may just be [['', '']].
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Parameters
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----------
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styles : list
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pandas.Styler translated styles.
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"""
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return [x for x in styles if any(any(y) for y in x["props"])]
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def _pandas_style_to_css(
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style_type: str,
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style: Mapping[str, Any],
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uuid: str,
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separator: str = "",
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) -> str:
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"""Convert pandas.Styler translated style to CSS.
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Parameters
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----------
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style_type : str
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Either "table_styles" or "cell_style".
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style : dict
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pandas.Styler translated style.
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uuid : str
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pandas.Styler uuid.
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separator : str
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A string separator used between table and cell selectors.
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"""
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declarations = []
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for css_property, css_value in style["props"]:
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declaration = css_property.strip() + ": " + css_value.strip()
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declarations.append(declaration)
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table_selector = f"#T_{uuid}"
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# In pandas < 1.1.0
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# translated_style["cellstyle"] has the following shape:
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# [
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# {
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# "props": [["color", " black"], ["background-color", "orange"], ["", ""]],
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# "selector": "row0_col0"
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# }
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# ...
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# ]
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#
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# In pandas >= 1.1.0
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# translated_style["cellstyle"] has the following shape:
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# [
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# {
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# "props": [("color", " black"), ("background-color", "orange"), ("", "")],
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# "selectors": ["row0_col0"]
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# }
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# ...
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# ]
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if style_type == "table_styles" or (
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style_type == "cell_style" and type_util.is_pandas_version_less_than("1.1.0")
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):
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cell_selectors = [style["selector"]]
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else:
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cell_selectors = style["selectors"]
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selectors = []
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for cell_selector in cell_selectors:
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selectors.append(table_selector + separator + cell_selector)
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selector = ", ".join(selectors)
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declaration_block = "; ".join(declarations)
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rule_set = selector + " { " + declaration_block + " }"
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return rule_set
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def _marshall_display_values(
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proto: ArrowProto, df: DataFrame, styles: Mapping[str, Any]
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) -> None:
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"""Marshall pandas.Styler display values into an Arrow proto.
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Parameters
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----------
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proto : proto.Arrow
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Output. The protobuf for Streamlit Arrow proto.
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df : pandas.DataFrame
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A dataframe with original values.
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styles : dict
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pandas.Styler translated styles.
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"""
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new_df = _use_display_values(df, styles)
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proto.styler.display_values = type_util.data_frame_to_bytes(new_df)
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def _use_display_values(df: DataFrame, styles: Mapping[str, Any]) -> DataFrame:
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"""Create a new pandas.DataFrame where display values are used instead of original ones.
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Parameters
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----------
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df : pandas.DataFrame
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A dataframe with original values.
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styles : dict
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pandas.Styler translated styles.
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"""
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import re
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# If values in a column are not of the same type, Arrow
|
||
|
|
# serialization would fail. Thus, we need to cast all values
|
||
|
|
# of the dataframe to strings before assigning them display values.
|
||
|
|
new_df = df.astype(str)
|
||
|
|
|
||
|
|
cell_selector_regex = re.compile(r"row(\d+)_col(\d+)")
|
||
|
|
if "body" in styles:
|
||
|
|
rows = styles["body"]
|
||
|
|
for row in rows:
|
||
|
|
for cell in row:
|
||
|
|
match = cell_selector_regex.match(cell["id"])
|
||
|
|
if match:
|
||
|
|
r, c = map(int, match.groups())
|
||
|
|
new_df.iat[r, c] = str(cell["display_value"])
|
||
|
|
|
||
|
|
return new_df
|