o 沪g @sUddlmZddlZddlmZddlmZddlmZm Z m Z m Z m Z m Z mZmZmZddlmZddlmZddlmZdd lmZmZmZmZmZmZmZmZm Z m!Z!m"Z"dd l#m$Z$dd l%m&Z&dd l'm(Z(dd l)m*Z*m+Z+m,Z,ddl-m.Z.ddl/m0Z1ddl2m3Z3ddl4m5Z5ddl6m7Z7m8Z8m9Z9m:Z:ddl;mZ>erddl?m@Z@mAZAddlBZCddlDZEddlFZGddlHmIZIddlJmKZKeLeMZNdeOd<e deejPe eQe eRe eSe eTeUe ffdZVeddddd d!eQe eRe eSe eTeUe ff ZWd"eOd#<Gd$d%d%e d&d'ZXeGd(d)d)ZYdTd0d1ZZdUd8d9Z[dVd column name -> value. added_rows : List[Dict[str, str | int | float | bool | None]] A list of added rows, where each row is a mapping from column name to the cell value. deleted_rows : List[int] A list of deleted rows, where each row is the numerical position of the deleted row. z5dict[int, dict[str, str | int | float | bool | None]] edited_rowsz0list[dict[str, str | int | float | bool | None]] added_rows list[int] deleted_rowsN)__name__ __module__ __qualname____doc____annotations__r@r@b/var/www/html/chatdoc2/venv/lib/python3.10/site-packages/streamlit/elements/widgets/data_editor.pyr6ps  r6F)totalc@s&eZdZdZddd d Zdd d ZdS)DataEditorSerdezKDataEditorSerde is used to serialize and deserialize the data editor state.ui_value str | None widget_idstrreturnr6cCsl|dur iggdnt|}d|vri|d<d|vrg|d<d|vr'g|d<dd|dD|d<|S)N)r7r8r:r7r:r8cSsi|] \}}t||qSr@)int).0kvr@r@rA sz/DataEditorSerde.deserialize..)jsonloadsitems)selfrErGdata_editor_stater@r@rA deserializes"   zDataEditorSerde.deserialize editing_statecCstj|tdS)N)default)rOdumpsrH)rRrUr@r@rA serializeszDataEditorSerde.serializeN)rD)rErFrGrHrIr6)rUr6rIrH)r;r<r=r>rTrXr@r@r@rArCs rCvaluestr | int | float | bool | Nonecolumn_data_kindrrIrc CsF|durdSddl}zx|tjkrt|WS|tjkrt|WS|tjkr)t|WS|tjkr3t |WS|tj kr?t t|WS|tj krJ| |WS|tjtjtjfvr}||}||juraWdS|tjkri|WS|tjkrs|WS|tjkr|WSW|SW|St|jjfy}ztjd|||dWYd}~dSd}~ww)aConvert a value to the correct type. Parameters ---------- value : str | int | float | bool | None The value to convert. column_data_kind : ColumnDataKind The determined data kind of the column. The column data kind refers to the shared data type of the values in the column (e.g. int, float, str). Returns ------- The converted value. NrzFailed to parse value %s as %s.)exc_info)pandasrSTRINGrHINTEGERrJFLOATfloatBOOLEANboolDECIMALr TIMEDELTA TimedeltaDATETIMEDATETIME TimestampNaTdatetime ValueErrorerrors ParserErrorr0warning)rYr[pddatetime_valueexr@r@rA _parse_valuesX                   rudfr7;Mapping[int, Mapping[str, str | int | float | bool | None]]dataframe_schemarNonec Cst|D]3\}}t|}|D]&\}}|tkr$t||t|jj|<q|j|}t||||j||f<qqdS)aApply cell edits to the provided dataframe (inplace). Parameters ---------- df : pd.DataFrame The dataframe to apply the cell edits to. edited_rows : Mapping[int, Mapping[str, str | int | float | bool | None]] A hierarchical mapping based on row position -> column name -> value dataframe_schema: DataframeSchema The schema of the dataframe. N) rQrJrruindexvaluescolumnsget_lociat) rvr7rxrow_id row_changesrow_poscol_namerYcol_posr@r@rA_apply_cell_editss rr8list[dict[str, Any]]c Cs|sdSddl}d}d}t|j|jr|jj}|jj}|D]U}d}ddt|jdD}|D]!} || } | t krCt | |t }q1|j | } t | || || <q1|dure||j |ddf<||7}q|durr||j |ddf<qdS)aApply row additions to the provided dataframe (inplace). Parameters ---------- df : pd.DataFrame The dataframe to apply the row additions to. added_rows : List[Dict[str, Any]] A list of row additions. Each row addition is a dictionary with the column position as key and the new cell value as value. dataframe_schema: DataframeSchema The schema of the dataframe. NrcSsg|]}dqSNr@)rK_r@r@rA <sz(_apply_row_additions..)r] isinstancerz RangeIndexstopsteprangeshapekeysrrur|r}loc) rvr8rxrrrange_index_stoprange_index_step added_row index_valuenew_rowrrYrr@r@rA_apply_row_additionss0   rr:r9cCs|j|j|dddS)zApply row deletions to the provided dataframe (inplace). Parameters ---------- df : pd.DataFrame The dataframe to apply the row deletions to. deleted_rows : List[int] A list of row numbers to delete. T)inplaceN)droprz)rvr:r@r@rA_apply_row_deletionsTs rrScCsT|dr t||d||drt||d|dr(t||d|dSdS)aApply edits to the provided dataframe (inplace). This includes cell edits, row additions and row deletions. Parameters ---------- df : pd.DataFrame The dataframe to apply the edits to. data_editor_state : EditingState The editing state of the data editor component. dataframe_schema: DataframeSchema The schema of the dataframe. r7r:r8N)getrrr)rvrSrxr@r@rA_apply_dataframe_editscs   rdf_indexrccCsBddl}t||j|j|j|jfvp t|dp t|dp t|dS)zCheck if the index is supported by the data editor component. Parameters ---------- df_index : pd.Index The index to check. Returns ------- bool True if the index is supported, False otherwise. rNz&pandas.core.indexes.numeric.Int64Indexz(pandas.core.indexes.numeric.Float64Indexz'pandas.core.indexes.numeric.UInt64Index)r]typerIndex DatetimeIndexCategoricalIndexr*)rrrr@r@rA_is_supported_indexs rdata_dfcCsfddl}t|j|jrdd|jD|_dS|jj|jdkr1|jdd|jDdd dSdS) z`Fix the column headers of the provided dataframe inplace to work correctly for data editing.rNcSsg|] }dtt|qS)r)joinmaprH)rKheaderr@r@rArsz'_fix_column_headers..stringcSsi|]}|t|qSr@)rH)rKcolumnr@r@rArNsz'_fix_column_headers..T)r|r) r]rr| MultiIndex to_flat_indexapitypes infer_dtyperename)rrrr@r@rA_fix_column_headerss  rcCsZ|jjrdS|j|j}t|dkrtdt|dt|jvr+tdtddS)zCheck if the column names in the provided dataframe are valid. It's not allowed to have duplicate column names or column names that are named ``_index``. If the column names are not valid, a ``StreamlitAPIException`` is raised. NrzrAll column names are required to be unique for usage with data editor. The following column names are duplicated: z<. Please rename the duplicated columns in the provided data.zThe column name 'zu' is reserved for the index column and can't be used for data columns. Please rename the column in the provided data.)r|empty duplicatedlenr"listr)rduplicated_columnsr@r@rA_check_column_namess   rcolumns_configrc Cst|jfg}|t|D]C}|\}}||}||vrQ||}|ddur(q|d} | dur2q| d} | dur||j?d|t@||S)u`!Display a data editor widget. The data editor widget allows you to edit dataframes and many other data structures in a table-like UI. Parameters ---------- data : Anything supported by st.dataframe The data to edit in the data editor. .. note:: - Styles from ``pandas.Styler`` will only be applied to non-editable columns. - Text and number formatting from ``column_config`` always takes precedence over text and number formatting from ``pandas.Styler``. - Mixing data types within a column can make the column uneditable. - Additionally, the following data types are not yet supported for editing: ``complex``, ``list``, ``tuple``, ``bytes``, ``bytearray``, ``memoryview``, ``dict``, ``set``, ``frozenset``, ``fractions.Fraction``, ``pandas.Interval``, and ``pandas.Period``. - To prevent overflow in JavaScript, columns containing ``datetime.timedelta`` and ``pandas.Timedelta`` values will default to uneditable, but this can be changed through column configuration. width : int or None Desired width of the data editor expressed in pixels. If ``width`` is ``None`` (default), Streamlit sets the data editor width to fit its contents up to the width of the parent container. If ``width`` is greater than the width of the parent container, Streamlit sets the data editor width to match the width of the parent container. height : int or None Desired height of the data editor expressed in pixels. If ``height`` is ``None`` (default), Streamlit sets the height to show at most ten rows. Vertical scrolling within the data editor element is enabled when the height does not accomodate all rows. use_container_width : bool Whether to override ``width`` with the width of the parent container. If ``use_container_width`` is ``False`` (default), Streamlit sets the data editor's width according to ``width``. If ``use_container_width`` is ``True``, Streamlit sets the width of the data editor to match the width of the parent container. hide_index : bool or None Whether to hide the index column(s). If ``hide_index`` is ``None`` (default), the visibility of index columns is automatically determined based on the data. column_order : Iterable of str or None Specifies the display order of columns. This also affects which columns are visible. For example, ``column_order=("col2", "col1")`` will display 'col2' first, followed by 'col1', and will hide all other non-index columns. If None (default), the order is inherited from the original data structure. column_config : dict or None Configures how columns are displayed, e.g. their title, visibility, type, or format, as well as editing properties such as min/max value or step. This needs to be a dictionary where each key is a column name and the value is one of: - ``None`` to hide the column. - A string to set the display label of the column. - One of the column types defined under ``st.column_config``, e.g. ``st.column_config.NumberColumn("Dollar values”, format=”$ %d")`` to show a column as dollar amounts. See more info on the available column types and config options `here `_. To configure the index column(s), use ``_index`` as the column name. num_rows : "fixed" or "dynamic" Specifies if the user can add and delete rows in the data editor. If "fixed", the user cannot add or delete rows. If "dynamic", the user can add and delete rows in the data editor, but column sorting is disabled. Defaults to "fixed". disabled : bool or Iterable of str Controls the editing of columns. If True, editing is disabled for all columns. If an Iterable of column names is provided (e.g., ``disabled=("col1", "col2"))``, only the specified columns will be disabled for editing. If False (default), all columns that support editing are editable. key : str An optional string to use as the unique key for this widget. If this is omitted, a key will be generated for the widget based on its content. No two widgets may have the same key. on_change : callable An optional callback invoked when this data_editor's value changes. args : tuple An optional tuple of args to pass to the callback. kwargs : dict An optional dict of kwargs to pass to the callback. Returns ------- pandas.DataFrame, pandas.Series, pyarrow.Table, numpy.ndarray, list, set, tuple, or dict. The edited data. The edited data is returned in its original data type if it corresponds to any of the supported return types. All other data types are returned as a ``pandas.DataFrame``. Examples -------- >>> import streamlit as st >>> import pandas as pd >>> >>> df = pd.DataFrame( >>> [ >>> {"command": "st.selectbox", "rating": 4, "is_widget": True}, >>> {"command": "st.balloons", "rating": 5, "is_widget": False}, >>> {"command": "st.time_input", "rating": 3, "is_widget": True}, >>> ] >>> ) >>> edited_df = st.data_editor(df) >>> >>> favorite_command = edited_df.loc[edited_df["rating"].idxmax()]["command"] >>> st.markdown(f"Your favorite command is **{favorite_command}** 🎈") .. output:: https://doc-data-editor.streamlit.app/ height: 350px You can also allow the user to add and delete rows by setting ``num_rows`` to "dynamic": >>> import streamlit as st >>> import pandas as pd >>> >>> df = pd.DataFrame( >>> [ >>> {"command": "st.selectbox", "rating": 4, "is_widget": True}, >>> {"command": "st.balloons", "rating": 5, "is_widget": False}, >>> {"command": "st.time_input", "rating": 3, "is_widget": True}, >>> ] >>> ) >>> edited_df = st.data_editor(df, num_rows="dynamic") >>> >>> favorite_command = edited_df.loc[edited_df["rating"].idxmax()]["command"] >>> st.markdown(f"Your favorite command is **{favorite_command}** 🎈") .. output:: https://doc-data-editor1.streamlit.app/ height: 450px Or you can customize the data editor via ``column_config``, ``hide_index``, ``column_order``, or ``disabled``: >>> import pandas as pd >>> import streamlit as st >>> >>> df = pd.DataFrame( >>> [ >>> {"command": "st.selectbox", "rating": 4, "is_widget": True}, >>> {"command": "st.balloons", "rating": 5, "is_widget": False}, >>> {"command": "st.time_input", "rating": 3, "is_widget": True}, >>> ] >>> ) >>> edited_df = st.data_editor( >>> df, >>> column_config={ >>> "command": "Streamlit Command", >>> "rating": st.column_config.NumberColumn( >>> "Your rating", >>> help="How much do you like this command (1-5)?", >>> min_value=1, >>> max_value=5, >>> step=1, >>> format="%d ⭐", >>> ), >>> "is_widget": "Widget ?", >>> }, >>> disabled=["command", "is_widget"], >>> hide_index=True, >>> ) >>> >>> favorite_command = edited_df.loc[edited_df["rating"].idxmax()]["command"] >>> st.markdown(f"Your favorite command is **{favorite_command}** 🎈") .. output:: https://doc-data-editor-config.streamlit.app/ height: 350px rNF) default_valuewrites_allowedzThe data type (z) or format is not supported by the data editor. Please convert your data into a Pandas Dataframe or another supported data format.T) ensure_copyz"The type of the dataframe index - z+ - is not yet supported by the data editor.rrrequireddynamichiddenr) user_keyform_idrrrrrcolumn_config_mappingr string_value)on_change_handlerrr deserializer serializerctx value_typearrow_data_frame)Ar]pyarrowr!rdgrrdetermine_data_format DataFormatUNKNOWNr"rr;convert_anything_to_pandas_dfrrzrrrQ is_colum_type_arrow_incompatiblerastyperrrrrrcTable from_pandasrschemar"convert_arrow_table_to_arrow_bytesr%r rrH ArrowProtoidrrrrr EditingModeDYNAMICFIXED editing_moderis_pandas_stylerr+_get_delta_path_strset_uuidrrrrCr)rTrXrrY_enqueue convert_pandas_df_to_data_format) rRrrrrrrrrrrrrrrrpar data_formatrr column_datahas_range_indexr arrow_tablerx arrow_bytesr element_idproto styler_uuidserde widget_stater@r@rAr@sN                       r/cCs td|S)zGet our DeltaGenerator.r/)r )rRr@r@rArs zDataEditorMixin.dg)rr1rrrrrrcrrrrrrrrrrrrrrrrrrrIr1)rrrrrrrrcrrrrrrrrrrrrrrrrrrrIr3)rr5rrrrrrcrrrrrrrrrrrrrrrrrrrIr5)rIr/)r;r<r=r rr$propertyrr@r@r@rArs^r)rYrZr[rrIr)rvr3r7rwrxrrIry)rvr3r8rrxrrIry)rvr3r:r9rIry)rvr3rSr6rxrrIry)rr4rIrc)rr3rIry)rr3)rr3rrrxr)d __future__rrO dataclassesrdecimalrtypingrrrrr r r r r typing_extensionsr streamlitrr_logger*streamlit.elements.lib.column_config_utilsrrrrrrrrrrr!streamlit.elements.lib.form_utilsr*streamlit.elements.lib.pandas_styler_utilsrstreamlit.elements.lib.policiesrstreamlit.elements.lib.utilsrr r!streamlit.errorsr"streamlit.proto.Arrow_pb2r#rstreamlit.runtime.metrics_utilr$7streamlit.runtime.scriptrunner_utils.script_run_contextr%streamlit.runtime.stater&r'r(r)streamlit.type_utilr*streamlit.utilr+collections.abcr,r-numpynpr]rrrrpandas.io.formats.styler.streamlit.delta_generatorr/ get_loggerr;r0r?DataFrameGenericAliastuplersetdictrHr1r5r6rCrurrrrrrrrrr@r@r@rAs  ,  4              # L # <  %  >