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| <!-- An exception thrown inside a promise will not be caught by a nesting try block due to the asynchronous nature of execution. | ||
| # streamlit-rxdb-dataframe | ||
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| Promises are designed to propagate errors to the next error handler or catch() block in the promise chain. Promises are asynchronous and operate outside of the normal call stack. When a Promise is created, it is added to the microtask queue, which is processed after the current call stack has completed. This means that the try-catch block surrounding the Promise will have already completed by the time the Promise is resolved or rejected. Therefore, any error occurring within the Promise will not be caught by the try-catch block. | ||
| Custom `streamlit` component connecting local browser `indexedDB` database as `RxDB` collection as `dataframe` | ||
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| ## Demo | ||
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| [demo](https://st-rxdb-dataframe.streamlit.app/) - based on TodoMVC | ||
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|  | ||
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| ## Usage | ||
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| ### Provide JSONSchema | ||
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| <details> | ||
| <summary>JSONSchema</summary> | ||
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| ```json | ||
| { | ||
| "definitions": {}, | ||
| "$schema": "http://json-schema.org/draft-07/schema#", | ||
| "type": "object", | ||
| "title": "Todo", | ||
| "description": "Todo Schema", | ||
| "required": ["id", "title", "createdAt"], | ||
| "version": 0, | ||
| "properties": { | ||
| "id": { | ||
| "type": "string", | ||
| "format": "uuid", | ||
| "title": "Id", | ||
| "pattern": "^(.*)$", | ||
| "maxLength": 36, | ||
| "readOnly": true | ||
| }, | ||
| "title": { | ||
| "type": "string", | ||
| "title": "Title", | ||
| "minLength": 3 | ||
| }, | ||
| "completed": { | ||
| "type": "boolean", | ||
| "title": "Done" | ||
| }, | ||
| "createdAt": { | ||
| "type": "string", | ||
| "title": "Created Date", | ||
| "format": "date-time", | ||
| "readOnly": true | ||
| }, | ||
| "last_modified": { | ||
| "type": "integer", | ||
| "format": "time", | ||
| "title": "Last Modified Date" | ||
| } | ||
| }, | ||
| "__indexes": ["createdAt"], | ||
| "primaryKey": "id", | ||
| "attachments": { | ||
| "encrypted": false | ||
| } | ||
| } | ||
| ``` | ||
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| </details> | ||
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| ### Provide Collection Config and use streamlit dataframe, data_editor or table | ||
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| ```python | ||
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| todoSchema: Dict = json.load(open(os.path.join(data_dir, "todo.schema.json"))) | ||
| # initial_docs: List = json.load(open(os.path.join(data_dir, "col.dump.json")))["docs"] | ||
| collection_config = { | ||
| "name": "todo", | ||
| "schema": todoSchema, # to auto load schema from remote url pass None | ||
| "localDocuments": True, | ||
| "options": { | ||
| # 'schemaUrl': 'assets/data/todo.schema.json', | ||
| # "initialDocs": initial_docs, | ||
| }, | ||
| } | ||
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| def on_change_dataframe(rxdb_state: RxDBSessionState): | ||
| print("RxDBDataframe component on_change call") | ||
| print("collection.info()", rxdb_state.info) | ||
| print("dataframe.head()", rxdb_state.dataframe.head()) | ||
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| df = rxdb_dataframe( | ||
| collection_config, | ||
| query=None, | ||
| with_rev=False, | ||
| on_change=on_change_dataframe, | ||
| ) | ||
| st.dataframe( | ||
| df, | ||
| use_container_width=True, | ||
| hide_index=True, | ||
| column_config=st.session_state["rxdb"]["column_config"], | ||
| column_order=["title", "completed", "createdAt"], | ||
| ) | ||
| ``` | ||
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| ## Run & Build | ||
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| ### Run | ||
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| ```bash | ||
| cd packages/streamlit-rxdb-dataframe/ | ||
| poetry run streamlit run example.py | ||
| ``` | ||
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| ### Build | ||
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| ```bash | ||
| poetry build -o ../../dist/packages/streamlit-rxdb-dataframe | ||
| ``` | ||
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| ### Publish | ||
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| ```bash | ||
| poetry publish -r test-pypi --dist-dir ../../dist/packages/streamlit-rx | ||
| db-dataframe | ||
| ``` | ||
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| <!-- | ||
| # TODO: Add form to construct RxQuery | ||
| # query_container = st.container() | ||
| # with query_container: | ||
| # to_filter_columns = st.multiselect( | ||
| # "Filter dataframe on", | ||
| # df.columns, | ||
| # key=f"{prefix}_multiselect", | ||
| # ) | ||
| # filters: Dict[str, Any] = dict() | ||
| # for column in to_filter_columns: | ||
| # left, right = st.columns((1, 20)) | ||
| # # Treat columns with < 10 unique values as categorical | ||
| # if is_categorical_dtype(df[column]) or df[column].nunique() < 10: | ||
| # left.write("↳") | ||
| # filters[column] = right.multiselect( | ||
| # f"Values for {column}", | ||
| # df[column].unique(), | ||
| # default=list(df[column].unique()), | ||
| # key=f"{prefix}_{column}", | ||
| # ) | ||
| # df = df[df[column].isin(filters[column])] | ||
| # elif is_numeric_dtype(df[column]): | ||
| # left.write("↳") | ||
| # _min = float(df[column].min()) | ||
| # _max = float(df[column].max()) | ||
| # step = (_max - _min) / 100 | ||
| # filters[column] = right.slider( | ||
| # f"Values for {column}", | ||
| # _min, | ||
| # _max, | ||
| # (_min, _max), | ||
| # step=step, | ||
| # key=f"{prefix}_{column}", | ||
| # ) | ||
| # df = df[df[column].between(*filters[column])] | ||
| # elif is_datetime64_any_dtype(df[column]): | ||
| # left.write("↳") | ||
| # filters[column] = right.date_input( | ||
| # f"Values for {column}", | ||
| # value=( | ||
| # df[column].min(), | ||
| # df[column].max(), | ||
| # ), | ||
| # key=f"{prefix}_{column}", | ||
| # ) | ||
| # if len(filters[column]) == 2: | ||
| # filters[column] = tuple(map(pd.to_datetime, filters[column])) # noqa: E501 | ||
| # start_date, end_date = filters[column] | ||
| # df = df.loc[df[column].between(start_date, end_date)] | ||
| # else: | ||
| # left.write("↳") | ||
| # filters[column] = right.text_input( | ||
| # f"Pattern in {column}", | ||
| # key=f"{prefix}_{column}", | ||
| # ) | ||
| # if filters[column]: | ||
| # print(filters[column]) | ||
| --> |
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