pdstools.utils.streamlit_utils¶
Module Contents¶
Functions¶
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Adds a UI on top of a dataframe to let viewers filter columns |
Returns unique model id count and row count from a dataframe |
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Processes a list of file paths. If there's only one file, returns the file's content as bytes |
- cachedSample()¶
- cachedDatamart(*args, **kwargs)¶
- import_datamart(**opts)¶
- fromUploadedFile(**opts)¶
- fromFilePath(**opts)¶
- model_selection_df(df: polars.LazyFrame, context_keys: list)¶
- Parameters:
df (polars.LazyFrame)
context_keys (list)
- filter_dataframe(df: polars.LazyFrame, schema: dict | None = None, queries=[]) polars.LazyFrame¶
Adds a UI on top of a dataframe to let viewers filter columns
- Parameters:
df (pl.DataFrame) – Original dataframe
schema (Optional[dict])
- Returns:
The filtered LazyFrame
- Return type:
pl.LazyFrame
- model_and_row_counts(df: pdstools.utils.types.any_frame)¶
Returns unique model id count and row count from a dataframe
- Parameters:
df (Union[pl.DataFrame, pl.LazyFrame]) – The input dataframe
- Returns:
unique model count row count
- Return type:
Tuple[int, int]
- configure_predictor_categorization()¶
- convert_df(df)¶
- process_files(file_paths: List[str], file_name: str) Tuple[bytes, str]¶
Processes a list of file paths. If there’s only one file, returns the file’s content as bytes and the provided file name. If there are multiple files, creates a zip file containing all the files and returns the zip file’s data as bytes and the generated zip file name.
- Parameters:
file_paths (List[str]) – A list of file paths to process.
file_name (str) – The file name to use when returning the file or zip file’s name.
- Returns:
The content of the single file as bytes and the file name if there’s only one file, or the zip file’s data as bytes and the zip file’s name if there are multiple files.
- Return type:
(bytes, str)