pdstools.utils.streamlit_utils¶

Attributes¶

`_MENU_ITEMS`
`_ASSETS_DIR`

Functions¶

`_is_newer_version_available`(→ bool)	Return True only when latest is strictly newer than installed.
`_apply_sidebar_logo`()	Re-apply the sidebar logo from session state (for sub-pages).
`standard_page_config`(page_title[, layout])	Apply a consistent `st.set_page_config` across all pdstools apps.
`show_sidebar_branding`(title)	Display the Pega logo and an app title at the top of the sidebar.
`show_version_header`([check_latest])	Display the pdstools version, an upgrade hint, and optionally a staleness warning.
`ensure_session_data`(key[, message])	Guard that stops page execution when key is missing from session state.
`get_data_path`(→ str \| None)	Return the data path set via `--data-path` CLI flag.
`get_sample_limit`(→ str \| None)	Return the raw sample limit string set via `--sample` CLI flag.
`get_temp_dir`(→ str \| None)	Return the temp directory set via `--temp-dir` CLI flag.
`parse_sample_spec`(→ dict[str, int \| float])	Parse a `--sample` flag value into keyword arguments.
`get_current_index`(options, key[, default])	Get index from session state if key exists and value is in options, else return default.
`cached_sample`()
`cached_datamart`(**kwargs)	Load ADMDatamart with caching.
`cached_sample_prediction`()
`cached_prediction_table`(**kwargs)	Load Prediction with caching.
`import_datamart`(extract_pyname_keys[, infer_schema_length])	Import ADMDatamart data from various sources.
`from_uploaded_file`(extract_pyname_keys, codespaces[, ...])
`from_file_path`(extract_pyname_keys, codespaces[, ...])
`model_selection_df`(df, context_keys)
`filter_dataframe`(→ polars.LazyFrame)	Adds a UI on top of a dataframe to let viewers filter columns
`model_and_row_counts`(df)	Returns unique model id count and row count from a dataframe
`configure_predictor_categorization`()
`convert_df`(df)
`st_get_latest_pdstools_version`()
`show_about_page`()	Render a standardised About page with version and dependency information.

Module Contents¶

_MENU_ITEMS¶

_ASSETS_DIR¶

_is_newer_version_available(installed: str, latest: str) → bool¶

Return True only when latest is strictly newer than installed.

Uses PEP 440 parsing so that pre-release / dev versions of installed (e.g. 4.6.0rc1) are correctly recognised as newer than an older stable release on PyPI (e.g. 4.5.2).

Parameters:

installed (str)
latest (str)

Return type:

bool

_apply_sidebar_logo()¶: Re-apply the sidebar logo from session state (for sub-pages).

standard_page_config(page_title: str, layout: str = 'wide', **kwargs)¶

Apply a consistent st.set_page_config across all pdstools apps.

Parameters:

page_title (str) – The browser-tab title for the page.
layout (str, default "wide") – Streamlit layout mode.
**kwargs – Extra keyword arguments forwarded to st.set_page_config.

show_sidebar_branding(title: str)¶

Display the Pega logo and an app title at the top of the sidebar.

Uses st.logo for the logo and CSS injection for the title, so both render above the page navigation. Call once from the Home page; sub-pages re-apply automatically via standard_page_config or ensure_data.

Parameters:: title (str) – Application title shown below the logo in the sidebar.

show_version_header(check_latest: bool = True)¶

Display the pdstools version, an upgrade hint, and optionally a staleness warning.

Parameters:: check_latest (bool, default True) – If True, queries PyPI for the latest version and shows an upgrade warning when the installed version is outdated.

ensure_session_data(key: str, message: str | None = None)¶

Guard that stops page execution when key is missing from session state.

Parameters:

key (str) – The st.session_state key to check.
message (str or None) – Custom warning text. Falls back to a generic “Please load data on the Home page.”

get_data_path() → str | None¶

Return the data path set via --data-path CLI flag.

Returns None when no path was configured.

Return type:: str | None

get_sample_limit() → str | None¶

Return the raw sample limit string set via --sample CLI flag.

Returns None when no sampling was requested.

Return type:: str | None

get_temp_dir() → str | None¶

Return the temp directory set via --temp-dir CLI flag.

Returns None when no temp directory was configured.

Return type:: str | None

parse_sample_spec(value: str) → dict[str, int | float]¶

Parse a --sample flag value into keyword arguments.

Supports absolute counts ("100000"), percentages ("10%"), and human-readable notation ("100k", "1M").

Returns:: Either {"n": <int>} or {"fraction": <float>}.
Return type:: dict
Parameters:: value (str)

get_current_index(options, key, default=0)¶: Get index from session state if key exists and value is in options, else return default.

cached_sample()¶

cached_datamart(**kwargs)¶

Load ADMDatamart with caching.

Parameters:: **kwargs – Arguments passed to ADMDatamart.from_ds_export

cached_sample_prediction()¶

cached_prediction_table(**kwargs)¶

Load Prediction with caching.

Parameters:: **kwargs – Arguments passed to Prediction.from_ds_export

import_datamart(extract_pyname_keys: bool, infer_schema_length: int = 10000)¶

Import ADMDatamart data from various sources.

Parameters:

extract_pyname_keys (bool) – Whether to extract additional keys from pyName column
infer_schema_length (int, default 10000) – Number of rows to scan for schema inference when reading CSV/JSON files. For large production datasets, increase this value (e.g., 200000) if columns are not being detected correctly.

from_uploaded_file(extract_pyname_keys, codespaces, infer_schema_length=10000)¶

from_file_path(extract_pyname_keys, codespaces, infer_schema_length=10000)¶

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 (dict | None)

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)¶

st_get_latest_pdstools_version()¶

show_about_page()¶

Render a standardised About page with version and dependency information.

Mirrors the Credits section of the Quarto ADM Health Check report. Call this from a Streamlit page to display pdstools version info, platform details, and an expandable dependency listing.