__init__.py

"""
    This module implements the create_diff_report([df1, df2]) function.
"""
import warnings
from typing import Any, Dict, List, Optional, Union

from collections import defaultdict
import pandas as pd
from bokeh.resources import INLINE
from jinja2 import Environment, PackageLoader

from .diff_formatter import format_diff_report
from ..configs import Config
from ..create_report.report import Report

__all__ = ["create_diff_report"]

ENV_LOADER = Environment(
    loader=PackageLoader("dataprep", "eda/create_diff_report/templates"),
)


def create_diff_report(
    df_list: Union[List[pd.DataFrame], Dict[str, pd.DataFrame]],
    target: Optional[str] = None,
    config: Optional[Dict[str, Any]] = None,
    display: Optional[List[str]] = None,
    title: Optional[str] = "DataPrep Report",
    mode: Optional[str] = "basic",
    progress: bool = True,
) -> Report:
    """
    This function is to generate and render elements in a report object given multiple dataframes.

    Parameters
    ----------
    df_list
        The DataFrames for which data are calculated.
    target
        Target feature to be compared against all other columns.
    config
        A dictionary for configuring the visualizations
        E.g. config={"hist.bins": 20}
    display
        The list that contains the names of plots user wants to display,
        E.g. display =  ["bar", "hist"]
        Without user's specifications, the default is "auto"
    title: Optional[str], default "DataPrep Report"
        The title of the report, which will be shown on the navigation bar.
    mode: Optional[str], default "basic"
        This controls what type of report to be generated.
        Currently only the 'basic' is fully implemented.
    progress
        Whether to show the progress bar.

    Examples
    --------
    from dataprep.datasets import load_dataset
    from dataprep.eda import create_diff_report
    df_train = load_dataset('house_prices_train')
    df_test = load_dataset('house_prices_test')
    create_diff_report([df_train, df_test]) # show in browser on jupyter notebook
    """
    # pylint: disable=too-many-arguments

    _suppress_warnings()
    cfg = Config.from_dict(display, config)

    components = format_diff_report(df_list, cfg, mode, progress, target)

    dict_stats = defaultdict(list)

    for comps in components["dfs"]:
        for key, value in comps["overview"][0].items():
            if value is not None:
                dict_stats[key].append(value)

    context = {
        "resources": INLINE.render(),
        "title": title,
        "stats": dict_stats,
        "components": components,
        "is_diff_report": True,
        "df_labels": cfg.diff.label,
        "legend_labels": components["legend_lables"],
    }

    template_base = ENV_LOADER.get_template("base.html")
    report = template_base.render(context=context, zip=zip)
    return Report(report)


def _suppress_warnings() -> None:
    """
    suppress warnings in create_diff_report
    """
    warnings.filterwarnings(
        "ignore",
        "The default value of regex will change from True to False in a future version",
        category=FutureWarning,
    )