import pandas as pd

pid = snakemake.params["pid"]
requested_features = snakemake.params["features"]
baseline_features = pd.DataFrame(columns=requested_features)
question_filename = snakemake.params["question_filename"]

dict_JCQ_demand_control_reverse = {
    "demand_0": " [Od mene se ne zahteva,",
    "demand_1": " [Imam dovolj časa, da končam",
    "demand_2": " [Pri svojem delu se ne srečujem s konfliktnimi"
}

participant_info = pd.read_csv(snakemake.input[0], parse_dates=["date_of_birth"])
if not participant_info.empty:
    if "age" in requested_features:
        now = pd.Timestamp("now")
        baseline_features.loc[0, "age"] = (
            now - participant_info.loc[0, "date_of_birth"]
        ).days / 365.25245
    if "gender" in requested_features:
        baseline_features.loc[0, "gender"] = participant_info.loc[0, "gender"]
    if "startlanguage" in requested_features:
        baseline_features.loc[0, "startlanguage"] = participant_info.loc[
            0, "startlanguage"
        ]
    if "demand" in requested_features:
        limesurvey_questions = pd.read_csv(question_filename, header=None).T
        limesurvey_questions[["code", "text"]] = limesurvey_questions[0].str.split(r"\.\s", expand=True, n=1)
        demand_reverse_lime_rows = limesurvey_questions["text"].str.startswith(dict_JCQ_demand_control_reverse["demand_0"]) | \
                                   limesurvey_questions["text"].str.startswith(dict_JCQ_demand_control_reverse["demand_1"]) | \
                                   limesurvey_questions["text"].str.startswith(dict_JCQ_demand_control_reverse["demand_2"])
        demand_reverse_lime = limesurvey_questions[demand_reverse_lime_rows]
        demand_reverse_lime.loc[:, "qid"] = demand_reverse_lime["code"].str.extract(r"\[(\d+)\]")

baseline_features.to_csv(
    snakemake.output[0], index=False, encoding="utf-8",
)