modules.pull_config.convert.convert()

Complexity

Conditions

11

Size

Total Lines	76
Code Lines	54

Duplication

Lines	76
Ratio	100 %

Importance

Changes

0

import pandas as pd
def convert():

This function exceeds the maximum number of variables (20/15).

This code seems to be duplicated in your project.

    """

    :return:
    :rtype:
    """
    pd.set_option('mode.chained_assignment', None)
    print("Loading data")
    values_input = import_from_sheets()
    df = pd.DataFrame(values_input[1:], columns=values_input[0])

    print("Transforming data")
    monsters_df = df[["name", "type"]]
    monsters_df["type"] = pd.to_numeric(df["type"])

    triggers = df.drop(['name', 'role', 'type', 'id'], axis=1)
    triggers = triggers.applymap(lambda s: s.lower() if isinstance(s) == str else s)
    # triggers = triggers.applymap(lambda s: unidecode.unidecode(s) if type(s) == str else s)

    triggers_list = []
    with tqdm(total=len(triggers), file=sys.stdout) as pbar:
        for row in triggers.itertuples(index=False):
            helpt = pd.Series(row)
            helpt = helpt[~helpt.isna()]
            # Drop empty strings
            helpt = pd.Series(filter(None, helpt))
            # Copy strings with spaces without keeping them
            for trigger in helpt:
                trigger_nospace = trigger.replace(' ', '')
                if trigger_nospace != trigger:
                    helpt = helpt.append(pd.Series(trigger_nospace))
            helpt = helpt.drop_duplicates()
            triggers_list.append(helpt)
            pbar.update(1)

    print("Creating trigger structure")
    triggers_def = []
    with tqdm(total=len(triggers_list), file=sys.stdout) as pbar:
        for i in triggers_list:
            triggers_def.append(list(i))
            pbar.update(1)
    triggers_def_series = pd.Series(triggers_def)
    monsters_df.insert(loc=0, column='triggers', value=triggers_def_series)

    print("Creating output")

    types = {'id': [4, 3, 2, 1, 0], 'label': ["Common", "Event_Likan", "Event_Ulf", "Legendary", "Rare"]}
    types_df = pd.DataFrame(data=types)
    milestones = {'total': [150, 1000, 5000], 'name': ["Rare Spotter", "Legendary Spotter", "Mythic Spotter"]}
    milestones_df = pd.DataFrame(data=milestones)
    json_final = {'milestones': milestones_df, 'types': types_df, 'commands': monsters_df}

    # convert dataframes into dictionaries
    data_dict = {
        key: json_final[key].to_dict(orient='records')
        for key in json_final
    }

    # write to disk
    with open('json_files/config.json', 'w', encoding='utf8') as f:
        json.dump(
            data_dict,
            f,
            indent=4,
            ensure_ascii=False,
            sort_keys=False
        )
    with open('modules/pull_config/output/config.txt', 'w', encoding='utf8') as f:
        json.dump(
            data_dict,
            f,
            indent=4,
            ensure_ascii=False
        )

    print(".json saved")