import ebay_api
import numpy as np

'''
file used to compile methods from ebay_api.py for curating training data
'''

curate = ebay_api.CurateData()
raw_data = curate.import_raw()
training = curate.to_training(raw_data) # NOTE have to reference PictureURL list here if you want to expand. Other column is string in subsequent dfs
# or use dropd.PictureURL.split(' ')
class_training = curate.class_training(training)
nvl_training = curate.nvl_training(training)
extracted_df = curate.extract_contents(nvl_training)
dropd = curate.drop_nvl_cols(extracted_df)

def expand_nvlclass(class_training, dropd):
    '''
    takes image url list from each cell and expands them into separate/duplicate
    instances. Modifies both class training and dropd dfs. Appends custom
    image url dict {'source':'destination'}.
    '''
    #interm_s =class_training.PictureURL.apply(lambda x: len(x))
    #expanded_class_training = class_training.loc[np.repeat(class_training.index.values, interm_s)].reset_index(drop=True)
    expanded_class_training = class_training.explode('PictureURL').reset_index(drop=True)
    expanded_dropd = dropd.loc[np.repeat(dropd.index.values, interm_s)].reset_index(drop=True) # TODO CHANGE this to use explode(). picture list needs preservation
    # prior to creating dropd and extracted. maybe run extraced_df after dropd or after running nvl_training

    #interm_s = interm_s.astype(str).applymap(lambda x: x.split(',')*4)