Edmond Yoo
2018-09-16 0dab894a5be9f7d10d85e89dea91d02c71bae84d
fetch_data.py
@@ -1,16 +1,26 @@
from urllib import request
import ast
import json
import pandas as pd
import re
import os
import transform_data
import time
all_set_list = ['cmd', 'bfz', 'all', 'ulg',
                'mrd', 'dst', '5dn', 'chk', 'bok', 'sok', 'rav', 'gpt', 'dis', 'csp', 'tsp', 'plc', 'fut',
                '10e', 'lrw', 'mor', 'shm', 'eve', 'ala', 'con', 'arb', 'm10', 'zen', 'wwk', 'roe', 'm11', 'som', 'mbs',
                'nph', 'm12', 'isd', 'dka', 'avr', 'm13', 'rtr', 'gtc', 'dgm', 'm14', 'ths', 'bng', 'jou']
def fetch_all_cards_text(url='https://api.scryfall.com/cards/search?q=layout:normal+format:modern+lang:en+frame:2003',
                         csv_name=''):
    has_more = True
    cards = []
    # get cards dataset as a json from the query
    while has_more:
        res_file_dir, http_message = request.urlretrieve(url)
        with open(res_file_dir) as res_file:
        with open(res_file_dir, 'r') as res_file:
            res_json = json.loads(res_file.read())
            cards += res_json['data']
            has_more = res_json['has_more']
@@ -18,23 +28,30 @@
                url = res_json['next_page']
            print(len(cards))
    # Convert them into a dataframe, and truncate unnecessary columns
    df = pd.DataFrame.from_dict(cards)
    df['image'] = ''
    for ind, row in df.iterrows():
        df.set_value(ind, 'image', row['image_uris']['png'])
    if csv_name != '':
        df = df[['artist', 'border_color', 'collector_number', 'color_identity', 'colors', 'flavor_text', 'image_uris',
                 'image', 'mana_cost', 'legalities', 'name', 'oracle_text', 'rarity', 'type_line', 'set', 'set_name',
                 'power', 'toughness']]
        df.to_csv(csv_name, sep=';')
                 'mana_cost', 'legalities', 'name', 'oracle_text', 'rarity', 'type_line', 'set', 'set_name', 'power',
                 'toughness']]
        #df.to_json(csv_name)
        df.to_csv(csv_name, sep=';')  # Comma doesn't work, since some columns are saved as a dict
    return cards
    return df
def load_all_cards_text(csv_name):
    #with open(csv_name, 'r') as json_file:
    #    cards = json.loads(json_file.read())
    #df = pd.DataFrame.from_dict(cards)
    df = pd.read_csv(csv_name, sep=';')
    return df
# Pulled from Django framework (https://github.com/django/django/blob/master/django/utils/text.py)
def get_valid_filename(s):
    """
    NOTE: Pulled from Django framework (https://github.com/django/django/blob/master/django/utils/text.py)
    Return the given string converted to a string that can be used for a clean
    filename. Remove leading and trailing spaces; convert other spaces to
    underscores; and remove anything that is not an alphanumeric, dash,
@@ -46,14 +63,45 @@
    return re.sub(r'(?u)[^-\w.]', '', s)
def fetch_cards_image(cards_json, out_dir, size='large'):
    for card in cards_json:
        request.urlretrieve(card['image_uris'][size], '%s\%s' % (out_dir, card['name']))
    pass
def fetch_all_cards_image(df, out_dir='', size='png'):
    if isinstance(df, pd.Series):
        fetch_card_image(df, out_dir, size)
    else:
        for ind, row in df.iterrows():
            fetch_card_image(row, out_dir, size)
def fetch_card_image(row, out_dir='', size='png'):
    if isinstance(row['image_uris'], str):  # For some reason, dict isn't being parsed in the previous step
        png_url = ast.literal_eval(row['image_uris'])[size]
    else:
        png_url = row['image_uris'][size]
    if out_dir == '':
        out_dir = 'data/%s/%s' % (size, row['set'])
    if not os.path.exists(out_dir):
        os.makedirs(out_dir)
    img_name = '%s/%s_%s.png' % (out_dir, row['collector_number'], get_valid_filename(row['name']))
    if not os.path.isfile(img_name):
        request.urlretrieve(png_url, filename=img_name)
        print(img_name)
def main():
    fetch_all_cards_text(csv_name='data/all_cards.csv')
    for set_name in all_set_list:
        csv_name = '%s/csv/%s.csv' % (transform_data.data_dir, set_name)
        print(csv_name)
        if not os.path.isfile(csv_name):
            df = fetch_all_cards_text(url='https://api.scryfall.com/cards/search?q=set:%s+lang:en'
                                          % set_name, csv_name=csv_name)
        else:
            df = load_all_cards_text(csv_name)
        time.sleep(1)
        #fetch_all_cards_image(df, out_dir='../usb/data/png/%s' % set_name)
    #df = fetch_all_cards_text(url='https://api.scryfall.com/cards/search?q=layout:normal+lang:en+frame:2003',
    #                          csv_name='data/csv/all.csv')
    pass
if __name__ == '__main__':
    main()
    pass