import re # csv格式 # ‘k1,k2,k3\nv1,v2,v3\nv4,v5,v6\n‘ market_list_data = { "data": [ { "finance_mic": "SS", "finance_name": "上海证券交易所" }, { "finance_mic": "SZ", "finance_name": "深圳证券交易所" }, { "finance_mic": "CCFX", "finance_name": "中国金融期货交易所" } ] } tick_data = { "data": { "tick": { "fields": [ "business_time", "hq_px", "business_amount", "business_balance", "business_count", "business_direction" ], "600570.SS": [ [ 20150907092501, 41.58, 13000378, 540555717, 0, 0 ], [ 20150907093000, 42.1, 148300, 6254573, 0, 1 ] ] } } } kline_data = { "data": { "candle": { "fields": [ "min_time", "open_px", "high_px", "low_px", "close_px" ], "600570.SS": [ [ 201501061401, 54890, 54890, 54600, 54600 ], [ 201501061402, 54610, 54610, 54400, 54400 ] ] } } } trend_data = { "data": { "trend": { "fields": [ "min_time", "last_px", "avg_px", "business_amount" ], "600570.SS": [ [ 201501090930, 54.98, 54.98, 28327 ], [ 201501090931, 54.63, 54.829486, 49700 ] ] } } } real_data = { "data": { "snapshot": { "fields": [ "data_timestamp", "shares_per_hand", "open_px", "high_px", "low_px", "last_px", "business_amount", "business_balance", "offer_grp", "bid_grp" ], "600570.SS": [ 150305133, 100, 53980, 56000, 52510, 54950, 14465811, 788995643, "54850,9887,0,54860,1500,0,54900,13300,0,54950,10000,0,54990,800,0,", "54820,8000,0,54810,2100,0,54800,202900,0,54770,100,0,54720,1200,0," ], "000001.SZ": [ 153229327, 100, 15560, 15830, 15300, 15480, 170012067, 2634796408, "15490,93700,0,15500,260609,0,15510,69996,0,15520,87008,0,15530,71400,0,", "15480,438292,0,15470,149000,0,15460,411400,0,15450,414573,0,15440,303733,0," ] } } } trend5day_data = { "data": { "trend": { "fields": [ "min_time", "last_px", "avg_px", "business_amount", "business_balance" ], "600570.SS": [ [ 201504170931, 124.07, 124.83, 387955, 48426658 ], [ 201504170932, 123.01, 124.59, 572900, 71378859 ], [ 201504170933, 121.89, 123.94, 834100, 103378268 ], [ 201504170934, 122.44, 123.74, 941239, 116465390 ] ] } } } def one_prod_to_csv(data): csv = ‘‘ # head csv = csv + ‘,‘.join(data.get(‘fields‘)) + ‘\n‘ # body for item in data.keys(): if not item is ‘fields‘: body_key = item body_data = data.get(body_key) for item in body_data: new_item = [] for v in item: new_item.append(re.sub(r‘,‘, ‘|‘, str(v))) csv = csv + ‘,‘.join(new_item) + ‘\n‘ return csv def multi_prod_to_csv(data): csv = ‘‘ # head csv = csv + ‘,‘.join(data.get(‘fields‘)) + ‘\n‘ # body for k,v in data.items(): if not k is ‘fields‘: new_v = [] for item in v: new_v.append(re.sub(r‘,‘, ‘|‘, str(item))) csv = csv + ‘,‘.join(new_v) + ‘\n‘ return csv def dict_to_csv(data): csv = ‘‘ head_data = [] body_data = [] for item in data[0].keys(): head_data.append(item) # head csv = csv + ‘,‘.join(head_data) + ‘\n‘ # body for item in data: new_item = [] for k,v in item.items(): new_item.append(v) body_data.append(new_item) for item in body_data: csv = csv + ‘,‘.join(item) + ‘\n‘ return csv def market_list_to_csv(data): return dict_to_csv(data) def tick_to_csv(data): return one_prod_to_csv(data) def kline_to_csv(data): return one_prod_to_csv(data) def trend5day_to_csv(data): return one_prod_to_csv(data) def trend_to_csv(data): return one_prod_to_csv(data) def real_to_csv(data): return multi_prod_to_csv(data) print(market_list_to_csv(market_list_data.get(‘data‘))) print(tick_to_csv(tick_data.get(‘data‘).get(‘tick‘))) print(kline_to_csv(kline_data.get(‘data‘).get(‘candle‘))) print(trend5day_to_csv(trend5day_data.get(‘data‘).get(‘trend‘))) print(trend_to_csv(trend_data.get(‘data‘).get(‘trend‘))) print(real_to_csv(real_data.get(‘data‘).get(‘snapshot‘)))
时间: 2024-10-12 04:42:07