def gen_rows(plate_type, stock_type):
for elm in jo['data'][plate_type]:
bdat = dict_selector(elm, mode='plain')
bdat['plate_type'] = plate_type
bdat['stock_type'] = stock_type
for item in elm[stock_type]['items']:
item.update(bdat)
yield item
def pool_detail(self):
url = self.flashapi + '/pool/detail?pool_name=limit_up'
jo = self.get_json(url)
# dic = flatten_json(jo)
rows = []
for elm in jo['data']:
bdat = dict_selector(elm, mode='plain')
for item in elm['surge_reason']['related_plates']:
item.update(bdat)
rows.append(item)
df = pd.DataFrame.from_records(rows)
if self.debug: pdb.set_trace()
return df
def plate_data(self,plates):
fields ='plate_id,plate_name,fund_flow,rise_count,fall_count,stay_count,limit_up_count,core_avg_pcp,core_avg_pcp_rank,core_avg_pcp_rank_change,top_n_stocks,bottom_n_stocks'
url = self.flashapi+'/plate/data?fields={0}&plates={1}'.format(fields,','.join(plates))
jo = self.get_json(url)
rows = []
dic = flatten_json(jo)
for plate_id,elm in jo['data'].items():
bdat = dict_selector(elm,mode='plain')
bdat['key_plate'] = plate_id
for item in elm['bottom_n_stocks']['items']:
item.update(bdat)
rows.append(item)
df = pd.DataFrame.from_records(rows)
if self.debug: pdb.set_trace()
return df