def api_panorama_dynamic_valuation_chg():
date = request.values.get('date')
result = {'industry_name': [], 'chg': []}
date_list = get_offset_open_date_list(date, 2)
chg_data = {}
chg_data_sorted = {}
chg_result = {}
for i in range(0, len(date_list)):
data = Stock_Industry_Basic.query.join(Stock_Industry_CSRC_1,
Stock_Industry_Basic.industry_code == Stock_Industry_CSRC_1.industry_csrc_1_code).add_columns(
Stock_Industry_CSRC_1.industry_csrc_1_name).filter(Stock_Industry_Basic.trade_date == date_list[i]).all()
if i == 0:
for j in data:
chg_data[j.industry_csrc_1_name] = []
chg_data[j.industry_csrc_1_name].append(j.Stock_Industry_Basic.pe_ttm_overall)
else:
for j in data:
chg_data[j.industry_csrc_1_name].append(j.Stock_Industry_Basic.pe_ttm_overall)
for i in chg_data:
chg_data_sorted[i] = round((chg_data[i][1] - chg_data[i][0]) / chg_data[i][0], 3)
sum_result = sorted(chg_data_sorted.items(), key=lambda x: x[1], reverse=True)
for i in sum_result:
industry = i[0][4:]
result['industry_name'].append(industry)
result['chg'].append(i[1])
return jsonify(result)
def api_panorama_dynamic_valuation_n():
date = request.values.get('date')
days=request.values.get('days')
result={'industry_name':[],'amount':[]}
date_list=get_offset_open_date_list(date,int(days))
sum_data={}
sum_data_sorted={}
sum_result={}
for i in range(0,len(date_list)):
data=Stock_Industry_Basic.query.join(Stock_Industry_CSRC_1,Stock_Industry_Basic.industry_code==Stock_Industry_CSRC_1.industry_csrc_1_code).add_columns(Stock_Industry_CSRC_1.industry_csrc_1_name).filter(Stock_Industry_Basic.trade_date==date_list[i]).all()
if i==0:
for j in data:
sum_data[j.industry_csrc_1_name]=[]
sum_data[j.industry_csrc_1_name].append(j.Stock_Industry_Basic.pe_ttm_overall)
else:
for j in data:
sum_data[j.industry_csrc_1_name].append(j.Stock_Industry_Basic.pe_ttm_overall)
for i in sum_data:
sum = 0
for a in sum_data[i]:
if a is None:
a = 0
sum += a
sum_data_sorted[i] = int(sum)
sum_result = sorted(sum_data_sorted.items(), key=lambda x: x[1], reverse=True)
for i in sum_result:
industry=i[0][4:]
result['industry_name'].append(industry)
result['amount'].append(i[1])
return jsonify(result)
def api_trading_point_sorting_steady():
date = request.args.get('date')
date_list = get_offset_open_date_list(date)
buy_count_data = []
sell_count_data = []
category_data = []
for i in date_list:
buy_count_data.append(
Model_Trading_Point.query.filter_by(trade_date=i,
steady_buy_point=1).count())
sell_count_data.append(
Model_Trading_Point.query.filter_by(trade_date=i,
steady_sell_point=1).count())
category_data.append(i[0:4] + '/' + i[4:6] + '/' + i[6:8])
model_result = Model_Trading_Point.query.filter_by(
trade_date=date, steady_buy_point=1).all()
model_data = []
for i in model_result:
code = i.ts_code
stock_basic = Stock_Basic.query.filter_by(ts_code=code).first()
stock_bar_result = Stock_Daily_Bar.query.filter(
Stock_Daily_Bar.ts_code == code,
Stock_Daily_Bar.trade_date <= date,
Stock_Daily_Bar.trade_date >= get_offset_date(
date, -365)).order_by(Stock_Daily_Bar.trade_date.asc()).all()
close = []
for j in stock_bar_result:
close.append(j.close)
basic_data = Stock_Daily_Basic.query.filter_by(
ts_code=code, trade_date=date).first()
model_data.append({
'symbol': stock_basic.symbol,
'name': stock_basic.name,
'bar': close[-60:],
'close': close[-1],
'min': min(close),
'max': max(close),
'turnover_rate': basic_data.turnover_rate
})
return jsonify({
'chart': {
'category': category_data,
'buy': buy_count_data,
'sell': sell_count_data
},
'table': model_data
})
def api_panorama_capital_flow_table():
date = request.values.get('date')
date_list = get_offset_open_date_list(date, 30)
data_list = {}
chg_list={}
cur_pcg_list={}
data_sorted = {}
flag=0
result = {'industry':[],'data':[],'chg':[],'cur_chg':[]}
for i in range(0, len(date_list)):
data = Stock_Industry_Basic.query.join(Stock_Industry_CSRC_1,
Stock_Industry_Basic.industry_code == Stock_Industry_CSRC_1.industry_csrc_1_code).add_columns(
Stock_Industry_CSRC_1.industry_csrc_1_name).filter(Stock_Industry_Basic.trade_date == date_list[i]).all()
if len(data)>0:
if i == flag:
for j in data:
data_list[j.industry_csrc_1_name] = []
data_list[j.industry_csrc_1_name].append(j.Stock_Industry_Basic.amount_sum/100000000)
else:
for j in data:
data_list[j.industry_csrc_1_name].append(j.Stock_Industry_Basic.amount_sum/100000000)
else:
flag+=1
for i in data_list:
chg_list[i]=[]
for j in range(1,len(data_list[i])):
if j == (len(data_list[i]) - 1):
k=(data_list[i][j]-data_list[i][j-1])/data_list[i][j-1]
cur_pcg_list[i]=k
chg_list[i].append(k)
else:
k = (data_list[i][j] - data_list[i][j - 1]) / data_list[i][j - 1]
chg_list[i].append(k)
data_sorted = sorted(cur_pcg_list.items(), key=lambda x: x[1], reverse=True)
for i in data_sorted:
result['industry'].append(i[0][4:])
result['data'].append(data_list[i[0]])
result['chg'].append(chg_list[i[0]])
result['cur_chg'].append(i[1])
return jsonify(result)
def api_trading_point_sorting_comprehensive():
date = request.args.get('date')
date_list = get_offset_open_date_list(date)
buy_count_data = []
sell_count_data = []
category_data = []
for i in date_list:
buy_count_data.append(
Model_Trading_Point.query.filter_by(
trade_date=i, aggressive_buy_point=1).count() +
Model_Trading_Point.query.filter_by(trade_date=i,
steady_buy_point=1).count())
sell_count_data.append(
Model_Trading_Point.query.filter_by(
trade_date=i, aggressive_sell_point=1).count() +
Model_Trading_Point.query.filter_by(trade_date=i,
steady_sell_point=1).count())
category_data.append(i[0:4] + '/' + i[4:6] + '/' + i[6:8])
model_aggressive_result = Model_Trading_Point.query.filter_by(
trade_date=date, aggressive_buy_point=1).all()
model_steady_result = Model_Trading_Point.query.filter_by(
trade_date=date, steady_buy_point=1).all()
aggressive_code_list = []
steady_code_list = []
for i in model_aggressive_result:
aggressive_code_list.append(i.ts_code)
for i in model_steady_result:
steady_code_list.append(i.ts_code)
model_common_data = []
model_aggressive_data = []
model_steady_data = []
for i in list(
set(aggressive_code_list).intersection(set(steady_code_list))):
stock_basic = Stock_Basic.query.filter_by(ts_code=i).first()
bar_data = Stock_Daily_Bar.query.filter_by(ts_code=i,
trade_date=date).first()
basic_data = Stock_Daily_Basic.query.filter_by(
ts_code=i, trade_date=date).first()
model_common_data.append({
'symbol': stock_basic.symbol,
'name': stock_basic.name,
'pct_chg': bar_data.pct_chg,
'turnover_rate': basic_data.turnover_rate
})
for i in list(set(aggressive_code_list).difference(set(steady_code_list))):
stock_basic = Stock_Basic.query.filter_by(ts_code=i).first()
bar_data = Stock_Daily_Bar.query.filter_by(ts_code=i,
trade_date=date).first()
basic_data = Stock_Daily_Basic.query.filter_by(
ts_code=i, trade_date=date).first()
model_aggressive_data.append({
'symbol': stock_basic.symbol,
'name': stock_basic.name,
'pct_chg': bar_data.pct_chg,
'turnover_rate': basic_data.turnover_rate
})
for i in list(set(steady_code_list).difference(set(aggressive_code_list))):
stock_basic = Stock_Basic.query.filter_by(ts_code=i).first()
bar_data = Stock_Daily_Bar.query.filter_by(ts_code=i,
trade_date=date).first()
basic_data = Stock_Daily_Basic.query.filter_by(
ts_code=i, trade_date=date).first()
model_steady_data.append({
'symbol': stock_basic.symbol,
'name': stock_basic.name,
'pct_chg': bar_data.pct_chg,
'turnover_rate': basic_data.turnover_rate
})
return jsonify({
'chart': {
'category': category_data,
'buy': buy_count_data,
'sell': sell_count_data
},
'table': {
'common': model_common_data,
'aggressive': model_aggressive_data,
'steady': model_steady_data
}
})
