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fund-morning-star-crawler
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jackluson 3 years ago
parent e9cc424ca2
commit f5315450b5
1 changed files with 17 additions and 50 deletions
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67
src/fund_statistic.py
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@ -12,7 +12,6 @@ Copyright (c) 2020 Camel Lu
import time
import re
import decimal
import os
from pprint import pprint
import pandas as pd
import numpy as np
@ -35,11 +34,10 @@ def get_fund_code_pool():
'operator': '='
}
last_year_time = time.localtime(time.time() - 365 * 24 * 3600)
last_year_date = time.strftime('%Y-%m-%d', last_year_time)
# last_year_date = time.strftime('%Y-%m-%d', last_year_time)
condition_dict = {
'morning_star_rating_5': morning_star_rating_5_condition,
'morning_star_rating_3': morning_star_rating_3_condition,
# 'manager_start_date': '2020-05-25'
}
fund_code_pool = each_statistic.select_fund_pool(
**condition_dict,
@ -54,16 +52,12 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, fund_code_poo
quarter_index = get_last_quarter_str(2)
print("比较-->quarter_index", quarter_index)
last_quarter_input_file = './outcome/数据整理/strategy/all_stock_rank/' + \
quarter_index + '.xlsx'
data_last_quarter = pd.read_excel(io=last_quarter_input_file, engine="openpyxl", dtype={
"代码": np.str}, sheet_name=None)
last_quarter_input_file = './outcome/数据整理/strategy/all_stock_rank/' + quarter_index + '.xlsx'
data_last_quarter = pd.read_excel(io=last_quarter_input_file, engine="openpyxl", dtype={"代码": np.str}, sheet_name=None)
if market:
df_data_target_market = data_last_quarter.get(market)
df_data_target_market[quarter_index + '持有数量（只）'] = df_data_target_market[quarter_index + '持有数量（只）'].astype(
int)
each_statistic = FundStatistic()
df_data_target_market[quarter_index + '持有数量（只）'] = df_data_target_market[quarter_index + '持有数量（只）'].astype(int)
filter_list = []
for stock in stock_list:
@ -76,7 +70,6 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, fund_code_poo
holder_asset = stock_holder_detail.get('holder_asset')
if not market:
target_market = get_stock_market(stock_code)
print("target_market", target_market)
df_data_target_market = data_last_quarter.get(target_market)
target_loc = df_data_target_market[df_data_target_market['代码'] == stock_code]
last_holder_count = 0
@ -89,33 +82,21 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, fund_code_poo
target_loc[col_target].iloc[0]), 4)
diff_holder_count = holder_count - last_holder_count
diff_holder_asset = holder_asset - last_holder_asset
diff_holder_count_percent = '{:.2%}'.format(
diff_holder_count / last_holder_count) if last_holder_count != 0 else "+∞"
diff_holder_asset_percent = '{:.2%}'.format(
diff_holder_asset / last_holder_asset) if last_holder_asset != 0 else "+∞"
diff_holder_count_percent = '{:.2%}'.format(diff_holder_count / last_holder_count) if last_holder_count != 0 else "+∞"
diff_holder_asset_percent = '{:.2%}'.format(diff_holder_asset / last_holder_asset) if last_holder_asset != 0 else "+∞"
# flag = '📈' if diff_holder_count > 0 else '📉'
# if diff_holder_count == 0:
# flag = '⏸'
flag_count = 'up' if diff_holder_count > 0 else 'down'
if diff_holder_count == 0:
flag = '='
flag_asset = 'up' if diff_holder_asset > 0 else 'down'
if diff_holder_asset == 0:
flag = '='
item_tuple = [stock_code, stock_name, holder_count, last_holder_count,
diff_holder_count, diff_holder_count_percent, flag_count, holder_asset, last_holder_asset, diff_holder_asset, diff_holder_asset_percent, flag_asset]
if is_A_stock:
industry_name_third = stock_holder_detail.get(
'industry_name_third')
industry_name_second = stock_holder_detail.get(
'industry_name_second')
industry_name_first = stock_holder_detail.get(
'industry_name_first')
item_tuple = [*item_tuple, industry_name_third,
industry_name_second, industry_name_first]
industry_name_third = stock_holder_detail.get('industry_name_third')
industry_name_second = stock_holder_detail.get('industry_name_second')
industry_name_first = stock_holder_detail.get('industry_name_first')
item_tuple = [*item_tuple, industry_name_third,industry_name_second, industry_name_first]
# if diff_percent == "+∞" or not float(diff_percent.rstrip('%')) < -20:
filter_list.append(item_tuple)
@ -132,14 +113,12 @@ def t100_stocks_rank(each_statistic=None, *, quarter_index=None):
last_quarter_index = get_last_quarter_str(2)
output_file = './outcome/数据整理/strategy/top100_rank.xlsx'
sheet_name = quarter_index + '基金重仓股T100'
columns = ['代码',
'名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降']
columns = ['代码','名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降']
stock_top_list = each_statistic.all_stock_fund_count(
quarter_index=quarter_index,
filter_count=80)
stock_top_list = stock_top_list[:100] # 获取top100权重股
# pprint(stock_top_list)
filter_list = stocks_compare(stock_top_list)
df_filter_list = pd.DataFrame(filter_list, columns=columns)
update_xlsx_file(output_file, df_filter_list, sheet_name)
@ -154,8 +133,7 @@ def all_stocks_rank(each_statistic=None):
quarter_index = get_last_quarter_str(1)
print("该quarter_index为", quarter_index)
last_quarter_index = get_last_quarter_str(2)
columns = ['代码',
'名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降']
columns = ['代码','名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降']
output_file = './outcome/数据整理/strategy/all_stock_rank/' + quarter_index + '.xlsx'
stock_top_list = each_statistic.all_stock_fund_count(
@ -167,7 +145,6 @@ def all_stocks_rank(each_statistic=None):
other_stock_list = []
for stock_name_code in stock_top_list:
stock_code = stock_name_code[0].split('-', 1)[0]
#path = 'other'
if bool(re.search("^\d{5}$", stock_code)):
#path = '港股'
@ -176,8 +153,7 @@ def all_stocks_rank(each_statistic=None):
# 'A股/深证主板'、'A股/创业板'、'A股/上证主板'、'A股/科创板'
a_condition = bool(re.search(
"^(00(0|1|2|3)\d{3})|(30(0|1)\d{3})|(60(0|1|2|3|5)\d{3})|68(8|9)\d{3}$", stock_code))
target_item = find_from_list_of_dict(
all_a_stocks_industry_info_list, 'stock_code', stock_code)
target_item = find_from_list_of_dict(all_a_stocks_industry_info_list, 'stock_code', stock_code)
if a_condition and target_item:
stock_name_code[1]['industry_name_first'] = target_item.get(
'industry_name_first')
@ -204,7 +180,6 @@ def all_stocks_rank(each_statistic=None):
a_columns = [*columns, '三级行业', '二级行业', '一级行业']
df_a_list = pd.DataFrame(a_stock_compare_list, columns=a_columns)
print("df_a_list", df_a_list)
df_hk_list = pd.DataFrame(hk_stock_compare_list, columns=columns)
df_other_list = pd.DataFrame(other_stock_compare_list, columns=columns)
@ -251,22 +226,16 @@ def all_stock_holder_detail(each_statistic=None, *, quarter_index=None, threshol
path = 'A股/科创板'
else:
print('stock_name_code', stock_name_code)
hold_fund_count = stock[1]['count']
hold_fund_list = sorted(
stock[1]['fund_list'], key=lambda x: x['持有市值(亿元)'], reverse=True)
hold_fund_list = sorted(stock[1]['fund_list'], key=lambda x: x['持有市值(亿元)'], reverse=True)
df_list = pd.DataFrame(hold_fund_list)
# if stock_code == 'NTES':
# print('stock_code', df_list)
stock_name_code = stock_name_code.replace('-*', '-').replace('/', '-')
path = './outcome/数据整理/stocks/' + path + '/' + stock_name_code + '.xlsx'
path = path.replace('\/', '-')
print("path", path)
update_xlsx_file(path, df_list, quarter_index)
def get_special_fund_code_holder_stock_detail(each_statistic=None, quarter_index=None):
""" 获取某些基金的十大持仓股票信息
"""获取某些基金的十大持仓股票信息
"""
if each_statistic == None:
each_statistic = FundStatistic()
@ -337,11 +306,9 @@ def get_special_fund_code_holder_stock_detail(each_statistic=None, quarter_index
# 基金组合信息
fund_portfolio = holder_history_list[1]
fund_code_pool = list(fund_portfolio.keys())
holder_stock_industry_list = each_statistic.summary_special_funds_stock_detail(
fund_code_pool, quarter_index)
holder_stock_industry_list = each_statistic.summary_special_funds_stock_detail(fund_code_pool, quarter_index)
path = './outcome/数据整理/funds/高分权益基金组合十大持仓明细.xlsx'
columns = ['基金代码', '基金名称', '基金类型', '基金经理', '基金总资产（亿元）', '基金股票总仓位',
'十大股票仓位', '股票代码', '股票名称', '所占仓位', '所处仓位排名', '三级行业', '二级行业', '一级行业']
columns = ['基金代码', '基金名称', '基金类型', '基金经理', '基金总资产（亿元）', '基金股票总仓位', '十大股票仓位', '股票代码', '股票名称', '所占仓位', '所处仓位排名', '三级行业', '二级行业', '一级行业']
df_a_list = pd.DataFrame(holder_stock_industry_list, columns=columns)
# print("df_a_list", df_a_list)

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