def generate_miscbuffs_source():
j = json_read(JSON_PATH)
miscbuffs = parse_miscbuffs(j["miscbuffs"])
miscbuffs_map_elements = []
for (_, t) in miscbuffs.items():
uniqueness_tags = []
for uniqueness_tag in t["uniqueness_tags"]:
uniqueness_tags.append(f" \"{uniqueness_tag}\"")
uniqueness_tags_str = "\n".join(uniqueness_tags)
miscbuffs_map_elements.append(
f" {{\n"
f" \"{t['miscbuff_id']}\",\n"
f" {{\n"
f" \"{t['miscbuff_id']}\", // id\n"
f" \"{t['miscbuff_name']}\", // name\n"
f" {t['added_raw']}, // added_raw\n"
f" {t['base_raw_multiplier']}, // base_raw_multiplier\n"
f" {{\n"
f"{uniqueness_tags_str}\n"
f" }}\n"
f" }}\n"
f" }},")
file_write(H_PATH, data=H_BASE)
cpp_file_data = CPP_BASE.format(
miscbuffs_map_elements="\n".join(miscbuffs_map_elements), )
file_write(CPP_PATH, data=cpp_file_data)
def generate_skills_source():
j = json_read(SKILLS_JSON_PATH)
skills = parse_skills(j["skills"])
setbonuses = parse_setbonuses(j["set_bonuses"])
skill_declarations = []
skill_nids = []
skill_definitions = []
skill_map_elements = []
setbonus_declarations = []
setbonus_definitions = []
setbonus_map_elements = []
setbonus_array_elements = []
num_setbonuses = len(setbonuses)
next_nid = 0
for (_, skill) in skills.items():
skill_declarations.append(f"extern const Skill {skill['identifier']};")
skill_nids.append(
f"constexpr std::size_t {skill['nid_identifier']} = {next_nid};")
skill_definitions.append(
f"const Skill {skill['identifier']} = {{\n"
f" {next_nid}, // nid\n"
f" \"{skill['skill_id']}\", // id\n"
f" \"{skill['skill_name']}\", // name\n"
f" {skill['normal_limit']}, // normal_limit\n"
f" {skill['secret_limit']}, // secret_limit\n"
f" {skill['states']} // states\n"
f"}};")
skill_map_elements.append(
f" {{ \"{skill['skill_id']}\", &{skill['identifier']} }},")
next_nid += 1
for (_, setbonus) in setbonuses.items():
stages = []
highest_stage = 0
for (parts, skill_id) in setbonus["stages"]:
stages.append(
f" {{ {parts}, &{skills[skill_id]['identifier']} }},")
if parts > highest_stage:
highest_stage = parts
stages_str = "\n".join(stages)
setbonus_declarations.append(
f"extern const SetBonus {setbonus['identifier']};")
setbonus_definitions.append(
f"const SetBonus {setbonus['identifier']} = {{\n"
f" \"{setbonus['sb_id']}\", // id\n"
f" \"{setbonus['sb_name']}\", // name\n"
f" {{ // stages\n"
f"{stages_str}\n"
f" }},\n"
f" {highest_stage} // highest_stage\n"
f"}};")
setbonus_map_elements.append(
f" {{ \"{setbonus['sb_id']}\", &{setbonus['identifier']} }},")
setbonus_array_elements.append(f" &{setbonus['identifier']},")
h_file_data = SKILLS_H_BASE.format(
skill_declarations="\n".join(skill_declarations),
skill_nids="\n".join(skill_nids),
setbonus_declarations="\n".join(setbonus_declarations),
num_setbonuses=num_setbonuses,
)
file_write(SKILLS_H_PATH, data=h_file_data)
cpp_file_data = SKILLS_CPP_BASE.format(
skill_definitions="\n\n".join(skill_definitions),
setbonus_definitions="\n\n".join(setbonus_definitions),
skill_map_elements="\n".join(skill_map_elements),
setbonus_map_elements="\n".join(setbonus_map_elements),
setbonus_array_elements="\n".join(setbonus_array_elements),
num_setbonuses=num_setbonuses,
)
file_write(SKILLS_CPP_PATH, data=cpp_file_data)
def get_h_data(code, threadName):
# engine = sql_model.get_conn()
# stock_data = ts.get_h_data(code, start="2017-01-01", end="2017-01-05", autype='hfq')
# stock_data['sCode'] = code
# stock_data['tDateTime'] = stock_data.index
# stock_data.rename(columns={'open': 'iOpeningPrice', 'high': 'iMaximumPrice', 'close': 'iClosingPrice',
# 'low': 'iMinimumPrice', 'volume': 'iVolume', 'amount': 'iAmount'}, inplace=True)
# stock_data = common.get_average_line('600077', stock_data)
# stock_data2 = stock_data.sort_index(ascending=True)
# stock_data2.to_sql('stock_daily_data', engine, if_exists='append', index=False)
# debug.p(stock_data2)
# start_year = 1991
# start_year = 1990
# 从这个股票已有数据的最后一个日期开始获取
engine = sql_model.get_conn()
sql = "select * from stock_daily_data where sCode = '" + code + "' order by tDateTime desc limit 1"
print("%s %s" % (threadName, sql))
df = pd.read_sql(sql, engine)
if not df.empty:
start_date = df.loc[0, ['tDateTime']].values[0] + datetime.timedelta(
days=1)
# s = start_datetime.strftime("%Y-%m-%d")
date_str = "2016-11-30 13:53:59"
# datetime.datetime.strptime(date_str, "%Y-%m-%d %H:%M:%S")
# start_year = t.year
else:
start_date = "1990-01-01"
# 日期字符串转换为日期格式
start_time = datetime.datetime.strptime(str(start_date), "%Y-%m-%d")
# 判断开始时间如果是礼拜六, 则加两天
weekday = start_time.weekday()
if weekday == 5:
start_time = start_time + datetime.timedelta(days=2)
if start_time.strftime("%Y-%m-%d") == datetime.datetime.now().strftime(
"%Y-%m-%d") and datetime.datetime.now().hour < 15:
print("\n")
print("%s %s %s 无需更新" % (threadName, code, start_time))
return 1
conn = ts.get_apis()
while start_time < datetime.datetime.now():
try:
# fh = open("testfile", "w")
# fh.write("这是一个测试文件，用于测试异常!!")
# fh.close()
# if start_time >= datetime.datetime.now():
# continue
end_time = start_time + datetime.timedelta(days=365)
# end = str(end_year) + "-01-01"
# debug.p(start_time.year)
print("%s %s %s %s 开始" % (threadName, code, start_time, end_time))
stock_data = ts.bar(code,
conn,
adj="hfq",
start_date=str(start_time),
end_date=str(end_time),
factors=['tor'])
# p(start_time)
# stock_data = ts.get_h_data(code, start=str(start_time), end=str(end_time), autype='hfq')
# stock_data = ts.get_h_data('000007', start="2018-06-13", end="2018-07-12", autype='hfq')
# print(stock_data)
# stock_data = ts.bar('000010', conn, adj="hfq", start_date="2018-06-14", end_date="2018-06-14",
# factors=['vr', 'tor'])
# p(stock_data)
# exit("dsfds")
# p(stock_data )
# 下市了的股 df的值是None。 没下市只是当时没数据的股 df的值空的dataframe
if stock_data is None:
return False
del stock_data['p_change']
stock_data['tDateTime'] = stock_data.index
stock_data2 = stock_data.sort_index(ascending=True)
# stock_data['sCode'] = code
# stock_data2.rename(columns={'open': 'iOpeningPrice', 'high': 'iMaximumPrice', 'close': 'iClosingPrice',
# 'low': 'iMinimumPrice', 'volume': 'iVolume', 'amount': 'iAmount'}, inplace=True)
stock_data2.rename(columns={
'open': 'iOpeningPrice',
'high': 'iMaximumPrice',
'close': 'iClosingPrice',
'low': 'iMinimumPrice',
'vol': 'iVolume',
'amount': 'iAmount',
'code': 'sCode',
'tor': 'iTurnoverRate'
},
inplace=True)
# p(stock_data2.iloc[1]['iAmount'] > 0)
# p(stock_data2.iloc[1]['iAmount'] > 0)
stock_data2 = stock_data2[stock_data2.iVolume > 1]
# stock_data2['iVolume'] = '{:.5f}'.format(stock_data2['iVolume'])
# p(stock_data2)
# 存入数据库
tosql_res = stock_data2.to_sql('stock_daily_data',
engine,
if_exists='append',
index=False)
if tosql_res:
common.file_write("tosql_" + threadName, tosql_res)
print("%s %s %s" % (threadName, __name__, str(tosql_res)))
except IOError:
conn = ts.get_apis()
except TypeError:
conn = ts.get_apis()
# traceback.print_exc()
# # print("IOError等待60秒")
# # time.sleep(60)
# proxy_address = requests.get("http://112.124.4.247:5010/get/").text
# print("%s 更换代理 %s" % (threadName, proxy_address))
#
# # 请求接口获取数据
# proxy = {
# # 'http': '106.46.136.112:808'
# # 'https': "https://112.112.236.145:9999",
# "http": proxy_address
# }
# print(proxy)
# # 创建ProxyHandler
# proxy_support = ProxyHandler(proxy)
# # 创建Opener
# opener = build_opener(proxy_support)
# # 安装OPener
# install_opener(opener)
else:
print("\n")
print("%s %s %s %s 成功" % (threadName, code, start_time, end_time))
start_time = end_time + datetime.timedelta(days=1)
def get_h_week_data(code, threadName, conn):
# 从这个股票已有数据的最后一个日期开始获取
engine = sql_model.get_conn()
sql = "select * from stock_weekly_data where sCode = '" + code + "' order by tDateTime desc limit 1"
print("%s %s" % (threadName, sql))
df = pd.read_sql(sql, engine)
if not df.empty:
start_date = df.loc[0, ['tDateTime']].values[0] + datetime.timedelta(
days=1)
start_time = datetime.datetime.strptime(str(start_date), "%Y-%m-%d")
else:
start_date = "1990-01-01"
start_time = datetime.datetime.strptime(str(start_date), "%Y-%m-%d")
while start_time < datetime.datetime.now():
try:
end_time = start_time + datetime.timedelta(days=365)
print("%s %s %s %s 开始" % (threadName, code, start_time, end_time))
stock_data = ts.bar(code,
conn=conn,
freq='W',
start_date=str(start_time),
end_date=str(end_time),
adj='hfq')
# stock_data = ts.get_h_data(code, start=str(start_time), end=str(end_time), autype='hfq')
# stock_data['sCode'] = code
stock_data['tDateTime'] = stock_data.index
stock_data2 = stock_data.sort_index(ascending=True)
stock_data2.rename(columns={
'code': 'sCode',
'open': 'iOpeningPrice',
'high': 'iMaximumPrice',
'close': 'iClosingPrice',
'low': 'iMinimumPrice',
'vol': 'iVolume',
'amount': 'iAmount'
},
inplace=True)
# 存入数据库
tosql_res = None
if len(stock_data2) > 1:
tosql_res = stock_data2.to_sql('stock_weekly_data',
engine,
if_exists='append',
index=False)
if tosql_res:
common.file_write("tosql_" + threadName, tosql_res)
print("%s %s %s" % (threadName, __name__, str(tosql_res)))
except IOError:
traceback.print_exc()
# print("IOError等待60秒")
# time.sleep(60)
proxy_address = requests.get("http://112.124.4.247:5010/get/").text
print("%s 更换代理 %s" % (threadName, proxy_address))
# 请求接口获取数据
proxy = {
# 'http': '106.46.136.112:808'
# 'https': "https://112.112.236.145:9999",
"http": proxy_address
}
print(proxy)
# 创建ProxyHandler
proxy_support = ProxyHandler(proxy)
# 创建Opener
opener = build_opener(proxy_support)
# 安装OPener
install_opener(opener)
else:
print("\n")
print("%s %s %s %s 成功" % (threadName, code, start_time, end_time))
start_time = end_time + datetime.timedelta(days=1)