def match_announcement(announcement_dir, history_dir, output_dir, origin_file):
"""匹配公告数据与历史股价数据"""
keywords = ["分配"]
stopwords = []
ou.check_ret(
su.match_announcement(ou.check_path(announcement_dir),
ou.check_path(history_dir),
ou.check_path(output_dir), origin_file, keywords,
stopwords, True))
def get_fundamental_data(opath):
print("获取沪深上市公司的基本面情况（会花费较长时间，请耐心等待）")
if not os.path.exists(opath):
print("创建保存数据的文件夹", opath)
os.makedirs(opath, exist_ok=True)
print("#1 获取股票列表")
csvpath = ou.check_path(opath) + "stock_basics.csv"
if os.path.exists(csvpath): # 如果存在，则直接跳过，不重复获取
print("已有该股票列表数据，跳过获取")
else:
stock_basics = ts.get_stock_basics()
print("数据总数:", stock_basics.index.size)
print("全量数据将保存为", csvpath)
stock_basics.sort_index().to_csv(csvpath)
print("数据保存成功")
title = ["业绩报告", "盈利能力", "营运能力", "成长能力", "偿债能力", "现金流量"]
en_name = [
"report_data", "profit_data", "operation_data", "growth_data",
"debtpaying_data", "cashflow_data"
]
count = 0
while count < len(title):
print("#%d 获取 %s 报表" % (count + 2, title[count]))
# 从 1989 到现在
now = datetime.datetime.now()
year = 1989
while year <= now.year:
season = 1
while season <= 4:
print("获取 %d 年第 %d 季度的 %s 报表" % (year, season, title[count]))
try:
csvpath = "%s%d-%d-%s.csv" % (ou.check_path(opath), year,
season, en_name[count])
if os.path.exists(csvpath): # 如果存在，则直接跳过，不重复获取
print("已有该季度数据，跳过获取")
season = season + 1
continue
exec("data = ts.get_%s(%d, %d)" %
(en_name[count], year, season))
exec('data.sort_index().to_csv(csvpath)')
print("\n数据保存成功")
except IOError:
print("获取数据错误，跳过该季度")
season = season + 1
year = year + 1
count = count + 1
return 0
def get_period_history_data(code, interval, path, start, end):
print("获取单个股票一段时间内的历史数据")
print("要获取的股票代码为:", code)
data = ts.get_k_data(code, ktype=interval)
if data is None:
print("没有该股票的数据（可能是网络问题，也可能是本身就没有这个编号）")
return -1
else:
print("共", data.index.size, "行数据")
path = ou.check_path(path) + code + "#" + interval + ".csv"
print("数据获取成功，将被保存在: ", path)
data.to_csv(path)
print("数据保存成功")
return 0
def get_stock_list(path):
print("获取沪深上市公司基本情况")
stock_basics = ts.get_stock_basics()
# stock_basics.index, stock_basics.columns, stock_basics.values
print("数据总数:", stock_basics.index.size)
print("索引列名:", stock_basics.index.name)
print("其他列名:", end=' ')
for item in stock_basics.columns:
print(item, end=' ')
print("\n数据前 3 行")
print(stock_basics.head(3))
if not os.path.exists(path):
print("创建保存数据的文件夹", path)
os.mkdir(path)
csvpath = ou.check_path(path) + "stock_basics.csv"
print("全量数据将保存为", csvpath)
stock_basics.sort_index().to_csv(csvpath)
print("数据保存成功")
return 0
def get_history_data(code, interval, path):
print("获取单个股票的历史数据")
if ou.check_interval(interval) == -1:
print("时间间隔设置错误，请参考 help 文档")
return -1
if not os.path.exists(path):
print("创建保存数据的文件夹", path)
os.makedirs(path, exist_ok=True)
print("要获取的股票代码为:", code)
data = ts.get_k_data(code, ktype=interval)
if data is None:
print("没有该股票的数据（可能是网络问题，也可能是本身就没有这个编号）")
return -1
else:
print("共", data.index.size, "行数据")
path = ou.check_path(path) + code + "#" + interval + ".csv"
print("数据获取成功，将被保存在: ", path)
data.to_csv(path)
print("数据保存成功")
return 0
def get_macro_enco_data(opath):
print("获取沪深上市公司的基本面情况（会花费较长时间，请耐心等待）")
if not os.path.exists(opath):
print("创建保存数据的文件夹", opath)
os.makedirs(opath, exist_ok=True)
now = datetime.datetime.now()
title = [
"存款利率", "贷款利率", "存款准备金率", "货币供应量", "货币供应量(年底余额)", "国内生产总值(年度)",
"国内生产总值(季度)", "三大需求对 GPD 贡献", "三大产业对 GDP 拉动", "三大产业贡献率", "居民消费价格指数",
"工业品出场价格指数"
]
en_name = [
"deposit_rate", "loan_rate", "rrr", "money_supply", "money_supply_bal",
"gdp_year", "gdp_quarter", "gdp_for", "gdp_pull", "gdp_contrib", "cpi",
"ppi"
]
count = 0
while count < len(title):
print("#%d 获取 %s 报表" % (count + 1, title[count]))
try:
csvpath = "%s%d-%2d-%2d-%s.csv" % (ou.check_path(opath), now.year,
now.month, now.day,
en_name[count])
if os.path.exists(csvpath): # 如果存在，则直接跳过，不重复获取
print("已有该数据，跳过获取")
count = count + 1
continue
exec("data = ts.get_%s()" % en_name[count])
exec('data.sort_index().to_csv(csvpath)')
print("数据保存成功")
except IOError:
print("获取数据错误，跳过指标")
count = count + 1
return 0
def daily_crawler(interval, path, root):
now = datetime.datetime.now()
oneday = datetime.timedelta(days=1)
today = now.strftime("%Y-%m-%d")
tomorrow = (now + oneday).strftime("%Y-%m-%d")
folder = root + interval
print("爬取", today, "所有股票的", interval, "分钟数据")
if not os.path.exists(folder):
print("创建保存数据的文件夹", folder)
os.makedirs(folder, exist_ok=True)
f = codecs.open(path, "r", "utf-8")
csv_reader = csv.reader(f)
count = -1
fail_count = 0
for line in csv_reader:
count = count + 1
if count == 0:
# 过滤表头
continue
code = line[0]
name = line[1]
data = ts.get_hist_data(code,
ktype=interval,
start=today,
end=tomorrow)
if data is None:
fail_count = fail_count + 1
continue
else:
dpath = ou.check_path(folder) + code + "-" + today + ".csv"
data.to_csv(dpath)
print("共尝试获取", count, "支股票的历史数据,其中", fail_count, "支股票获取失败")
f.close()
return 0
def macro_enco_data(output_dir):
"""获取宏观经济数据"""
ou.check_ret(su.get_macro_enco_data(ou.check_path(output_dir)))
def fundamental_data(output_dir):
"""获取基本面数据"""
ou.check_ret(su.get_fundamental_data(ou.check_path(output_dir)))
def get_all_history(list_file, interval, output):
"""获取指定时间间隔的全部股价数据"""
ou.check_file(list_file, "请先使用 stock-list 命令来获取")
# 读取默认输出文件夹中的 stock_basics.csv 来获取股票列表
ou.check_ret(
su.get_all_history_data(interval, list_file, ou.check_path(output)))
def get_history_data(code, interval, output):
"""获取指定股票指定时间间隔的股价数据"""
ou.check_ret(su.get_history_data(code, interval, ou.check_path(output)))
def daily(list_file, output):
"""获取 A 股的股票列表及对应详情"""
intervals = ["5", "15", "30", "60"]
for i in intervals:
ou.check_ret(su.daily_crawler(i, list_file, ou.check_path(output)))
def get_stock_list(output):
"""获取 A 股的股票列表及对应详情"""
ou.check_ret(su.get_stock_list(ou.check_path(output)))
def generate_label_data(input_dir, output_dir):
"""生成用于标注的公告数据"""
ou.check_ret(
su.generate_label_data(ou.check_path(input_dir),
ou.check_path(output_dir)))
def keyword_cluster(input_dir, output_dir):
"""根据指定关键词聚类公告"""
ou.check_ret(
su.cluster_announcement(ou.check_path(input_dir),
ou.check_path(output_dir)))
