def retrieve_company_info() -> DataFrame:
df = pro_api().stock_basic()
industry_df = unique_of(
transform(df, [Pipeline('industry', Industry.industry.key)]),
Industry.industry.key)
insert_dataframe(industry_df, Industry)
exchange_df = unique_of(
transform(df, [
Pipeline('ts_code', ExchangeMarkets.exchange.key,
lambda x: x.split('.')[-1]),
]), ExchangeMarkets.exchange.key)
insert_dataframe(exchange_df, ExchangeMarkets)
areas_df = unique_of(transform(df, [Pipeline('area', Areas.area.key)]),
Areas.area.key)
insert_dataframe(areas_df, Areas)
stocks_df = transform(df, [
Pipeline('symbol', Stocks.code.key),
Pipeline('name', Stocks.full_name.key),
Pipeline('ts_code', Stocks.exchange.key, lambda x: x.split('.')[-1]),
Pipeline('list_date', Stocks.list_date.key, ts_date_to_sql)
],
preserve_list=['industry', 'area'])
return stocks_df
def ts_daily_to_daily_price_summaries_table(df, trade_date=None):
if trade_date:
trade_date_pipeline = Pipeline([], DailyPriceSummaries.date.key,
lambda: trade_date)
else:
trade_date_pipeline = Pipeline("trade_date",
DailyPriceSummaries.date.key,
ts_date_to_sql)
return transform(df, [
Pipeline('ts_code', DailyPriceSummaries.exchange.key,
lambda x: x.split('.')[-1]),
Pipeline('ts_code', DailyPriceSummaries.code.key,
lambda x: x.split('.')[0]),
Pipeline('pre_close', DailyPriceSummaries.last_day_close.key),
Pipeline('vol', DailyPriceSummaries.volume.key),
Pipeline('amount', DailyPriceSummaries.turnover.key),
trade_date_pipeline
], ['open', 'close', 'high', 'low'])
def retrieve_interval_price_summaries(market: str, code: str, interval_minute: int, data_num: int = 1023):
params = {
"symbol": market + str(code),
"scale": interval_minute,
"datalen": data_num,
"ma": "no",
}
url = "http://money.finance.sina.com.cn/quotes_service/api/json_v2.php/CN_MarketData.getKLineData"
with urlopen("%s?%s" % (url, urlencode(params))) as response:
page = response.read()
result = json.loads(page)
df = DataFrame(result)
price_df = transform(df, [
Pipeline([], IntervalPriceSummary.code.key, lambda: code),
Pipeline([], IntervalPriceSummary.exchange.key, lambda: market),
Pipeline("day", IntervalPriceSummary.time.key,
lambda day_str: day_str.replace(" ", "T")),
Pipeline([], IntervalPriceSummary.interval_len.key, lambda: time(minute=interval_minute)),
], ["open", "close", "high", "low", "volume"])
insert_dataframe(price_df, IntervalPriceSummary)
def ts_daily_to_stocks_transform(df):
return transform(df, [
Pipeline('ts_code', Stocks.exchange.key, lambda x: x.split('.')[-1]),
Pipeline('ts_code', Stocks.code.key, lambda x: x.split('.')[0]),
])
def ts_daily_to_exchange_table(df):
return unique_of(
transform(df, [
Pipeline('ts_code', ExchangeMarkets.exchange.key,
lambda x: x.split('.')[-1]),
]), Stocks.exchange.key)