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https://github.com/1nchaos/adata.git
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MOD: example fix some pylint warning/error
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rui.luo
parent
78b9de6683
commit
ad0c53649f
@ -16,11 +16,12 @@ from adata.common.utils import requests
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from adata.sentiment.alist import AList
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class Hot(AList):
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class Hot(AList): # 参考 pylint 改完之后实际上这个 Hot 和 AList 没有啥实例化的意义
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"""热门榜单"""
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# 东方财富人气榜
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def pop_rank_100_east(self):
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@staticmethod
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def pop_rank_100_east():
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"""
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东方财富人气榜100
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http://guba.eastmoney.com/rank/
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@ -40,7 +41,6 @@ class Hot(AList):
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df = pd.DataFrame(res["data"])
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df["mark"] = ["0" + "." + item[2:] if "SZ" in item else "1" + "." + item[2:] for item in df["sc"]]
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",".join(df["mark"]) + "?v=08926209912590994"
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params = {
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"ut": "f057cbcbce2a86e2866ab8877db1d059",
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"fltt": "2",
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@ -66,7 +66,8 @@ class Hot(AList):
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rank_df["rank"] = range(1, len(rank_df) + 1)
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return rank_df[["rank", "stock_code", "short_name", "price", "change", "change_pct"]]
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def hot_rank_100_ths(self):
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@staticmethod
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def hot_rank_100_ths():
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"""
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同花顺热股100
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https://dq.10jqka.com.cn/fuyao/hot_list_data/out/hot_list/v1/stock?stock_type=a&type=hour&list_type=normal
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@ -96,7 +97,8 @@ class Hot(AList):
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rank_df = rank_df[["rank", "stock_code", "short_name", "change_pct", "hot_value", "pop_tag", "concept_tag"]]
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return rank_df
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def hot_concept_20_ths(self, plate_type=1):
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@staticmethod
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def hot_concept_20_ths(plate_type=1):
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"""
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同花热门概念板块
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:param plate_type: 1.概念板块，2.行业板块；默认：概念板块
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@ -19,6 +19,7 @@ import math
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import pandas as pd
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import adata # 函数内 import，挪过来
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from adata.common import requests
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from adata.common.base.base_ths import BaseThs
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from adata.common.exception.exception_msg import THS_IP_LIMIT_RES, THS_IP_LIMIT_MSG
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@ -42,9 +43,6 @@ class NorthFlow(BaseThs):
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__NORTH_FLOW_MIN_COLUMNS = ["trade_time", "net_hgt", "net_sgt", "net_tgt"]
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__NORTH_FLOW_CURRENT_COLUMNS = __NORTH_FLOW_MIN_COLUMNS
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def __init__(self) -> None:
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super().__init__()
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def north_flow(self, start_date=None):
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"""
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获取北向资金历史的数据，开始时间到最新的历史数据，
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@ -71,8 +69,7 @@ class NorthFlow(BaseThs):
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if start_date:
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start_date = datetime.datetime.strptime(start_date, "%Y-%m-%d")
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date_min = datetime.datetime.strptime("2017-01-01", "%Y-%m-%d")
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if start_date < date_min:
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start_date = date_min
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start_date = max(start_date, date_min)
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curr_page = 1
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data = []
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while curr_page < 18:
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@ -95,28 +92,29 @@ class NorthFlow(BaseThs):
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if not sgt_data:
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break
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is_end = False
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for i in range(len(sgt_data)):
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# pylint 报的用 enumerate，所以这里保留一下 i 做示范
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for i, (hgt_item, sgt_item) in enumerate(zip(hgt_data, sgt_data)):
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if not start_date and i >= 30:
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is_end = True
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break
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if start_date:
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date_min = datetime.datetime.strptime(hgt_data[i]["TRADE_DATE"], "%Y-%m-%d %H:%M:%S")
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date_min = datetime.datetime.strptime(hgt_item["TRADE_DATE"], "%Y-%m-%d %H:%M:%S")
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if start_date > date_min:
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is_end = True
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break
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data.append(
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{
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"trade_date": hgt_data[i]["TRADE_DATE"],
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"net_hgt": math.ceil(hgt_data[i]["NET_DEAL_AMT"] * 1000000),
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"buy_hgt": math.ceil(hgt_data[i]["BUY_AMT"] * 1000000),
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"sell_hgt": math.ceil(hgt_data[i]["SELL_AMT"] * 1000000),
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"net_sgt": math.ceil(sgt_data[i]["NET_DEAL_AMT"] * 1000000),
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"buy_sgt": math.ceil(sgt_data[i]["BUY_AMT"] * 1000000),
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"sell_sgt": math.ceil(sgt_data[i]["SELL_AMT"] * 1000000),
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"net_tgt": math.ceil((hgt_data[i]["NET_DEAL_AMT"] + sgt_data[i]["NET_DEAL_AMT"]) * 1000000),
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"buy_tgt": math.ceil((hgt_data[i]["BUY_AMT"] + sgt_data[i]["BUY_AMT"]) * 1000000),
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"sell_tgt": math.ceil((hgt_data[i]["SELL_AMT"] + sgt_data[i]["SELL_AMT"]) * 1000000),
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"trade_date": hgt_item["TRADE_DATE"],
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"net_hgt": math.ceil(hgt_item["NET_DEAL_AMT"] * 1000000),
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"buy_hgt": math.ceil(hgt_item["BUY_AMT"] * 1000000),
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"sell_hgt": math.ceil(hgt_item["SELL_AMT"] * 1000000),
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"net_sgt": math.ceil(sgt_item["NET_DEAL_AMT"] * 1000000),
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"buy_sgt": math.ceil(sgt_item["BUY_AMT"] * 1000000),
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"sell_sgt": math.ceil(sgt_item["SELL_AMT"] * 1000000),
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"net_tgt": math.ceil((hgt_item["NET_DEAL_AMT"] + sgt_item["NET_DEAL_AMT"]) * 1000000),
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"buy_tgt": math.ceil((hgt_item["BUY_AMT"] + sgt_item["BUY_AMT"]) * 1000000),
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"sell_tgt": math.ceil((hgt_item["SELL_AMT"] + sgt_item["SELL_AMT"]) * 1000000),
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}
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)
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@ -149,7 +147,7 @@ class NorthFlow(BaseThs):
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def __north_flow_min_ths(self):
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# 1.接口 url
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api_url = f" https://data.hexin.cn/market/hsgtApi/method/dayChart/"
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api_url = "https://data.hexin.cn/market/hsgtApi/method/dayChart/"
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headers = copy.deepcopy(ths_headers.json_headers)
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headers["Host"] = "data.hexin.cn"
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res = requests.request("get", api_url, headers=headers, proxies={})
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@ -164,17 +162,16 @@ class NorthFlow(BaseThs):
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hgt_list = result_json["hgt"]
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sgt_list = result_json["sgt"]
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data = []
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for i in range(len(time_list)):
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for time_item, hgt_item, sgt_item in zip(time_list, hgt_list, sgt_list):
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row = [
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time_list[i],
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math.ceil(hgt_list[i] * 100000000),
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math.ceil(sgt_list[i] * 100000000),
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math.ceil((hgt_list[i] + sgt_list[i]) * 100000000),
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time_item,
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math.ceil(hgt_item * 100000000),
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math.ceil(sgt_item * 100000000),
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math.ceil((hgt_item + sgt_item) * 100000000),
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]
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data.append(row)
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# 3. 封装数据
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result_df = pd.DataFrame(data=data, columns=self.__NORTH_FLOW_MIN_COLUMNS)
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import adata
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trade_year = adata.stock.info.trade_calendar()
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# 获取当前日期
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@ -216,7 +213,7 @@ class NorthFlow(BaseThs):
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math.ceil(float(row[3]) * 10000),
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]
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)
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except Exception as e:
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except Exception: # pylint: disable=broad-except
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print("north_flow_min_east is ERROR!!!")
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return pd.DataFrame(data=data, columns=self.__NORTH_FLOW_MIN_COLUMNS)
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result_df = pd.DataFrame(data=data, columns=self.__NORTH_FLOW_MIN_COLUMNS)
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@ -21,12 +21,9 @@ from adata.common import requests
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from adata.common.headers import east_headers
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class SecuritiesMargin(object):
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class SecuritiesMargin:
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__SECURITIES_MARGIN_COLUMN = ["trade_date", "rzye", "rqye", "rzrqye", "rzrqyecz"]
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def __init__(self) -> None:
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super().__init__()
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def securities_margin(self, start_date=None):
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"""
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查询开始时间到现在的融资融券余额数据，默认：查询最近一年的数据
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@ -20,12 +20,9 @@ from adata.common.headers import ths_headers
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from adata.common.utils import cookie
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class StockLifting(object):
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class StockLifting:
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__STOCK_LIFTING_COLUMN = ["stock_code", "short_name", "lift_date", "volume", "amount", "ratio", "price"]
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def __init__(self) -> None:
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super().__init__()
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def stock_lifting_last_month(self):
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"""
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查询最近一个月的股票解禁列表
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@ -45,7 +42,7 @@ class StockLifting(object):
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total_pages = 1
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curr_page = 1
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while curr_page <= total_pages:
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api_url = f"http://data.10jqka.com.cn/market/xsjj/field/enddate/order/desc/ajax/1/free/1/"
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api_url = "http://data.10jqka.com.cn/market/xsjj/field/enddate/order/desc/ajax/1/free/1/"
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if curr_page > 1:
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api_url = api_url + f"page/{curr_page}/free/1/"
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headers = copy.deepcopy(ths_headers.text_headers)
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3
pylintrc
3
pylintrc
@ -96,6 +96,9 @@ disable=raw-checker-failed,
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missing-function-docstring,
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missing-module-docstring,
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invalid-name,
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unsubscriptable-object, # dataframe 相关操作
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unsupported-assignment-operation, # dataframe 相关操作
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# Enable the message, report, category or checker with the given id(s). You can
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# either give multiple identifier separated by comma (,) or put this option
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