修改了宏观经济接口的API，让宏观经济接口可以正常工作。并且增加了获取进出口总额以及固定资产投资量的接口

test/macro_test.py

@@ -1,7 +1,11 @@
-# -*- coding:utf-8 -*- 
+# -*- coding:utf-8 -*-
 '''
-Created on 2015/3/14
+Created on 2015/01/24
 @author: Jimmy Liu
+
+Modified on 2020/06/28
+@contributor: Cole ZHANG
+@email: longzonejazz@gmail.com
 '''
 import unittest
 import tushare.stock.macro as fd
@@ -29,9 +33,6 @@ def test_get_cpi(self):
     def test_get_ppi(self):
         print(fd.get_ppi())
 
-    def test_get_deposit_rate(self):
-        print(fd.get_deposit_rate())
-
     def test_get_loan_rate(self):
         print(fd.get_loan_rate())
 
@@ -43,8 +44,13 @@ def test_get_money_supply(self):
 
     def test_get_money_supply_bal(self):
         print(fd.get_money_supply_bal())
+
+    def test_get_total_import_export(self):
+        print(fd.get_total_import_export())
+
+    def test_get_industry_fixed_investment(self):
+        print(fd.get_industry_fixed_investment())
 
 
 if __name__ == "__main__":
-    #import sys;sys.argv = ['', 'Test.testName']
-    unittest.main()
+    unittest.main()

tushare/__init__.py

@@ -35,7 +35,9 @@
                                  get_ppi, get_deposit_rate,
                                  get_loan_rate, get_rrr,
                                  get_money_supply, get_money_supply_bal,
-                                 get_gold_and_foreign_reserves)
+                                 get_gold_and_foreign_reserves,
+                                 get_industry_fixed_investment,
+                                 get_total_import_export)
 
 """
 for classifying data

tushare/stock/macro.py

@@ -6,6 +6,10 @@
 @author: Jimmy Liu
 @group : waditu
 @contact: jimmysoa@sina.cn
+
+Modified on 2020/06/28
+@contributor: Cole ZHANG
+@email: longzonejazz@gmail.com
 """
 
 import pandas as pd
@@ -248,21 +252,23 @@ def get_deposit_rate():
         deposit_type :存款种类
         rate:利率（%）
     """
-    rdint = vs.random()
-    request = Request(vs.MACRO_URL%(vs.P_TYPE['http'], vs.DOMAINS['sina'],
-                                    rdint, vs.MACRO_TYPE[2], 2, 600,
-                                    rdint))
-    text = urlopen(request, timeout=10).read()
-    text = text.decode('gbk')
-    regSym = re.compile(r'\,count:(.*?)\}')
-    datastr = regSym.findall(text)
-    datastr = datastr[0]
-    datastr = datastr.split('data:')[1]
-    js = json.loads(datastr)
-    df = pd.DataFrame(js, columns=vs.DEPOSIT_COLS)
-    for i in df.columns:
-        df[i] = df[i].apply(lambda x:np.where(x is None, '--', x))
-    return df
+    return "get_deposit_rate is unavailable"
+
+    # rdint = vs.random()
+    # request = Request(vs.MACRO_URL%(vs.P_TYPE['http'], vs.DOMAINS['sina'],
+    #                                 rdint, vs.MACRO_TYPE[2], 2, 600,
+    #                                 rdint))
+    # text = urlopen(request, timeout=10).read()
+    # text = text.decode('gbk') if ct.PY3 else text
+    # regSym = re.compile(r'\,count:(.*?)\}')
+    # datastr = regSym.findall(text)
+    # datastr = datastr[0]
+    # datastr = datastr.split('data:')[1]
+    # js = json.loads(datastr)
+    # df = pd.DataFrame(js, columns=vs.DEPOSIT_COLS)
+    # for i in df.columns:
+    #     df[i] = df[i].apply(lambda x:np.where(x is None, '--', x))
+    # return df
 
 
 def get_loan_rate():
@@ -275,21 +281,22 @@ def get_loan_rate():
         loan_type :存款种类
         rate:利率（%）
     """
-    rdint = vs.random()
-    request = Request(vs.MACRO_URL%(vs.P_TYPE['http'], vs.DOMAINS['sina'],
-                                    rdint, vs.MACRO_TYPE[2], 3, 800,
-                                    rdint))
-    text = urlopen(request, timeout=10).read()
-    text = text.decode('gbk')
-    regSym = re.compile(r'\,count:(.*?)\}')
-    datastr = regSym.findall(text)
-    datastr = datastr[0]
-    datastr = datastr.split('data:')[1]
-    js = json.loads(datastr)
-    df = pd.DataFrame(js, columns=vs.LOAN_COLS)
-    for i in df.columns:
-        df[i] = df[i].apply(lambda x:np.where(x is None, '--', x))
-    return df
+    return "get_loan_rate is unavailable"
+    # rdint = vs.random()
+    # request = Request(vs.MACRO_URL%(vs.P_TYPE['http'], vs.DOMAINS['sina'],
+    #                                 rdint, vs.MACRO_TYPE[2], 3, 800,
+    #                                 rdint))
+    # text = urlopen(request, timeout=10).read()
+    # text = text.decode('gbk') if ct.PY3 else text
+    # regSym = re.compile(r'\,count:(.*?)\}')
+    # datastr = regSym.findall(text)
+    # datastr = datastr[0]
+    # datastr = datastr.split('data:')[1]
+    # js = json.loads(datastr)
+    # df = pd.DataFrame(js, columns=vs.LOAN_COLS)
+    # for i in df.columns:
+    #     df[i] = df[i].apply(lambda x:np.where(x is None, '--', x))
+    # return df
 
 
 def get_rrr():
@@ -308,7 +315,7 @@ def get_rrr():
                                     rdint, vs.MACRO_TYPE[2], 4, 100,
                                     rdint))
     text = urlopen(request, timeout=10).read()
-    text = text.decode('gbk')
+    text = text.decode('gbk') if ct.PY3 else text
     regSym = re.compile(r'\,count:(.*?)\}')
     datastr = regSym.findall(text)
     datastr = datastr[0]
@@ -349,7 +356,7 @@ def get_money_supply():
                                     rdint, vs.MACRO_TYPE[2], 1, 600,
                                     rdint))
     text = urlopen(request, timeout=10).read()
-    text = text.decode('gbk')
+    text = text.decode('gbk') if ct.PY3 else text
     regSym = re.compile(r'\,count:(.*?)\}')
     datastr = regSym.findall(text)
     datastr = datastr[0]
@@ -382,7 +389,7 @@ def get_money_supply_bal():
                                     rdint, vs.MACRO_TYPE[2], 0, 200,
                                     rdint))
     text = urlopen(request,timeout=10).read()
-    text = text.decode('gbk')
+    text = text.decode('gbk') if ct.PY3 else text
     regSym = re.compile(r'\,count:(.*?)\}')
     datastr = regSym.findall(text)
     datastr = datastr[0]
@@ -409,7 +416,7 @@ def get_gold_and_foreign_reserves():
                                       rdint, vs.MACRO_TYPE[2], 5, 200,
                                       rdint))
     text = urlopen(request,timeout=10).read()
-    text = text.decode('gbk')
+    text = text.decode('gbk') if ct.PY3 else text
     regSym = re.compile(r'\,count:(.*?)\}')
     datastr = regSym.findall(text)
     datastr = datastr[0]
@@ -419,3 +426,62 @@ def get_gold_and_foreign_reserves():
     for i in df.columns:
         df[i] = df[i].apply(lambda x: np.where(x is None, '--', x))
     return df
+
+
+def get_total_import_export():
+    """
+    获取进出口总额
+    Returns
+    -------
+    DataFrame
+        year:统计时间
+        total:进出口总额(美元亿元)
+        export:出口总额(美元亿元)
+        import:进口总额(美元亿元)
+        delta:差额(美元亿元)
+        """
+    rdint = vs.random()
+    request = Request(vs.MACRO_URL % (vs.P_TYPE['http'], vs.DOMAINS['sina'],
+                                      rdint, vs.MACRO_TYPE[3], 0, 400,
+                                      rdint))
+    text = urlopen(request, timeout=10).read()
+    text = text.decode('gbk')
+    regSym = re.compile(r'\,count:(.*?)\}')
+    datastr = regSym.findall(text)
+    datastr = datastr[0]
+    datastr = datastr.split(u'\'美元\':')[1]
+    datastr = datastr.replace("\"", "")
+    js = json.loads(datastr)
+    df = pd.DataFrame(js, columns=vs.TOTAL_IMPORT_EXPORT)
+    for i in df.columns:
+        df[i] = df[i].apply(lambda x: np.where(x is None, '--', x))
+    return df
+
+
+def get_industry_fixed_investment():
+    """
+    获取行业固投完成情况
+    Returns
+    -------
+    DataFrame
+        month:统计时间
+        industry:行业
+        amount:固定资产投资完成额(亿元)
+        increment:固定资产投资完成额同比增长(%)
+        """
+    rdint = vs.random()
+    request = Request(vs.MACRO_URL % (vs.P_TYPE['http'], vs.DOMAINS['sina'],
+                                      rdint, vs.MACRO_TYPE[4], 10, 10000,
+                                      rdint))
+    text = urlopen(request, timeout=10).read()
+    text = text.decode('gbk')
+    regSym = re.compile(r'\,count:(.*?)\}')
+    datastr = regSym.findall(text)
+    datastr = datastr[0]
+    datastr = datastr.split('data:')[1]
+    js = json.loads(datastr)
+    df = pd.DataFrame(js, columns=vs.INDUSTRY_FIXED_INVESTMENT)
+    for i in df.columns:
+        df[i] = df[i].apply(lambda x: np.where(x is None, '--', x))
+
+    return df

tushare/stock/macro_vars.py

@@ -2,8 +2,8 @@
 
 P_TYPE = {'http':'http://','ftp':'ftp://'}
 DOMAINS = {'sina':'sina.com.cn','sinahq':'sinajs.cn','ifeng':'ifeng.com'}
-MACRO_TYPE = ['nation','price','fininfo']
-MACRO_URL = '%smoney.finance.%s/mac/api/jsonp.php/SINAREMOTECALLCALLBACK%s/MacPage_Service.get_pagedata?cate=%s&event=%s&from=0&num=%s&condition=&_=%s'
+MACRO_TYPE = ['nation','price','fininfo','foreign','fixed']
+MACRO_URL = '%squotes.%s/mac/api/jsonp_v3.php/SINAREMOTECALLCALLBACK%s/MacPage_Service.get_pagedata?cate=%s&event=%s&from=0&num=%s&condition=&_=%s'
 GDP_YEAR_COLS = ['year','gdp','pc_gdp','gnp','pi','si','industry','cons_industry','ti','trans_industry','lbdy']
 GDP_QUARTER_COLS = ['quarter','gdp','gdp_yoy','pi','pi_yoy','si','si_yoy','ti','ti_yoy']
 GDP_FOR_COLS = ['year','end_for','for_rate','asset_for','asset_rate','goods_for','goods_rate']
@@ -17,6 +17,8 @@
 MONEY_SUPPLY_COLS = ['month','m2','m2_yoy','m1','m1_yoy','m0','m0_yoy','cd','cd_yoy','qm','qm_yoy','ftd','ftd_yoy','sd','sd_yoy','rests','rests_yoy']
 MONEY_SUPPLY_BLA_COLS = ['year','m2','m1','m0','cd','qm','ftd','sd','rests']
 GOLD_AND_FOREIGN_CURRENCY_RESERVES = ['month','gold','foreign_reserves']
+TOTAL_IMPORT_EXPORT = ['year', 'total', 'export', 'import', 'delta']
+INDUSTRY_FIXED_INVESTMENT = ['month', 'industry', 'amount', 'increment']
 
 def random(n=13):
     from random import randint