生成pdf

app/templates/v2/monthReportV2.html

@@ -903,7 +903,7 @@
     <div class="box0">
       <div class="cover_head dtable">
         <div class="dcell">
-          <img src="./img/logo.png" alt="" class="cover_logo">
+          <img src={{logo}} alt="" class="cover_logo">
         </div>
         <div class="dcell">
           <div class="cover_line"></div>
@@ -920,13 +920,13 @@
           敬呈
         </span>
         <span class="cover_name">
-          王晶
+          {{customer_name}}
         </span>
         <span class="cover_sir">
           先生
         </span>
       </div>
-      <img src="./img/cover-back.png" alt="" class="cover_back">
+      <img src={{cover_back}} alt="" class="cover_back">
       <div class="cover_date">
         <div class="cover_time">
           2020.10
@@ -985,7 +985,7 @@
         </div>
         <div class="page_head dcell">
           <div class="dcell">
-            <img src="./img/logo.png" alt="" class="page_logo">
+            <img src={{logo}} alt="" class="page_logo">
           </div>
           <div class="dcell">
             <div class="page_line"></div>
@@ -1167,9 +1167,6 @@
               <td>
                 {{value[12]["profit"]}}
               </td>
-<!--              <td>-->
-<!--                {{value[13]["profit"]}}-->
-<!--              </td>-->
             </tr>
             <tr>
               <td>
@@ -1211,11 +1208,6 @@
               <td>
                 {{value[12]["net_amount"]}}
               </td>
-<!--              <td>-->
-<!--                {{value[13]["net_amount"]}}-->
-<!--              </td>      <td>-->
-<!--                {{value[13]["net_amount"]}}-->
-<!--              </td>-->
             </tr>
             {%endfor%}
           </table>
@@ -1234,7 +1226,7 @@
         </div>
         <div class="page_head dcell">
           <div class="dcell">
-            <img src="./img/logo.png" alt="" class="page_logo">
+            <img src={{logo}} alt="" class="page_logo">
           </div>
           <div class="dcell">
             <div class="page_line"></div>
@@ -1460,7 +1452,7 @@
         </div>
         <div class="page_head dcell">
           <div class="dcell">
-            <img src="./img/logo.png" alt="" class="page_logo">
+            <img src={{logo}} alt="" class="page_logo">
           </div>
           <div class="dcell">
             <div class="page_line"></div>
@@ -1612,7 +1604,7 @@
         </div>
         <div class="page_head dcell">
           <div class="dcell">
-            <img src="./img/logo.png" alt="" class="page_logo">
+            <img src={{logo}} alt="" class="page_logo">
           </div>
           <div class="dcell">
             <div class="page_line"></div>
@@ -1697,7 +1689,7 @@
         </div>
         <div class="page_head dcell">
           <div class="dcell">
-            <img src="./img/logo.png" alt="" class="page_logo">
+            <img src={{logo}} alt="" class="page_logo">
           </div>
           <div class="dcell">
             <div class="page_line"></div>
@@ -1921,7 +1913,7 @@
         </div>
         <div class="page_head dcell">
           <div class="dcell">
-            <img src="./img/logo.png" alt="" class="page_logo">
+            <img src={{logo}} alt="" class="page_logo">
           </div>
           <div class="dcell">
             <div class="page_line"></div>
@@ -2004,7 +1996,7 @@
         <div class="financial_show dtable">
           <div class="financial_left dcell">
             <div class="financial_scene">
-              <img src="./img/scene.png" alt="" class="financial_scene_img">
+              <img src={{scene}}" alt="" class="financial_scene_img">
               <div class="financial_scene_text">
                 我们挣的是⻆度和变化的钱⽽不是纠正市场错 误的钱，市场永远是正确的，关键是在其正确 被反复证明后的逆向⽽⾏，⼀定是避开它的正 确被展开的过程 。
               </div>
@@ -2015,7 +2007,7 @@
           </div>
           <div class="financial_show_right dcell">
             <div class="financial_team">
-              <img src="./img/team.png" alt="" class="financial_team_img">
+              <img src={{team}} alt="" class="financial_team_img">
             </div>
           </div>
         </div>

app/utils/fund_rank.py

@@ -8,7 +8,7 @@
 import logging
 logging.basicConfig(level=logging.INFO)
 
-from app.api.engine import tamp_fund_engine, TAMP_SQL, tamp_product_engine
+from app.api.engine import tamp_fund_engine, TAMP_SQL
 from app.utils.week_evaluation import *
 
 
@@ -32,66 +32,35 @@ def get_nav(fund, start_date, rollback=False, invest_type='public'):
     Returns:df[DataFrame]: 索引为净值公布日， 列为复权净值的净值表; 查询失败则返回None
 
     """
-    with TAMP_SQL(tamp_fund_engine) as tamp_fund:
-        tamp_fund_session = tamp_fund.session
+    with TAMP_SQL(tamp_fund_engine) as tamp_product:
+        tamp_product_session = tamp_product.session
         if invest_type == 'public':
             sql = "SELECT ts_code, end_date, adj_nav FROM public_fund_nav " \
                   "WHERE ts_code='{}'".format(fund)
-            cur = tamp_fund_session.execute(sql)
+            cur = tamp_product_session.execute(sql)
             data = cur.fetchall()
-            df1 = pd.DataFrame(list(data), columns=['fund_id', 'end_date', 'adj_nav']).dropna(how='any')
-            df1.rename({'ts_code': 'fund_id'}, axis=1, inplace=True)
+            df = pd.DataFrame(list(data), columns=['fund_id', 'end_date', 'adj_nav']).dropna(how='any')
+            df.rename({'ts_code': 'fund_id'}, axis=1, inplace=True)
         else:
-            sql = "SELECT fund_id, price_date, cumulative_nav FROM fund_nav " \
-                  "WHERE fund_id='{}'".format(fund)
-            # df = pd.read_sql(sql, con).dropna(how='any')
-            cur = tamp_fund_session.execute(sql)
-            data = cur.fetchall()
-            df1 = pd.DataFrame(data, columns=['fund_id', 'price_date', 'cumulative_nav']).dropna(how='any')
-            df1.rename({'price_date': 'end_date', 'cumulative_nav': 'adj_nav'}, axis=1, inplace=True)
-
-        # if df1['adj_nav'].count() == 0:
-        #     logging.log(logging.ERROR, "CAN NOT FIND {}".format(fund))
-        #     return None
-
-        df1['end_date'] = pd.to_datetime(df1['end_date'])
-
-        if rollback and df1['end_date'].min() < start_date < df1['end_date'].max():
-            while start_date not in list(df1['end_date']):
-                start_date -= datetime.timedelta(days=1)
-
-        df1 = df1[df1['end_date'] >= start_date]
-        df1.drop_duplicates(subset='end_date', inplace=True, keep='first')
-        # df1.set_index('end_date', inplace=True)
-        # df1.sort_index(inplace=True, ascending=True)
-
-    with TAMP_SQL(tamp_product_engine) as tamp_product:
-        tamp_product_session = tamp_product.session
-        if invest_type == "private":
             sql = "SELECT fund_id, price_date, cumulative_nav FROM fund_nav " \
                   "WHERE fund_id='{}'".format(fund)
             # df = pd.read_sql(sql, con).dropna(how='any')
             cur = tamp_product_session.execute(sql)
             data = cur.fetchall()
-            df2 = pd.DataFrame(data, columns=['fund_id', 'price_date', 'cumulative_nav']).dropna(how='any')
-            df2.rename({'price_date': 'end_date', 'cumulative_nav': 'adj_nav'}, axis=1, inplace=True)
+            df = pd.DataFrame(data, columns=['fund_id', 'price_date', 'cumulative_nav']).dropna(how='any')
+            df.rename({'price_date': 'end_date', 'cumulative_nav': 'adj_nav'}, axis=1, inplace=True)
 
-        # if df2['adj_nav'].count() == 0:
-        #     logging.log(logging.ERROR, "CAN NOT FIND {}".format(fund))
-        #     return None
+        if df['adj_nav'].count() == 0:
+            logging.log(logging.ERROR, "CAN NOT FIND {}".format(fund))
+            return None
 
-        df2['end_date'] = pd.to_datetime(df2['end_date'])
+        df['end_date'] = pd.to_datetime(df['end_date'])
 
-        if rollback and df2['end_date'].min() < start_date < df2['end_date'].max():
-            while start_date not in list(df2['end_date']):
+        if rollback and df['end_date'].min() < start_date < df['end_date'].max():
+            while start_date not in list(df['end_date']):
                 start_date -= datetime.timedelta(days=1)
 
-        df2 = df2[df2['end_date'] >= start_date]
-        df2.drop_duplicates(subset='end_date', inplace=True, keep='first')
-        # df2.set_index('end_date', inplace=True)
-        # df2.sort_index(inplace=True, ascending=True)
-
-    df = pd.concat([df1, df2])
+        df = df[df['end_date'] >= start_date]
         df.drop_duplicates(subset='end_date', inplace=True, keep='first')
         df.set_index('end_date', inplace=True)
         df.sort_index(inplace=True, ascending=True)
@@ -132,10 +101,10 @@ def get_trade_cal():
     Returns:df[DataFrame]: 索引为交易日， 列为交易日的上交所交易日历表
 
     """
-    with TAMP_SQL(tamp_fund_engine) as tamp_fund:
-        tamp_fund_session = tamp_fund.session
+    with TAMP_SQL(tamp_fund_engine) as tamp_product:
+        tamp_product_session = tamp_product.session
         sql = 'SELECT cal_date FROM stock_trade_cal WHERE is_open=1'
-        cur = tamp_fund_session.execute(sql)
+        cur = tamp_product_session.execute(sql)
         data = cur.fetchall()
         df = pd.DataFrame(list(data), columns=['cal_date']).dropna(how='all')
         # df = pd.read_sql(sql, con)
@@ -153,30 +122,20 @@ def get_manager(invest_type):
     Returns:
 
     """
-    with TAMP_SQL(tamp_fund_engine) as tamp_fund:
-        tamp_fund_session = tamp_fund.session
+    with TAMP_SQL(tamp_fund_engine) as tamp_product:
+        tamp_product_session = tamp_product.session
         if invest_type == 'public':
             sql = 'SELECT ts_code, name FROM public_fund_manager WHERE end_date IS NULL'
             # df = pd.read_sql(sql, con)
-            cur = tamp_fund_session.execute(sql)
+            cur = tamp_product_session.execute(sql)
             data = cur.fetchall()
-            df1 = pd.DataFrame(list(data), columns=['ts_code', 'name'])
+            df = pd.DataFrame(list(data), columns=['ts_code', 'name'])
         else:
-            sql = 'SELECT fund_id, fund_manager_id, management_start_date FROM fund_manager_mapping'
+            sql = 'SELECT fund_id, fund_manager_id FROM fund_manager_mapping'
             # df = pd.read_sql(sql, con)
-            cur = tamp_fund_session.execute(sql)
-            data = cur.fetchall()
-            df1 = pd.DataFrame(list(data), columns=['fund_id', 'fund_manager_id', 'management_start_date'])
-
-    with TAMP_SQL(tamp_product_engine) as tamp_product:
-        tamp_product_session = tamp_product.session
-        if invest_type == 'private':
-            sql = 'SELECT fund_id, fund_manager_id, management_start_date FROM fund_manager_mapping'
             cur = tamp_product_session.execute(sql)
             data = cur.fetchall()
-            df2 = pd.DataFrame(list(data), columns=['fund_id', 'fund_manager_id', 'management_start_date'])
-
-    df = pd.concat([df1, df2]).drop_duplicates()
+            df = pd.DataFrame(list(data), columns=['fund_id', 'fund_manager_id'])
         return df
 
 
@@ -190,47 +149,31 @@ def get_fund_info(end_date, invest_type):
     Returns:
         [type]: [description]
     """
-    with TAMP_SQL(tamp_fund_engine) as tamp_fund:
-        tamp_fund_session = tamp_fund.session
+    with TAMP_SQL(tamp_fund_engine) as tamp_product:
+        tamp_product_session = tamp_product.session
         if invest_type == 'public':
             sql = "SELECT ts_code, fund_type, management FROM public_fund_basic " \
                   "WHERE delist_date IS NULL AND (due_date IS NULL OR due_date>'{}')".format(end_date.strftime('%Y%m%d'))
             # df = pd.read_sql(sql, con).dropna(how='all')
-            cur = tamp_fund_session.execute(sql)
+            cur = tamp_product_session.execute(sql)
             data = cur.fetchall()
 
-            df1 = pd.DataFrame(list(data), columns=['fund_id', 'fund_type', 'management'])
-            # manager_info = get_manager(invest_type)
+            df = pd.DataFrame(list(data), columns=['ts_code', 'fund_type', 'management'])
+            manager_info = get_manager(invest_type)
 
-            # df1.rename({'ts_code': 'fund_id'}, axis=1, inplace=True)
-            # df = pd.merge(df, manager_info, how="left", on='fund_id')
+            df.rename({'ts_code': 'fund_id'}, axis=1, inplace=True)
+            df = pd.merge(df, manager_info, how="left", on='fund_id')
         else:
-            sql = "SELECT id, substrategy FROM fund_info WHERE delete_tag=0 " \
-                  "AND substrategy!=-1"
-            cur = tamp_fund_session.execute(sql)
-            data = cur.fetchall()
-            df1 = pd.DataFrame(list(data), columns=['fund_id', 'substrategy'])
-            # df = pd.read_sql(sql, con).dropna(how='all')
 
-            # df1.rename({'id': 'fund_id'}, axis=1, inplace=True)
-            # manager_info = get_manager(invest_type)
-            # df = pd.merge(df, manager_info, how="inner", on='fund_id')
-
-    with TAMP_SQL(tamp_product_engine) as tamp_product:
-        tamp_product_session = tamp_product.session
-        if invest_type == "private":
             sql = "SELECT id, substrategy FROM fund_info WHERE delete_tag=0 " \
                   "AND substrategy!=-1"
             cur = tamp_product_session.execute(sql)
             data = cur.fetchall()
-            df2 = pd.DataFrame(list(data), columns=['fund_id', 'substrategy'])
+            df = pd.DataFrame(list(data), columns=['id', 'substrategy'])
             # df = pd.read_sql(sql, con).dropna(how='all')
 
-            # df2.rename({'id': 'fund_id'}, axis=1, inplace=True)
-            # manager_info = get_manager(invest_type)
-
+            df.rename({'id': 'fund_id'}, axis=1, inplace=True)
             manager_info = get_manager(invest_type)
-    df = pd.concat([df1, df2]).drop_duplicates()
             df = pd.merge(df, manager_info, how="inner", on='fund_id')
         return df
 
@@ -333,12 +276,11 @@ def fund_rank(start_date, end_date, invest_type='private'):
                     continue
                 n = get_frequency(df)
             except Exception as e:
-                logging.log(logging.ERROR, repr(e))
+                # logging.log(logging.ERROR, repr(e))
                 logging.log(logging.INFO, 'Skipped {}'.format(fund))
-                skipped_funds.append(fund)
                 continue
 
-            df = resample(df, trading_cal, n, simple_flag=False)
+            df = resample(df, trading_cal, n)
 
             try:
                 _ = get_frequency(df)
@@ -360,8 +302,7 @@ def fund_rank(start_date, end_date, invest_type='private'):
             down_risk = downside_risk(sim_return, bank_rate=0.015, n=n)
             sor_ratio = sortino_ratio(ex_return, down_risk, n)
 
-            manager = fund_info[fund_info['fund_id'] == fund].groupby("management_start_date").last()
-            manager = manager['fund_manager_id'].values
+            manager = fund_info[fund_info['fund_id'] == fund]['fund_manager_id'].values
             # management = fund_info[fund_info['fund_id'] == fund]['management'].values
 
             row = pd.Series([fund, rng_return, ann_return, drawdown, shp_ratio,
@@ -383,8 +324,8 @@ def fund_rank(start_date, end_date, invest_type='private'):
 if __name__ == '__main__':
     end_date = datetime.datetime.now() - datetime.timedelta(days=1)
     start_date = cal_date(end_date, 'Y', 1)
-    fund_rank = fund_rank(start_date, end_date, invest_type="private")
-    fund_rank.to_csv("fund_rank.csv", encoding='gbk')
-    df = pd.read_csv('fund_rank.csv')
+    fund_rank = fund_rank(start_date, end_date, False)
+    # fund_rank.to_csv("fund_rank.csv", encoding='gbk')
+    # df = pd.read_csv('fund_rank.csv')
     # df.to_sql("fund_rank", con, if_exists='replace')
     # con.close()

app/utils/html_to_pdf.py

@@ -17,7 +17,7 @@ def html_to_pdf(source_path, target_path):
         'encoding': "utf-8",
         # 'page-size': 'A5',
         # 'page-width': '300mm',
-        # 'page-height': 'auto',
+        'page-height': '2.3mm',
         'margin-top': '0mm',
         'margin-right': '0mm',
         'margin-bottom': '0mm',

app/utils/jinjia2html.py

@@ -3,6 +3,7 @@ import uuid
 
 from jinja2 import PackageLoader, Environment
 
+from app.api.engine import work_dir, pdf_folder, template_folder
 from app.service.portfolio_diagnose import portfolio_diagnose
 from app.service.result_service_v2 import UserCustomerResultAdaptor
 import numpy as np
@@ -80,8 +81,6 @@ class DataIntegrate:
         self.single_fund_data_list = []
         portfolio_evaluation = portfolio_diagnose.old_portfolio_evaluation()
         radar_chart_data = portfolio_diagnose.single_fund_radar()
-        print('***************************')
-        print(portfolio_evaluation)
         for i in range(len(portfolio_evaluation)):
             if portfolio_evaluation[i]['status'] == '保留':
                 portfolio_evaluation[i]['status'] = '<div class="self_type fl">保留</div>'
@@ -167,8 +166,15 @@ class DataIntegrate:
 
     def render_data(self):
         # 全部数据
-        data = {'customer_name': self.customer_name, 'customer_gender': '女',
-                'year_month': '2020年10月', 'ifa_company': '飞度工作室',
+        data = {
+                'cover_back': template_folder + '/v2/img/cover-back.png',
+                'logo': template_folder + '/v2/img/logo.png',
+                'scene': template_folder + '/v2/img/scene/png',
+                'team': template_folder + '/v2/img/team.png',
+                'customer_name': self.customer_name,
+                'customer_gender': '女',
+                'year_month': '2020年10月',
+                'ifa_company': '飞度工作室',
                 'title': '10月综述', 'brand_name': '飞度工作室',
                 'customer_old': 42, 'customer_level': '平衡型',
                 # 'new_evaluation': self.new_evaluation,
@@ -219,10 +225,10 @@ class DataIntegrate:
         # with open(save_file, 'w', encoding="utf-8") as f:
         #     f.write(monthReport_html)
 
-        save_file = "app/html/v2/monthReportV2.html"
-        with open(save_file, 'w', encoding="utf-8") as f:
-            f.write(monthReport_html)
-        # html_to_pdf(monthReport_html, '/Users/pengxiong/Desktop/fund_report/app/pdf/%s.pdf' % str(uuid.uuid4()))
+        # save_file = "app/html/v2/monthReportV2.html"
+        # with open(save_file, 'w', encoding="utf-8") as f:
+        #     f.write(monthReport_html)
+        html_to_pdf(monthReport_html, pdf_folder + str(uuid.uuid4()))