Update 'Demand_forcasting/forcasting2.py'

Demand_forcasting/forcasting2.py

@@ -18,21 +18,19 @@ list_output=[]
 
 def day(Num,get_url,get_url_token,post_url,post_url_token):
 
+    import requests
 
-    #url='https://qa.bizgaze.app/apis/v4/bizgaze/integrations/demandforecast/getitemdata'
-    url= get_url
-    response = urlopen(url)
-    data_json = json.loads(response.read())
+    url = get_url
+
+    payload = {}
     headers = {
-            'Authorization':get_url_token,
-            #'Authorization':'stat 873f2e6f70b3483e983972f96fbf5ea4',#qa
-            'Content-Type': 'application/json'
+    'Authorization': get_url_token
     }
-    response = requests.request("GET", url, headers=headers, data=data_json)
-    #print("##############################################################")
-    a=response.text
+
+    response = requests.request("GET", url, headers=headers, data=payload)
+    #a=response.text
     # print(response.text)
-    
+
     import pandas as pd
     
     df2 = pd.read_json(response.text, orient ='index')
@@ -49,7 +47,7 @@ def day(Num,get_url,get_url_token,post_url,post_url_token):
     
     #df1=pd.read_csv(r'./upload/' + name)
     #df1=df1[df1['obdate']!='01/01/0001']
-    userdata.columns = ['journaldate','sum','itemname','itemid']
+    userdata.columns = ['journaldate','sum','itemid','itemname']
     
     
     # import pandas as pd
@@ -57,7 +55,8 @@ def day(Num,get_url,get_url_token,post_url,post_url_token):
     # itemid = userdata[['itemname', 'itemid']]
     #userdata['journaldate'] = pd.to_datetime(userdata['journaldate'])
     userdata["journaldate"] = userdata["journaldate"].astype(str)
-    userdata[["year", "month", "day"]] = userdata["journaldate"].str.split("/", expand = True)
+    #userdata[["year", "month", "day"]] = userdata["journaldate"].str.split("/", expand = True)
+    userdata[[ "day","month","year", ]] = userdata["journaldate"].str.split("-", expand = True)
     #userdata['Month-Year']=userdata['year'].astype(str)+'-'+userdata['month'].astype(str)
     item_unique_name = userdata['itemname'].unique()
     
@@ -86,9 +85,10 @@ def day(Num,get_url,get_url_token,post_url,post_url_token):
         ## Use Techniques Differencing
         import pandas as pd
         from pandas import DataFrame
+
         
         # userdata=pd.read_csv(r"C:\Users\Bizgaze\ipynb files\TS forcasting\working\139470.csv")
-        
+        userdata=userdata[['journaldate','sum','itemid']]
         userdata.columns = ['Date', 'sales','sku']
         from statsmodels.tsa.stattools import adfuller
         
@@ -151,8 +151,11 @@ def day(Num,get_url,get_url_token,post_url,post_url_token):
     #####################################################################################################################  
         userdata=df4
         a = userdata.iloc[-1]['Date']
-        userdata['Date'] = pd.to_datetime(userdata['Date'])
+
+        #userdata['Date'] = pd.to_datetime(userdata['Date'])
         userdata["Date"] = userdata["Date"].astype(str)
+        print('after testing')
+        print(userdata)
         userdata[["year", "month", "day"]] = userdata["Date"].str.split("-", expand = True)
         #userdata[["year", "month"]] = userdata["Month"].str.split("-", expand=True)
         #userdata = userdata[["year","month",'sum']]
@@ -231,14 +234,14 @@ def day(Num,get_url,get_url_token,post_url,post_url_token):
         with open('forcast.json', 'r') as json_file:
             json_load = json.load(json_file)
             #url = "https://demo.bizgaze.app/apis/v4/bizgaze/integrations/demandforecast/saveforecast/List"
-            url=post_url
+        url=post_url
     
         payload = json.dumps(json_load)#.replace("]", "").replace("[", "")
-        print(payload)
+        #print(payload)
         headers = {
             #'Authorization': 'stat 263162e61f084d3392f162eb7ec39b2c',#demo
             'Authorization': post_url_token,#test
-            'Content-Type': 'application/json'
+            #'Content-Type': 'application/json'
         }
         response = requests.request("POST", url, headers=headers, data=payload)
         print("##############################################################")
@@ -253,19 +256,31 @@ def day(Num,get_url,get_url_token,post_url,post_url_token):
 
 def month(Num,get_url,get_url_token,post_url,post_url_token):
     #url='https://qa.bizgaze.app/apis/v4/bizgaze/integrations/demandforecast/getitemdata'
-    url= get_url
-    response = urlopen(url)
-    data_json = json.loads(response.read())
+    # url= get_url
+    # response = urlopen(url)
+    # data_json = json.loads(response.read())
+    # headers = {
+    #         'Authorization':get_url_token,
+    #         #'Authorization':'stat 873f2e6f70b3483e983972f96fbf5ea4',#qa
+    #         'Content-Type': 'application/json'
+    # }
+    # response = requests.request("GET", url, headers=headers, data=data_json)
+    # #print("##############################################################")
+    # a=response.text
+    # # print(response.text)
+    import requests
+
+    url = get_url
+
+    payload = {}
     headers = {
-            'Authorization':get_url_token,
-            #'Authorization':'stat 873f2e6f70b3483e983972f96fbf5ea4',#qa
-            'Content-Type': 'application/json'
+    'Authorization': get_url_token
     }
-    response = requests.request("GET", url, headers=headers, data=data_json)
-    #print("##############################################################")
-    a=response.text
-    # print(response.text)
-    
+
+    response = requests.request("GET", url, headers=headers, data=payload)
+
+    #print(response.text)
+
     import pandas as pd
     
     df2 = pd.read_json(response.text, orient ='index')
@@ -290,13 +305,15 @@ def month(Num,get_url,get_url_token,post_url,post_url_token):
     
     #df1=pd.read_csv(r'./upload/' + name)
     #df1=df1[df1['obdate']!='01/01/0001']
-    userdata.columns = ['journaldate','sum','itemname','itemid']
+    userdata.columns = ['journaldate','sum','itemid','itemname']
     # import pandas as pd
     # userdata = pd.read_csv(r'C:\Users\Bizga\Desktop\forcast\5yearsitems.csv')
     # itemid = userdata[['itemname', 'itemid']]
     #userdata['journaldate'] = pd.to_datetime(userdata['journaldate'])
     userdata["journaldate"] = userdata["journaldate"].astype(str)
-    userdata[["year", "month", "day"]] = userdata["journaldate"].str.split("-", expand = True)
+    #userdata[["year", "month", "day"]] = userdata["journaldate"].str.split("-", expand = True)
+    userdata[[ "day","month","year", ]] = userdata["journaldate"].str.split("-", expand = True)
+    #userdata[["year", "day", "month"]] = userdata["journaldate"].str.split("/", expand=True)
     userdata['Month-Year']=userdata['year'].astype(str)+'-'+userdata['month'].astype(str)
     item_unique_name = userdata['itemname'].unique()
     
@@ -471,18 +488,18 @@ def month(Num,get_url,get_url_token,post_url,post_url_token):
         with open('forcast.json', 'r') as json_file:
             json_load = json.load(json_file)
             #url = "https://demo.bizgaze.app/apis/v4/bizgaze/integrations/demandforecast/saveforecast/List"
-            url=post_url
+        url=post_url
     
         payload = json.dumps(json_load)#.replace("]", "").replace("[", "")
-        print(payload)
+        #print(payload)
         headers = {
             #'Authorization': 'stat 263162e61f084d3392f162eb7ec39b2c',#demo
             'Authorization': post_url_token,#test
-            'Content-Type': 'application/json'
+           # 'Content-Type': 'application/json'
         }
         response = requests.request("POST", url, headers=headers, data=payload)
-        print("##############################################################")
-        print(response.text)
+        # print("##############################################################")
+        # print(response.text)
         
         # filePath='path.csv'
 
@@ -527,7 +544,7 @@ def sales_forcast():
     #print(wise)
     #print(Num)
     Dataset = request.get_json()
-    a = url_list
+    a = Dataset
     wise = a['wise']
     # print(x)
     Num = a['future_dates']
@@ -537,9 +554,9 @@ def sales_forcast():
     post_url_token = a['post_url_token']
 
     #print(Dataset)
-    import pandas as pd
-    df=pd.DataFrame(Dataset)
-    print(df)
+    # import pandas as pd
+    # df=pd.DataFrame(Dataset)
+    # print(df)
     # a = Dataset
     #x = a['wise']
     # cmd = "python C:\\Users\\Bizga\\Desktop\\forcast\\XGdaywise.py"