From 63177fcdaa2141f01a7f551fa83793fa1ea73405 Mon Sep 17 00:00:00 2001 From: SadhulaSaiKumar Date: Fri, 12 Jan 2024 11:18:55 +0000 Subject: [PATCH] Update 'Demand_forcasting/forcasting2.py' --- Demand_forcasting/forcasting2.py | 97 +++++++++++++++++++------------- 1 file changed, 57 insertions(+), 40 deletions(-) diff --git a/Demand_forcasting/forcasting2.py b/Demand_forcasting/forcasting2.py index 3570758..1dbc58e 100644 --- a/Demand_forcasting/forcasting2.py +++ b/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"