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Update 'Demand_forcasting/forcasting2.py'

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SadhulaSaiKumar
2024-01-12 11:18:55 +00:00
Ursprung b4ae8b3a7f
Commit 63177fcdaa
1 geänderte Dateien mit 57 neuen und 40 gelöschten Zeilen
Patch-Datei herunterladen Vergleichs-Datei herunterladen Alle Dateien ausklappen Alle Dateien einklappen
Demand_forcasting/forcasting2.py
+50 -33
Datei anzeigen
@@ -18,19 +18,17 @@ list_output=[]
def day(Num,get_url,get_url_token,post_url,post_url_token): 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 url = get_url
response = urlopen(url)
data_json = json.loads(response.read()) payload = {}
headers = { headers = {
'Authorization':get_url_token, 'Authorization': get_url_token
#'Authorization':'stat 873f2e6f70b3483e983972f96fbf5ea4',#qa
'Content-Type': 'application/json'
} }
response = requests.request("GET", url, headers=headers, data=data_json)
#print("##############################################################") response = requests.request("GET", url, headers=headers, data=payload)
a=response.text #a=response.text
# print(response.text) # print(response.text)
import pandas as pd import pandas as pd
@@ -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=pd.read_csv(r'./upload/' + name)
#df1=df1[df1['obdate']!='01/01/0001'] #df1=df1[df1['obdate']!='01/01/0001']
userdata.columns = ['journaldate','sum','itemname','itemid'] userdata.columns = ['journaldate','sum','itemid','itemname']
# import pandas as pd # 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']] # itemid = userdata[['itemname', 'itemid']]
#userdata['journaldate'] = pd.to_datetime(userdata['journaldate']) #userdata['journaldate'] = pd.to_datetime(userdata['journaldate'])
userdata["journaldate"] = userdata["journaldate"].astype(str) 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) #userdata['Month-Year']=userdata['year'].astype(str)+'-'+userdata['month'].astype(str)
item_unique_name = userdata['itemname'].unique() item_unique_name = userdata['itemname'].unique()
@@ -87,8 +86,9 @@ def day(Num,get_url,get_url_token,post_url,post_url_token):
import pandas as pd import pandas as pd
from pandas import DataFrame from pandas import DataFrame
# userdata=pd.read_csv(r"C:\Users\Bizgaze\ipynb files\TS forcasting\working\139470.csv")
# 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'] userdata.columns = ['Date', 'sales','sku']
from statsmodels.tsa.stattools import adfuller 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 userdata=df4
a = userdata.iloc[-1]['Date'] 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) userdata["Date"] = userdata["Date"].astype(str)
print('after testing')
print(userdata)
userdata[["year", "month", "day"]] = userdata["Date"].str.split("-", expand = True) userdata[["year", "month", "day"]] = userdata["Date"].str.split("-", expand = True)
#userdata[["year", "month"]] = userdata["Month"].str.split("-", expand=True) #userdata[["year", "month"]] = userdata["Month"].str.split("-", expand=True)
#userdata = userdata[["year","month",'sum']] #userdata = userdata[["year","month",'sum']]
@@ -234,11 +237,11 @@ def day(Num,get_url,get_url_token,post_url,post_url_token):
url=post_url url=post_url
payload = json.dumps(json_load)#.replace("]", "").replace("[", "") payload = json.dumps(json_load)#.replace("]", "").replace("[", "")
print(payload) #print(payload)
headers = { headers = {
#'Authorization': 'stat 263162e61f084d3392f162eb7ec39b2c',#demo #'Authorization': 'stat 263162e61f084d3392f162eb7ec39b2c',#demo
'Authorization': post_url_token,#test 'Authorization': post_url_token,#test
'Content-Type': 'application/json' #'Content-Type': 'application/json'
} }
response = requests.request("POST", url, headers=headers, data=payload) response = requests.request("POST", url, headers=headers, data=payload)
print("##############################################################") print("##############################################################")
@@ -253,17 +256,29 @@ 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): 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='https://qa.bizgaze.app/apis/v4/bizgaze/integrations/demandforecast/getitemdata'
# 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 url = get_url
response = urlopen(url)
data_json = json.loads(response.read()) payload = {}
headers = { headers = {
'Authorization':get_url_token, 'Authorization': get_url_token
#'Authorization':'stat 873f2e6f70b3483e983972f96fbf5ea4',#qa
'Content-Type': 'application/json'
} }
response = requests.request("GET", url, headers=headers, data=data_json)
#print("##############################################################") response = requests.request("GET", url, headers=headers, data=payload)
a=response.text
#print(response.text) #print(response.text)
import pandas as pd import pandas as pd
@@ -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=pd.read_csv(r'./upload/' + name)
#df1=df1[df1['obdate']!='01/01/0001'] #df1=df1[df1['obdate']!='01/01/0001']
userdata.columns = ['journaldate','sum','itemname','itemid'] userdata.columns = ['journaldate','sum','itemid','itemname']
# import pandas as pd # import pandas as pd
# userdata = pd.read_csv(r'C:\Users\Bizga\Desktop\forcast\5yearsitems.csv') # userdata = pd.read_csv(r'C:\Users\Bizga\Desktop\forcast\5yearsitems.csv')
# itemid = userdata[['itemname', 'itemid']] # itemid = userdata[['itemname', 'itemid']]
#userdata['journaldate'] = pd.to_datetime(userdata['journaldate']) #userdata['journaldate'] = pd.to_datetime(userdata['journaldate'])
userdata["journaldate"] = userdata["journaldate"].astype(str) 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) userdata['Month-Year']=userdata['year'].astype(str)+'-'+userdata['month'].astype(str)
item_unique_name = userdata['itemname'].unique() item_unique_name = userdata['itemname'].unique()
@@ -474,15 +491,15 @@ def month(Num,get_url,get_url_token,post_url,post_url_token):
url=post_url url=post_url
payload = json.dumps(json_load)#.replace("]", "").replace("[", "") payload = json.dumps(json_load)#.replace("]", "").replace("[", "")
print(payload) #print(payload)
headers = { headers = {
#'Authorization': 'stat 263162e61f084d3392f162eb7ec39b2c',#demo #'Authorization': 'stat 263162e61f084d3392f162eb7ec39b2c',#demo
'Authorization': post_url_token,#test 'Authorization': post_url_token,#test
'Content-Type': 'application/json' # 'Content-Type': 'application/json'
} }
response = requests.request("POST", url, headers=headers, data=payload) response = requests.request("POST", url, headers=headers, data=payload)
print("##############################################################") # print("##############################################################")
print(response.text) # print(response.text)
# filePath='path.csv' # filePath='path.csv'
@@ -527,7 +544,7 @@ def sales_forcast():
#print(wise) #print(wise)
#print(Num) #print(Num)
Dataset = request.get_json() Dataset = request.get_json()
a = url_list a = Dataset
wise = a['wise'] wise = a['wise']
# print(x) # print(x)
Num = a['future_dates'] Num = a['future_dates']
@@ -537,9 +554,9 @@ def sales_forcast():
post_url_token = a['post_url_token'] post_url_token = a['post_url_token']
#print(Dataset) #print(Dataset)
import pandas as pd # import pandas as pd
df=pd.DataFrame(Dataset) # df=pd.DataFrame(Dataset)
print(df) # print(df)
# a = Dataset # a = Dataset
#x = a['wise'] #x = a['wise']
# cmd = "python C:\\Users\\Bizga\\Desktop\\forcast\\XGdaywise.py" # cmd = "python C:\\Users\\Bizga\\Desktop\\forcast\\XGdaywise.py"