DV Script and Walmart changes

Scripts/AddGroupsUsers/addgroup_users.py

@@ -0,0 +1,97 @@
+import requests
+import sys
+import http
+import pandas as pd
+
+apiKey = "SlpQlju219WnWogn94dQUT6Yt"
+#groupName = sys.argv[1]
+peopleCsv = "/Users/normrasmussen/Downloads/peopletogroups.csv"
+
+def createGroup(groupName, apiKey):
+    # Create a Group endpoint - params: group_uuid 
+    url = "https://api.northpass.com/v2/groups"
+    payload = {"data": {"attributes": {"name": f"{groupName}"}}}
+    headers = {
+    "accept": "application/json",
+    "content-type": "application/json",
+    "X-Api-Key": apiKey
+    }
+    groupresponse = requests.post(url, json=payload, headers=headers)
+    if "already have a group with this name" in groupresponse.text:
+        groupName = input("Group already created, what name would you like instead? ")
+        print("Got it, thanks! Attempting to create the group now.")
+        createGroup(groupName, apiKey)
+    else:
+        readCSV(apiKey, groupresponse)
+
+def readCSV(apiKey, groupresponse):
+    people = []
+    readExport = pd.read_csv(
+            peopleCsv, 
+            usecols=['UUID'],
+            skipinitialspace=True,
+            )
+    people.extend(readExport['UUID'].tolist())
+    getgroupId(people, groupresponse, apiKey)
+
+def getgroupId(people, groupresponse, apiKey):
+    groupresponse = groupresponse.json()
+    groupID = groupresponse['data']['id']
+    ppltoGroup(people, groupID, apiKey)
+
+def ppltoGroup(people, groupID, apiKey):
+    print(groupID)
+    
+    # Add People to a Group. Params needed: group_uuid
+    url = f"https://api.northpass.com/v2/groups/{groupID}/relationships/people"
+    # Loop through this payload and/or add everyone as new { "type":"people", "id":"uuid"}
+    #for uuid in people:
+    #    itempayload = []
+    #    jsonpayload = { "type":"people", "id":uuid },
+    #    itempayload.append(jsonpayload)
+    payload = {"data": [
+                { 
+                    "type":"people", 
+                    "id":people
+                 },
+             #   { "type":"people", "id":people[1]},
+             #   { "type":"people", "id":people[2]},
+                
+        ]}
+    headers = {
+        "accept": "*/*",
+        "content-type": "application/json",
+        "X-Api-Key": apiKey
+    }
+    print(url)
+    print(payload)
+    print(headers)
+    response = requests.post(url, json=payload, headers=headers)
+    print(response.text)
+
+if __name__ == "__main__":
+    ppltoGroup(people="0b31c435-c18b-4573-984e-32cda57045b4", groupID="4f83841f-939f-469f-b98f-29ce7f980c6e",apiKey="SlpQlju219WnWogn94dQUT6Yt")
+    #createGroup(groupName, apiKey)
+
+
+    url = "https://api.northpass.com/v2/groups/4c2e807c-2b65-4ce7-a359-2e470fe4f322/relationships/people"
+
+payload = {"data": [
+        {
+            "type": "people",
+            "id": "0b31c435-c18b-4573-984e-32cda57045b4"
+        },
+        {
+            "type": "people",
+            "id": "0b31c435-c18b-4573-984e-32cda57045b4"
+        }
+    ]}
+headers = {
+    "accept": "*/*",
+    "content-type": "application/json",
+    "X-Api-Key": "SlpQlju219WnWogn94dQUT6Yt"
+}
+
+response = requests.post(url, json=payload, headers=headers)
+
+print(response.text)

Scripts/WalmartExcel/walmart.py

@@ -34,9 +34,11 @@ def copytoDash(latestdownload, currentDash):
             latestdownload, 
             index_col=False,
             header=0,
+            low_memory=False,
             dtype={
-                'Progress':int
-        })
+                'Progress':object
+        }
+            )
     print(readExport)
     readExport.drop(
             readExport.filter(
@@ -45,7 +47,6 @@ def copytoDash(latestdownload, currentDash):
                 inplace=True)
     copiedData = readExport.copy()
     bringtoExcel(latestdownload, currentDash, copiedData)
-    #with pd.ExcelWriter("")
 
 def bringtoExcel(latestdownload, currentDash, copiedData):
     with pd.ExcelWriter(
@@ -60,7 +61,6 @@ def bringtoExcel(latestdownload, currentDash, copiedData):
                 sheet_name="Data",
                 index=False,
     )
-#    cleanitUp(currentDash)
 
 def cleanitUp(currentDash):
     cleanExcel = pd.read_excel(currentDash, sheet_name="Data", index_col=None)

Scripts/WalmartExcel/walmart_numeric.py

@@ -0,0 +1,68 @@
+import os
+import sys
+from datetime import date
+import glob
+import shutil
+import csv
+import pandas as pd
+
+rootdir = "/Users/normrasmussen/Documents/Resources/Walmart/"
+downloadir = "/Users/normrasmussen/Google Drive/My Drive/Shared with Clients/Walmart/"
+basefile = "WalmartTemplate.xlsx"
+
+def copytemplate(rootdir, basefile):
+    today = date.today()
+    today = today.strftime("%m.%d.%Y")
+    template = rootdir+basefile
+    todayFile = f"Walmart-{today}.xlsx"
+    if os.path.exists(rootdir):
+        shutil.copy2(template, rootdir+todayFile)
+        #dirfiles = os.listdir(rootdir)
+        #print(dirfiles)
+        currentDash = rootdir+f"Walmart-{today}.xlsx"
+        print(currentDash)
+        findlatestExport(currentDash)
+
+def findlatestExport(currentDash):
+    listfiles = glob.glob(downloadir + '*.xlsx')
+    latestdownload = max(listfiles, key=os.path.getctime)
+    print(latestdownload)
+    copytoDash(latestdownload, currentDash)
+
+def copytoDash(latestdownload, currentDash):
+    readExport = pd.read_excel(
+            latestdownload, 
+            index_col=False,
+            header=0,
+            )
+    readExport.drop(
+            readExport.filter(
+                regex="Unname"
+                ),axis=1, 
+                inplace=True)
+    readExport['Progress_replace'] = readExport['Progress'].str.replace('%','')
+    readExport['Progress_replace'] = pd.to_numeric(readExport['Progress_replace'])
+    copiedData = readExport.copy()
+    bringtoExcel(latestdownload, currentDash, copiedData)
+    #cleanitUp(latestdownload, currentDash, copiedData)
+
+def bringtoExcel(latestdownload, currentDash, copiedData):
+    with pd.ExcelWriter(
+            currentDash,
+            mode="a",
+            engine="openpyxl",
+            if_sheet_exists="overlay",
+    ) as writer:
+        copiedData.to_excel(
+                writer,
+                engine="xlsxwriter",
+                sheet_name="Data",
+                index=False,
+    )
+
+#def cleanitUp(latestdownload, currentDash, copiedData):
+    #cleanExcel = pd.read_excel(currentDash, sheet_name="Data", index_col=None)
+#    print(cleanExcel)
+
+if __name__ == "__main__":
+    copytemplate(rootdir, basefile)