Walmart Notes, Skuid script, etc

Scripts/API_Tests/api_test.py

@@ -1,6 +1,7 @@
 import requests
 
-apiKey = "SlpQlju219WnWogn94dQUT6Yt"
+# apiKey = "SlpQlju219WnWogn94dQUT6Yt"
+apiKey = "VNDXh8K4tLYJ-Nvp78bo6w"
 url = "https://api.northpass.com/v1/media"
 # function = sys.argv[1]
 
@@ -25,8 +26,9 @@ def putTest(apiKey, url):
 def getTest(apiKey, url):
     headers = {"accept": "application/json", "X-Api-Key": apiKey}
     response = requests.get(url, headers=headers)
-    print(response.text)
-
+    # print(response.text)
+    jsonResponse = response.json()
+    # print(jsonResponse["data"][1]["attributes"])
 
 def postTest(apiKey, url):
     headers = {

Scripts/API_Tests/medialib_csv.py

@@ -0,0 +1,24 @@
+import requests
+import pandas as pd
+
+apiKey = "VNDXh8K4tLYJ-Nvp78bo6w"
+url = "https://api.northpass.com/v1/media"
+
+
+def getMedia(apiKey, url):
+    headers = {"accept": "application/json", "X-Api-Key": apiKey}
+    response = requests.get(url, headers=headers)
+    json = response.json()
+    print(json)
+    toCsv(json)
+
+
+def toCsv(json):
+    js = pd.json_normalize(json, "links", "data", ["type", "attributes", ["asset_type"]])
+    # js = pd.read_json(json, orient="index")
+    print(js)
+    js.to_csv("/Users/normrasmussen/Documents/Northpass/Scripts/API_Tests/spsmedia.csv")
+
+
+if __name__ == "__main__":
+    getMedia(apiKey, url)

Scripts/Skuid_LPs/find_completed.py

@@ -2,7 +2,7 @@ from collections import Counter
 import pandas as pd
 
 basecsv = "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/Skuid_MCA125.csv"
-lpcsv = "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/skuidlps2.csv"
+lpcsv = "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/skuidlps.csv"
 
 """
 Example multivalue dictionary
@@ -29,28 +29,50 @@ How to create this by automation?
 """
 
 
-def lpLevels(lpcsv):
+def lpLevels(basecsv, lpcsv):
     levels = pd.read_csv(
         lpcsv,
-        index_col=None,
-        header=None,
+        index_col=1,
     )
+    newDf = levels.groupby("Learning Path")
+    learningpaths = newDf.apply(lambda x: x["Course Name"].unique())
+    # learningpaths = newDf2.apply(pd.Series)
+    # learningpaths.rename_axis(index=0)
+    mainFunc(basecsv, learningpaths)
     # print(levels.Level.unique())  # Print only unique values from the Level column
 
 
-def mainFunc(basecsv):
+def mainFunc(basecsv, learningpaths):
+    # Part 1
     readData = pd.read_csv(
         basecsv,
     )
-    #    lp01 = readData[readData["Course Name"] ==
-    #    print(lp01)
-    # people = lp01.groupby(["Email", "Learner Full Name"])["Course Name"].nunique()
-    # print(people)
-    # readData.drop_duplicates(subset="Course Name", keep="first")
-    lvl1 = readData.loc["Course Name"].any()
-    if lvl1.str.contains('Level 1'):
-        emailGroups = readData.groupby(["Email", "Learner Full Name"])["Course Name"].nunique()
-        print(emailGroups)
+    group = readData.groupby("Learner Full Name")
+    df2 = group.apply(lambda x: x["Course Name"].unique())
+    df2 = df2.apply(pd.Series, dtype="string")
+    # print(df2)
+    # This prints a dataframe with the learner's name as the index column and the courses as adjacent columns
+
+    # Part 2
+    # learningpaths.set_index(0)
+    # print(courses)
+    lp_dict = learningpaths.to_dict()
+    courses = lp_dict.values()
+    print(courses)
+    # crs = courses
+    # print(crs)
+
+    # Part 3
+    # for course in courses:
+      #  print(df2.isin(course))
+
+    # df3 = df2.columns
+    # print(df3)
+    # for name in df3.items():
+    #    print(f"name: {name}")
+
+    # emailGroups = readData.groupby(["Email", "Learner Full Name"])["Course Name"].nunique()
+    # print(emailGroups)
     # emailGroups = people.to_csv(
     #    "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/outtest2.csv"
     # )
@@ -70,5 +92,5 @@ def mainFunc(basecsv):
 
 
 if __name__ == "__main__":
-    mainFunc(basecsv)
-    # lpLevels(lpcsv)
+    # mainFunc(basecsv)
+    lpLevels(basecsv, lpcsv)

Scripts/Skuid_LPs/skuidlps.csv

@@ -1,4 +1,4 @@
-Level,LP,Course Name
+Level,Learning Path,Course Name
 Level 1,01: Skuid Ethos - Level 1,Congratulations! You've been accepted to Skuid Skool
 Level 1,01: Skuid Ethos - Level 1,Create Your Own Dev Org Environment/Install Skuid - Level 1
 Level 1,01: Skuid Ethos - Level 1,Skuid Resources