working but disorganized outcome import workflow

courses.py

@@ -1861,6 +1861,27 @@ def list_all_assignments():
         print(f"{a['name']}\t{p}\t{date}")
 
 
+def bulk_unenroll():
+    course_id = input("course id> ")
+    enrollments = fetch(f"{url}/api/v1/courses/{course_id}/enrollments")
+
+    for enrollment in enrollments:
+        enrollment_id = enrollment['id']
+        skiplist = ['51237','58362','237']
+        if enrollment_id in skiplist:
+            continue
+
+        # Set the headers and parameters for the DELETE API call
+        api_url = f"{url}/api/v1/courses/{course_id}/enrollments/{enrollment_id}"
+
+        # Make the DELETE request
+        response = requests.delete(api_url, headers=header)
+
+        # Check the response
+        if response.status_code == 200:
+            print(f"Successfully unenrolled student with id {enrollment_id} from course {course_id}.")
+        else:
+            print(f"Failed to unenroll student with id {enrollment_id} from course {course_id}. Error: {response.text}")
 
 
 
@@ -1907,6 +1928,7 @@ if __name__ == "__main__":
 
                 40: ['Enroll GOTT Workshops', enroll_gott_workshops_su23], 
                 42: ['Add teacher to many shells', teacher_to_many_shells], 
+                43: ['Bulk unenroll from course', bulk_unenroll],
                 # 24: ['Add course evals to whole semester',instructor_list_to_activate_evals],   
                 # 21: ['Add announcements to homepage', change_course_ann_homepage],
                 # TODO wanted: group shell for each GP (guided pathway) as a basic student services gateway....

curric2022.py

@@ -14,8 +14,11 @@ displaynames = []
 
 from canvas_secrets import cq_user, cq_pasw
 
+from outcomes import quick_add_course_outcomes
+
 
 CQ_URL = "https://secure.curricunet.com/scripts/webservices/generic_meta/clients/versions/v4/gavilan.cfc"
+CQ_URL = "https://mws.services.curriqunet.com/scripts/webservices/generic_meta/clients/versions/v4/gavilan.cfc"
 PARAM = "?returnFormat=json&method=getCourses"
 
 user = cq_user
@@ -669,6 +672,7 @@ def another_request(url,startat):
     newparam = "&skip=" + str(startat)
     print((url+newparam))
     r = requests.get(url+newparam, auth=(user,pasw))
+    #print(r.text)
     try:
         mydata = json.loads(r.text, strict=False)
     except Exception as e:
@@ -851,11 +855,11 @@ if __name__ == "__main__":
     options = { 1: ['fetch all courses', fetch_all_classes],
                 2: ['process all classes', path_style_test],
                 3: ['courses - path style to html catalog', course_path_style_2_html],
-                4: ['courses - rank by all versions', course_rank],
+                4: ['show course outcomes', all_outcomes],
-                5: ['fetch all programs', fetch_all_programs],
+                5: ['courses - rank by all versions', course_rank],
-                6: ['process all programs', path_style_prog],
+                10: ['fetch all programs', fetch_all_programs],
-                9: ['show course outcomes', all_outcomes],
+                11: ['process all programs', path_style_prog],
-               10: ['programs - path style to html catalog', path_style_2_html],
+                12: ['programs - path style to html catalog', path_style_2_html],
              }
     
     print ('')

outcomes.py

@@ -13,6 +13,8 @@ f = codecs.open('cache/slo/log.txt','w','utf-8')
 
 VERBOSE = 1
 
+TERM = '180'
+
 SLO_CURRENT_SOURCE = 'cache/slo/2018_slo.csv'          # term 21
 #SLO_CURRENT_SOURCE = 'cache/slo/2020_slo.csv'
 
@@ -294,7 +296,7 @@ def create_dept_group(short):
     r = requests.post(t,data=new_group, headers=header)
     print(r.text)
     
-def outcomes_attached_to_courses(term=65,limitdept=''):
+def outcomes_attached_to_courses(term=TERM,limitdept=''):
     # For each class in a term, check to see if it has outcomes and/or
     # an outcome group attached to it. 
     courses = getCoursesInTerm(term,show=0,active=0)
@@ -840,7 +842,7 @@ def all_linked_outcomes_in_term(termid=''):
     #terms = [172,174,176,178]
     #for t in terms:
     #    all_linked_outcomes_in_term_sub(str(t))
-    all_linked_outcomes_in_term_sub('180')
+    all_linked_outcomes_in_term_sub(TERM)
         
         
 def all_linked_outcomes_in_term_sub(termid=''):
@@ -1277,7 +1279,7 @@ def parse_ilearn_course_names_ALLSEMESTERS():
         
 
 
-def parse_ilearn_course_names(term='178',fresh=0,log=0):
+def parse_ilearn_course_names(term=TERM,fresh=0,log=0):
     non_matches = []
 
     courses = getCoursesInTerm(term,get_fresh=fresh)

outcomes2022.py

@@ -13,7 +13,8 @@
 #     + Whether they are present in the relevant classes in iLearn
 #     + Insert SLO into course if not present
 #     + Mark as inactive (change name) if necessary
-
+#
+# - Update shell with correct outcomes
 
 # - Issue:
 #     + Course naming / sections joined...
@@ -21,16 +22,16 @@
 import concurrent.futures
 import pandas as pd
 from pipelines import fetch, url, header
-from courses import getCoursesInTerm
+from outcomes import quick_add_course_outcomes, code_from_ilearn_name, all_linked_outcomes_in_term
-import codecs, json
+from courses import getCoursesInTerm, getCourses
+import codecs, json, sys, re, csv, requests, textwrap
 from path_dict import PathDict
 
+outputfile = ''
+csvwriter = ''
 
-NUM_THREADS = 20
+TERM = 180
-get_fresh = 0
 
-TERM = 180  # fa23
-sem_courses = getCoursesInTerm(TERM,get_fresh)
 
 def escape_commas(s):
     if ',' in s:
@@ -38,15 +39,34 @@ def escape_commas(s):
     else:
         return s
 
-# shorter list for test?
-#sem_courses = sem_courses[:50]
 
-print("Got %i courses in current semester." % len(sem_courses))
+def add_outcome_to_course(shell_id=''):
+    if shell_id == '':
+        shell_id = input("Enter shell id > ")
+    course = getCourses(str(shell_id))
+    dept, code, crn = code_from_ilearn_name(course['name'])
+    print(f"{dept} {code} {crn} for course named: {course['name']}")
+    #xyz = input(f"Using: {code} for {course['name']}. Enter a different code, q to skip or press enter to continue > ")
+    #if xyz == 'q': 
+    #    return
+    #if xyz != '':
+    #    code = xyz
+    cq_course_id = find_recent_cqcourseid(code)
+    oc = codecs.open('cache/courses/alloutcomes.csv','r','utf-8')
+    reader = csv.reader(oc)
+    cols = next(reader)  # skip header
+
+    # Filter rows matching the code
+    rows = [row for row in reader if row[1] == cq_course_id]
+    rows_dicts = [  {cols[i]: r[i] for i in range(len(cols))} for r in rows ]
+    #abc = input(f"Using outcomes:\n{rows_dicts}\n\nPress enter to continue > ")
+
+    quick_add_course_outcomes(shell_id, rows_dicts)
+
 
-outputfile = codecs.open(f'cache/slo/outcomes_bycourse_{TERM}.output.txt','w','utf-8')
-outputfile.write( "coursename,assessed,courseid,outcome_id,points,title,displayname,description,guid\n")
 
 def course_slo_getter(q):
+    global outputfile, csvwriter
     (name,id) = q
     info = {'ilearnname':name,'ilearnid':id}
     print("  + Thread getting %s %s" % (str(name),str(id)))
@@ -70,6 +90,8 @@ def course_slo_getter(q):
                     og['full_outcomes'][this_outcome['id']] = this_outcome
                     saveme = [name, this_outcome['assessed'], id, this_outcome['id'], this_outcome['points_possible'], this_outcome['title'], this_outcome['display_name'], this_outcome['description'], this_outcome['vendor_guid'] ]
                     saveme2 = [escape_commas(str(x)) for x in saveme]
+                    
+                    csvwriter.writerow([id, name, og['id'], this_outcome['id'], this_outcome['vendor_guid'], this_outcome['points_possible'], this_outcome['mastery_points'], this_outcome['assessed'], this_outcome['description']])
                     outputfile.write(",".join(saveme2) + "\n")
                     outputfile.flush()
     if type(og_for_course) == list:
@@ -79,25 +101,43 @@ def course_slo_getter(q):
     print("  - Thread %s DONE" % str(id))
     return og_for_course
 
-raw_log = codecs.open('cache/outcome_raw_log.txt','w','utf-8')
-#raw_log.write( json.dumps(output,indent=2) )
 
-output = []
+# I duplicate???
-with concurrent.futures.ThreadPoolExecutor(max_workers=NUM_THREADS) as pool:
+def outcomes_in_shell(course_id):
-    futures = []
+    print(f"Getting root outcome group for course id {course_id}")
-    for C in sem_courses:
+    root_og = fetch(f"{url}/api/v1/courses/{course_id}/root_outcome_group")
-        print("Adding ", C['name'], C['id'], " to queue")
+    print(f"Getting outcomes")
-        futures.append( pool.submit(course_slo_getter, [C['name'], C['id']] ) )
+    u1 =f"{url}/api/v1/courses/{course_id}/outcome_groups/{root_og['id']}/outcomes"
-    for future in concurrent.futures.as_completed(futures):
+    outcomes_list = fetch( u1 )
-        output.append(future.result())
+    the_outcomes = []
-        print(future.result())
-        raw_log.write( json.dumps(future.result(),indent=2) + "\n" )
-    #print("--  Done")
-    #print("results array has %i items" % len(results))
-    
-    #for r in concurrent.futures.as_completed(results):
-    #    output.append(r.result())
 
+    if 'errors' in outcomes_list:
+        print(f"Error: {outcomes_list}")
+
+    if len(outcomes_list):
+        for oo in outcomes_list:
+            print(f"Getting outcome id {oo['outcome']['id']}")
+            outcome = fetch( url + '/api/v1/outcomes/%s' % str(oo['outcome']['id']) )
+            outcome['parent_group'] = root_og['id']
+            the_outcomes.append(outcome)
+    u2 = f"{url}/api/v1/courses/{course_id}/outcome_groups/{root_og['id']}/subgroups"
+    g2 = fetch( u2 )
+
+    for subgroup in g2:
+        print("doing subgroup id %s" % str(subgroup['id']))
+        u3 = f"{url}/api/v1/courses/{course_id}/outcome_groups/{subgroup['id']}/outcomes"
+        outcomes_list = fetch( u3 )
+        
+        if 'errors' in outcomes_list:
+            print(f"Error: {outcomes_list}")
+            continue
+        
+        if len(outcomes_list):
+            for oo in outcomes_list:
+                outcome = fetch( f"{url}/api/v1/outcomes/{oo['outcome']['id']}" )
+                outcome['parent_group'] = subgroup['id']
+                the_outcomes.append(outcome)
+    return root_og, the_outcomes, g2
 
 
 def ilearn_shell_slo_to_csv(shell_slos):
@@ -146,11 +186,325 @@ def ilearn_shell_slo_to_csv(shell_slos):
         
     df.to_csv('cache/outcome.csv')
     print(df)
+
+
+def get_outcomes_term_index():
+    global outputfile, csvwriter
+    NUM_THREADS = 20
+    get_fresh = 0
+
+    sem_courses = getCoursesInTerm(TERM,get_fresh)
+
+    # shorter list for test?
+    #sem_courses = sem_courses[:50]
+
+    print("Got %i courses in current semester." % len(sem_courses))
+
+    outputfile = codecs.open(f'cache/slo/outcomes_bycourse_{TERM}.output.txt','w','utf-8')
+    outputfile.write( "coursename,assessed,courseid,outcome_id,points,title,displayname,description,guid\n")
+
+    csvfile = codecs.open(f'cache/slo/linked_slos_term_{TERM}_compact.csv','w','utf-8')
+    csvwriter = csv.writer(csvfile)
+    csvwriter.writerow('courseid coursename ogid oid vendorguid points mastery assessed desc'.split(' '))
+
+    raw_log = codecs.open('cache/outcome_raw_log.txt','w','utf-8')
+    #raw_log.write( json.dumps(output,indent=2) )
+
+    output = []
+    with concurrent.futures.ThreadPoolExecutor(max_workers=NUM_THREADS) as pool:
+        futures = []
+        for C in sem_courses:
+            print("Adding ", C['name'], C['id'], " to queue")
+            futures.append( pool.submit(course_slo_getter, [C['name'], C['id']] ) )
+        for future in concurrent.futures.as_completed(futures):
+            output.append(future.result())
+            print(future.result())
+            raw_log.write( json.dumps(future.result(),indent=2) + "\n" )
+    csvfile.close()
+    ilearn_shell_slo_to_csv(output)
+
     
         
+def classify_shell(lines):
+    # given a list of lines like this, determine status of shell
+    # (from linked_slos_term_180_compact.csv) outcomes.py  all_linked_outcomes_in_term()
+
+    # 
+    # courseid,coursename,ogid,oid,vendorguid,points,mastery,assessed,desc
+    # 16909,AH11 FA23 10003/10014/12251,10860,819,,5,3,False,Use scientific facts and principles to critically analyze nutrition information and use the information to assess personal diet and the diets of other cultures.
+    # 16909,AH11 FA23 10003/10014/12251,10860,820,,5,3,False,Evaluate nutrition information for accuracy and reliability.
+    # 16909,AH11 FA23 10003/10014/12251,10860,821,,5,3,False,Analyze and identify the relationship between nutrition and health.
+    # 16909,AH11 FA23 10003/10014/12251,10860,822,,5,3,False,Differentiate among food habits and practices related to traditional foods and preparation techniques in selected cultures or religions.
+    # 16909,AH11 FA23 10003/10014/12251,10860,823,,5,3,False,Analyze nutritional problems of selected cultures and create a nutritionally balanced menu.
+    #
+    # 1. number of outcomes
+    # 2. points are correct (max=3,mastery=2) or incorrect (max=5,mastery=3)
+    # 3. assessed or not
+
+    course_status = {'outcome_count':0, 'id':0, 'name':'', 'assessed_count':0, 'points_ok':1}
+    
+    for L in lines:
+        #print(L)
+        #L = L.split(',')
+        course_status['outcome_count'] += 1
+        course_status['id'] = L[0]
+        course_status['name'] = L[1]
+        outcome_status = {'courseid':L[0],'coursename':L[1],'ogid':L[2],'oid':L[3],'vendorguid':L[4],'points':L[5],'mastery':L[6],'assessed':L[7],'desc':L[8], 'pointscorrect':0}
+        if L[5] == '5' and L[6] == '3':
+            outcome_status['pointscorrect'] = 0
+            course_status['points_ok'] = 0
+        elif (L[5] == '3.0' or L[5] == '3') and L[6] == '2':
+            outcome_status['pointscorrect'] = 1
+        else:
+            outcome_status['pointscorrect'] = -1
+        if L[7] == 'True':
+            course_status['assessed_count'] += 1
+    return course_status
+
+
+
+
+def find_recent_cqcourseid(code):
+    # code example:  CSIS42
+    with open('cache/courses/all_courses_ranked.csv', 'r') as f:
+        reader = csv.reader(f)
+        next(reader)  # skip header
+
+        # Filter rows matching the code
+        rows = [row for row in reader if row[0] == code]
+
+        print(f"All entries for {code}:\n{rows}")
         
+        if not rows:
+            raise ValueError(f"No rows found for code {code}")
+            
+        # Sort by 'termineffect', in descending order
+        rows.sort(key=lambda row: row[3], reverse=True)
+
+        # Return cqcourseid of the first row
+        myrow = rows[0][1]
+        print(f"Using: {myrow}")
+        return myrow
+
+
+
+
+
+
+def remove_old_outcomes(course_id):
+    root_og, current_outcomes, subgroups = outcomes_in_shell(course_id)
+    print(f"Got {len(current_outcomes)} outcomes for course id {course_id}")
+    print(f"Current outcomes:\n{json.dumps(current_outcomes,indent=2)}")
+
+    # Try deleting them
+    if 1:
+        for deleted_outcome in current_outcomes:
+            print(f"Deleting outcome id {deleted_outcome['id']}")
+            u9 = f"{url}/api/v1/courses/{course_id}/outcome_groups/{deleted_outcome['parent_group']}/outcomes/{deleted_outcome['id']}"
+            print(u9)
+
+            # make the DELETE request (update with your actual access token)
+            response = requests.delete(u9, headers=header)
+
+            # check the status of the request
+            if response.status_code == 200:
+                print('    Delete operation was successful')
+            else:
+                print('    Failed to delete, response code:', response.status_code)
+                print('    Response message:', response.text)
+    
+
+def repair_outcome_points(course_id):
+    # Compare to what Outcomes SHOULD be
+    course = getCourses(course_id)
+    dept, code, crn = code_from_ilearn_name(course['name'])
+    xyz = input(f"Using: {code} for {course['name']}. Enter a different code or press enter to continue > ")
+    if xyz != '':
+        code = xyz
+    cq_course_id = find_recent_cqcourseid(code)
+    oc = codecs.open('cache/courses/alloutcomes.csv','r','utf-8')
+    reader = csv.reader(oc)
+    cols = next(reader)  # skip header
+
+    # Filter rows matching the code
+    rows = [row for row in reader if row[1] == cq_course_id]
+    rows_dicts = [  {cols[i]: r[i] for i in range(len(cols))} for r in rows ]
+    abc = input(f"Using outcomes:\n{json.dumps(rows_dicts,indent=2)}\n\nPress enter to continue > ")
+
+
+    return
+
+    outcome_id = 0
+
+    data = {
+        'mastery_points': '2',
+        'calculation_method': 'decaying_average',
+        'calculation_int': '65',
+        'ratings[0][description]': 'Exceeds Expectations',
+        'ratings[0][points]': '3',
+        'ratings[1][description]': 'Meets Expectations',
+        'ratings[1][points]': '2',
+        'ratings[2][description]': 'Does Not Meet Expectations',
+        'ratings[2][points]': '0'
+    }
+
+    response = requests.put(f'{url}/api/v1/outcomes/{outcome_id}.json', headers=header, data=data)
+
+    if response.status_code == 200:
+        print(f"Successfully updated outcome with id {outcome_id}.")
+    else:
+        print(f"Failed to update outcome with id {outcome_id}. Error: {response.text}")
+
+def add_o_dept_dry_run():
+    add_o_dept(1)
+
+
+def add_o_dept(dry_run=0):
+    d = input("Enter dept or deps separated with a space > ")
+    d_list = d.split(' ')
+    course_groups = full_term_overview(0)
+
+    dept_shells_to_add = [ a for a in course_groups['no outcomes'] if a['dept'] in d_list ]
+    sorted_dept_shells_to_add = sorted(dept_shells_to_add, key=lambda x: f"{x['dept']}{x['code']}")
+
+    print(f"Adding to {len(sorted_dept_shells_to_add)} shells.")
+
+    for shell in sorted_dept_shells_to_add:
+        print(f"Adding outcomes to {shell['name']}")
+        if not dry_run:
+            try:
+                add_outcome_to_course(shell['id'])
+            except Exception as e:
+                print(f"Failed on {shell['id']}: {e}")
+        else:
+            print("  Dry run, not adding")
+
+def remove_all_bad_points():
+    course_groups = full_term_overview(0)
+
+    dept_shells_to_zap = [ a for a in course_groups['fix_points'] ]
+    for shell in dept_shells_to_zap:
+        print(f"Removing outcomes from {shell['name']}")
+        remove_old_outcomes(shell['id'])
+
+
+def full_term_overview(verbose=1):
+    out2 = codecs.open(f'cache/slo_status_{TERM}.json','w','utf-8')
+    out3 = codecs.open(f'cache/slo_status_{TERM}.txt','w','utf-8')
+    fn1 = f"cache/courses_in_term_{TERM}.json"
+    all_courses = json.loads(codecs.open(fn1,'r','utf-8').read())
+    all_courses_status = {}
+    
+    # default values for all courses
+    for C in all_courses:
+        dept,code,crn = code_from_ilearn_name(C['name'])
+        all_courses_status[str(C['id'])] = {'outcome_count':0, 'id':C['id'], 'name':C['name'], 'dept':dept, 'code':code, 'crn':crn, 'assessed_count':0, 'points_ok':1}
+
+    # read the existing ilearn outcomes and group by shell
+    filename = f"cache/slo/linked_slos_term_{TERM}_compact.csv"
+    with open(filename, 'r') as csvfile:
+        reader = csv.reader(csvfile)
+        next(reader)  # skip header
+
+        # Read the rows into a list
+        rows = list(reader)
+
+        # Sort the rows based on a specific column (e.g., column 0)
+        sorted_rows = sorted(rows, key=lambda x: x[0])
+
+        groups = []
+        current_group = []
+        last_courseid = None
+        for row in sorted_rows:
+            courseid = row[0]
+            if last_courseid != courseid and current_group:
+                # courseid changed from last row to current row
+                groups.append(current_group)
+                current_group = []
+            current_group.append(row)
+            last_courseid = courseid
+
+    # append the last group if any
+    if current_group:
+        groups.append(current_group)
+
+    for g in groups:
+        classified = classify_shell(g)
+        dept,code,crn = code_from_ilearn_name(g[0][1])
+        classified['dept'] = dept
+        classified['code'] = code
+        classified['crn'] = crn
+        all_courses_status[str(classified['id'])] = classified
+
+    #for C in all_courses_status:
+    #    print(all_courses_status[C])
+
+    course_groups = {
+        'no outcomes': [],
+        'ok': [],
+        'fix_points_and_scores': [],
+        'fix_points': []
+        }
+
+    for d in all_courses_status.values():
+        outcome_count = d['outcome_count']
+        points_ok = d['points_ok']
+        assessed_count = d['assessed_count']
+
+        if outcome_count == 0:
+            course_groups['no outcomes'].append(d)
+        elif points_ok == 1 and assessed_count > 0:
+            course_groups['fix_points_and_scores'].append(d)
+        elif points_ok == 0 and assessed_count > 0:
+            course_groups['fix_points_and_scores'].append(d)
+        elif points_ok == 1:
+            course_groups['ok'].append(d)
+        elif points_ok == 0:
+            course_groups['fix_points'].append(d)
+    
+    # Print out the groups
+    out2.write(json.dumps(course_groups,indent=2))
+    if verbose:
+        for group, dicts in course_groups.items():
+            sorted_dicts = sorted(dicts, key=lambda x: f"{x['dept']}{x['code']}")
+            print(f"{group} - {len(sorted_dicts)} item(s)")
+            out3.write(f"{group} - {len(sorted_dicts)} item(s)\n")
+            for d in sorted_dicts:
+                print(d)
+                out3.write(str(d) + "\n")
+            print("\n")
+            out3.write("\n")
+
+    return course_groups
+
+def fetch_term_outcomes_and_report():
+    get_outcomes_term_index()
+    full_term_overview()
+
+if __name__ == "__main__":
+    options = { 1: ['Refresh term outcome list & report', fetch_term_outcomes_and_report],
+                3: ['Add outcomes to course id', add_outcome_to_course],
+                4: ['Fix outcome points', remove_old_outcomes], 
+                5: ['Add outcomes to dept, dry run', add_o_dept_dry_run],
+                6: ['Add outcomes to dept', add_o_dept],
+                7: ['Remove all outcomes with wrong points', remove_all_bad_points],
+              }
+    print ('')
+
+    if len(sys.argv) > 1 and re.search(r'^\d+',sys.argv[1]):
+        resp = int(sys.argv[1])
+        print("\n\nPerforming: %s\n\n" % options[resp][0])
+    
+    else:
+        print ('')
+        for key in options:
+            print(str(key) + '.\t' + options[key][0])
         
-ilearn_shell_slo_to_csv(output)
+        print('')
+        resp = input('Choose: ')
+    
+    # Call the function in the options dict
+    options[ int(resp)][1]()