mods for running w/out cache
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phowell
parent
25028b6df2
commit
6a18cb6866
112
depricated.py
112
depricated.py
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@ -908,41 +908,41 @@ rez = [[m[j][i] for j in range(len(m))] for i in range(len(m[0]))]
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"""
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ilearn_by_id = {}
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ilearn_by_name = {}
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for x in ilearn_list:
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"""
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ilearn_by_id = {}
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ilearn_by_name = {}
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for x in ilearn_list:
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ilearn_by_id[x[3]] = x
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ilearn_by_name[x[0]] = x
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for ml in open('cache/teacher_manual_name_lookup.csv','r').readlines():
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for ml in open('cache/teacher_manual_name_lookup.csv','r').readlines():
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parts = ml.strip().split(',')
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try:
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manual_list[parts[0]] = ilearn_by_id[parts[1]]
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except Exception as e:
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print "Teacher missing: " + parts[0]
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il_names = [ x[0] for x in ilearn_list ]
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il_byname = {}
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for x in ilearn_list: il_byname[x[0]] = x
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sched_list_missed = [x for x in sched_list]
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il_names = [ x[0] for x in ilearn_list ]
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il_byname = {}
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for x in ilearn_list: il_byname[x[0]] = x
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sched_list_missed = [x for x in sched_list]
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#
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# key is long name (with middle name) from schedule, value is tuple with everything
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name_lookup = manual_list
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matches = []
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#
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# key is long name (with middle name) from schedule, value is tuple with everything
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name_lookup = manual_list
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matches = []
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#print ilearn_list
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#print ilearn_list
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num_in_sched = len(sched_list)
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num_in_ilearn = len(ilearn_list)
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num_in_sched = len(sched_list)
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num_in_ilearn = len(ilearn_list)
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#for i in range(min(num_in_sched,num_in_ilearn)):
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# print "|"+sched_list[i] + "|\t\t|" + ilearn_list[i][0] + "|"
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#for i in range(min(num_in_sched,num_in_ilearn)):
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# print "|"+sched_list[i] + "|\t\t|" + ilearn_list[i][0] + "|"
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print("Sched names: %i, iLearn names: %i" % (num_in_sched,num_in_ilearn))
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print("Sched names: %i, iLearn names: %i" % (num_in_sched,num_in_ilearn))
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for s in sched_list:
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for s in sched_list:
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for t in il_names:
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if first_last(s) == t:
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#print ' MATCHED ' + s + ' to ' + t
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@ -955,65 +955,67 @@ rez = [[m[j][i] for j in range(len(m))] for i in range(len(m[0]))]
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matches.append(s)
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print "Matched: " + str(matches)
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print "Matched: " + str(matches)
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print "\nDidn't match: " + str(len(sched_list_missed)) + " schedule names."
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print "\nDidn't match: " + str(len(sched_list_missed)) + " schedule names."
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print "\nFinal results: "
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print name_lookup
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print "\nFinal results: "
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print name_lookup
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nlf = codecs.open('cache/sched_to_ilearn_names.json','w','utf-8')
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nlf.write(json.dumps(name_lookup,indent=2))
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# STRING DISTANCE
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nlf = codecs.open('cache/sched_to_ilearn_names.json','w','utf-8')
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nlf.write(json.dumps(name_lookup,indent=2))
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# STRING DISTANCE
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#sim = find_most_similar(s,i_names)
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#print ' CLOSEST MATCHES to ' + s + ' are: ' + str(sim)
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#mm.write(s+',\n')
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"""
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"""
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#ilearn_list = sorted(list(set(map(
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# lambda x: #(tfi[x]['name'],tfi[x]['email'],tfi[x]['dept'],str(tfi[x]['id']),tfi[x]['goo']),
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# tfi.keys()))))
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#i_names = [ x[0] for x in ilearn_list ]
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# lambda x: #(tfi[x]['name'],tfi[x]['email'],tfi[x]['dept'],str(tfi[x]['id']),tfi[x]['goo']),
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# tfi.keys()))))
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#i_names = [ x[0] for x in ilearn_list ]
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#print json.dumps(i_names,indent=2)
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#return
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#print json.dumps(i_names,indent=2)
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#return
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# how to filter a dict based on values
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# filtered = {k: v for k, v in course_combos.items() if v['dept'] == 'LIB' or v['dept'] == 'CSIS' }
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# how to filter a dict based on values
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# filtered = {k: v for k, v in course_combos.items() if v['dept'] == 'LIB' or v['dept'] == 'CSIS' }
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# more pandas
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# gapminder['continent'].unique()
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# more pandas
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# gapminder['continent'].unique()
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#for name,group in bycode:
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# #print name
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# print name, " ", group['type']
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#for name,group in bycode:
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# #print name
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# print name, " ", group['type']
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#onl = gg.agg( lambda x: has_online(x) )
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#ttl = gg.agg( lambda x: len(x) )
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#ttl = ttl.rename(columns={'type':'total_sections'})
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#onl = gg.agg( lambda x: has_online(x) )
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#ttl = gg.agg( lambda x: len(x) )
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#ttl = ttl.rename(columns={'type':'total_sections'})
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#onl.join(gg.agg( lambda x: has_hybrid(x) ),how='outer')
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#onl.join(gg.agg( lambda x: has_lecture(x) ), how='outer')
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#onl.join(gg.agg( lambda x: has_hybrid(x) ),how='outer')
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#onl.join(gg.agg( lambda x: has_lecture(x) ), how='outer')
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#onl['num_sections'] = 0
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#onl['num_lec'] = 0
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#onl['num_online'] = 0
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#onl['num_sections'] = 0
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#onl['num_lec'] = 0
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#onl['num_online'] = 0
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#all = pd.merge([onl,hyb,lec])
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#print onl
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#total=len, f2f=lambda x: ) set(x)
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#{ 'num_sections': "count",
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# 'num_lec': lambda x: 5,
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# 'num_online': lambda x: 5 } )
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#print gg
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#all = pd.merge([onl,hyb,lec])
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#print onl
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#total=len, f2f=lambda x: ) set(x)
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#{ 'num_sections': "count",
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# 'num_lec': lambda x: 5,
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# 'num_online': lambda x: 5 } )
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#print gg
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"""
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def has_online(series):
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# if any items of the series have the string 'online', return 1
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for i in series:
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@ -20,10 +20,13 @@ sqlite_file = local_data_folder + 'data.db' #'data_su20_4hr_blocks.db'
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mylog = codecs.open(local_data_folder + 'canvas_data_log.txt','w')
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thefiles_dat = {}
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for L in open('cache/canvas_data_index.txt','r').readlines():
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try:
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for L in open('cache/canvas_data_index.txt','r').readlines():
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L = L.strip()
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(fname,start,finish) = L.split(',')
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thefiles_dat[fname] = start
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except Exception as e:
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print("cache/canvas_data_index.txt was not found")
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thefiles = open('cache/canvas_data_index_temp.txt','a') # rename me if nothing crashes :)
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@ -1,4 +1,3 @@
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alabaster==0.7.10
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anaconda-client==1.6.5
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anaconda-navigator==1.6.9
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anaconda-project==0.8.0
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