1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
1530
1531
1532
1533
1534
1535
1536
1537
1538
1539
1540
1541
1542
1543
1544
1545
1546
1547
1548
1549
1550
1551
1552
1553
1554
1555
1556
1557
1558
1559
1560
1561
1562
1563
1564
1565
1566
1567
1568
1569
1570
1571
1572
1573
1574
1575
1576
1577
1578
1579
1580
1581
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
1633
1634
1635
1636
1637
1638
1639
1640
1641
1642
1643
1644
1645
1646
1647
1648
1649
1650
1651
1652
1653
1654
1655
1656
1657
1658
1659
1660
1661
1662
1663
1664
1665
1666
1667
1668
1669
1670
1671
1672
1673
1674
1675
1676
1677
1678
1679
1680
1681
1682
1683
1684
1685
1686
1687
1688
1689
1690
1691
1692
1693
1694
1695
1696
1697
1698
1699
1700
1701
1702
1703
1704
1705
1706
1707
1708
1709
1710
1711
1712
1713
1714
1715
1716
1717
1718
1719
1720
1721
1722
1723
1724
1725
1726
1727
1728
1729
1730
1731
1732
1733
1734
1735
1736
1737
1738
1739
1740
1741
1742
1743
1744
1745
1746
1747
1748
1749
1750
1751
1752
1753
1754
1755
1756
1757
1758
1759
1760
1761
1762
1763
1764
1765
1766
1767
1768
1769
1770
1771
1772
1773
1774
1775
1776
1777
1778
1779
1780
1781
1782
1783
1784
1785
1786
1787
1788
1789
1790
1791
1792
1793
1794
1795
1796
1797
1798
1799
1800
1801
1802
1803
1804
1805
1806
1807
1808
1809
1810
1811
1812
1813
1814
1815
1816
1817
1818
1819
1820
1821
1822
1823
1824
1825
1826
1827
1828
1829
1830
1831
1832
1833
1834
1835
1836
1837
1838
1839
1840
1841
1842
1843
1844
1845
1846
1847
1848
1849
1850
1851
1852
1853
1854
1855
1856
1857
1858
1859
1860
1861
1862
1863
1864
1865
1866
1867
1868
1869
1870
1871
1872
1873
1874
1875
1876
1877
1878
1879
1880
1881
1882
1883
1884
1885
1886
1887
1888
1889
1890
1891
1892
1893
1894
1895
1896
1897
1898
1899
1900
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
|
from django.shortcuts import render
from django.http import HttpResponse
from gnowsys_ndf.ndf.models import *
from gnowsys_ndf.ndf.views.methods import get_execution_time
from django.template import RequestContext
#from stemming.porter2 import stem
try:
from collections import OrderedDict
except ImportError:
# python 2.6 or earlier, use backport
from ordereddict import OrderedDict
import json
import difflib
import string
import datetime
import itertools
import nltk
from gnowsys_ndf.ndf.models import node_collection, triple_collection
from gnowsys_ndf.ndf.models import *
my_doc_requirement = u'storing_orignal_doc'
reduced_doc_requirement = u'storing_reduced_doc'
to_reduce_doc_requirement = u'storing_to_be_reduced_doc'
indexed_word_list_requirement = u'storing_indexed_words'
KEYWORD_SEARCH = u'KEYWORD_SEARCH'
ADVANCED_SEARCH = u'ADVANCED_SEARCH'
RELATION_SEARCH = u'RELATION_SEARCH'
SEMANTIC_SEARCH = u'SEMANTIC_SEARCH'
POSSIBLE_SEARCH_TYPES = ["GSystem", "File"]
# CLASS FOR ENCODING INTO JSON - OBJECTID TO STRING CONVERSION
class Encoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, ObjectId):
return str(obj)
else:
return obj
# DISPLAYS THE SEARCH PAGE - USEFUL ONLY IF COMING TO THE SEARCH PAGE FROM THE OUTSIDE
def search_page(request, group_id):
ins_objectid = ObjectId()
if ins_objectid.is_valid(group_id) is False :
group_ins = node_collection.find_one({'_type': "Group","name": group_id})
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if group_ins:
group_id = str(group_ins._id)
else:
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if auth :
group_id = str(auth._id)
else:
pass
context_to_return = getRenderableContext(group_id)
return render(request, 'ndf/search_page.html', context_to_return)
# FUNCTION THAT RETURNS A MINIMUM COMMON CONTEXT THAT ALL SEARCH RESULTS RETURN
def getRenderableContext(group_id):
temp = node_collection.find({"_type":"GSystemType"}, {"name":1, "_id":0})
ins_objectid = ObjectId()
allGSystems = []
allGroups=[]
for gs in temp:
allGSystems.append(gs.name)
#allGroups = get_public_groups() # LIST OF ALL PUBLIC GROUPS
if ins_objectid.is_valid(group_id) is False :
group_ins = node_collection.find_one({'_type': "Group","name": group_id})
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if group_ins:
group_id = str(group_ins._id)
else:
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if auth :
group_id = str(auth._id)
group_ins=auth
else:
group_ins = node_collection.find_one({'_type': "Group", "_id": ObjectId(group_id)})
if not group_ins:
group_ins = node_collection.find_one({'_type': "Author", "_id": ObjectId(group_id)})
allGroups.append(group_ins.name)
allUsers = populate_list_of_group_members(allGroups) # LIST OF ALL USERS IN PUBLIC GROUPS
memList = populate_list_of_members() # LIST OF ALL USERS
return {"allGSystems":allGSystems, "groupid":group_id, "allGroups":allGroups, "authors":memList, "allUsers":allUsers, "group_id":group_id}
# VIEW FOR KEYWORD SEARCH
def search_query(request, group_id):
col = get_database()[Node.collection_name]
# SCRIPT FOR CONVERTING GROUP NAME RECEIVED TO OBJECTID
ins_objectid = ObjectId()
if ins_objectid.is_valid(group_id) is False :
group_ins = node_collection.find_one({'_type': "Group", "name": group_id})
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if group_ins:
group_id = str(group_ins._id)
else:
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if auth :
group_id = str(auth._id)
else:
pass
memList = populate_list_of_members() # memList holds the list of all authors
return render(request, 'ndf/search_home.html', {"groupid":group_id, "authors":memList}, context_instance=RequestContext(request))
# View for returning the search results according to group search
# def search_query_group(request, group_id):
# # SCRIPT FOR CONVERTING GROUP NAME RECEIVED TO OBJECTID
# ins_objectid = ObjectId()
# if ins_objectid.is_valid(group_id) is False :
# group_ins = node_collection.find_one({'_type': "Group","name": group_id})
# auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
# if group_ins:
# group_id = str(group_ins._id)
# else:
# auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
# if auth :
# group_id = str(auth._id)
# else:
# pass
# # CHANGE THIS TO GROUP SPECIFIC MEMBERS
# memList = populate_list_of_members() # memList holds the list of all authors
# return render(request, 'ndf/search_home.html', {"groupid":group_id, "authors":memList}, context_instance=RequestContext(request))
@get_execution_time
def results_search(request, group_id, return_only_dict = None):
"""
This view returns the results for global search on all GSystems by name, tags and contents.
Only publicly accessible GSystems are returned in results.
"""
userid = request.user.id
# print "\n------\n", request.GET
ins_objectid = ObjectId()
if ins_objectid.is_valid(group_id) is False :
group_ins = node_collection.find_one({'_type': "Group", "name": group_id})
if group_ins:
group_id = str(group_ins._id)
else:
auth = node_collection.one({'_type': 'Author', 'created_by': unicode(userid) })
if auth :
group_id = str(auth._id)
# INTIALISE THE FLAGS FOR SEARCHING BY NAME / TAGS / CONTENTS
user = "" # stores username
user_reqd = -1 # user_reqd = -1 => search all users else user_reqd = pk of the user in user table
# GET THE LIST OF CHECKBOXES TICKED AND SET CORR. FLAGS
checked_fields = request.GET.getlist('search_fields')
if checked_fields:
search_by_name = True if ("name" in checked_fields) else False
search_by_tags = True if ("tags" in checked_fields) else False
search_by_contents = True if ("contents" in checked_fields) else False
else:
search_by_name = search_by_tags = search_by_contents = True
# FORMAT OF THE RESULTS TO BE RETURNED
search_results_ex = {'name': [], 'tags': [], 'content': []}
search_results_st = {'name': [], 'tags': [], 'content': []}
# search_results_li = {'name':[], 'tags':[], 'content':[], 'user':[]}
# ALL SORTED SEARCH RESULTS
search_results = {'exact': search_results_ex, 'stemmed': search_results_st}
# STORES OBJECTID OF EVERY SEARCH RESULT TO CHECK FOR DUPLICATES
all_ids = []
if request.method == "GET":
try:
user_reqd_name = str(request.GET['users'])
except Exception:
# IF USERNAME IS NOT RECEIVED OR ANY INCORRECT USERNAME IS RECEIVED SEARCH ALL USERS
user_reqd_name = "all"
# CONVERT USERNAME TO INTEGER
if user_reqd_name != "all":
#Query writtent o avoid the error due to User.Object
auth = node_collection.one({'_type': 'Author', 'name': user_reqd_name})
if auth:
user_reqd = int(auth.created_by)
search_str_user = str(request.GET['search_text']).strip() # REMOVE LEADING / TRAILING SPACES
search_str_user = search_str_user.lower() # CONVERT TO LOWERCASE
search_str_noArticles = list(removeArticles(str(search_str_user))) # REMOVES ARTICLES
search_str_stemmed = list(stemWords(search_str_noArticles, search_str_user)) # STEMS THE WORDS
#Check if the user is the super User
Access_policy=""
if request.user.is_superuser:
Access_policy=["PUBLIC","PRIVATE"]
else:
Access_policy=["PUBLIC"]
# GET A CURSOR ON ALL THE GSYSTEM TYPES
all_GSystemTypes = node_collection.find({"_type":"GSystemType"}, {"_id":1})
#public_groups = get_public_groups() # GET LIST OF PUBLIC GROUPS
#public_groups = group_name_to_id(public_groups) # CONVERT GROUP NAMES TO OBJECTIDS
if (search_by_name == True): # IF TRUE, THEN SEARCH BY NAME
all_GSystemTypes.rewind()
count = 0
if (search_by_name == True): # IF TRUE, THEN SEARCH BY NAME
all_GSystemTypes.rewind() # amn Corrected
"""
Following lines search for all GSystemTypes and then all GSystems in those GSystem types created by the selected user
of public access policy in case insensitive regex match. If no user is specified, then it searches for GSystems created
by any user
"""
# Search in all GSystem types
all_list = [ each_gst._id for each_gst in all_GSystemTypes ]
# EXACT MATCH OF SEARCH_USER_STR IN NAME OF GSYSTEMS OF ONE GSYSTEM TYPE
# print "group id", group_id
if user_reqd != -1:
exact_match = node_collection.find({'$and':[
{"member_of":{'$in':all_list}},
{"created_by":user_reqd},
{"group_set":ObjectId(group_id)},
{'$or':[{"access_policy":{"$in":Access_policy}},{'created_by':request.user.id}]},
{"name":search_str_user}]},
{"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "group_set":1, "url":1}).sort('last_update',-1)
else:
exact_match = node_collection.find({'$and':[
{"member_of":{'$in':all_list}},
{'$or':[{"access_policy":{"$in":Access_policy}},{'created_by':request.user.id}]},
{"group_set":ObjectId(group_id)},
{"name":{"$regex":search_str_user,"$options":"i"}}]},
{"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "group_set":1, "url":1}).sort('last_update',-1)
# SORT THE NAMES ACCORDING TO THEIR SIMILARITY WITH THE SEARCH STRING
#exact_match.rewind()
exact_match = list(exact_match)
"""
For each matching GSystem, see if the GSystem has already been added to the list of ids and add if not added.
result is added only if belongs to the list of public groups
"""
for j in exact_match:
j.name=(j.name).replace('"',"'")
if j._id not in all_ids:
grps = j.group_set
#for gr in public_groups:
# if gr in grps:
j = addType(j)
search_results_ex['name'].append(j)
all_ids.append(j['_id'])
# SORTS THE SEARCH RESULTS BY SIMILARITY WITH THE SEARCH QUERY
#search_results_ex['name'] = sort_names_by_similarity(search_results_ex['name'], search_str_user)
# split stemmed match
split_stem_match = [] # will hold all the split stem match results
len_stemmed = len(search_str_stemmed)
c = 0 # GEN. COUNTER
while c < len_stemmed:
word = search_str_stemmed[c]
temp=""
if user_reqd != -1: # user_reqd = -1 => search all users, else user_reqd = pk of user
temp = node_collection.find({'$and':[
{"member_of":{'$in':all_list}}, {"created_by":user_reqd},
{"group_set":ObjectId(group_id)},
{'$or':[{"access_policy":{"$in":Access_policy}},{'created_by':request.user.id}]},
{"name":{"$regex":word, "$options":"i"}}]},
{"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "group_set":1, "url":1}).sort('last_update',-1)
else:
# search all users in created by
temp = node_collection.find({'$and':[
{"member_of":{'$in':all_list}},
{"group_set":ObjectId(group_id)},
{'$or':[{"access_policy":{"$in":Access_policy}},{'created_by':request.user.id}]},
{"name":{"$regex":str(word), "$options":"i"}}] },
{"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "group_set":1, "url":1}).sort('last_update',-1)
split_stem_match.append(temp)
c += 1
"""
For each matching GSystem, see if the GSystem has already been returned in search results and add if not already added.
Result is added only if belongs to the list of public groups and has public access policy
"""
for j in split_stem_match:
c = 0
for k in j:
k.name=(k.name).replace('"',"'")
if (k._id not in all_ids):# check if this GSYstem has already been added to search results
#grps = k.group_set
# group_set holds all the groups that the current GSystem is published in
#for gr in public_groups:
# for each public group
# if gr in grps:
# check that the GSystem should belong to at least one public group
k = addType(k) # adds the link and datetime to the
search_results_st['name'].append(k)
all_ids.append(k['_id'])#append to the list of all ids of GSYstems in the results
c += 1
# SORTS THE SEARCH RESULTS BY SIMILARITY WITH THE SEARCH QUERY
#search_results_st['name'] = sort_names_by_similarity(search_results_st['name'], search_str_user)
if (search_by_tags == True): # IF True, THEN SEARCH BY TAGS
all_GSystemTypes.rewind() # Rewinds the cursor to first result
count = 0
# EXACT MATCH OF SEARCH_USER_STR IN NAME OF GSYSTEMS OF ONE GSYSTEM TYPE
if user_reqd != -1:
exact_match = node_collection.find({'$and':[
{"member_of":{'$in':all_list}},
{"created_by":user_reqd},
{"group_set":ObjectId(group_id)},
{'$or':[{"access_policy":{"$in":Access_policy}},{'created_by':request.user.id}]},
{"tags":search_str_user}]},
{"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "group_set":1, "url":1}).sort('last_update',-1)
else:
exact_match = node_collection.find({'$and':[
{"member_of":{'$in':all_list}}, {'$or':[{"access_policy":{"$in":Access_policy}},{'created_by':request.user.id}]},
{"group_set":ObjectId(group_id)},
{"tags":search_str_user}]},
{"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "group_set":1, "url":1}).sort('last_update',-1)
for j in exact_match:
j.name=(j.name).replace('"',"'")
if j._id not in all_ids:
#grps = j.group_set
#for gr in public_groups:
# if gr in grps:
j = addType(j)
search_results_ex['tags'].append(j)
all_ids.append(j['_id'])
#search_results_ex['tags'] = sort_names_by_similarity(search_results_ex['tags'], search_str_user)
# split stemmed match
split_stem_match = []
c = 0 # GEN. COUNTER
len_stemmed = len(search_str_stemmed)
while c < len_stemmed:
word = search_str_stemmed[c]
if user_reqd != -1:
temp = node_collection.find({'$and':[{"tags":word},
{"member_of":{'$in':all_list}},
{"created_by":user_reqd},
{"group_set":ObjectId(group_id)},
{'$or':[{"access_policy":{"$in":Access_policy}},{'created_by':request.user.id}]}]},
{"name":1, "_id":1, "member_of":1, "created_by":1, "group_set":1, "last_update":1, "url":1}).sort('last_update',-1)
else:
temp = node_collection.find({'$and':[{"tags":word},
{"member_of":{'$in':all_list}},
{'$or':[{"access_policy":{"$in":Access_policy}},{'created_by':request.user.id}]},
{"group_set":ObjectId(group_id)}]},
{"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "group_set":1, "url":1}).sort('last_update',-1)
split_stem_match.append(temp)
c += 1
#search_results_st['tags'] = sort_names_by_similarity(search_results_st['tags'], search_str_user)
"""
For each matching GSystem, see if the GSystem has already been returned in search results and add if not already added.
Result is added only if belongs to the list of public groups and has public access policy
"""
for j in split_stem_match:
c = 0
for k in j:
k.name=(k.name).replace('"',"'")
if k._id not in all_ids:
#grps = k.group_set
#for gr in public_groups:
# if gr in grps:
k = addType(k)
search_results_st['tags'].append(k)
all_ids.append(k['_id'])
c += 1
"""
The following lines implement search over the contents of all GSystems.
It uses the Map Reduce algorithm to keep track of which GSystems contain which words and how many times.
The more the count of matches, the more relevant the search result is for the user.
"""
#print "stemmed query: ", search_str_stemmed
content_docs = []
content_match_pairs = [] # STORES A DICTIONARY OF MATCHING DOCUMENTS AND NO_OF_WORDS THAT MATCH SEARCH QUERY
sorted_content_match_pairs = [] # STORES THE ABOVE DICTIONARY IN A SORTED MANNER
if (search_by_contents == True):
# FETCH ALL THE GSYSTEMS THAT HAVE BEEN MAP REDUCED.
all_Reduced_documents = node_collection.find({"required_for": reduced_doc_requirement}, {"content": 1, "_id": 0, "orignal_id": 1})
# ABOVE LINE DOES NOT RETURN ALL GSYSTEMS. IT RETURNS OBJECTS OF "ToReduceDocs" class.
for singleDoc in all_Reduced_documents:
if singleDoc.orignal_id not in all_ids: # IF THE GSYSTEM HAS NOT ALREADY BEEN ADDED TO SEARCH RESULTS
content = singleDoc.content
match_count = 0 # KEEPS A CUMMULATIVE COUNT OF MATCHES OF ALL SEARCH QUERY WORDS IN THE CURRENT GSYSTEM CONTENTS
for word in search_str_stemmed:
if word in content.keys():# IF THE WORD EXISTS IN THE CURRENT DOCUMENT
match_count += content[word] # ADD IT TO THE MATCHES COUNT
if match_count > 0:
all_ids.append(singleDoc.orignal_id)
content_match_pairs.append({'doc_id':singleDoc.orignal_id, 'matches':match_count})
match_counts = [] # KEEPS A SORTED LIST OF COUNT OF MATCHES IN RESULT DOCUMENTS
for pair in content_match_pairs:
c = 0
while ((c < len(match_counts)) and (pair['matches'] < match_counts[c])):# INSERT IN SORTED ORDER BY INCREASING ORDER
c += 1
match_counts.insert(c, pair['matches'])
sorted_content_match_pairs.insert(c, pair) # SORTED INSERT (INCREASING ORDER)
for docId in sorted_content_match_pairs:
doc = node_collection.find_one({"_id":docId['doc_id'], "access_policy":Access_policy}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "group_set":1, "url":1})
try:
grps = doc.group_set
"""
For each matching GSystem, see if the GSystem has already been returned in search results and add if not already added.
Result is added only if belongs to the list of public groups and has public access policy
"""
#for gr in public_groups:
# if gr in grps:
doc = addType(doc)
#matching for current group Only
if ObjectId(group_id) in grps:
if user_reqd != -1:
if User.objects.get(username=doc['created_by']).pk == user_reqd:
search_results_st['content'].append(doc)
else:
search_results_st['content'].append(doc)
except:
pass
#search_results = json.dumps(search_results, cls=Encoder)
memList = populate_list_of_members()
search_results = json.dumps(search_results, cls=Encoder)
# print "search_results:", search_results
if return_only_dict:
return search_results
else:
context_to_return = getRenderableContext(group_id) # RETURNS BASIC CONTEXT
context_to_return['search_results'] = search_results # ADD SEARCH RESULTS TO CONTEXT
context_to_return['processed'] = "1"
context_to_return['search_type'] = KEYWORD_SEARCH # TYPE OF SEARCH IS KEYWORD SEARCH
return render(request, 'ndf/search_page.html', context_to_return)
# KEYWORD SEARCH FOR A SPECIFIC GROUP
def results_search_group(request, group_id):
"""
This view returns the results for search on all GSystems by name, tags and contents in the group currently chosen.
Only publicly accessible GSystems are returned in results.
"""
group_ins = {}
ins_objectid = ObjectId()
if ins_objectid.is_valid(group_id) is False :
group_ins = node_collection.find_one({'_type': "Group", "name": group_id})._id
group_id = ObjectId(group_ins)
else:
pass
group_id = ObjectId(group_id)
# DECLARE THE VARIABLES
search_by_name = 0
search_by_tags = 0
search_by_contents = 0
user = ""
user_reqd = -1
try:
if request.method == "GET":
try:
user_reqd_name = str(request.GET['users'])
except Exception:
user_reqd_name = "all"
if user_reqd_name != "all":
user_reqd = int(User.objects.get(username = user_reqd_name).pk)
search_str_user = str(request.GET['search_text']).strip()
##print "\noriginal search string:", search_str_user, "\n"
search_str_user = search_str_user.lower()
search_str_noArticles = list(removeArticles(str(search_str_user)))
##print "\narticles removed:",search_str_noArticles,"\n"
search_str_stemmed = list(stemWords(search_str_noArticles, search_str_user))
##print "\nwords stemmed:",search_str_stemmed,"\n\n\n"
# -------------------------------------------------------
##print "Search string lowercase:", search_str_user
# GET THE LIST OF CHECKBOXES TICKED AND SET CORR. FLAGS
checked_fields = request.GET.getlist('search_fields')
nam = "name"
##print "\n\nfields: ", checked_fields, "\n\n"
if (nam in checked_fields):
##print "by_name"
search_by_name = 1
nam = "tags"
if (nam in checked_fields):
##print "by_tags"
search_by_tags = 1
nam = "contents"
if (nam in checked_fields):
##print "by_contents"
search_by_contents = 1
#user = str(request.GET['author']) # GET THE VALUE OF AUTHOR FROM THE FORM
# FORMAT OF THE RESULTS RETURNED
search_results_ex = {'name':[], 'tags':[], 'content':[], 'user':[]}
search_results_st = {'name':[], 'tags':[], 'content':[], 'user':[]}
search_results_li = {'name':[], 'tags':[], 'content':[], 'user':[]}
# ALL SORTED SEARCH RESULTS
search_results = {'exact':search_results_ex, 'stemmed':search_results_st, 'like':search_results_li}
# STORES OBJECTID OF EVERY SEARCH RESULT TO CHECK FOR DUPLICATES
all_ids = []
# GET A CURSOR ON ALL THE GSYSTEM TYPES
all_GSystemTypes = node_collection.find({"_type":"GSystemType"}, {"_id":1})
len1 = all_GSystemTypes.count()
if (search_by_name == 1): # IF 1, THEN SEARCH BY NAME
all_GSystemTypes.rewind()
count = 0
for GSType in all_GSystemTypes:
# EXACT MATCH OF SEARCH_USER_STR IN NAME OF GSYSTEMS OF ONE GSYSTEM TYPE
if user_reqd != -1:
exact_match = node_collection.find({'$and':[{"member_of":GSType._id},{"created_by":user_reqd}, {"access_policy":Access_policy},{"group_set":group_id},{"name":{"$regex":search_str_user, "$options":"i"}}]}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
else:
exact_match = node_collection.find({'$and':[{"member_of":GSType._id},{ "access_policy":Access_policy}, {"group_set":group_id}, {"name":{"$regex":search_str_user, "$options":"i"}}]}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
# SORT THE NAMES ACCORDING TO THEIR SIMILARITY WITH THE SEARCH STRING
exact_match = list(exact_match)
#exact_match = sort_names_by_similarity(exact_match, search_str_user)
for j in exact_match:
j.name=(j.name).replace('"',"'")
if j._id not in all_ids:
j = addType(j)
search_results_ex['name'].append(j)
all_ids.append(j['_id'])
search_results_ex['name'] = sort_names_by_similarity(search_results_ex['name'], search_str_user)
# split stemmed match
split_stem_match = []
len_stemmed = len(search_str_stemmed)
c = 0 # GEN. COUNTER
while c < len_stemmed:
word = search_str_stemmed[c]
if user_reqd != -1:
temp = node_collection.find({'$and':[{"member_of":GSType._id},{ "group_set":group_id},{ "created_by":user_reqd},{ "access_policy":Access_policy},{ "name":{"$regex":word, "$options":"i"}}]}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
else:
temp = node_collection.find({'$and':[{"member_of":GSType._id},{ "group_set":group_id}, {"access_policy":Access_policy}, {"name":{"$regex":word, "$options":"i"}}]}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
#temp_sorted = sort_names_by_similarity(temp, search_str_user)
split_stem_match.append(temp)#temp_sorted)
c += 1
for j in split_stem_match:
c = 0
for k in j:
k.name=(k.name).replace('"',"'")
if (k._id not in all_ids):
k = addType(k)
search_results_st['name'].append(k)
all_ids.append(k['_id'])
c += 1
search_results_st['name'] = sort_names_by_similarity(search_results_st['name'], search_str_user)
if (search_by_tags == 1): # IF 1, THEN SEARCH BY TAGS
all_GSystemTypes.rewind()
count = 0
for GSType in all_GSystemTypes:
# EXACT MATCH OF SEARCH_USER_STR IN NAME OF GSYSTEMS OF ONE GSYSTEM TYPE
if user_reqd != -1:
exact_match = node_collection.find({"member_of":GSType._id, "group_set":group_id, "created_by":user_reqd, "access_policy":Access_policy, "tags":search_str_user}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
else:
exact_match = node_collection.find({"member_of":GSType._id, "access_policy":Access_policy, "group_set":group_id, "tags":search_str_user}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
#exact_match = sort_names_by_similarity(exact_match, search_str_user)
for j in exact_match:
j.name=(j.name).replace('"',"'")
if j._id not in all_ids:
j = addType(j)
search_results_ex['tags'].append(j)
all_ids.append(j['_id'])
search_results_ex['tags'] = sort_names_by_similarity(search_results_ex['tags'], search_str_user)
# split stemmed match
split_stem_match = []
c = 0 # GEN. COUNTER
len_stemmed = len(search_str_stemmed)
while c < len_stemmed:
word = search_str_stemmed[c]
if user_reqd != -1:
temp = node_collection.find({"member_of":GSType._id, "group_set":group_id, "tags":word, "created_by":user_reqd, "access_policy":Access_policy}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
else:
temp = node_collection.find({"member_of":GSType._id, "group_set":group_id, "access_policy":Access_policy, "tags":word}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
#temp_sorted = sort_names_by_similarity(temp, search_str_user)
split_stem_match.append(temp)#_sorted)
c += 1
search_results_st['tags'] = sort_names_by_similarity(search_results_st['tags'], search_str_user)
for j in split_stem_match:
c = 0
for k in j:
k.name=(k.name).replace('"',"'")
if k._id not in all_ids:
k = addType(k)
search_results_st['tags'].append(k)
all_ids.append(k['_id'])
c += 1
content_docs = []
content_match_pairs = []
sorted_content_match_pairs = []
if (search_by_contents == 1):
all_Reduced_documents = node_collection.find({"required_for": reduced_doc_requirement}, {"content": 1, "_id": 0, "orignal_id": 1})
##print "cursor: ", all_Reduced_documents, all_Reduced_documents.count()
for singleDoc in all_Reduced_documents:
if singleDoc.orignal_id not in all_ids:
content = singleDoc.content
#print "Content: ", content, "\n\n"
match_count = 0
for word in search_str_stemmed:
if word in content.keys():
match_count += content[word]
if match_count > 0:
all_ids.append(singleDoc.orignal_id)
content_match_pairs.append({'doc_id':singleDoc.orignal_id, 'matches':match_count})
match_counts = []
for pair in content_match_pairs:
c = 0
while ((c < len(match_counts)) and (pair['matches'] < match_counts[c])):
c += 1
match_counts.insert(c, pair['matches'])
sorted_content_match_pairs.insert(c, pair)
#sorted_content_match_pairs = OrderedDict(sorted(content_match_pairs.items(), key=lambda t: t[1]))
#print "sorted pairs: ", sorted_content_match_pairs
for docId in sorted_content_match_pairs:
doc = node_collection.find_one({"_id":docId['doc_id'], "group_set":group_id, "access_policy":Access_policy}, {"name":1, "_id":1, "member_of":1, "created_by":1, "last_update":1, "url":1})
if (doc != None):
doc = addType(doc)
#print "type added ", doc['created_by'], "value: ", User.objects.get(username=doc['created_by']).pk == 1
if user_reqd != -1:
if User.objects.get(username=doc['created_by']).pk == user_reqd:
search_results_st['content'].append(doc)
else:
search_results_st['content'].append(doc)
##print "stemmed results: ", search_results_st
#search_results = json.dumps(search_results, cls=Encoder)
#print "final results: ", search_results
#memList = populate_list_of_members()
except Exception:
pass
search_results = json.dumps(search_results, cls=Encoder)
context_to_return = getRenderableContext(group_id)
context_to_return['search_results'] = search_results
context_to_return['processed'] = 1
context_to_return['search_type'] = KEYWORD_SEARCH
return render(request, 'ndf/search_page.html', context_to_return)
# def advanced_search(request, group_id):
# ins_objectid = ObjectId()
# if ins_objectid.is_valid(group_id) is False :
# group_ins = node_collection.find_one({'_type': "Group","name": group_id})
# auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
# if group_ins:
# group_id = str(group_ins._id)
# else:
# auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
# if auth :
# group_id = str(auth._id)
# else:
# pass
# #print "Group id is: ", group_id
# temp = node_collection.find({"_type":"GSystemType"}, {"name":1, "_id":0})
# allGSystems = []
# for gs in temp:
# allGSystems.append(gs.name)
# allGroups = get_public_groups()
# #print "groups: ", allGroups
# allUsers = populate_list_of_group_members(allGroups)
# #print "members: ", allUsers
# ##print allGSystems
# return render(request, 'ndf/advanced_search2.html', {"allGSystems":allGSystems, "groupid":group_id, "allGroups":allGroups, "allUsers":allUsers, "group_id":group_id})
def get_attributes(request, group_id):
attributes = []
##print request.GET['GSystem']
#print "names: ", request.GET.get('GSystem',"")
##print "testing !: ", request.GET['tex']
list_of_keys = ['name', 'last_update', 'tags']
#try:
GSystem_names = request.GET['GSystem']
GSystem_names = GSystem_names.split(',')
#print "name of GSystem", GSystem_names
for GSystem_name in GSystem_names:
#print GSystem_name
test_obj = node_collection.find_one({"_type":"GSystemType", "name":GSystem_name})
##print test_obj.keys()
for sg_key in list_of_keys:
if sg_key in test_obj.keys():
if sg_key not in attributes:
attributes.append(sg_key)
#print "\n\nattr: ", attributes, "\n\n"
temp = node_collection.one({"_type":"GSystemType", "name":GSystem_name})
for attr in temp.attribute_type_set:
attributes.append(attr.name)
#except Exception:
# #print "Exception occurred"
# pass
#print attributes
return HttpResponse(json.dumps(attributes, cls=Encoder))
def user_name_to_id(userNames):
allUsers = []
for user in userNames:
sg_id = User.objects.get(username=user).pk
allUsers.append(sg_id)
return allUsers
def group_name_to_id(groupNames):
allGroups = []
for gr in groupNames:
sg_gr = node_collection.find({"_type":"Group", "name":gr})
for each in sg_gr:
allGroups.append(each._id)
return allGroups
def advanced_search_results(request, group_id):
# READ THE GET VALUES
search_str_user = str(request.GET['search_text']).strip()
search_groups = request.GET.getlist('Groups')
search_users = request.GET.getlist('Users')
GSystem_names = request.GET.getlist('GSystems')
attr_name = request.GET.getlist('attribs')
all_groups = []
all_users = []
split_query = search_str_user.split()
#print "name of GSystems: ", GSystem_names
#print "name of Groups: ", search_groups
#print "name of Authors: ", search_users
all_users = 0
if search_users[0] != "all":
all_users = user_name_to_id(search_users)
else:
temp1 = get_public_groups()
temp2 = populate_list_of_group_members(temp1)
#print "publics: ", temp1, temp2
all_users = user_name_to_id(temp2)
if search_groups[0] != "all":
all_groups = group_name_to_id(search_groups)
else:
all_groups = group_name_to_id(get_public_groups())
#print "name of Authors: ", all_users
#print "name of Groups: ", all_groups
search_results = []
all_ids = []
for word in split_query:
for at_name in attr_name:
#print "attr: ", at_name
# CASE 1 -- SEARCH IN THE STRUCTURE OF THE GSYSTEM
for GSystem_name in GSystem_names:
GSystem_obj = node_collection.one({"_type":"GSystemType", "name":GSystem_name})
##print GSystem_obj
if at_name in GSystem_obj:
if all_users != 0:
res = node_collection.find({"_type":{"$in":POSSIBLE_SEARCH_TYPES}, "member_of":GSystem_obj._id, at_name:{"$regex":word, "$options":"i" }}, {"name":1, "created_by":1, "last_update":1, "member_of":1 , "group_set":1, "url":1})
else:
res = node_collection.find({"_type":{"$in":POSSIBLE_SEARCH_TYPES}, "created_by":{"$in":all_users}, "member_of":GSystem_obj._id, at_name:{"$regex":word, "$options":"i" }}, {"name":1, "created_by":1, "last_update":1, "member_of":1, "group_set":1, "url":1})
for obj in res:
flag = False
#print obj.name
if obj._id not in all_ids:
GSystem_groups = obj.group_set
#print "groups: ", GSystem_groups
for gr_id in all_groups:
if gr_id in GSystem_groups:
link_obj = addType(obj)
search_results.append({'name':obj.name, 'link':link_obj['link'], 'created_by':link_obj['created_by'], 'last_update':link_obj['last_update'], '_id':link_obj['_id']})
all_ids.append(obj._id)
break
continue
# CASE 2 -- SEARCH THE GATTRIBUTES
try:
attr_id = node_collection.one({"_type":"AttributeType", "name":at_name}, {"_id":1})
res = triple_collection.find({"_type":"GAttribute", "attribute_type.$id":ObjectId(attr_id._id), "object_value":{"$regex":word, "$options":"i"}}, {"name":1, "object_value":1, "subject":1})
#print "Sttr type: ", attr_id
for obj in res:
if all_users == 0:
GSystem = node_collection.one({"_id":obj.subject}, {"name":1, "created_by":1, "last_update":1, "member_of":1 , "group_set":1, "url":1})
else:
GSystem = node_collection.one({"_id":obj.subject, "created_by":{"$in":all_users}}, {"name":1, "created_by":1, "last_update":1, "member_of":1, "group_set":1, "url":1})
if GSystem._id not in all_ids:
#print "adding: ", GSystem._id
# THE FOLLOWING CODE MAY BE WRONG IF THE RETURNED NODE IS A MEMBER OF MORE THAN ONE GSYSTEM_TYPE
#link_obj = node_collection.one({"member_of":GSystem.member_of[0], "required_for":"Links"}, {"link":1})
#print "731"
GSystem_groups = GSystem.group_set
#print "groups: ", GSystem_groups
for gr_id in all_groups:
if gr_id in GSystem_groups:
link_obj = addType(GSystem)
search_results.append({'name':GSystem.name, 'link':link_obj['link'], 'created_by':link_obj['created_by'], 'last_update':link_obj['last_update'], '_id':link_obj['_id']})
all_ids.append(GSystem._id)
break
except:
continue
search_results = sort_names_by_similarity(search_results, search_str_user)
#print search_results
search_results = json.dumps(search_results, cls=Encoder)
context_to_return = getRenderableContext(group_id)
context_to_return['search_results'] = search_results
context_to_return['processed'] = 1
context_to_return['search_type'] = ADVANCED_SEARCH
return render(request, 'ndf/search_page.html', context_to_return)
def get_public_groups():
cur = node_collection.find({"_type": "Group", "group_type": "PUBLIC"}, {"name": 1})
allGroups = []
for obj in cur:
allGroups.append(obj.name)
return allGroups
def addType(obj):
##print "received: ", obj.member_of[0]
#i = ObjectId(obj.member_of[0])
#links = node_collection.find({"member_of":i, "required_for":"Links"}, {"link":1})
##print "links count", links.count(), "\n"
auth = node_collection.one({'_type': 'Author', 'created_by': obj.created_by})
#for ob in links:
obj2 = {}
obj2['_id'] = obj._id
obj2['name'] = obj.name
obj2['link'] = obj.url
if auth:
obj2['created_by'] = auth.name
##print "lst update: ", type(obj.last_update)
obj2['last_update'] = str(obj.last_update.date())
#datetime.datetime.strptime(obj.last_update, "%Y-%m-%dT%H:%M:%S.%fZ").date()
#print "obj", obj2
return obj2
def sort_names_by_similarity(exact_match, search_str_user):
matches = [] # TO STORE A LIST OF SORTED MATCH PERCENTAGE
final_list = [] # FINAL LIST OF SORTED OBJECTS
#print exact_match
for obj in exact_match:
##print obj
match = difflib.SequenceMatcher(None, obj['name'], search_str_user)
per_match = match.ratio()
##print "sorting", obj['name'], ": ", per_match, "\n"
if len(matches) == 0:
matches.append(per_match)
final_list.append(obj)
else:
c = 0
while ((c < len(matches)) and (per_match < matches[c])):
c += 1
matches.insert(c, per_match)
final_list.insert(c, obj)
return final_list
def removeArticles(text):
words = text.split()
articles=['a', 'an', 'and', 'the', 'i', 'is', 'this', 'that', 'there', 'here', 'am', 'on', 'at', 'of', 'where']
for w in articles:
if w in words:
words.remove(w)
words = removeDuplicateWords(words)
return words
def removeDuplicateWords(words):
return list(OrderedDict.fromkeys(words))
def stemWords(words, search_str_user):
stemmed = []
l = len(words)
c = 0
stemmer = nltk.stem.porter.PorterStemmer()
while (c < l):
temp = words[c].lower() #THE WORD IS CONVERTED INTO LOWER CASE IN THIS STEP
temp = stemmer.stem_word(temp)
stemmed.append(temp)
c+=1
#temp = stem(words[c])
#if (temp != search_str_user):
#print stemmed
return stemmed
"""
This function returns a list of all authors.
"""
def populate_list_of_members():
members = User.objects.all()
memList = []
for mem in members:
memList.append(mem.username)
return memList
def populate_list_of_group_members(group_ids):
"""
This function returns a list of users in a given list of groups.
Groups should be given as a list of group ids.
"""
memList = []
try:
for gr in group_ids:
# THIS CODE WILL CAUSE PROBLEMS IF THERE ARE MANY GROUPS WITH THE SAME NAME
group_id = node_collection.find_one({"_type":"Group", "name":gr}, {"_id":1})
author_list = node_collection.one({"_type":"Group", "_id":group_id._id}, {"author_set":1, "_id":0})
for author in author_list.author_set:
name_author = User.objects.get(pk=author).username
if name_author not in memList:
memList.append(name_author)
except:
pass
return memList
def get_users(request, group_id):
group_ids = str(request.GET['Groups'])
group_ids = group_ids.split(",")
#print group_ids
if group_ids[0] == "all":
#print "hi there"
allGroups = get_public_groups()
allUsers = populate_list_of_group_members(allGroups)
else:
allUsers = populate_list_of_group_members(group_ids)
return HttpResponse(json.dumps(allUsers, cls=Encoder))
def get_node_info(request, group_id, node_name):
ins_objectid = ObjectId()
if ins_objectid.is_valid(group_id) is False :
group_ins = node_collection.find_one({'_type': "Group", "name": group_id})
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if group_ins:
group_id = str(group_ins._id)
else:
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if auth :
group_id = str(auth._id)
else:
pass
is_list = False
list_of_nodes = node_collection.find({"name": node_name}, {"_id": 1})
if list_of_nodes.count() > 1:
list_of_nodes.rewind()
is_list = True
list_nodes = []
for obj in list_of_nodes:
list_nodes.append(obj._id)
list_nodes = json.dumps(list_nodes, cls=Encoder)
return render(request, 'ndf/node_details.html', {'is_list':1, 'list_nodes':list_nodes, 'all_fields':'', 'groupid':group_id})
else:
sg_node = node_collection.one({"name": node_name})
GSTypes = sg_node.member_of
attrs = []
results = {}
results['name'] = sg_node.name
results['created_by'] = sg_node.created_by
results['last_update'] = str(sg_node.last_update.date())
for GSType in GSTypes:
obj = node_collection.one({"_id": ObjectId(GSType)})
for attr in obj.attribute_type_set:
custom_attrs = triple_collection.find({"_type": "GAttribute", "subject": ObjectId(sg_node._id), "attribute_type.$id": ObjectId(attr._id)}, {"name":1, "object_value":1})
for sg_attr in custom_attrs:
temp = sg_attr.name
i1 = temp.index('--') + 3
temp = temp[i1:]
i1 = temp.index('--') - 1
temp = temp[:i1]
results[temp] = sg_attr.object_value
results = json.dumps(results, cls=Encoder)
return render(request, 'ndf/node_details.html', {'is_list':0, 'list_nodes':'', 'all_fields':results, 'groupid':group_id})
def get_node_info2(request, group_id, node_id):
"""
This view displays the info about a node - the basic fields - name, created_by, last_update as well as all the GAttributes.
Useful for GSystems that dont have an output .html template
"""
ins_objectid = ObjectId()
if ins_objectid.is_valid(group_id) is False :
group_ins = node_collection.find_one({'_type': "Group","name": group_id})
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if group_ins:
group_id = str(group_ins._id)
else:
auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
if auth :
group_id = str(auth._id)
else:
pass
sg_node = node_collection.one({"_id": ObjectId(node_id)})
GSTypes = sg_node.member_of
attrs = []
results = {}
results['name'] = sg_node.name
results['created_by'] = sg_node.created_by
results['last_update'] = str(sg_node.last_update.date())
for GSType in GSTypes:
obj = node_collection.one({"_id": ObjectId(GSType)})
for attr in obj.attribute_type_set:
custom_attrs = triple_collection.find({"_type": "GAttribute", "subject": ObjectId(sg_node._id), "attribute_type.$id": ObjectId(attr._id)}, {"name":1, "object_value":1})
for sg_attr in custom_attrs:
temp = sg_attr.name
i1 = temp.index('--') + 3
temp = temp[i1:]
i1 = temp.index('--') - 1
temp = temp[:i1]
results[temp] = sg_attr.object_value
results = json.dumps(results, cls=Encoder)
return render(request, 'ndf/node_details.html', {'is_list':0, 'list_nodes':'', 'all_fields':results, 'groupid':group_id})
def get_relations_for_autoSuggest(request, group_id):
"""
This function returns a list of names of RelationsTypes, GSystemTypes and GSYstems in the database according to the search query already typed by the user.
This function is repeatedly called by an ajax call as the user types.
"""
col = get_database()[Node.collection_name]
x = request.GET['sVal'] # CURRENT WORD BEING TYPED
prefix = request.GET['prefix'] # ALREADY TYPED WORDS
ins = [] # HOLDS LIST OF SUGGESTIONS TO RETURN
# FIND NAMES OF ALL GSYSTEMTYPES OR RELATIONTYPES THAT START WITH WHAT HAS BEEN TYPED BY THE USER
instances = node_collection.find({ "$or": [{ "_type": "RelationType"}, {"_type": "GSystemType"}], "name":{'$regex':"^"+x, "$options":"i"}}, {"name":1})
for inst in instances:
ins.append(prefix + ' ' + inst.name)
instances = node_collection.find({"_type": "GSystem", "name":{'$regex':"^"+x, "$options":"i"}}, {"name":1})
for inst in instances:
ins.append(prefix + ' ' + inst.name)
# NOTE: RESULTS FOR AUTO SUGGEST HAVE THE USER TYPED QUERY APPENDED AS PREFIX
return HttpResponse(json.dumps(ins))
# def ra_search(request, group_id):
# # GET VALUE FROM TEXT BOX
# ins_objectid = ObjectId()
# if ins_objectid.is_valid(group_id) is False :
# group_ins = node_collection.find_one({'_type': "Group","name": group_id})
# auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
# if group_ins:
# group_id = str(group_ins._id)
# else:
# auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
# if auth :
# group_id = str(auth._id)
# else:
# pass
# return render(request, 'ndf/ra_search.html', {"groupid":group_id})
def ra_search_results(request, group_id):
"""
This function implements the graph search.
We have implemented the search in two cases:
Case 1: <relation_type> <GSystem>
In this case we look for a matching "relation type" from the left of the search query.
Then the rest of the search query is matched with the GSystem names.
In effect this case looks for GRelations with the matched Relation type and having the matched GSystem as either left or right subject.
Case 2a: <GSystem_type> <Relation_Type> <GSystem>
Case 2b: <GSystem> <Relation_Type> <GSystem_Type>
In this case we look for a matching "GSystem type" from the left of the search query.
Then all GSystems which are "member_of" the matched "GSystemType" are fetched.
Then the rest of the search query is matched with the "GSystem" names.
In effect this case looks for GRelations with the matched "GSystem" as one subject and any of the GSystems which are "member_of" the matched "GSystemType" as the other subject.
"""
sq = str(request.GET['search_text']).strip() # SEARCH QUERY
relations = node_collection.find({"_type": "RelationType"}, {"name": 1, "inverse_name": 1})
CASE_TWO_THRESHOLD = 0.6
GSYSTEM_MIN_THRESHOLD_CASE1 = 0.69
result_members = []
sorted_rel = {}
max_length = 0
for rel in relations:
length = len(rel.name.split('_'))
if str(length) in sorted_rel.keys():
sorted_rel[str(length)].append(rel.name)
else:
sorted_rel[str(length)] = [rel.name]
length = len(rel.inverse_name.split('_'))
if str(length) in sorted_rel.keys():
sorted_rel[str(length)].append(rel.inverse_name)
else:
sorted_rel[str(length)] = [rel.inverse_name]
if length > max_length:
max_length = length
split_word = sq.split()
c = 0
max_match = 0
max_match_rel = ""
rel_word_count = 0
while c < len(split_word):
cur_word = ""
i = 0
while i<c:
cur_word += split_word[i]
i += 1
(max_m, max_m_rel, rel_w_count) = get_max_match(sorted_rel, cur_word, max_length)
if max_m > max_match:
max_match = max_m
max_match_rel = max_m_rel
rel_word_count = rel_w_count
c += 1
GSystem_name = ""
c = rel_word_count
while c < len(split_word):
GSystem_name += split_word[c] + " "
c += 1
try:
relationType_obj = node_collection.one({"_type": "RelationType", "$or": [{"name": max_match_rel}, {"inverse_name": max_match_rel} ] }, {"_id": 1, "name": 1})
GRelation_objs = triple_collection.find({"_type": "GRelation", "relation_type.$id": relationType_obj._id})
#subjects = []
#right_subjects = []
for gr_obj in GRelation_objs:
name_Grel = gr_obj.name
left_sub = name_Grel[:name_Grel.index('--')-1]
right_sub = name_Grel[name_Grel.rfind('--')+3:]
if difflib.SequenceMatcher(None, GSystem_name, left_sub).ratio() > GSYSTEM_MIN_THRESHOLD_CASE1:
reqd_obj = node_collection.one({"_id":gr_obj.right_subject, "access_policy":"PUBLIC"}, {"_id":1, "name":1, "created_by":1, "last_update":1, "url":1})
#subjects.append(gr_obj.subject)
#right_subjects.append(gr_obj.name)
reqd_obj = addType(reqd_obj)
result_members.append(reqd_obj)
#print "match %: ", difflib.SequenceMatcher(None, GSystem_name, left_sub).ratio()
elif difflib.SequenceMatcher(None, GSystem_name, right_sub).ratio() > GSYSTEM_MIN_THRESHOLD_CASE1:
reqd_obj = node_collection.one({"_id":gr_obj.subject, "access_policy":"PUBLIC"}, {"_id":1, "name":1, "created_by":1, "last_update":1, "url":1})
#subjects.append(gr_obj.subject)
#right_subjects.append(gr_obj.name)
reqd_obj = addType(reqd_obj)
result_members.append(reqd_obj)
#print "match %: ", difflib.SequenceMatcher(None, GSystem_name, right_sub).ratio()
except Exception:
pass
############################################## CASE - 2 - A ##########################################
if max_match < CASE_TWO_THRESHOLD:
# LOOK FOR GSYSTEM_TYPE IN SEARCH QUERY
GSystemTypes = node_collection.find({"_type": "GSystemType"}, {"name": 1})
sorted_gst = {}
max_length = 0
for gst in GSystemTypes:
length = len(gst.name.split())
if str(length) in sorted_gst.keys():
sorted_gst[str(length)].append(gst.name)
else:
sorted_gst[str(length)] = [gst.name]
if length > max_length:
max_length = length
split_word = sq.split()
c = 0
max_match_gst = 0
max_match_rel_gst = ""
rel_word_count_gst = 0
while c < len(split_word):
cur_word = ""
i = 0
while i <= c:
if i!= 0:
cur_word += ' ' + split_word[i]
else:
cur_word = split_word[i]
i += 1
(max_m, max_m_rel, rel_w_count) = get_max_match(sorted_gst, cur_word, max_length)
if max_m > max_match_gst:
max_match_gst = max_m
max_match_rel_gst = max_m_rel
rel_word_count_gst = rel_w_count
c += 1
# LOOK FOR GSYSTEM IN THE SEARCH QUERY
sorted_gs = {}
max_length = 0
GSystems_sq = node_collection.find({"_type": {"$in": POSSIBLE_SEARCH_TYPES}}, {"name": 1})
for gs in GSystems_sq:
length = len(gs.name.split())
if str(length) in sorted_gs.keys():
sorted_gs[str(length)].append(gs.name)
else:
sorted_gs[str(length)] = [gs.name]
if length > max_length:
max_length = length
split_word = sq.split()
c = len(split_word)-1
max_match_gs = 0
max_match_rel_gs = ""
rel_word_count_gs = 0
while c >= rel_word_count_gst:
cur_word = ""
i = len(split_word)-1
while i >= c:
cur_word = split_word[i] + ' ' + cur_word
i -= 1
(max_m, max_m_rel, rel_w_count) = get_max_match(sorted_gs, cur_word, max_length)
if max_m > max_match_gs:
max_match_gs = max_m
max_match_rel_gs = max_m_rel
rel_word_count_gs = rel_w_count
c -= 1
try:
GStype = node_collection.one({"name": max_match_rel_gst}, {"_id": 1})
GS_sq = node_collection.find_one({"name": "GSystem", "name": max_match_rel_gs}, {"_id": 1})
allMembers = node_collection.find({"_type": {"$in": POSSIBLE_SEARCH_TYPES}, "member_of": GStype._id}, {"_id": 1, "name": 1})
# LOOK FOR GRELATIONS WITH BOTH GSYSTEMS ON EITHER SIDE
relations = triple_collection.find({"_type": "GRelation", "right_subject": GS_sq._id}, {"subject": 1})
relations.rewind()
for rel in relations:
allMembers.rewind()
for member in allMembers:
if rel.subject == member._id:
member = addType(member)
result_members.append(member)
allMembers.rewind()
relations = triple_collection.find({"_type": "GRelation", "subject": GS_sq._id}, {"right_subject": 1})
for rel in relations:
for member in allMembers:
if rel.right_subject == member._id:
member = addType(member)
result_members.append(member)
except Exception:
pass
######################################## CASE 2 - B ######################################
# LOOK FOR GSYSTEM IN THE SEARCH QUERY
sorted_gs = {}
max_length = 0
GSystems_sq = node_collection.find({"_type": {"$in": POSSIBLE_SEARCH_TYPES}}, {"name": 1})
for gs in GSystems_sq:
length = len(gs.name.split())
if str(length) in sorted_gs.keys():
sorted_gs[str(length)].append(gs.name)
else:
sorted_gs[str(length)] = [gs.name]
if length > max_length:
max_length = length
split_word = sq.split()
c = 0
max_match_gs = 0
max_match_rel_gs = ""
rel_word_count_gs = 0
while c < len(split_word):
cur_word = ""
i = 0
while i <= c:
cur_word += split_word[i]
i += 1
(max_m, max_m_rel, rel_w_count) = get_max_match(sorted_gs, cur_word, max_length)
if max_m > max_match_gs:
max_match_gs = max_m
max_match_rel_gs = max_m_rel
rel_word_count_gs = rel_w_count
c += 1
# LOOK FOR GSYSTEM_TYPE IN SEARCH QUERY
GSystemTypes = node_collection.find({"_type": "GSystemType"}, {"name": 1})
sorted_gst = {}
max_length = 0
for gst in GSystemTypes:
length = len(gst.name.split())
if str(length) in sorted_gst.keys():
sorted_gst[str(length)].append(gst.name)
else:
sorted_gst[str(length)] = [gst.name]
if length > max_length:
max_length = length
split_word = sq.split()
c = len(split_word)-1
max_match_gst = 0
max_match_rel_gst = ""
rel_word_count_gst = 0
while c >= rel_word_count_gs:
cur_word = ""
i = len(split_word)-1
while i >= c:
cur_word = split_word[i] + ' ' + cur_word
i -= 1
(max_m, max_m_rel, rel_w_count) = get_max_match(sorted_gst, cur_word, max_length)
if max_m > max_match_gst:
max_match_gst = max_m
max_match_rel_gst = max_m_rel
rel_word_count_gst = rel_w_count
c -= 1
try:
GStype = node_collection.one({"name": max_match_rel_gst}, {"_id": 1})
GS_sq = node_collection.find_one({"name": "GSystem", "name": max_match_rel_gs}, {"_id": 1})
allMembers = node_collection.find({"_type": {"$in": POSSIBLE_SEARCH_TYPES}, "member_of": GStype._id}, {"_id": 1, "name": 1, "created_by": 1, "last_update": 1, "url": 1})
# LOOK FOR GRELATIONS WITH BOTH GSYSTEMS ON EITHER SIDE
relations = triple_collection.find({"_type": "GRelation", "right_subject": GS_sq._id}, {"subject": 1})
relations.rewind()
for rel in relations:
allMembers.rewind()
for member in allMembers:
if rel.subject == member._id:
member = addType(member)
result_members.append(member)
relations = triple_collection.find({"_type": "GRelation", "subject": GS_sq._id}, {"right_subject": 1})
for rel in relations:
allMembers.rewind()
for member in allMembers:
if rel.right_subject == member._id:
member = addType(member)
result_members.append(member)
except Exception:
pass
#print result_members
result_members = json.dumps(result_members, cls=Encoder)
context_to_return = getRenderableContext(group_id) # BASIC CONTEXT
context_to_return['search_results'] = result_members # ADD SEARCH RESULTS TO CONTEXT
context_to_return['search_type'] = RELATION_SEARCH # ADD SEARCH TYPE TO CONTEXT
return render(request, 'ndf/search_page.html', context_to_return)
def get_max_match(sorted_rel, word_reqd, max_length):
"""
Helper function for the graph search function.
It takes as input a dictionary having names grouped by their lengths.
It returns the maximum matching word from the list to a required word.
"""
i = 1
max_match = 0
max_match_rel = ""
rel_word_count = 0
while i <= max_length:
if str(i) in sorted_rel.keys():
temp_list = sorted_rel[str(i)]
for rel in temp_list:
match_per = difflib.SequenceMatcher(None, word_reqd.lower(), rel.lower()).ratio()
if match_per > max_match:
max_match = match_per
max_match_rel = rel
rel_word_count = i
if max_match == 1.0:
return (max_match, max_match_rel, rel_word_count)
i += 1
return (max_match, max_match_rel, rel_word_count)
#######################################################################################################################################
#######################################################SEMANTIC SEARCH 8TH JULY########################################################
################################### PRE PROCESSING FOR MAP REDUCE #################################################################
def pre_process_for_map_reduce(text):
grammar = r"""
NBAR:
{<NN.*|JJ>*<NN.*>} # Nouns and Adjectives, terminated with Nouns
NP:
{<NBAR>}
{<NBAR><IN><NBAR>} # Above, connected with in/of/etc...
"""
chunker = nltk.RegexpParser(grammar) #This is the chunker for nltk.It chunks values accordingly
toks = nltk.word_tokenize(text) #This shall tokenize the words
postoks = nltk.tag.pos_tag(toks) #This shall perform tagging of words with their respective parts of speech
tree = chunker.parse(postoks) #It makes a tree of the tags and the words which are associated with that particular tag
terms = get_terms(tree)
return terms
def leaves(tree):
"""Finds NP (nounphrase) leaf nodes of a chunk tree."""
for subtree in tree.subtrees(filter = lambda t: t.node == 'NP'):
#print "SUBTREE:",subtree
yield subtree.leaves()
def normalise(word):
"""Normalises words to lowercase and stems and lemmatizes it.
Lemmatization and stemming of the words both are necessary in order to make sure that the words are properly indexed
"""
lemmatizer = nltk.WordNetLemmatizer()
stemmer = nltk.stem.porter.PorterStemmer()
word = word.lower() #THE WORD IS CONVERTED INTO LOWER CASE IN THIS STEP
word = stemmer.stem_word(word)
word = lemmatizer.lemmatize(word)
return word
from nltk.corpus import stopwords
stopwords = stopwords.words('english')
def acceptable_word(word):
"""Checks conditions for acceptable word: length, stopword.
A word is acceptable if
1. It is not a stopword
2. The length of the word is less than 40 characters
This is because, there is no point in storing a word more than 40chars long.This is because, user is not expected to
type words which are 40 chars long
"""
max_word_length = 40
accepted = bool(2 <= len(word) <= max_word_length and word.lower() not in stopwords)
return accepted
def get_terms(tree):
result = []
ALLOWED_LIST = ['CD','FW','JJ','JJR','JJS','NN','NNS','NNP','NNPS','VB','VBD','VBG','VBN','VBP','VBZ']
#print tree.leaves()
for leaf in tree.leaves():
#print leaf
#for (w,t) in leaf:
w = leaf[0]
t = leaf[1]
if acceptable_word(w) and t in ALLOWED_LIST:
term = normalise(w)
result.append(term)
return result
############################################################################################################################
######################################PRE PROCESSING FOR MAP REDUCE ########################################################
def remove_punctuation(s):
if not isinstance(s,unicode):
s = unicode(s)
translate_table = dict((ord(c),None) for c in string.punctuation)
return s.translate(translate_table)
def mapper(input_value):
input_value = remove_punctuation(input_value)
input_value_l = pre_process_for_map_reduce(input_value) #This performs pre_processing for map reduce
#This pre_processing is very important in order to save space
#This pre_processing function makes the map_reduce function slow
l = []
for i in input_value_l:
l.append([i,1])
return l
def reducer(intermediate_key,intermediate_value_list):
return(intermediate_key,sum(intermediate_value_list))
def map_reduce(x,mapper,reducer):
groups = {}
for key,group in itertools.groupby(sorted(mapper(x)),lambda x:x[0]):
groups[key] = list([y for x,y in group])
reduced_list = [reducer(intermediate_key,groups[intermediate_key]) for intermediate_key in groups ]
return reduced_list
"""
def perform_map_reduce(request,group_id):
#This function shall perform map reduce on all the objects which are present in the ToReduce() class Collection
all_instances = list(node_collection.collection.ToReduce.find({'required_for':'map_reduce_to_reduce'}))
for particular_instance in all_instances:
#print particular_instance._id,'\n'
particular_instance_id = particular_instance.id_of_document_to_reduce
#Now Pick up a node from the Node Collection class
orignal_node = node_collection.find_one({"_id":particular_instance_id})
map_reduce_node = node_collection.find_one({'required_for':'map_reduce_reduced','orignal_doc_id':particular_instance_id})
if map_reduce_node:
map_reduce_node.content_org = dict(map_reduce(orignal_node.content_org,mapper,reducer))
map_reduce_node.save()
else:
z = node_collection.collection.MyReduce()
z.content_org = dict(map_reduce(orignal_node.content_org,mapper,reducer))
z.orignal_doc_id = particular_instance_id
z.required_for = u'map_reduce_reduced'
z.save()
#After performing MapReduce that particular instance should be removed from the ToReduce() class collection
particular_instance.delete()
return HttpResponse("Map Reduce was performed successfully")
"""
def perform_map_reduce(request,group_id):
#connection.register([MyDocs])
#connection.register([ReducedDocs])
#connection.register([ToReduceDocs])
dltr=list(node_collection.find({'required_for':to_reduce_doc_requirement})) #document_list_to_reduce
for doc in dltr:
doc_id = doc.doc_id
#print "DOC ID LN 1504::",doc_id
#orignal_doc = node_collection.find_one({"_id": doc_id,'required_for': my_doc_requirement})
orignal_doc = node_collection.find_one({"_id": doc_id})
content_dict = dict(map_reduce(orignal_doc.content_org,mapper,reducer))
dord = node_collection.find_one({"orignal_id": doc_id, 'required_for': reduced_doc_requirement}) #doc of reduced docs
if dord:
dord.content=content_dict
dord.is_indexed = False
dord.save()
else:
new_doc = node_collection.collection.ReducedDocs()
new_doc.content = content_dict
new_doc.orignal_id = doc_id
new_doc.required_for = reduced_doc_requirement
new_doc.is_indexed = False
new_doc.save()
doc.delete()
#return render(request,'cf/thankYou.html',{})
return HttpResponse("Map Reduce was performed successfully")
############################################################################################################################
############################################################################################################################
################################################## POST PROCESSING FOR MAP REDUCE ############################################
#The code till above was to perform map_reduce
#The code below this will try and perform semantic search
#import scipy.sparse
import numpy
#import sparsesvd
from math import sqrt
def td_doc():
"""
#{'word':{'ObjectId':number_of_occurances,'ObjectId':number_of_occurances}}
This is the kind of dictionary which is required and will be created on the fly
Since we have already stored the map reduced documents, this function will be pretty fast.
The only thing which shall take time in our code is the MapReduce function
"""
#connection.register([IndexedWordList])
#connection.register([ReducedDocs])
#This is the list of documents which contains the indexed words
lod = node_collection.find({'required_for': indexed_word_list_requirement}) #list_of_documents_cursor
"""
What does indexing mean?
In our scenario,indexing simply means to store the number if occurances of a particular word in each and every document.
"""
mrd = node_collection.find({'required_for': reduced_doc_requirement}) #map_reduced_documents
mrdl = list(mrd)
for pwdl in lod:
#particulat_word_list
start_int = int(pwdl.word_start_id)
start_char = str(unichr(96+start_int)) #This tells what is the starting character of the word
wod = pwdl.words #word_object_dictionary
for pmrd in mrdl:
#particular_map_reduced_document
if not pmrd.is_indexed:
wd = pmrd.content
for i in wd:
if i.startswith(start_char):
if i not in wod:
wod[i] = {}
wod[i][str(pmrd.orignal_id)]=wd[i]
pwdl.words = wod
pwdl.save()
for pmrd in mrdl:
pmrd.is_indexed = True
pmrd.save()
def generate_big_dict():
#This function will generate a big dictionary i.e. it will simply go and combine all the dictionaries together
#connection.register([IndexedWordList])
lod = node_collection.find({'required_for': indexed_word_list_requirement})
lodl = list(lod)
prefs = {} #prefs ==> Preferences
for x in lodl:
if x.words:
prefs.update(x.words)
##print prefs
return prefs
####
#There are two kinds of similarity functions which we have defined and on whose basis recommendations are given
#If logic for semantic search needs to be changed then the only thing which is to be changed is this similarity function
####
def sim_distance(prefs,d1,d2):
#This fucntion simply finds the distance between two words. It works very well
si = {}
if d1 not in prefs.keys():
return 0 #NO RESULTS HAVE BEEN YET FOUND
for item in prefs[d1]: #This item is a dictionary containing book id and rating of that book for a user
##print prefs[person1]
if item in prefs[d2]:
si[item] = 1
if len(si) == 0:
return 0
#We know add the squares of all the differences
sum_of_squares = 0
for item in prefs[d1]:
##print prefs[person1]
if item in prefs[d2]:
##print prefs[person2]
##print "PERSON1 ITEM",item,prefs[d1][item]
##print "PERSON2 ITEM",item,prefs[d2][item]
##print "SUBTRACT",prefs[d1][item] - prefs[d2][item]
sum_of_squares += pow(prefs[d1][item] - prefs[d2][item],2)
##print sum_of_squares
#Tags
##print "SUM OF SQUARES :):)",sum_of_squares,(1.0/(1+sum_of_squares))
return (1.0/(1+sum_of_squares))
def sim_pearson(prefs,d1,d2):
#Theoretically --- The results of pearson similarity should be better, but practically the results are much worse
#Get the list of mutually rated items
si = {}
try:
for term in prefs[d1]:
if term in prefs[d2]:
si[term] = 1
except KeyError:
return 0
#sum calculations
n = len(si)
#sum of all preferences
sum1 = sum([prefs[d1][it] for it in si])
sum2 = sum([prefs[d2][it] for it in si])
#Sum of the squares
sum1Sq = sum([pow(prefs[d1][it],2) for it in si])
sum2Sq = sum([pow(prefs[d2][it],2) for it in si])
#Sum of the products
pSum = sum([prefs[d1][it] * prefs[d2][it] for it in si])
num = pSum - (sum1 * sum2/n)
den = sqrt((sum1Sq - pow(sum1,2)/n) * (sum2Sq - pow(sum2,2)/n))
if den == 0:
return 0
r = num/den
return r
def topMatches(prefs,document,n=5,similarity=sim_distance):
#This function returns the words which are closest to the word which are given to this function
scores = [(similarity(prefs,document,other),other) for other in prefs if other != document]
scores.sort()
scores.reverse()
return scores[0:n]
def recommend(prefs,term,similarity = sim_distance):
#This function returns the documents which will be closer to the given document
each_item_total = {}
similarity_total_for_each_item = {}
for other in prefs:
if other == term:
continue
else:
sim = similarity(prefs,term,other)
if sim==0:
continue
for single_ObjectId in prefs[other]:
if single_ObjectId in prefs[term]:
if single_ObjectId not in each_item_total:
each_item_total[single_ObjectId] = 0
each_item_total[single_ObjectId] += sim * prefs[other][single_ObjectId]
if single_ObjectId not in similarity_total_for_each_item:
similarity_total_for_each_item[single_ObjectId] = 0
similarity_total_for_each_item[single_ObjectId] += sim
rankings = []
for single_ObjectId,total_value in each_item_total.items():
rankings.append((total_value/similarity_total_for_each_item[single_ObjectId],single_ObjectId))
rankings.sort()
rankings.reverse()
return rankings
################## FUNCTIONS FOR CALLING/TESTING SEMANTIC SEARCH ########################################
# def generate_term_document_matrix(request,group_id):
# td_doc()
# return HttpResponse("Thank You")
# def cf_search(request, group_id):
# ins_objectid = ObjectId()
# if ins_objectid.is_valid(group_id) is False :
# group_ins = node_collection.find_one({'_type': "Group","name": group_id})
# auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
# if group_ins:
# group_id = str(group_ins._id)
# else:
# auth = node_collection.one({'_type': 'Author', 'name': unicode(request.user.username) })
# if auth :
# group_id = str(auth._id)
# else:
# pass
# return render(request,'ndf/semantic_search.html',{"groupid":group_id})
def get_nearby_words(request,group_id):
td_doc()
prefs = generate_big_dict()
search_text = str(request.GET['search_text']).strip()
search_text_l = search_text.split()
##print search_text_l
word_set = set()
ranking_list = []
stemmer = nltk.stem.porter.PorterStemmer()
for i in search_text_l:
score = topMatches(prefs,stemmer.stem_word(i.lower()),n=30,similarity=sim_distance)
for _,word in score:
word_set.add(word)
rankings = recommend(prefs,stemmer.stem_word(i.lower()),similarity = sim_distance)
ranking_list.extend(rankings[0:5])
# "5" -- It is the maximum number of documents which will be returned per word in search query
# Change this number to that number which you want i.e. the number of documents per word you want
final_ranking_list = sort_n_avg(ranking_list)
final_ranking_list.sort()
final_ranking_list.reverse()
result_array = []
for (relevance,each_id) in final_ranking_list:
obj = node_collection.find_one({"_id": ObjectId(each_id)}, {"name": 1, "_id": 1, "member_of": 1, "created_by": 1, "last_update": 1, "group_set": 1, "url": 1})
obj = addType(obj)
obj["relevance"]=relevance
result_array.append(obj)
result_array = json.dumps(result_array, cls=Encoder)
context_to_return = getRenderableContext(group_id)
context_to_return['search_results'] = result_array
context_to_return['search_type'] = SEMANTIC_SEARCH
return render(request, 'ndf/search_page.html', context_to_return)
def sort_n_avg(l):
"""
Helper Function for: get_nearby_words()
Parameters: List containing documents and their ratings
Return Value:List in which the ratings of the documents have been averaged out
INPUT:l = [(2,'alpha'),(3,'beta'),(1,'alpha'),(4,'alpha'),(5,'gamma'),(1,'alpha'),(2,'beta'),(3,'alpha')]
OUTPUT:[(2.2, 'alpha'), (2.5, 'beta'), (5.0, 'gamma')]
"""
visited_list = []
final_ranking_list = []
for (value,obj_id) in l:
if obj_id not in visited_list:
visited_list.append(obj_id)
i = 0
req_sum = 0
for (val,obj_id_added) in l:
if obj_id_added == obj_id:
i = i+1
req_sum += val
if i!=0:
final_ranking_list.append((float(req_sum)/i,obj_id))
return final_ranking_list
#################################################################################################################
|