PermissiveResearch

by leverdeterre

leverdeterre / PermissiveResearch

An iOS search engine that allows mistakes in the searched element.

412 Stars 35 Forks Last release: over 6 years ago (0.1.0) Other 41 Commits 3 Releases

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http://leverdeterre.github.io

Twitter License MIT Cocoapods

PermissiveResearch

An iOS search engine that allows mistakes in the searched element in huge data. Many developpers would have executed a fectch request on a CoreData database or a predicate to filter on a NSArray.

Image

PermissiveResearch is a alternative to simplify the search step. Advantages : - No more problems with CoreData (context/thread), - Performances, - 100% resusable for each projects that need to perform analysis in huge data, - Search algorithm are easy customizable, - 3 algorithms already implemented,

Performances (on iphone4, searchig in 5000 objects 4 properties)

| Type of search | time (ms) | data structure | | ------------- |:-------------:| -------------| | Exact search | 200 | Using predicates | | Exact search | 2800 | Using PermissiveResearch (ExactScoringOperation) | | Exact search | 100 | Using PermissiveResearch (HeuristicScoringOperation) | | Exact search | 700 | Using PermissiveResearch (HeurexactScoringOperation) | | Tolerated search | impossible.. | Using predicates | | Tolerated search | 2800 | Using PermissiveResearch (ExactScoringOperation) | | Tolerated search | 100 | Using PermissiveResearch (HeuristicScoringOperation) | | Tolerated search | 700 | Using PermissiveResearch (HeurexactScoringOperation) |

  • ExactScoringOperation : Make a complex and total analysis,
  • HeuristicScoringOperation : Scan using fragments (default size 3),
  • HeurexactScoringOperation : Scan using fragments (default size 3), then make a complex and total analysis of the best pre-selected objects.

Algorithms

It's a custom implementation of the Smith-Waterman algorithm. The purpose of the algorithm is to obtain the optimum local alignment. A similarity matrix is use to tolerate errors.

Shared instance

[[PermissiveResearchDatabase sharedDatabase] setDatasource:self];

Datasource methods to fill your search database

-(void)rebuildDatabase
- (void)addObject:(id)obj forKey:(NSString *)key;
- (void)addObjects:(NSArray *)obj forKey:(NSString *)key;
- (void)addObjects:(NSArray *)objs forKeys:(NSArray *)keys;
- (void)addObjects:(NSArray *)objs forKeyPaths:(NSArray *)KeyPaths;

  • (void)addManagedObject:(NSManagedObject *)obj forKey:(NSString *)key;

  • (void)addManagedObjects:(NSArray *)objs forKey:(NSString *)key;

  • (void)addManagedObjects:(NSArray *)objs forKeys:(NSArray *)keys;

  • (void)addManagedObjects:(NSArray *)objs forKeyPaths:(NSArray *)KeyPaths;

Example :

///PermissiveResearchDatabase datasource
  • (void)rebuildDatabase { NSString *jsonPath = [[NSBundle mainBundle] pathForResource:@"data5000"

                                                        ofType:@"json"];

    NSData *data = [NSData dataWithContentsOfFile:jsonPath]; NSError *error = nil; id json = [NSJSONSerialization JSONObjectWithData:data

                                             options:kNilOptions
                                               error:&error];

    [[PermissiveResearchDatabase sharedDatabase] addObjects:json forKeyPaths:@[@"name",@"gender",@"company",@"email"]]; self.searchedList = json; }

  • Datasource method to customize scoring methods

    -(NSInteger)customCostForEvent:(ScoringEvent)event
    

    Example (default values) : ```objective-c

  • (NSInteger)customCostForEvent:(ScoringEvent)event { switch (event) {

       case ScoringEventPerfectMatch:
           return 2;
           break;</p>
        case ScoringEventNotPerfectMatchKeyboardAnalyseHelp:
           return 1;
           break;
    
       case ScoringEventNotPerfectBecauseOfAccents:
           return 2;
           break;
    
       case ScoringEventLetterAddition:
           return -1;
           break;
    
       default:
           break;
    }
    
    
  • return NSNotFound;

    } ```

    Easy search operation using PermissiveResearch delegate

    [[PermissiveResearchDatabase sharedDatabase] setDelegate:self];
    [[PermissiveResearchDatabase sharedDatabase] searchString:searchedString withOperation:ScoringOperationTypeExact];
    
    

    #pragma mark PermissiveResearchDelegate

    -(void)searchCompletedWithResults:(NSArray *)results { dispatch_async(dispatch_get_main_queue(), ^{ self.findedElements = results; [self.tableView reloadData]; }); }

    Create your first search operation

        [[ScoringOperationQueue mainQueue] cancelAllOperations]
        HeuristicScoringOperation *ope = [[HeuristicScoringOperation alloc] init];
        ope.searchedString = searchedString;
    
    
    SearchCompletionBlock block = ^(NSArray *results) {
        dispatch_async(dispatch_get_main_queue(), ^{
            self.findedElements = results;
            NSLog(@"finded elements %@", results);
        });
    };
    
    [ope setCustomCompletionBlock:block];
    [[ScoringOperationQueue mainQueue] addOperation:ope];

    Actualy 3 operations are available, usage depends on the performance you need.

    Algorithms complexities are very differents. HeuristicScoringOperation < HeurexactScoringOperation << ExactScoringOperation

    ExactScoringOperation
    HeuristicScoringOperation
    HeurexactScoringOperation
    

    TODO

    • Tolerate keyboard errors, very proximal letters can be tolerate.

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