Package: huntela
HuntelaHuntelais a savvy search module that's an alternative to the defaultfiltermethod. It offers a range of powerful search functions, including fuzzy search, binary search, and searches for least/most frequent items in a list.>>>importhuntela>>>>>>huntela.fuzzy_search(term='app',items=['app','paper','hello','world'])[{'confidence':1,'index':0,'value':'app'},{'confidence':0.6,'index':1,'value':'paper'}]>>>>>>huntela.binary_search(term='a',items=['a','b','c']){'confidence':1,'index':0,'value':'a'}>>>>>>huntela.search_for_least_frequent_items(size=1,['a','b','a','e','a','e'])[{'confidence':1,'index':[1],'value':'b'}]>>>>>>huntela.search_for_most_frequent_items(size=2,['a','b','a','e','a','e'])[{'confidence':1,'value':'a','index':[0,2,4]},{'confidence':1,'value':'e','index':[3,5]}]With a variety of algorithms to choose from, finding what you're looking for has never been easier.From binary search to linear search and more, Huntela has everything you need to
quickly and efficiently search through your data. With a simple, intuitive interface
and lightning-fast performance, Huntela is the go-to package for anyone who needs to search through data.Whether you're a data scientist, engineer, or  developer, Huntela will help you find what you need.InstallationHuntela officially supports Python 3.9 upwards.Huntela is available on PyPi and it can be installed usingpippython-mpipinstallhuntelaReferenceParametersEach of the search methods take in three (3) parameters.term: The term being searched for.items: The items parameter could then be a iterable of the supported term types.key(Optional): Only to be specified if thetermis adict. In which case, thekeywill be used to pick the corresponding values from the list ofitems.Supported TypesTermThe term being searched for could be one of the following supported types:intfloatstrdict[str, Any]ItemsThe items parameter could then be a iterable of the supported term types. That is,List[int]List[float]List[str]List[Dict[str, str]]ResultsEach search result is adictwhich contains the following item:confidence: A number from0.0to1.0that indicates the degree of relevance of the search match.value: The specific item that matched the search criteria.index: The position, or a list of positions where the search term was found.Methodsfuzzy_search(term, items, key=None) -> List[Result]: Searches a list of items for a given search term and returns a list of results which exactly orcloselymatch the search term.>>>huntela.fuzzy_search(term='app',items=['app','paper','hello','world'])[{'confidence':1,'index':0,'value':'app'},{'confidence':0.6,'index':1,'value':'paper'}]binary_search(term, items, key=None) -> List[Result]: Performs a binary search on a list to find a target value.>>>huntela.binary_search(term='Alex',items=[{'name':'Alex'},{'name':'Mike'},{'name':'John'}],key='name'){'confidence':1,'index':0,'value':'Ade'}search_for_least_frequent_items: Finds the k least frequent item(s) in a list.>>>search_for_least_frequent_items(size,items)[{'confidence':1,'index':[0],'value':1},{'confidence':1,'index':[2,3],'value':3}]search_for_most_frequent_items: Finds the k most frequent item(s) in a list.>>>search_for_most_frequent_items(2,[1,2,2,3,3,3])[{'confidence':1,'index':[3,4,5],'value':3},{'confidence':1,'index':[1,2],'value':2}]