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In computer programming, lazy initialization is the tactic of delaying the creation of an object, the calculation of a value, or some other expensive process until the first time it is needed.
Here we use the 256 possible values of a byte. """ self. common_dictionary = common_dictionary def encode (self, plain_text: str)-> Generator [int]: # Changing the common dictionary is a bad idea. Make a copy. dictionary = list ( self . common_dictionary ) # Read in each character for c in plain_text . encode ( "latin-1" ): # Change to bytes ...
In computing, a hash table is a data structure that implements an associative array, also called a dictionary or simply map; an associative array is an abstract data type that maps keys to values. [2] A hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired value ...
find the value (if any) that is bound to a given key. The argument to this operation is the key, and the value is returned from the operation. If no value is found, some lookup functions raise an exception, while others return a default value (such as zero, null, or a specific value passed to the constructor).
When being inserted to a dictionary, the value object receives a retain message to increase its reference count. The value object will receive the release message when it will be deleted from the dictionary (either explicitly or by adding to the dictionary a different object with the same key).
40 indicates a 4 GB − 1 dictionary size; Even values less than 40 indicate a 2 v/2 + 12 bytes dictionary size; Odd values less than 40 indicate a 3×2 (v − 1)/2 + 11 bytes dictionary size; Values higher than 40 are invalid; LZMA2 data consists of packets starting with a control byte, with the following values: 0 denotes the end of the file
RDFLib is a Python library for working with RDF, [2] a simple yet powerful language for representing information. This library contains parsers/serializers for almost all of the known RDF serializations, such as RDF/XML, Turtle, N-Triples, & JSON-LD, many of which are now supported in their updated form (e.g. Turtle 1.1).
In all versions of Python, boolean operators treat zero values or empty values such as "", 0, None, 0.0, [], and {} as false, while in general treating non-empty, non-zero values as true. The boolean values True and False were added to the language in Python 2.2.1 as constants (subclassed from 1 and 0 ) and were changed to be full blown ...