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Many languages allow generic copying by one or either strategy, defining either one copy operation or separate shallow copy and deep copy operations. [1] Note that even shallower is to use a reference to the existing object A, in which case there is no new object, only a new reference. The terminology of shallow copy and deep copy dates to ...
FlatBuffers can be used in software written in C++, C#, C, Go, Java, JavaScript, Kotlin, Lobster, Lua, PHP, Python, Rust, Swift, and TypeScript. The schema compiler runs on Android , Microsoft Windows , macOS , and Linux , [ 3 ] but games and other programs use FlatBuffers for serialization work on many other operating systems as well ...
In computer programming, array slicing is an operation that extracts a subset of elements from an array and packages them as another array, possibly in a different dimension from the original. Common examples of array slicing are extracting a substring from a string of characters, the " ell " in "h ell o", extracting a row or column from a two ...
array[i] means element number i, 0-based, of array which is translated into *(array + i). The last example is how to access the contents of array. Breaking it down: array + i is the memory location of the (i) th element of array, starting at i=0; *(array + i) takes that memory address and dereferences it to access the value.
Flow diagram. In computing, serialization (or serialisation, also referred to as pickling in Python) is the process of translating a data structure or object state into a format that can be stored (e.g. files in secondary storage devices, data buffers in primary storage devices) or transmitted (e.g. data streams over computer networks) and reconstructed later (possibly in a different computer ...
In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine. For example, if x is an array, then y = sin (x) will result in an array y whose elements are sine of the corresponding elements of the array x. Vectorized index operations are also supported.
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})