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A lazy copy is an implementation of a deep copy. When initially copying an object, a (fast) shallow copy is used. A counter is also used to track how many objects share the data. When the program wants to modify an object, it can determine if the data is shared (by examining the counter) and can do a deep copy if needed.
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 ...
SQLAlchemy offers tools for database schema generation, querying, and object-relational mapping. Key features include: A comprehensive embedded domain-specific language for SQL in Python called "SQLAlchemy Core" that provides means to construct and execute SQL queries. A powerful ORM that allows the mapping of Python classes to database tables.
ZODB stores Python objects using an extended version of Python's built-in object persistence (pickle). A ZODB database has a single root object (normally a dictionary), which is the only object directly made accessible by the database. All other objects stored in the database are reached through the root object. Objects referenced by an object ...
In computer programming, create, read, update, and delete (CRUD) are the four basic operations (actions) of persistent storage. [1] CRUD is also sometimes used to describe user interface conventions that facilitate viewing, searching, and changing information using computer-based forms and reports.
Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
Python supports most object oriented programming (OOP) techniques. It allows polymorphism, not only within a class hierarchy but also by duck typing. Any object can be used for any type, and it will work so long as it has the proper methods and attributes. And everything in Python is an object, including classes, functions, numbers and modules.
Code reuse may be achieved different ways depending on a complexity of a programming language chosen and range from a lower-level approaches like code copy-pasting (e.g. via snippets), [3] simple functions (procedures or subroutines) or a bunch of objects or functions organized into modules (e.g. libraries) [4] [2]: 7 or custom namespaces, and ...