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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 ...
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 ...
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.
CRUD functionality can for example be implemented with document databases, object databases, XML databases, text files, or binary files. Some big data systems do not implement UPDATE, but have only a timestamped INSERT (journaling), storing a completely new version of the object each time.
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 .
In write ahead logging, durability is guaranteed by writing the prospective change to a persistent log before changing the database. That allows the database to return to a consistent state in the event of a crash. In shadowing, updates are applied to a partial copy of the database, and the new copy is activated when the transaction commits.
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.
In the field of programming a data transfer object (DTO [1] [2]) is an object that carries data between processes. The motivation for its use is that communication between processes is usually done resorting to remote interfaces (e.g., web services), where each call is an expensive operation. [ 2 ]