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An Item in DynamoDB is a set of attributes that can be uniquely identified in a Table. An Attribute is an atomic data entity that in itself is a Key-Value pair. The Key is always of String type, while the value can be of one of multiple data types. An Item is uniquely identified in a Table using a subset of its attributes called Keys. [7]
Dynamo is a set of techniques that together can form a highly available key-value structured storage system [1] or a distributed data store. [1] It has properties of both databases and distributed hash tables (DHTs).
2021: AWS CDK v2 is released and consolidates the AWS Construct Library into a single package called aws-cdk-lib, streamlining usage and updates, ensuring stable APIs, and offering developer productivity improvements such as CDK Watch, a refreshed API Reference, and a new assertions library for automated unit testing in all CDK-supported languages.
You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.
AWS Lambda is an event-driven, serverless Function as a Service (FaaS) provided by Amazon as a part of Amazon Web Services. It is designed to enable developers to run code without provisioning or managing servers.
CPython is the reference implementation of the Python programming language. Written in C and Python, CPython is the default and most widely used implementation of the Python language. CPython can be defined as both an interpreter and a compiler as it compiles Python code into bytecode before interpreting it.
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...