F# 4.0 Design Patterns by Gene Belitski
Author:Gene Belitski [Belitski, Gene]
Language: eng
Format: epub, mobi, pdf
Tags: Computers & Technology, Programming Languages, Programming, Functional Programming, F#, Design
Amazon: B01CGKAINU
Publisher: Packt Publishing
Published: 2016-11-28T23:00:00+00:00
Note that the binding for twoByTwo did not bring any calculations to life, but it wrapped the future calculation into the Lazy type. Then, the first twoByTwo.Force() function performed the wrapped calculation, so the side-effect popped up. Finally, any consequent twoByTwo.Force() function will just repeatedly bring the result of the very first calculation without any side-effects.
The lazy evaluation pattern has its own niche in enterprise F# development. I often use it when in need of a resource that's probably being initialized; if this need really materializes, I want it to happen only once. For example, we can consider reading the Production environment configuration settings from Azure KeyVault when a service runs in the Production environment while using some other configuration information carrier in other environments, for example, environment variables pointing to data stubs.
Download
F# 4.0 Design Patterns by Gene Belitski.mobi
F# 4.0 Design Patterns by Gene Belitski.pdf
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.
Access | Data Mining |
Data Modeling & Design | Data Processing |
Data Warehousing | MySQL |
Oracle | Other Databases |
Relational Databases | SQL |
Algorithms of the Intelligent Web by Haralambos Marmanis;Dmitry Babenko(8310)
Azure Data and AI Architect Handbook by Olivier Mertens & Breght Van Baelen(6826)
Building Statistical Models in Python by Huy Hoang Nguyen & Paul N Adams & Stuart J Miller(6805)
Serverless Machine Learning with Amazon Redshift ML by Debu Panda & Phil Bates & Bhanu Pittampally & Sumeet Joshi(6690)
Data Wrangling on AWS by Navnit Shukla | Sankar M | Sam Palani(6479)
Driving Data Quality with Data Contracts by Andrew Jones(6431)
Machine Learning Model Serving Patterns and Best Practices by Md Johirul Islam(6178)
Learning SQL by Alan Beaulieu(6006)
Weapons of Math Destruction by Cathy O'Neil(5800)
Big Data Analysis with Python by Ivan Marin(5405)
Data Engineering with dbt by Roberto Zagni(4413)
Solidity Programming Essentials by Ritesh Modi(4061)
Time Series Analysis with Python Cookbook by Tarek A. Atwan(3921)
Pandas Cookbook by Theodore Petrou(3626)
Blockchain Basics by Daniel Drescher(3308)
Hands-On Machine Learning for Algorithmic Trading by Stefan Jansen(2914)
Feature Store for Machine Learning by Jayanth Kumar M J(2822)
Learn T-SQL Querying by Pam Lahoud & Pedro Lopes(2804)
Mastering Python for Finance by Unknown(2748)
