| Published | 2022-05-10 |
| Platform | Udemy |
| Number of Students | 29 |
| Price | $84.99 |
| Instructors |
Uplatz Training
|
| Subjects |
Learn Mulesoft DataWeave functional programming language. Write transformations using functions, variables, & operators.
A warm welcome to the Functional Programming with DataWeave course by Uplatz.
DataWeave is one of the easy-to-use and efficient functional programming languages. DataWeave provides features and functionality for transforming data. DataWeave also serves as an expression language to configure components and connectors. In DataWeave there are multiple modules that can be imported and applied and can perform a huge variety of operations such as string manipulation, URL encoding, date formatting, etc. DataWeave facilitates performing use cases where data needs to be read and parsed, to be formatted and transformed, finally to be sent as an output in an entirely different format. Examples include transforming CSVs into JSONs, XML into JSON or CSV, and the like. The beauty of DataWeave functional programming is that the developers can actually focus on building the transformation logic rather than devoting time on syntax, formats and parsing efforts.
What is Functional Programming?
Functional Programming is essentially the process of building software by composing pure functions, avoiding shared state, mutable data, and side-effects. Functional programming is declarative rather than imperative, and application state flows through pure functions. Functional programming is based on mathematical functions. A few of the popular functional programming languages include: DataWeave, Lisp, Python (not in strict sense), Erlang, Haskell, Clojure, etc.
DataWeave - Course Syllabus
DATAWEAVE (DW) INTRODUCTION
EXAMPLES OF DATAWEAVE
DW OPERATORS
MERGE FIELD FROM DIFFERENT OBJECT OPERATORS AND UPDATE OPERATOR
DW VARIABLES CONDITIONS AND FUNTIONSVARS
FLOW CONTROL
DW PATTERN MATCHING
DW FUNCTIONS
MAP-AND-PLUCK-OPERATOR
MAP-AND-MAPOBJECT
FLATTEN FUNCTION
PLUCK OPERATOR
DW SELECTORS
JOINBY AND SPLITBY
DATAWEAVE FUNCTION CHEAT SHEET
DATAWEAVE OPERATORS
TYPES OF ERRORS AND ESC CHARACTERS
++ on DATES
DATAWEAVE BASIC TRANSFORMATION
DW DATA TYPES
SINGLE MULTI SELECTORS EXAMPLE
DW FILTER OPERATOR
ATTRIBUTE AND DESCENDANT SELECTOR
REDUCE AND ORDERBY FUNCTIONS
LOGICAL AND APPEND AND PREPEND OPERATORS
INDEXOF, KEYSOF, MINBY, MAXBY, REPLACE IN DW
SPLITAT, SPLITWHERE, TAKEWHILE, SUMOF
GEOMETRIC AND TIME OPERATIONS
GLOBAL VARIABLES AND DW FUNCTIONS
FUNCTIONS OVERLOADING AND LAMBDA EXPRESSIONS
HANDLING TRANSFORMATIONS IN DW
DEFAULT VALUES IN DATAWEAVE
RENAME JSON KEYS
TRANSFORM NESTED STRUCTURES TO FLAT
DATA ORGANIZATION USING DATAWEAVE