Mastering M Programming Language Pattern Matching: A Comprehensive How-To Guide

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Introduction:

M programming language is a versatile language that can handle complex data manipulation. One of its powerful features is pattern matching, which allows developers to extract specific patterns in data, making data processing faster and more efficient. This comprehensive guide will explain pattern matching in M programming language, its syntax, and how to use it in real-world applications.

Section 1: Understanding M Programming Language Pattern Matching

1.1 What is Pattern Matching in M Programming Language? Pattern matching is a programming technique that allows developers to search and extract specific data patterns in a structured or unstructured data set. In M programming language, pattern matching is used to search for specific data patterns in lists, records, or tables.

1.2 How Does M Programming Language Pattern Matching Work? Pattern matching works by comparing the pattern specified by the programmer to the data set. When a match is found, the data that matches the pattern is extracted or manipulated in some way. This process can be performed recursively to extract nested data patterns.

1.3 Syntax of M Programming Language Pattern Matching The syntax of pattern matching in M programming language is similar to other programming languages that support pattern matching. Here's an example of pattern matching syntax in M programming language:

case <expression> of pattern_1: <statement>; pattern_2: <statement>; ... pattern_n: <statement>; otherwise: <statement>; endcase

In this example, case is the keyword used to start the pattern matching statement. <expression> is the data set to search, and pattern_1 to pattern_n are the patterns to match. otherwise is a pattern that matches any data that doesn't match any of the previous patterns.

1.4 Types of Patterns in M Programming Language M programming language supports several types of patterns, including:

• Literal patterns: Match specific values such as numbers or strings.
• Variable patterns: Match any value and assign it to a variable.
• Wildcard patterns: Matches any value but doesn't assign it to a variable.
• Constructor patterns: Matches complex data structures such as records, tables, and lists.

Section 2: Implementing M Programming Language Pattern Matching

2.1 Basic Examples of M Programming Language Pattern Matching Let's look at some basic examples of pattern matching in M programming language:

Example 1: Matching Literal Patterns

case 5 of 1: "One"; 2: "Two"; 3: "Three"; 4: "Four"; 5: "Five"; otherwise: "Unknown"; endcase

In this example, we're matching a literal pattern. If the value is 5, the statement "Five" is returned.

Example 2: Matching Variable Patterns

declare @x int = 5; case @x of 1: "One"; 2: "Two"; 3: "Three"; 4: "Four"; n: "Greater than 4"; endcase

In this example, we're matching a variable pattern. If the value of @x is greater than 4, the statement "Greater than 4" is returned.

2.2 Advanced Examples of M Programming Language Pattern Matching Here are some advanced examples of pattern matching in M programming language:

Example 1: Matching Constructor Patterns

declare @employee record set @employee = (10, "John", "Doe") case @employee of (id, first_name, last_name): "Employee Name: " + first_name + " " + last_name; endcase

In this example, we're matching a constructor pattern for a record type. The @employee record contains three fields: id, first_name, and last_name. The pattern (id, first_name, last_name) matches the record and extracts the first_name and last_name fields. The resulting statement would be "Employee Name: John Doe".

Example 2: Matching Nested Patterns

declare @employees table (id int, first_name nvarchar(50), last_name nvarchar(50)) insert into @employees values (1, "John", "Doe") insert into @employees values (2, "Jane", "Doe") insert into @employees values (3, "Bob", "Smith") case @employees of []: "No employees found"; [(id, "John", last_name)]: "Employee Name: John " + last_name; [(id, first_name, last_name), (id, "Jane", last_name2)]: "Multiple Matches Found"; [(id, first_name, last_name)]: "Employee Name: " + first_name + " " + last_name; endcase

In this example, we're matching a nested pattern for a table type. The @employees table contains three records, each with an id, first_name, and last_name field. We're searching for specific patterns in the table. The first pattern [] matches an empty table. The second pattern [(id, "John", last_name)] matches a table with one record where the first name is "John". The third pattern [(id, first_name, last_name), (id, "Jane", last_name2)] matches a table with two records where the first name is "John" and "Jane". The fourth pattern [(id, first_name, last_name)] matches a table with one or more records and extracts the first and last name fields.

Section 3: Use Cases of M Programming Language Pattern Matching

3.1 Use Case 1: Extracting Data from Complex Data Structures Pattern matching in M programming language can be used to extract data from complex data structures such as records and tables. This makes it easier to manipulate and analyze data in real-world applications.

3.2 Use Case 2: Data Validation and Error Handling Pattern matching can be used for data validation and error handling in M programming language. By matching patterns and handling exceptions, developers can ensure that their code is robust and error-free.

Conclusion: Pattern matching is a powerful feature of M programming language that allows developers to search and extract specific data patterns in a structured or unstructured data set. This comprehensive guide has provided an overview of pattern matching in M programming language, its syntax, and examples of how it can be used in real-world applications. By mastering pattern matching, developers can enhance their skills and develop more efficient and effective M programs.

Here are some course suggestions from JBI Training related to M programming language:

1. Power BI - Power Query & M training course Use Advanced functionality in Power Query to import files, cleanse data, create functions in M Language.

2. Power BI - Beyond the Basics training course A "World Class" course - Learn to maximise Power BI's features - Create outstanding Visuals and complex Calculations in DAX

Here are some official documentation 

1. Microsoft's official documentation on DAX: https://docs.microsoft.com/en-us/dax/

2. Microsoft's official documentation on Power BI: https://docs.microsoft.com/en-us/power-bi/

3. Power BI community forums: https://community.powerbi.com/

4. Power BI YouTube channel: https://www.youtube.com/user/mspowerbi

5. DAX Patterns website: https://www.daxpatterns.com/