Welcome to another lesson on parsing tables from text files with C#. In today's digital world, data is frequently stored in tabular formats, reminiscent of spreadsheets. Text files provide a straightforward means to store this data when handling simple, organized datasets. Parsing, which involves reading and translating this data into usable formats, is an essential skill for data manipulation.
Imagine scenarios where you need to process configuration files, logs, or other reports exported from systems that store data in text file formats. By the end of this lesson, you will be equipped with the knowledge to parse such data into a structured format, facilitating easy manipulation in C#.
Text files frequently store tabular data using simple delimiters like spaces between values. Consider the following example of a data.txt
file:
Plain text1Name Age Occupation 2John 28 Engineer 3Alice 34 Doctor 4Bob 23 Artist
In this file, each line represents a row in a table, and each value within a line is separated by a space, forming distinct columns. The first line acts as a header, describing the data in the lines that follow.
To effectively parse these lines into a structured format, we'll use a Person
class:
C#1class Person 2{ 3 public string? Name { get; set; } 4 public int? Age { get; set; } 5 public string? Occupation { get; set; } 6}
The Person
class will help us organize the extracted data, allowing us to map each piece of information to the respective properties: Name
, Age
, and Occupation
.
To begin parsing the table data, we first need to read the text file. The File.ReadAllLines
method from the System.IO
namespace provides an efficient way to accomplish this, allowing us to easily access all lines in the file at once.
C#1// Read all lines from the text file, excluding the header line 2var lines = File.ReadAllLines("data.txt").Skip(1);
In this snippet:
File.ReadAllLines("data.txt")
retrieves all lines from the specified file.- By applying
Skip(1)
, we exclude the first line, which contains the header, from further processing.
This approach sets a solid foundation for capturing all the rows of data that we need to parse, focusing only on the meaningful data entries.
Once the lines are retrieved, the next move is to convert each line into a list of values, corresponding to the columns.
C#1var people = new List<Person>(); 2 3// Split each line by space and map it to a Person object 4foreach (var line in lines) 5{ 6 var parts = line.Split(' '); // Assuming space-separated values 7 8 people.Add(new Person 9 { 10 Name = parts[0], 11 Age = int.Parse(parts[1]), 12 Occupation = parts[2] 13 }); 14}
Explanation:
var people = new List<Person>()
initializes a list to storePerson
objects.line.Split(' ')
divides the line into components based on the space delimiter.people.Add(new Person { ... })
adds each parsed person to the list.
Lastly, to verify the parsed data, we should print it out in a structured manner.
C#1// Output the list of people to verify the result 2Console.WriteLine("Parsed People Data:"); 3foreach (var person in people) 4{ 5 Console.WriteLine($"Name: {person.Name}, Age: {person.Age}, Occupation: {person.Occupation}"); 6}
In this segment, a foreach
loop iterates through each Person
in the people
list, and Console.WriteLine
is used to print each person's information.
The output confirms that each Person
object is correctly populated with the corresponding data fields:
Plain text1Parsed People Data: 2Name: John, Age: 28, Occupation: Engineer 3Name: Alice, Age: 34, Occupation: Doctor 4Name: Bob, Age: 23, Occupation: Artist
In this lesson, we've explored the fundamental elements of parsing a table from a text file using C#. The key takeaways include understanding how to:
- Read a text file using
File.ReadAllLines
. - Utilize the
Split()
method to divide lines into components. - Structure the data using collections like
List<Person>
in C#.
These skills are crucial for handling straightforward tabular data formats efficiently. As you progress to practice exercises, I encourage you to experiment with different delimiters and file structures to reinforce these concepts. Use these exercises as an opportunity to experiment and solidify your knowledge.