How to Use File-Scoped Namespaces in C# for Cleaner Code

In C#, you can format an integer with commas (thousands separator) using ToString with a format specifier.

int number = 1234567;
string formattedNumber = number.ToString("N0"); // "1,234,567"
Console.WriteLine(formattedNumber);

Explanation:

"N0": The "N" format specifier stands for Number, and "0" means no decimal places. The output depends on the culture settings, so in regions where , is the decimal separator, you might get 1.234.567.

Alternative:

You can also specify culture explicitly if you need a specific format:

using System.Globalization;

int number = 1234567;
string formattedNumber = number.ToString("N0", CultureInfo.InvariantCulture);
Console.WriteLine(formattedNumber); // "1,234,567"

Reading a file line by line is useful when handling large files without loading everything into memory at once.

✅ Best Practice: Use File.ReadLines() which is more memory efficient.

Example

foreach (string line in File.ReadLines("file.txt"))
{
    Console.WriteLine(line);
}

Why use ReadLines()?

Reads one line at a time, reducing overall memory usage. Ideal for large files (e.g., logs, CSVs).

Alternative: Use StreamReader (More Control)

For scenarios where you need custom processing while reading the contents of the file:

using (StreamReader reader = new StreamReader("file.txt"))
{
    string? line;
    while ((line = reader.ReadLine()) != null)
    {
        Console.WriteLine(line);
    }
}

Why use StreamReader?

Lets you handle exceptions, encoding, and buffering. Supports custom processing (e.g., search for a keyword while reading).

When to Use ReadAllLines()? If you need all lines at once, use:

string[] lines = File.ReadAllLines("file.txt");

Caution: Loads the entire file into memory—avoid for large files!

When working with SQL Server, you may often need to count the number of unique values in a specific column. This is useful for analyzing data, detecting duplicates, and understanding dataset distributions.

Using COUNT(DISTINCT column_name)

To count the number of unique values in a column, SQL Server provides the COUNT(DISTINCT column_name) function. Here’s a simple example:

SELECT COUNT(DISTINCT column_name) AS distinct_count
FROM table_name;

This query will return the number of unique values in column_name.

Counting Distinct Values Across Multiple Columns

If you need to count distinct combinations of multiple columns, you can use a subquery:

SELECT COUNT(*) AS distinct_count
FROM (SELECT DISTINCT column1, column2 FROM table_name) AS subquery;

This approach ensures that only unique pairs of column1 and column2 are counted.

Why Use COUNT DISTINCT?

• Helps in identifying unique entries in a dataset.
• Useful for reporting and analytics.
• Efficient way to check for duplicates.

By leveraging COUNT(DISTINCT column_name), you can efficiently analyze your database and extract meaningful insights. Happy querying!