Working with Constraints in SQLite: A Deep Dive

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In this article, we will explore the world of constraints in SQLite. We’ll start by examining a common use case where a check constraint is applied to a string column, and then dive into some nuances of working with regular expressions and wildcards.

Understanding Check Constraints in SQLite

A check constraint in SQLite is used to enforce a specific condition on a column or set of columns. When you create a table with a check constraint, the database engine verifies that every row inserted into that table conforms to the specified condition.

In our example, we have a patient table with a column named CONTACT. We’ve applied a check constraint to ensure that all contact numbers are in the format (000)0000000.

CREATE TABLE patient (
    USERNUM INT PRIMARY KEY,
    CONTACT varchar(15) CONSTRAINT check_contact CHECK (contact LIKE '%([0-9]*3)[0-9]*10%'),
    age int CONSTRAINT check_age CHECK (age > 0 AND age <= 100),
    location varchar(50)
);

However, we soon realize that our initial approach is not sufficient. We can’t insert records with contact numbers that don’t match the pattern.

Alternative Approach Using SUBSTRING

As an alternative, we decide to use a different approach. Instead of using the LIKE operator directly, we break down the contact number into individual parts and apply separate checks for each part.

ALTER TABLE patient ADD CONTACT varchar(15) CONSTRAINT ch_contact CHECK (
    SUBSTRING(contact, 1, 1) = '(' AND
    SUBSTRING(contact, 5, 1) = ')' AND
    SUBSTRING(contact, 2, 4) LIKE '[0-9]' AND
    SUBSTRING(contact, 6, 15) LIKE '[0-9]'
);

However, we soon discover that this approach doesn’t allow us to insert records with contact numbers in the correct format.

Using the GLOB Operator

One possible solution is to use the GLOB operator. This operator allows us to match patterns in string data. We can use it to define a pattern that matches our specific requirements.

CONTACT varchar(15) CONSTRAINT check_contact CHECK (contact GLOB '([0-9][0-9][0-9])[0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9]')

The GLOB operator works by matching the pattern against the string data. In our case, we define a pattern that starts with three digits ([0-9]) followed by a group of nine digits ([0-9]{10}). This ensures that only contact numbers in the format (000)0000000 are allowed.

How GLOB Works

So, let’s dive deeper into how GLOB works. The GLOB operator uses regular expressions to match patterns against string data.

Regular expressions are a powerful tool for matching patterns in text data. They provide a way to describe complex patterns using special characters and syntax.

In the context of GLOB, we use regular expression syntax to define our pattern. Here’s a breakdown of how it works:

• ^ matches the start of the string.
• [0-9] matches any single digit (0-9).
• \d{10} matches exactly 10 digits.
• $ matches the end of the string.

By combining these elements, we define a pattern that ensures only contact numbers in the format (000)0000000 are allowed.

Best Practices for Working with Regular Expressions

While GLOB is an effective tool for working with regular expressions, it’s essential to use it judiciously. Here are some best practices to keep in mind:

• Test thoroughly: Make sure your pattern works as expected by testing it against various inputs.
• Keep it simple: Complex patterns can be difficult to read and maintain. Break down complex patterns into simpler ones when possible.
• Use anchors: Use anchors (^ and $) to ensure that the entire string matches the pattern.

Conclusion

In this article, we explored working with constraints in SQLite, focusing on using regular expressions and wildcards. We examined a common use case where a check constraint is applied to a string column and then dove into some nuances of working with GLOB and regular expressions.

By following best practices for working with regular expressions and using tools like GLOB, you can create robust and efficient constraints in your SQLite database.

Last modified on 2024-03-01