Delim Converter

Convert lists between comma, pipe, tab, and custom delimiters with advanced options.

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Quotes

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Delimiter

SQL Value Generator — Build a SQL IN Clause from a List

The SQL Value Generator wraps a list of values in quotes and parentheses to build a ready-to-paste SQL IN (...) clause. It's built for analysts and developers who need to generate a SQL IN clause from a list of IDs, names, or codes without manually quoting and comma-separating hundreds of values by hand. Paste your list and get a properly formatted SQL fragment instantly.

⚡ Key Takeaways

Wraps a list of values in quotes and commas inside parentheses automatically.
Produces a ready-to-paste SQL IN (...) clause — no manual quoting required.
Quotes every value by default, correct for text; remove quotes manually for numeric columns.
Handles lists of any size instantly, avoiding manual comma-placement errors.

What, Who, When & Why

What it's for	Wraps a list of values in quotes and parentheses to build a ready-to-paste SQL IN (...) clause.
Who it's for	Analysts and developers who need to filter a query against a known list of IDs, names, or codes.
When to use it	Whenever you're about to write a WHERE column IN (...) clause and have more than a couple of values to quote.
Why it's needed	Manually quoting and comma-separating hundreds of values is slow, and a single missing quote or comma breaks the whole query.
Best way to use it	Remove duplicates from your source list first for a cleaner, easier-to-review result, even though duplicates don't break the query itself.

How to Use the SQL Value Generator

Paste your list into the Input box, one value per line.
The tool automatically wraps each value in quotes and joins them with commas inside parentheses.
Copy the result and paste it directly into your SQL query's WHERE column IN (...) clause.

Example

Given a list of customer names:

Alice
Bob
Charlie

The SQL Value Generator produces:

('Alice','Bob','Charlie')

Drop this directly into a query: SELECT * FROM customers WHERE name IN ('Alice','Bob','Charlie'); — no manual quoting or comma placement required, even for lists of hundreds of values, where manually typing each quote and comma would be both slow and highly error-prone.

Key Features

Automatically quotes and comma-separates every value from your list.
Wraps the full result in parentheses, ready to paste into a SQL IN clause.
Handles lists of any size instantly, without manual formatting.
One-click copy of the generated SQL fragment.

Practical Use Cases

Filtering by a known list of IDs: quickly build a WHERE clause to pull records matching a specific set of IDs.
Ad hoc data investigations: paste a list of flagged accounts or order numbers to investigate in a query.
Building test queries: generate a quick IN clause for QA testing against specific known values.
Cross-referencing exports: use a list exported from one system to filter records in another via SQL.
Bulk lookups: quickly check the status of a batch of specific records pulled from a spreadsheet or support ticket.

Tips for Best Results

Remove duplicate values with the Duplicate Remover first if your source list might contain repeats — an IN clause doesn't need duplicates to work correctly, but a shorter, deduplicated list is easier to review.
For numeric columns, you can strip the generated quotes manually if your database prefers unquoted numbers, though most engines accept quoted numeric values without issue.
Very long IN clauses (thousands of values) may hit a limit in some databases — check your specific engine's documentation if you're working with an unusually large list.

Related Terminology

The SQL IN operator lets you filter rows where a column's value matches any value in a provided list, functioning as a shorthand for multiple OR conditions. Each value in the list typically needs to be quoted if it's a text/string value, which is exactly what this tool automates.

Important Considerations

This tool always wraps values in single quotes, which is correct for text/string values in most SQL dialects — if your column is numeric, you may want to remove the quotes manually, since numeric IN clauses don't require quoting (though most databases will still accept quoted numbers). Extremely large lists may run into a maximum-values limit depending on your specific database engine.

Related Tools

Need broader delimiter and quoting options beyond SQL formatting? The Delim Converter offers more flexible wrapping. For explaining what a query does once it's built, try the SQL Query Explainer, and for boilerplate query structures, see the SQL Query Templates.

Frequently Asked Questions

How do I generate a SQL IN clause from a list?

Paste your list of values (one per line) into the Input box — the tool automatically quotes and comma-separates them into a ready-to-use (...) fragment.

Does it work for numeric values, or just text?

It quotes every value by default, which is correct for text values. For numeric columns you can remove the quotes manually, though most SQL databases accept quoted numbers as well.

Is there a limit to how many values I can convert?

There's no fixed limit in this tool — it handles lists of any size, though extremely long IN clauses (thousands of values) may hit limits in your specific database engine.

Should I remove duplicates before generating the IN clause?

It's not required for the query to work, but removing duplicates first with the Duplicate Remover produces a shorter, easier-to-review result.

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Text Comparator

Compare two texts and see the differences highlighted.

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Click "Compare" to see differences highlighted.

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Detailed Results

SQL Query Templates

Ready-to-use boilerplate for common query patterns — CTEs, joins, date rollups, window functions, and stored procedures. Click Copy and adapt the table/column names.

CTE

Basic CTE (Common Table Expression)

Break a query into a readable, reusable named block.

WITH recent_orders AS (
    SELECT
        customer_id,
        order_id,
        order_date,
        total_amount
    FROM orders
    WHERE order_date >= DATEADD(day, -30, GETDATE())
)
SELECT
    customer_id,
    COUNT(order_id)   AS order_count,
    SUM(total_amount) AS total_spent
FROM recent_orders
GROUP BY customer_id
ORDER BY total_spent DESC;

Recursive CTE (hierarchy / org chart)

Walk a parent-child tree, e.g. an employee/manager hierarchy.

WITH RECURSIVE employee_hierarchy AS (
    -- Anchor: top-level rows (no manager)
    SELECT
        employee_id,
        manager_id,
        employee_name,
        1 AS level
    FROM employees
    WHERE manager_id IS NULL

    UNION ALL

    -- Recursive: join children to their parent's result
    SELECT
        e.employee_id,
        e.manager_id,
        e.employee_name,
        eh.level + 1
    FROM employees e
    INNER JOIN employee_hierarchy eh
        ON e.manager_id = eh.employee_id
)
SELECT *
FROM employee_hierarchy
ORDER BY level, employee_name;
-- Note: SQL Server / Oracle: drop the RECURSIVE keyword (just WITH employee_hierarchy AS (...))

Joins

INNER / LEFT JOIN across multiple tables

Combine orders with customers and line items in one query.

SELECT
    o.order_id,
    c.customer_name,
    o.order_date,
    p.product_name,
    oi.quantity
FROM orders o
INNER JOIN customers c
    ON o.customer_id = c.customer_id
LEFT JOIN order_items oi
    ON o.order_id = oi.order_id
LEFT JOIN products p
    ON oi.product_id = p.product_id
WHERE o.order_date >= '2026-01-01'
ORDER BY o.order_date DESC;

GROUP BY / Dates

Monthly rollup with GROUP BY on a date

Aggregate a date column by month (swap the truncation line for your engine).

SELECT
    DATE_TRUNC('month', order_date) AS order_month,     -- PostgreSQL
    -- FORMAT(order_date, 'yyyy-MM')  AS order_month,    -- SQL Server
    -- DATE_FORMAT(order_date, '%Y-%m') AS order_month,  -- MySQL
    COUNT(*)          AS order_count,
    SUM(total_amount) AS revenue
FROM orders
GROUP BY DATE_TRUNC('month', order_date)
ORDER BY order_month;

Window Functions

ROW_NUMBER + running total

Rank each customer's orders and compute a running total.

SELECT
    customer_id,
    order_id,
    order_date,
    total_amount,
    ROW_NUMBER() OVER (
        PARTITION BY customer_id
        ORDER BY order_date DESC
    ) AS order_rank,
    SUM(total_amount) OVER (
        PARTITION BY customer_id
        ORDER BY order_date
        ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
    ) AS running_total
FROM orders;

Stored Procedures

Parameterized stored procedure

A basic proc with optional date-range filters (T-SQL syntax).

CREATE PROCEDURE GetCustomerOrders
    @CustomerId INT,
    @StartDate  DATE = NULL,
    @EndDate    DATE = NULL
AS
BEGIN
    SET NOCOUNT ON;

    SELECT
        order_id,
        order_date,
        total_amount
    FROM orders
    WHERE customer_id = @CustomerId
        AND (@StartDate IS NULL OR order_date >= @StartDate)
        AND (@EndDate   IS NULL OR order_date <= @EndDate)
    ORDER BY order_date DESC;
END;
-- Call it: EXEC GetCustomerOrders @CustomerId = 101, @StartDate = '2026-01-01';

Upsert / Merge

MERGE (upsert) from a staging table

Insert new rows and update matching ones in a single statement.

MERGE INTO customers AS target
USING staging_customers AS source
    ON target.customer_id = source.customer_id
WHEN MATCHED THEN
    UPDATE SET
        target.customer_name = source.customer_name,
        target.email         = source.email,
        target.updated_at    = GETDATE()
WHEN NOT MATCHED THEN
    INSERT (customer_id, customer_name, email, created_at)
    VALUES (source.customer_id, source.customer_name, source.email, GETDATE());

🎨 Color Picker & Converter

Pick a color (or type a value) and get HEX, RGB, HSL, HSV, and CMYK instantly — copy any format with one click.

HEX

#FACC15

RGB

rgb(250, 204, 21)

RGB Percent

rgb(98%, 80%, 8%)

HSL

hsl(46, 96%, 53%)

HSV / HSB

hsv(46, 92%, 98%)

CMYK

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⚙️ Settings

SQL Value Generator — Build a SQL IN Clause from a List

⚡ Key Takeaways

What, Who, When & Why

How to Use the SQL Value Generator

Example

Key Features

Practical Use Cases

Tips for Best Results

Related Terminology

Important Considerations

Related Tools

Frequently Asked Questions

How do I generate a SQL IN clause from a list?

Does it work for numeric values, or just text?

Is there a limit to how many values I can convert?

Should I remove duplicates before generating the IN clause?

Archived Notes

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