Delim Converter

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

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Delimiter

Find and Replace — Bulk Text Replacement Tool Online

This Find and Replace tool lets you run multiple find-and-replace operations on a block of text in a single pass, with optional case-sensitive and regex matching. It's built for developers and analysts who need to bulk find and replace text across a document or dataset — swapping abbreviations for full names, cleaning up inconsistent formatting, or applying a pattern-based replacement using regular expressions — without doing each replacement one at a time.

⚡ Key Takeaways

Runs multiple find/replace pairs in a single pass instead of one at a time.
Optional regex support for pattern-based, not just exact-text, replacement.
Matching is case-insensitive by default — enable "Match case" for precision work.
An invalid regex pattern is skipped automatically without breaking your other conditions.

What, Who, When & Why

What it's for	Runs multiple find-and-replace operations across a block of text in a single pass, with optional regex support.
Who it's for	Developers and analysts cleaning up text, standardizing terminology, or applying pattern-based fixes to a document or dataset.
When to use it	Whenever a single find-and-replace isn't enough — you need several different replacements applied to the same text at once.
Why it's needed	Running find-and-replace one term at a time in a text editor is slow when you have several corrections to make, and easy to miss one.
Best way to use it	Add all your conditions first, then review the live preview before copying — this lets you catch any unintended matches before they're finalized.

How to Use Find and Replace

Paste your text into the Input box.
Click "+ Add condition" to create a find/replace pair, then enter the text to find and what to replace it with.
Add as many find/replace conditions as you need — they all run in a single pass.
Toggle "Match case" if you need case-sensitive matching, or "Use regex" for pattern-based find and replace.
The result updates live in the Output box as you edit your conditions.

Example

With input text:

I live in NY but work in LA.

and two conditions — NY → New York and LA → Los Angeles — the output becomes:

I live in New York but work in Los Angeles.

Both replacements happen in a single click, instead of running find-and-replace twice manually. A third condition could just as easily be added to catch a third abbreviation, all applied together in the same pass over the text.

Key Features

Multiple conditions at once — add as many find/replace pairs as needed, all applied together.
Match case toggle for case-sensitive or case-insensitive replacement.
Regex support for pattern-based matching beyond simple exact text.
Live preview that updates as you edit your conditions.
Works on multi-line text and large blocks of content.

Practical Use Cases

Standardizing terminology: replace abbreviations or old naming conventions across a document at once.
Cleaning data exports: replace inconsistent values (like state abbreviations) with a standard format.
Pattern-based cleanup: use regex to strip or replace recurring patterns like extra punctuation or formatting artifacts.
Preparing text for import: replace delimiters, placeholders, or template variables before importing into another system.
Applying multiple text corrections at once: fix several known typos or inconsistencies across a document in a single operation.

Tips for Best Results

Add conditions from most specific to least specific if some find terms could overlap, since each condition runs against the current state of the text.
Test regex patterns on a small sample first if you're not fully confident in the pattern, since an overly broad pattern can match more than intended.
Enable "Match case" when replacing short or common substrings that could otherwise accidentally match unrelated words.

Related Terminology

Regular expressions (regex) are a pattern-matching syntax that lets you find text based on structure rather than an exact match — for example, matching any sequence of digits rather than one specific number. Case-sensitive matching treats uppercase and lowercase letters as different characters, so "NY" and "ny" would only both match if case-sensitivity is turned off.

Important Considerations

When using regex, invalid patterns are skipped automatically rather than breaking the rest of your replacements, so a typo in one regex condition won't prevent your other find/replace pairs from working. Without "Match case" enabled, replacements are case-insensitive by default, which is usually what people expect but is worth confirming for precise, case-sensitive work. Multiple conditions run in sequence, so an earlier replacement can affect what a later condition matches against.

Related Tools

If you're standardizing text case as part of your cleanup, pair this with the Case Converter. For stripping extra whitespace introduced during replacement, use the Whitespace Trimmer. To compare before-and-after results, try the Text Comparator.

Frequently Asked Questions

How do I do multiple find and replace operations at once?

Click "+ Add condition" for each find/replace pair you need — all conditions run together in a single pass over your text.

Can I use regular expressions for find and replace?

Yes, enable "Use regex" to match patterns instead of exact text, useful for more flexible or structural replacements.

Is find and replace case-sensitive by default?

No, matching is case-insensitive unless you enable "Match case," which is usually the more useful default for general text cleanup.

What happens if I enter an invalid regex pattern?

That specific condition is skipped automatically without breaking your other find/replace pairs, so one mistake doesn't stop everything else from working.

Prefix / Suffix Stamper

Add custom prefix and suffix to every line.

Input

Output

Whitespace Trimmer

Strip, collapse, or remove all whitespace. "Clean All" does both trim and collapse in one click.

Input

Output

Column Extractor

Extract specific columns from CSV/TSV data.

Input (CSV/TSV)

Output

Split by Chunk

Split a long string into fixed-width chunks.

Input

Output

Alphabetical Sorter

Sort lines A→Z, Z→A, or by line length.

Input

Output

Escape / Unescape

Escape to HTML entities or JSON strings, or unescape back.

Input

Output

Line Number Stamper

Add incremental line numbers (001, 002, 003...) to each row.

Input

Output

SQL Value Generator

Wrap each line in quotes and join → ('a','b','c')

Input

Output

Date Range Generator

Generate a list of dates between two dates with custom intervals.

Start Date

End Date

Interval

Format

Output

Epoch Converter

Convert Unix timestamps to human-readable dates and vice versa.

Unix Timestamp

Human Date

Result

SQL Formatter

Beautify or minify SQL queries with proper indentation.

Input SQL

Output

CASE Statement Builder

Build SQL CASE WHEN statements one condition at a time — no special syntax to remember.

Column / Expression

Conditions

Else (default value)

Generated SQL

Query Sanitizer

Strip comments, SET statements, and trailing semicolons from SQL.

Input SQL

Output

📌 Sticky Notes

Organize your thoughts, tasks, and ideas with drag-and-drop sticky notes.

📌

Click "+ Add Note" to create your first sticky note.

Text Comparator

Compare two texts and see the differences highlighted.

Text A

Text B

Ignore case Ignore whitespace

Differences

Click "Compare" to see differences highlighted.

Ready to compare

Text Statistics

Get detailed statistics about your text: words, characters, paragraphs, sentences, and more.

Input Text

📝 Words

🔤 Characters

📏 Characters (no spaces)

📄 Sentences

📑 Paragraphs

📃 Lines

📊 Avg word length

📊 Avg sentence length

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

cmyk(0%, 18%, 92%, 2%)

CSV ⇄ JSON Converter

Paste CSV or JSON and convert between them. Handles quoted fields, embedded commas, and nested-safe escaping.

Input

Output

SQL Query Explainer

Paste a SQL query and get a plain-English, structured breakdown of what it does. Pattern-based — works fully offline, no AI involved.

SQL Query

Plain-English Breakdown

Unit Converter

Convert data sizes and time durations. Pick a category, enter a value, and see it converted to every other unit.

Tools for analysts, developers & QA engineers

33 free, browser-based utilities — text and list tools, SQL helpers, converters, and small productivity apps. Everything runs locally; nothing you type or paste is ever uploaded.

📊

For Analysts

Clean lists, build SQL fragments, and reshape data without opening a spreadsheet.

💻

For Developers

Format SQL, convert data formats, and handle everyday text and encoding tasks.

🧪

For QA Engineers

Generate test data, compare text output, and sanitize queries before sharing them.

⚙️ Settings

Find and Replace — Bulk Text Replacement Tool Online

⚡ Key Takeaways

What, Who, When & Why

How to Use Find and Replace

Example

Key Features

Practical Use Cases

Tips for Best Results

Related Terminology

Important Considerations

Related Tools

Frequently Asked Questions

How do I do multiple find and replace operations at once?

Can I use regular expressions for find and replace?

Is find and replace case-sensitive by default?

What happens if I enter an invalid regex pattern?

Archived Notes

Tools for analysts, developers & QA engineers

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