Filter any line-oriented text instantly: Paste a log file, CSV, or any multi-line text and keep or remove lines that match a search term. Chain multiple rules to narrow results progressively — no terminal, no grep command required.

What Is a Line Filter?

A line filter scans text line by line and keeps or discards each line based on whether it matches a search term or pattern. It is the browser equivalent of grep for keeping lines and grep -v for removing them.

This tool is useful whenever you need to isolate specific entries from large text output: server logs, application traces, CSV exports, database query results, or any file where the relevant information is buried among thousands of lines you do not need.

How to Use

1. Paste or upload your text into the input field.
2. Type a search term in the first filter row.
3. Click Keep or Remove to set the mode — the button toggles between the two.
4. The output updates instantly.
5. Click + Add filter to add another rule and narrow the results further.
6. Enable Case sensitive to match exact casing, or Regex to use regular expressions.
7. Click Copy to copy the result, or Download to save it as a .txt file.

Filter Modes: Keep vs Remove

Each filter rule operates in one of two modes:

• Keep — only lines that contain the search term are passed through. Lines that do not match are discarded.
• Remove — lines that contain the search term are discarded. Lines that do not match are passed through.

Click the mode button next to the search term input to toggle between Keep and Remove.

Sequential Filtering

Multiple rules are applied in sequence — each rule filters the output of the previous one. This lets you progressively narrow a large dataset:

1. Keep method = POST → shows only POST requests
2. Remove /healthcheck → removes health probe noise
3. Keep 5 → shows only 5xx status lines among remaining results

This is equivalent to chaining grep commands in a shell pipeline. You can add as many rules as needed.

Regex Support

Enable Regex to use regular expression patterns instead of plain text. This allows precise matching:

• POST|PUT — matches lines containing either POST or PUT
• ^ERROR — matches lines that start with ERROR
• [45]\d\d — matches 4xx and 5xx status codes

If a pattern is invalid, the input field turns red and that rule is skipped. Correct the pattern and the error clears automatically.

When Regex is disabled, all terms are treated as literal substrings — no special characters are interpreted.

Common Log Filtering Examples

Keep only POST requests:

Before:

2024-01-15 10:23:01 GET /api/users 200
2024-01-15 10:23:02 POST /api/orders 201
2024-01-15 10:23:03 GET /api/products 200
2024-01-15 10:23:04 POST /api/payments 200

After (Keep: POST):

2024-01-15 10:23:02 POST /api/orders 201
2024-01-15 10:23:04 POST /api/payments 200

Remove health check noise:

Before:

2024-01-15 10:23:02 POST /api/orders 201
2024-01-15 10:23:05 GET /healthcheck 200
2024-01-15 10:23:04 POST /api/payments 200
2024-01-15 10:23:10 GET /healthcheck 200

After (Remove: /healthcheck):

2024-01-15 10:23:02 POST /api/orders 201
2024-01-15 10:23:04 POST /api/payments 200

Isolate errors using regex:

Before:

2024-01-15 10:23:01 GET /api/users 200
2024-01-15 10:23:04 POST /api/payments 500
2024-01-15 10:23:07 GET /api/orders 404
2024-01-15 10:23:11 POST /api/auth 200

After (Keep regex: [45]\d\d$):

2024-01-15 10:23:04 POST /api/payments 500
2024-01-15 10:23:07 GET /api/orders 404

Use Cases

1. Narrowing Application Logs

Server logs contain thousands of lines per minute. Use Keep rules to isolate specific request paths, user IDs, or error codes, then add Remove rules to strip probe traffic and known noise. A 50,000-line trace can be reduced to the 20 lines that matter.

2. Filtering CSV and Spreadsheet Exports

Exported CSV files often contain rows for all record types. Use a Keep rule to show only rows where a column matches a specific value — a specific country, status, or category — before pasting into a report or importing into another tool.

3. Cleaning Up Command Output

Output from tools like docker ps, kubectl get pods, or git log --oneline includes headers, separators, and unrelated entries. Paste the output and filter to just the relevant lines rather than writing a complex shell one-liner.

4. Reviewing Diff Output

Large diffs contain additions, deletions, and context lines. Use a Keep rule to show only lines starting with + or -, or only lines touching a specific function name, making it easier to review a large changeset.

5. Searching Configuration Files

Config files can be hundreds of lines long. Keep only the lines containing a specific key or value, or Remove comment lines (lines starting with #) to compare two config files side by side.

Your Text Never Leaves Your Browser

When filtering logs that include session tokens, user data, internal API paths, or confidential system information, sending them to a server-side tool creates a real security risk.

At UPREK, our philosophy is simple: Your data stays yours. We don’t want it, we don’t collect it, and we can’t see it.

• 100% Local Processing: All filtering runs locally on your machine via your browser’s JavaScript engine.
• Zero Server Uploads: Your input text is never routed through, processed by, or uploaded to our servers.
• No Logs or Backups: We do not log, store, or back up any of the text or files you input into this tool.
• Instant Deletion: The text you work with exists only in your browser’s active memory. Close the tab and the data is gone.
• Enterprise-Grade Security: Because we never possess or transmit your data, using UPREK makes you inherently immune to server-side data breaches.

Data as Parameter

You can pre-fill the input field with the ?input= query parameter:

https://www.uprek.com/en/tools/line-filter?input=line+one%0Aline+two

For private text, avoid sharing URLs that contain the content itself.

Frequently Asked Questions (FAQ)

What is the difference between Keep and Remove?

Keep passes through only lines that match your search term — all non-matching lines are discarded. Remove does the opposite: lines that match are discarded, and everything else is kept. Click the mode button next to the search term to toggle between the two.

How does sequential filtering work?

Rules are applied from top to bottom. The second rule filters the output of the first, the third filters the output of the second, and so on. This is equivalent to chaining grep commands in a shell pipeline: grep "term1" | grep -v "term2" | grep "term3".

Can I filter large log files?

Yes. Upload a log file directly using the Upload button — the file is loaded into your browser without being sent to any server. All filtering happens locally. There is no file size limit enforced by the tool, though very large files may slow down processing depending on your device.

What regex syntax is supported?

The tool uses JavaScript’s built-in RegExp engine, which supports standard syntax: character classes ([a-z], \d, \w), quantifiers (*, +, ?, {n,m}), anchors (^, $), alternation (a|b), and groups ((abc)).

Does case sensitivity affect regex patterns?

Yes. When Case sensitive is disabled (the default), regex matching is case-insensitive — the pattern error also matches ERROR and Error. Enable Case sensitive if you need the pattern to match exact casing.

What happens when a regex is invalid?

The input field for that rule turns red and the rule is skipped — other valid rules still apply. Correct the pattern and the error clears automatically.

Can I save my filter rules?

Not in the current version — rules exist only for the current browser session and reset on page refresh. Copy your filter terms before leaving the page if you plan to reuse them.

Does this tool work on mobile?

Yes. The tool runs entirely in your browser and is responsive on mobile screens. You can paste text, set filter rules, and copy or download the filtered result on any modern smartphone or tablet.