- Highlight columns in comma (.csv), tab (.tsv), semicolon and pipe - separated files in different colors
- Provide info about column on hover
- Automatic consistency check for csv files (CSVLint)
- Multi-cursor column edit
- Run queries in SQL-like language
- Lightweight and dependency-free
If your csv, semicolon-separated or tab-separated file doesn't have .csv or .tsv extension, you can manually enable highlighting by clicking on the current language label mark in the right bottom corner and then choosing "CSV", "TSV", "CSV (semicolon)" or "CSV (pipe)" depending on the file content, see this screenshot
Another way to do this: select one separator character with mouse cursor -> right click -> "Set as Rainbow separator"
| language name | separator | separator can be escaped in double-quoted field | file extensions |
|---|---|---|---|
| CSV | , (comma) | YES | .csv |
| TSV | \t (TAB) | NO | .tsv, .tab |
| CSV (semicolon) | ; (semicolon) | YES | |
| | ~ ^ : " = . - | NO |
Rainbow CSV will run spreadsheet autodetection algorithm for all "Plain Text" files. In most cases this is a very cheap operation because autodetection would stop after checking only 1-2 topmost lines.
To disable autodetection for the current file press "Rainbow OFF" button inside the status line.
You can adjust autodetection parameters or disable it in Rainbow CSV extension settings section.
The linter will check the following:
- consistency of double quotes usage in CSV rows
- consistency of number of fields per CSV row
To disable automatic CSV Linting set "rainbow_csv.enable_auto_csv_lint": false in "Rainbow CSV" section of VS Code settings.
To recheck a csv file click on "CSVLint" button.
If "rainbow_csv.comment_prefix" in "Rainbow CSV" section of VS Code settings is set to some string, the linter will ignore all lines that start with it.
This is useful, e.g., if you have engineering CSVs that often start with multiple comment lines containing meta-data before the actual header.
To enable Rainbow CSV for very big files (more than 300K lines or 20MB) disable "Editor:Large File Optimizations" option in VS Code settings.
You can preview huge files by clicking "Preview... " option in VS Code File Explorer context menu.
All Rainbow CSV features would be disabled by VSCode if file is bigger than 50MB.
Enter RBQL - SQL-like language query editing mode.
Activate multi-cursor column editing for column under the cursor. Works only for files with less than 10000 lines. For larger files you can use an RBQL query.
WARNING: This is a dangerous mode. It is possible to accidentally corrupt table structure by incorrectly using "Backspace" or entering separator or double quote characters. Use RBQL if you are not sure.
To remove cursor/selection from the header line use "Alt+Click" on it.
Adjust column names displayed in hover tooltips. Actual header line and file content won't be affected.
Rainbow CSV always assumes the first row that is not a comment (if comments are enabled) as a header, so when there is no real header in a spreadsheet, you can use this command and provide comma-separated string with column names to create a "virtual" header for more comfortable data viewing. Accepted CSV format doesn't require you to customize all of the columns - this is useful when you want to name only some small subset of available columns. Note that you must provide comma-separated string no matter what separator is actually used in your spreadsheet file. "Virtual" header is persistent and will be associated with the parent file across VSCode sessions.
You can customize Rainbow CSV colors to increase contrast. Instructions
Rainbow CSV has built-in RBQL query language interpreter that allows you to run SQL-like queries using a1, a2, a3, ... column names.
Example:
SELECT a1, a2 * 10 WHERE a1 == "Buy" && a4.indexOf('oil') != -1 ORDER BY parseInt(a2), a4 LIMIT 100
To enter query-editing mode, execute RBQL VSCode command.
RBQL is a very simple and powerful tool which would allow you to quickly and easily perform most common data-manipulation tasks and convert your csv tables to bash scripts, single-lines json, single-line xml files, etc.
It is very easy to start using RBQL even if you don't know SQL. For example to cut out third and first columns use SELECT a3, a1
You can use RBQL command for all possible types of files (e.g. .js, .xml, .html), but for non-table files only two variables: NR and a1 would be available.
Screenshot of RBQL Console:
- Unlike Rainbow CSV, which always treats first line as header, RBQL is header-agnostic i.e. it never treats first line as header, so to skip over header line add
WHERE NR > 1to your query. - RBQL uses JavaScript or Python backend language. This means that you need to use
==to check for equality inside WHERE expressions. - If you want to use RBQL with Python backend language instead of JavaScript, make sure you have Python interpreter insatalled and added to PATH variable of your OS.
- WYSIWYG
- Familiar editing environment of your favorite text editor
- Zero-cost abstraction: Syntax highlighting is essentially free, while graphical column alignment can be computationally expensive
- High information density: Rainbow CSV shows more data per screen because it doesn't insert column-aligning whitespaces.
- Ability to visually associate two same-colored columns from two different windows. This is not possible with graphical column alignment
- Rainbow CSV may be less effective for CSV files with many (> 10) columns.
- Rainbow CSV can't correctly handle newlines inside double-quoted CSV fields (well, theorethically it can, but only under specific conditions)