Convert CSV to Textile

Why Convert CSV to Textile?

Converting CSV data to Textile markup creates properly formatted tables that render in Textile-compatible platforms like Redmine, Textpattern CMS, and other web-based content systems. While CSV files store data compactly for machines, Textile tables use a clean pipe-delimited syntax with special header markers that produce styled HTML tables when processed.

Textile's table syntax is intuitive: each row is a line, cells are separated by pipes (|), and header cells use the |_. prefix. The converter automatically detects your CSV delimiter, identifies headers, and generates Textile markup where the first row uses |_. header notation and subsequent rows use standard | cell notation. The result is ready to paste into any Textile-compatible platform.

This conversion is particularly valuable for teams using Redmine for project management. Redmine uses Textile as its default markup language for wiki pages, issue descriptions, and comments. If you have data in spreadsheets or databases that needs to appear in Redmine, converting CSV to Textile is the quickest way to create formatted tables without manually typing the markup.

CSV to Textile conversion is also useful for Textpattern CMS users, documentation writers who work with Textile-based systems, and anyone who needs to format data tables in Textile markup. The converter handles special characters and produces clean, valid Textile that renders correctly across all compliant processors.

Key Benefits of Converting CSV to Textile:

• Textile Tables: Proper Textile markup with |_. header cells and | data cells
• Auto-Detection: Automatically detects CSV delimiter (comma, semicolon, tab, pipe)
• Header Recognition: First row is formatted using |_. header cell syntax
• Redmine Ready: Output can be pasted directly into Redmine wiki pages and issues
• CMS Compatible: Works with Textpattern and other Textile-based systems
• Clean Markup: Generates readable, properly formatted Textile source
• Data Integrity: All cell values are preserved exactly as in the original CSV

Practical Examples

Example 1: Project Task List

Input CSV file (tasks.csv):

Task ID,Title,Assignee,Priority,Status
TASK-101,Fix login bug,Alice,High,In Progress
TASK-102,Update API docs,Bob,Medium,Open
TASK-103,Add unit tests,Carol,Low,Open
TASK-104,Deploy v2.0,Dave,Critical,Blocked

Output Textile file (tasks.textile):

|_. Task ID |_. Title |_. Assignee |_. Priority |_. Status |
| TASK-101 | Fix login bug | Alice | High | In Progress |
| TASK-102 | Update API docs | Bob | Medium | Open |
| TASK-103 | Add unit tests | Carol | Low | Open |
| TASK-104 | Deploy v2.0 | Dave | Critical | Blocked |

Example 2: Server Configuration Matrix

Input CSV file (servers.csv):

Environment,Server,Port,Database,Cache
Production,app-prod-01,8080,PostgreSQL,Redis
Staging,app-stage-01,8080,PostgreSQL,Memcached
Development,localhost,3000,SQLite,None

Output Textile file (servers.textile):

|_. Environment |_. Server |_. Port |_. Database |_. Cache |
| Production | app-prod-01 | 8080 | PostgreSQL | Redis |
| Staging | app-stage-01 | 8080 | PostgreSQL | Memcached |
| Development | localhost | 3000 | SQLite | None |

Example 3: Version Comparison Chart

Input CSV file (versions.csv):

Feature,v1.0,v2.0,v3.0
User Authentication,Basic,OAuth 2.0,SSO + MFA
API Rate Limiting,None,100 req/min,1000 req/min
File Upload,10 MB,50 MB,500 MB

Output Textile file (versions.textile):

|_. Feature |_. v1.0 |_. v2.0 |_. v3.0 |
| User Authentication | Basic | OAuth 2.0 | SSO + MFA |
| API Rate Limiting | None | 100 req/min | 1000 req/min |
| File Upload | 10 MB | 50 MB | 500 MB |

Frequently Asked Questions (FAQ)

Q: What is Textile markup format?

A: Textile is a lightweight markup language created by Dean Allen in 2002 for writing formatted web content. It uses simple syntax to generate HTML, including tables, bold/italic text, links, images, and lists. Textile is the default markup language in Redmine (project management) and Textpattern (CMS). Tables in Textile use pipe characters (|) to separate cells and |_. to denote header cells.

Q: How does the CSV delimiter detection work?

A: Our converter uses Python's csv.Sniffer to automatically detect the delimiter used in your CSV file. It supports commas, semicolons, tabs, and pipe characters. The sniffer analyzes a sample of your file to determine the correct delimiter and quoting style. CSV files from Excel, Google Sheets, European locale software, or database exports are all handled correctly without any manual configuration.

Q: Will my CSV headers be styled as Textile header cells?

A: Yes! The converter detects header rows and formats them using Textile's header cell syntax (|_.). Header cells are rendered as bold, centered text in the HTML output. If no header row is detected in the CSV, generic column names are generated and formatted as headers. All data values are preserved exactly as they appear in the original CSV.

Q: Can I paste the output directly into Redmine?

A: Absolutely! The generated Textile table is ready to paste into Redmine wiki pages, issue descriptions, comments, or any text field that supports Textile markup. Redmine will render the pipes and header markers into a properly formatted HTML table with borders and styling.

Q: What happens with pipe characters in CSV data?

A: Since pipe characters (|) are used as cell delimiters in Textile tables, any pipe characters within your CSV data need careful handling. The converter properly parses quoted CSV fields and places the values between pipe delimiters in the Textile output. If your data contains literal pipe characters, they may need to be escaped or replaced depending on your Textile processor.

Q: How are data types from CSV handled in Textile output?

A: All CSV values are treated as text and placed directly into Textile table cells. Numbers, dates, and other data types appear exactly as they do in the CSV. You can add Textile formatting within cells after conversion, such as *bold* or _italic_ text, to enhance the presentation of specific values.

Q: Is there a limit on the number of rows or columns?

A: There is no hard limit. However, for very wide tables (many columns), the Textile markup line can become long and hard to read in the source. For wiki pages and issue descriptions, tables with a moderate number of columns (5-8) work best. Very large datasets may be better served by attaching a CSV file or linking to a spreadsheet.

Q: Does the converter support CSV files from Excel?

A: Yes! CSV files exported from Microsoft Excel, Google Sheets, LibreOffice Calc, and other spreadsheet applications are fully supported. The converter handles both UTF-8 and UTF-8 with BOM encodings, as well as different line ending styles (Windows CRLF, Unix LF, Mac CR). Excel's default comma-separated format and locale-specific semicolon-separated formats are both detected automatically.