CSV to YAML Converter

This converter takes a comma-separated table -- the kind exported from a spreadsheet, a database query, or an analytics dashboard -- and turns each row into a YAML list item, with the header row supplying the keys. That shape fits a handful of genuinely common jobs rather than everything. Developers reach for it when a small lookup table, a set of feature flags, or seed data lives in a spreadsheet but the application reads YAML, so the CSV becomes a config fragment or fixtures file that drops into a repository.

It also suits lightweight data prep and handoff. If a colleague maintains records in Sheets or Excel and a teammate prefers to read or diff them as YAML, the row-per-entry layout is easier to scan and review line by line than a dense table. Students, analysts, and admins exporting a roster, an inventory list, or a tidy set of key/value attributes can use it to produce a readable structured snapshot without writing a script.

It is a poor fit when the source is not genuinely tabular -- documents, deeply nested records, or anything where one cell should expand into its own sub-structure. For those, a purpose-built export from the source system will serve you better than reshaping a flat grid.

The tool runs entirely in your browser. Paste CSV text or drop a file in, and conversion happens locally -- nothing is uploaded, and nothing persists once the tab is closed. The first line is read as the header and supplies the YAML keys; every following line becomes one item in a list, rendered as a `- key: value` block. You then copy the result or download it as a `.yaml` file.

Parsing is quote-aware: values wrapped in double quotes may contain commas, and a doubled quote ("") inside a quoted field is read as a literal quote. Carriage-return, line-feed, and Windows-style line endings are all handled. If a header cell is blank, the column is named `column_1`, `column_2`, and so on by position, so a row keeps its shape even with an unlabelled column.

Be clear about what it does not do. The delimiter is the comma -- it is not a general TSV or semicolon parser, and there are no options for custom delimiters, type inference, or output styling. Every cell is carried through as a string and written verbatim, so the YAML is a faithful flat transcription of the table rather than a typed or nested document.

The most consequential limit is types: values are never coerced. A column of numbers, a `true`/`false` flag, or an empty cell all arrive in the YAML as plain text, so a parser downstream may read `42` or `true` as a string unless you quote-and-cast them yourself. Empty fields become empty values, not explicit nulls. If your config depends on real integers or booleans, plan to adjust them after conversion.

Because cell values are written without escaping or quoting, content that carries meaning in YAML can produce output that looks right but parses wrong. A value containing a colon-space, a leading `#`, a leading space, a stray quote, or a line break inside a quoted CSV cell can break the key/value structure or shift indentation. Inspect any row with punctuation-heavy or free-text fields rather than trusting it blind.

Structure and scale matter too. The output is always a flat list of single-level records -- dotted headers like `address.city` stay literal keys, they do not nest. Everything is processed in memory in the page, so very large exports can be slow or strain the browser tab; and the converter assumes UTF-8 text, so a file saved in another encoding (or with a byte-order mark) may surface odd characters.

Start at the top: confirm the header row produced the keys you expected and that no column collapsed into a `column_2`-style placeholder. Then count items -- the number of `- ` entries should match your data rows -- and open a row that contains commas, quotes, or longer free text to verify the quote-aware parser split the fields the way you intended. Finally, scan for any value that should be a number, boolean, or null and decide where those need adjusting.

The reliable last step is to run the YAML through the actual parser or application that will consume it. A quick load in your target tool will catch indentation slips, an unquoted special character, or a type mismatch far faster than reading the text by eye, and tells you the file is usable rather than merely plausible.

For anything official, financial, or otherwise consequential -- records tied to accounts, payments, compliance, or published configuration -- verify the converted values against the original source manually. This tool reshapes text; it does not validate that the underlying data is correct, complete, or safe to act on.