Random CSV Quoting Edge-Case Corpus Generator

Description

Construct cell-level delimiter, quote, LF, CRLF, Unicode, empty and unmodified CSV edge cases from text fragments, delegate JSON/CSV conversion, and retain original cells separately from parsed cells; numeric inference is off, empty cells become null, single-empty-field rows are skipped, and identifier-only headers avoid the old unquoted-header limitation.

CSV stores records as delimited text fields. Quoting can protect embedded delimiters and newlines, so a record need not equal one physical line. Cleaning field contents, interpreting their types, and preserving an exact import/export round trip are separate operations.

When to use this tool

Use this generator to create reproducible csv quoting edge case corpus cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply headers, fragments, kinds, delimiter, caseCount, rowCount in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read headers, cases. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Draw cells containing delimiters, quotes, newlines, Unicode, empty values, or plain fragments. Serialize through JSON-to-CSV and reimport without numeric inference, independently checking the converter's documented treatment of empty fields and records.^[1]

Delegated operations used for this result: json to csv; csv to json. Their calculation or parsing conventions apply to the corresponding result fields.^{[2, 3]}

Input field	Meaning and units	Accepted input
headers	Headers	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 32.; minimum items 1; maximum items 8.
fragments	Fragments	Required. Array of Text; maximum UTF-16 length 64.; minimum items 1; maximum items 16.
kinds	Kinds	Required. Array of Text; one of "delimiter", "quote", "lf", "crlf", "unicode", "empty", "unmodified".; minimum items 1; maximum items 7.
delimiter	Delimiter	Required. Text; one of ",", ";", "\t", "\|".
caseCount	Case Count	Required. Safe integer; minimum 1; maximum 16.
rowCount	Row Count	Required. Safe integer; minimum 1; maximum 64.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
headers	Headers	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 32.; minimum items 1; maximum items 8.
cases	Cases	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
cases[].cells	Cells	Required. Array of Array of Text; maximum UTF-16 length 130.; minimum items 1; maximum items 8.; minimum items 1; maximum items 64.
cases[].cellKinds	Cell Kinds	Required. Array of Array of Text; one of "delimiter", "quote", "lf", "crlf", "unicode", "empty", "unmodified".; minimum items 1; maximum items 8.; minimum items 1; maximum items 64.
cases[].csv	Csv	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 131072.
cases[].parsedJson	Parsed Json	Required. Text; minimum UTF-16 length 2; maximum UTF-16 length 131072.
cases[].parsedCells	Parsed Cells	Required. Array of Array of Text; maximum UTF-16 length 130. or Null.; minimum items 1; maximum items 8.; maximum items 64.
cases[].skippedSingleEmptyRows	Skipped Single Empty Rows	Required. Safe integer; minimum 0; maximum 64.
cases[].exactRoundTrip	Exact Round Trip	Required. Boolean.
randomness	Replay source and normalized 32-bit seed, or null seed for an advancing context source.	Required. Object; no unknown keys.
randomness.seed	Optional safe-integer replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "headers": [
      "a",
      "b"
    ],
    "fragments": [
      "x",
      "y"
    ],
    "kinds": [
      "delimiter",
      "quote",
      "lf",
      "empty"
    ],
    "delimiter": ",",
    "caseCount": 1,
    "rowCount": 2,
    "seed": 42
  },
  "output": {
    "headers": [
      "a",
      "b"
    ],
    "cases": [
      {
        "cells": [
          [
            "x\nx",
            ""
          ],
          [
            "y,y",
            "y\"y"
          ]
        ],
        "cellKinds": [
          [
            "lf",
            "empty"
          ],
          [
            "delimiter",
            "quote"
          ]
        ],
        "csv": "a,b\n\"x\nx\",\n\"y,y\",\"y\"\"y\"\n",
        "parsedJson": "[{\"a\":\"x\\nx\",\"b\":null},{\"a\":\"y,y\",\"b\":\"y\\\"y\"}]",
        "parsedCells": [
          [
            "x\nx",
            null
          ],
          [
            "y,y",
            "y\"y"
          ]
        ],
        "skippedSingleEmptyRows": 0,
        "exactRoundTrip": false
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Empty cells become null and a single empty-cell record can disappear. exactRoundTrip is therefore allowed to be false even when both converters behave as designed; count and quoting controls are bounded.
A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random CSV Quoting Edge-Case Corpus Generator — tool.io
Calculation or validation: convert/json-to-csv — tool.io
Calculation or validation: convert/csv-to-json — tool.io

Similar or alternative tools

Random CSV Aggregate Reconciliation Exercise Generator
Generate synthetic grouped integer observations, plant one declared subtotal discrepancy and retain exact decimal-string subtotal, grand-total and checksum-row reconciliation answers.
Random CSV Boolean Token Cleaning Exercise Generator
Sample caller-selected Boolean spellings, blank cells and unknown controls, retaining explicit classifications and nullable normalization answers from the Boolean token core.