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feat(cli): memory-efficient streaming for encoding

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This commit is contained in:
Johann Schopplich
2025-11-21 14:02:22 +01:00
parent be8bcfe9b2
commit 1c003c6118
7 changed files with 308 additions and 50 deletions
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13
README.md
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@@ -764,6 +764,19 @@ console.log(encode(data))
// 2,Bob,user
```
**Streaming large datasets:**
```ts
import { encodeLines } from '@toon-format/toon'
const largeData = await fetchThousandsOfRecords()
// Memory-efficient streaming for large data
for (const line of encodeLines(largeData)) {
process.stdout.write(`${line}\n`)
}
```
## Playgrounds
Experiment with TOON format interactively using these community-built tools for token comparison, format conversion, and validation:

19
docs/cli/index.md
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@@ -1,6 +1,6 @@
# Command Line Interface
The `@toon-format/cli` package provides a command-line interface for encoding JSON to TOON and decoding TOON back to JSON. Use it for quick conversions without writing code, estimating token savings before sending data to LLMs, or integrating TOON into shell pipelines with tools like curl and jq. It supports stdin/stdout workflows, multiple delimiter options, token statistics, and all encoding/decoding features available in the library.
The `@toon-format/cli` package provides a command-line interface for encoding JSON to TOON and decoding TOON back to JSON. Use it to analyze token savings before integrating TOON into your application, or to process JSON data through TOON in shell pipelines using stdin/stdout with tools like curl and jq. The CLI supports token statistics, streaming for large datasets, and all encoding options available in the library.
The CLI is built on top of the `@toon-format/toon` TypeScript implementation and adheres to the [latest specification](/reference/spec).
@@ -108,6 +108,14 @@ cat data.toon | toon --decode
JSON→TOON conversions use line-by-line encoding internally, which avoids holding the entire TOON document in memory. This makes the CLI efficient for large datasets without requiring additional configuration.
```bash
# Encode large JSON file with minimal memory usage
toon huge-dataset.json -o output.toon
# Process millions of records efficiently via stdin
cat million-records.json | toon > output.toon
```
::: info Token Statistics
When using the `--stats` flag, the CLI builds the full TOON string once to compute accurate token counts. For maximum memory efficiency on very large files, omit `--stats`.
:::
@@ -139,6 +147,15 @@ toon data.json --stats -o output.toon
This helps you estimate token cost savings before sending data to LLMs.
Example output:
```
✔ Encoded data.json → output.toon
ℹ Token estimates: ~15,145 (JSON) → ~8,745 (TOON)
✔ Saved ~6,400 tokens (-42.3%)
```
### Alternative Delimiters
TOON supports three delimiters: comma (default), tab, and pipe. Alternative delimiters can provide additional token savings in specific contexts.

23
docs/guide/llm-prompts.md
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@@ -95,6 +95,29 @@ const toon = encode(data, { delimiter: '\t' })
Tell the model "fields are tab-separated" when using tabs. For more on delimiters, see the [Format Overview](/guide/format-overview#delimiter-options).
## Streaming Large Outputs
When working with large datasets (thousands of records or deeply nested structures), use `encodeLines()` to stream TOON output line-by-line instead of building the full string in memory.
```ts
import { encodeLines } from '@toon-format/toon'
const largeData = await fetchThousandsOfRecords()
// Stream large dataset without loading full string in memory
for (const line of encodeLines(largeData, { delimiter: '\t' })) {
process.stdout.write(`${line}\n`)
}
```
The CLI also supports streaming for memory-efficient JSON-to-TOON conversion:
```bash
toon large-dataset.json --output output.toon
```
This streaming approach prevents out-of-memory errors when preparing large context windows for LLMs. For complete details on `encodeLines()`, see the [API reference](/reference/api#encodelines).
## Tips and Pitfalls
**Show, don't describe.** Don't explain TOON syntax in detail – just show an example. Models learn the pattern from context. A simple code block with 2-5 rows is more effective than paragraphs of explanation.

8
docs/reference/api.md
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@@ -129,14 +129,14 @@ encode(data, { delimiter: '\t', keyFolding: 'safe' })
## `encodeLines(value, options?)`
Converts any JSON-serializable value to TOON format as a sequence of lines, without building the full string in memory. Suitable for streaming large outputs to files, HTTP responses, or process stdout.
**Preferred method for streaming TOON output.** Converts any JSON-serializable value to TOON format as a sequence of lines, without building the full string in memory. Suitable for streaming large outputs to files, HTTP responses, or process stdout.
```ts
import { encodeLines } from '@toon-format/toon'
// Stream to stdout
// Stream to stdout (Node.js)
for (const line of encodeLines(data)) {
console.log(line)
process.stdout.write(`${line}\n`)
}
// Write to file line-by-line
@@ -158,7 +158,7 @@ const lineArray = Array.from(encodeLines(data))
### Return Value
Returns an `Iterable<string>` that yields TOON lines one at a time. Each yielded string is a single line without a trailing newline character.
Returns an `Iterable<string>` that yields TOON lines one at a time. **Each yielded string is a single line without a trailing newline character** — you must add `\n` when writing to streams or stdout.
::: info Relationship to `encode()`
`encode(value, options)` is equivalent to:

29
packages/cli/README.md
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@@ -1,8 +1,8 @@
# @toon-format/cli
Command-line tool for converting between JSON and TOON formats.
Command-line tool for converting JSON to TOON and back, with token analysis and streaming support.
[TOON (Token-Oriented Object Notation)](https://toonformat.dev) is a compact, human-readable serialization format designed for passing structured data to Large Language Models with significantly reduced token usage.
[TOON (Token-Oriented Object Notation)](https://toonformat.dev) is a compact, human-readable encoding of the JSON data model that minimizes tokens for LLM input. The CLI lets you test conversions, analyze token savings, and integrate TOON into shell pipelines with stdin/stdout support—no code required.
## Installation
@@ -79,11 +79,12 @@ toon data.json --stats -o output.toon
```
Example output:
```
✓ Encoded to TOON
Input: 15,145 tokens (JSON)
Output: 8,745 tokens (TOON)
Saved: 6,400 tokens (42.3% reduction)
✔ Encoded data.json → output.toon
ℹ Token estimates: ~15,145 (JSON) → ~8,745 (TOON)
✔ Saved ~6,400 tokens (-42.3%)
```
### Alternative Delimiters
@@ -115,6 +116,21 @@ cat large-dataset.json | toon --delimiter "\t" > output.toon
jq '.results' data.json | toon > filtered.toon
```
### Large Dataset Processing
The CLI streams output line-by-line without building the full string in memory, making it suitable for processing large datasets:
```bash
# Encode large JSON file with minimal memory usage
toon huge-dataset.json -o output.toon
# Process millions of records efficiently
cat million-records.json | toon > output.toon
```
> [!NOTE]
> When using `--stats`, the full output string is kept in memory for token counting. Omit `--stats` for maximum memory efficiency with very large datasets.
### Key Folding (Since v1.5)
Collapse nested wrapper chains to reduce tokens:
@@ -190,6 +206,7 @@ toon data.json --key-folding safe --delimiter "\t" --stats -o output.toon
- **Pipeline integration** with existing JSON-based workflows
- **Flexible formatting** with delimiter and indentation options
- **Key folding** to collapse nested wrappers for additional token savings
- **Memory-efficient streaming** for processing large datasets without loading everything into memory
## Related

78
packages/cli/src/conversion.ts
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@@ -1,3 +1,4 @@
import type { FileHandle } from 'node:fs/promises'
import type { DecodeOptions, EncodeOptions } from '../../toon/src'
import type { InputSource } from './types'
import * as fsp from 'node:fs/promises'
@@ -34,38 +35,42 @@ export async function encodeToToon(config: {
flattenDepth: config.flattenDepth,
}
let toonOutput: string
// When printing stats, we need the full string for token counting
if (config.printStats) {
toonOutput = encode(data, encodeOptions)
}
else {
// Use streaming encoder for non-stats path
const lines = Array.from(encodeLines(data, encodeOptions))
toonOutput = lines.join('\n')
}
const toonOutput = encode(data, encodeOptions)
if (config.output) {
await fsp.writeFile(config.output, toonOutput, 'utf-8')
const relativeInputPath = formatInputLabel(config.input)
const relativeOutputPath = path.relative(process.cwd(), config.output)
consola.success(`Encoded \`${relativeInputPath}\` → \`${relativeOutputPath}\``)
}
else {
console.log(toonOutput)
}
if (config.printStats) {
const jsonTokens = estimateTokenCount(jsonContent)
const toonTokens = estimateTokenCount(toonOutput)
const diff = jsonTokens - toonTokens
const percent = ((diff / jsonTokens) * 100).toFixed(1)
if (config.output) {
const relativeInputPath = formatInputLabel(config.input)
const relativeOutputPath = path.relative(process.cwd(), config.output)
consola.success(`Encoded \`${relativeInputPath}\` → \`${relativeOutputPath}\``)
}
console.log()
consola.info(`Token estimates: ~${jsonTokens} (JSON) → ~${toonTokens} (TOON)`)
consola.success(`Saved ~${diff} tokens (-${percent}%)`)
}
else {
// Use streaming encoder for memory-efficient output
await writeStreamingToon(encodeLines(data, encodeOptions), config.output)
if (config.output) {
const relativeInputPath = formatInputLabel(config.input)
const relativeOutputPath = path.relative(process.cwd(), config.output)
consola.success(`Encoded \`${relativeInputPath}\` → \`${relativeOutputPath}\``)
}
}
}
export async function decodeToJson(config: {
@@ -102,3 +107,50 @@ export async function decodeToJson(config: {
console.log(jsonOutput)
}
}
/**
* Writes TOON lines to a file or stdout using streaming approach.
* Lines are written one at a time without building the full string in memory.
*
* @param lines - Iterable of TOON lines (without trailing newlines)
* @param outputPath - File path to write to, or undefined for stdout
*/
async function writeStreamingToon(
lines: Iterable<string>,
outputPath?: string,
): Promise<void> {
let isFirst = true
// Stream to file using fs/promises API
if (outputPath) {
let fileHandle: FileHandle | undefined
try {
fileHandle = await fsp.open(outputPath, 'w')
for (const line of lines) {
if (!isFirst)
await fileHandle.write('\n')
await fileHandle.write(line)
isFirst = false
}
}
finally {
await fileHandle?.close()
}
}
// Stream to stdout
else {
for (const line of lines) {
if (!isFirst)
process.stdout.write('\n')
process.stdout.write(line)
isFirst = false
}
// Add final newline for stdout
process.stdout.write('\n')
}
}

176
packages/cli/test/index.test.ts
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@@ -33,15 +33,16 @@ describe('toon CLI', () => {
}
const cleanup = mockStdin(JSON.stringify(data))
const stdout: string[] = []
vi.spyOn(console, 'log').mockImplementation((message?: unknown) => {
stdout.push(String(message ?? ''))
const writeChunks: string[] = []
vi.spyOn(process.stdout, 'write').mockImplementation((chunk) => {
writeChunks.push(String(chunk))
return true
})
try {
await runCli()
expect(stdout).toHaveLength(1)
expect(stdout[0]).toBe(encode(data))
const fullOutput = writeChunks.join('')
expect(fullOutput).toBe(`${encode(data)}\n`)
}
finally {
cleanup()
@@ -83,16 +84,17 @@ describe('toon CLI', () => {
'input.json': JSON.stringify(data),
})
const stdout: string[] = []
vi.spyOn(console, 'log').mockImplementation((message?: unknown) => {
stdout.push(String(message ?? ''))
const writeChunks: string[] = []
vi.spyOn(process.stdout, 'write').mockImplementation((chunk) => {
writeChunks.push(String(chunk))
return true
})
try {
await context.run(['input.json'])
expect(stdout).toHaveLength(1)
expect(stdout[0]).toBe(encode(data))
const fullOutput = writeChunks.join('')
expect(fullOutput).toBe(`${encode(data)}\n`)
}
finally {
await context.cleanup()
@@ -230,16 +232,17 @@ describe('toon CLI', () => {
const data = { items: [1, 2, 3] }
const cleanup = mockStdin(JSON.stringify(data))
const stdout: string[] = []
vi.spyOn(console, 'log').mockImplementation((message?: unknown) => {
stdout.push(String(message ?? ''))
const writeChunks: string[] = []
vi.spyOn(process.stdout, 'write').mockImplementation((chunk) => {
writeChunks.push(String(chunk))
return true
})
try {
await runCli({ rawArgs: ['--delimiter', '|'] })
expect(stdout).toHaveLength(1)
expect(stdout[0]).toBe(encode(data, { delimiter: '|' }))
const fullOutput = writeChunks.join('')
expect(fullOutput).toBe(`${encode(data, { delimiter: '|' })}\n`)
}
finally {
cleanup()
@@ -254,16 +257,17 @@ describe('toon CLI', () => {
}
const cleanup = mockStdin(JSON.stringify(data))
const stdout: string[] = []
vi.spyOn(console, 'log').mockImplementation((message?: unknown) => {
stdout.push(String(message ?? ''))
const writeChunks: string[] = []
vi.spyOn(process.stdout, 'write').mockImplementation((chunk) => {
writeChunks.push(String(chunk))
return true
})
try {
await runCli({ rawArgs: ['--indent', '4'] })
expect(stdout).toHaveLength(1)
expect(stdout[0]).toBe(encode(data, { indent: 4 }))
const fullOutput = writeChunks.join('')
expect(fullOutput).toBe(`${encode(data, { indent: 4 })}\n`)
}
finally {
cleanup()
@@ -293,6 +297,138 @@ describe('toon CLI', () => {
})
})
describe('streaming output', () => {
it('streams large JSON to TOON file with identical output', async () => {
const data = {
items: Array.from({ length: 1000 }, (_, i) => ({
id: i,
name: `Item ${i}`,
value: Math.random(),
})),
}
const context = await createCliTestContext({
'large-input.json': JSON.stringify(data, undefined, 2),
})
const consolaSuccess = vi.spyOn(consola, 'success').mockImplementation(() => undefined)
try {
await context.run(['large-input.json', '--output', 'output.toon'])
const output = await context.read('output.toon')
// Verify streaming produces identical output to `encode()`
const expected = encode(data, {
delimiter: DEFAULT_DELIMITER,
indent: 2,
})
expect(output).toBe(expected)
expect(consolaSuccess).toHaveBeenCalledWith(expect.stringMatching(/Encoded .* → .*/))
}
finally {
await context.cleanup()
}
})
it('streams to stdout using process.stdout.write', async () => {
const data = {
users: [
{ id: 1, name: 'Alice' },
{ id: 2, name: 'Bob' },
],
}
const context = await createCliTestContext({
'input.json': JSON.stringify(data),
})
const writeChunks: string[] = []
const writeSpy = vi.spyOn(process.stdout, 'write').mockImplementation((chunk) => {
writeChunks.push(String(chunk))
return true
})
try {
await context.run(['input.json'])
expect(writeSpy).toHaveBeenCalled()
// Verify complete output matches `encode()`
const fullOutput = writeChunks.join('')
const expected = `${encode(data)}\n`
expect(fullOutput).toBe(expected)
}
finally {
await context.cleanup()
}
})
it('handles empty object streaming correctly', async () => {
const data = {}
const context = await createCliTestContext({
'empty.json': JSON.stringify(data),
})
try {
await context.run(['empty.json', '--output', 'output.toon'])
const output = await context.read('output.toon')
expect(output).toBe(encode(data))
}
finally {
await context.cleanup()
}
})
it('handles single-line output streaming correctly', async () => {
const data = { key: 'value' }
const context = await createCliTestContext({
'single.json': JSON.stringify(data),
})
try {
await context.run(['single.json', '--output', 'output.toon'])
const output = await context.read('output.toon')
expect(output).toBe(encode(data))
}
finally {
await context.cleanup()
}
})
it('uses non-streaming path when stats are enabled', async () => {
const data = {
items: [
{ id: 1, value: 'test' },
{ id: 2, value: 'data' },
],
}
const context = await createCliTestContext({
'input.json': JSON.stringify(data),
})
const consoleLogSpy = vi.spyOn(console, 'log').mockImplementation(() => undefined)
const consolaInfo = vi.spyOn(consola, 'info').mockImplementation(() => undefined)
const consolaSuccess = vi.spyOn(consola, 'success').mockImplementation(() => undefined)
try {
await context.run(['input.json', '--stats'])
expect(consolaInfo).toHaveBeenCalledWith(expect.stringMatching(/Token estimates:/))
expect(consolaSuccess).toHaveBeenCalledWith(expect.stringMatching(/Saved.*tokens/))
expect(consoleLogSpy).toHaveBeenCalledWith(encode(data))
}
finally {
await context.cleanup()
}
})
})
describe('error handling', () => {
it('rejects invalid delimiter', async () => {
const context = await createCliTestContext({