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d47b053 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 | import { mkdir, readdir, readFile, writeFile } from 'node:fs/promises'
import { join } from 'node:path'
import { spawn } from 'node:child_process'
import { StudioRunCancelledError, readAbortReason } from '../../studio-agent/runtime/execution/run-cancellation'
export interface MatplotlibExecutionResult {
outputDir: string
scriptPath: string
imageDataUris: string[]
imagePaths: string[]
stdout: string
stderr: string
}
export async function executeMatplotlibRender(input: {
workspaceDirectory: string
renderId: string
code: string
signal?: AbortSignal
}): Promise<MatplotlibExecutionResult> {
const outputDir = join(input.workspaceDirectory, 'renders', input.renderId)
const matplotlibConfigDir = join(input.workspaceDirectory, '.cache', 'matplotlib')
await mkdir(outputDir, { recursive: true })
await mkdir(matplotlibConfigDir, { recursive: true })
const sourcePath = join(outputDir, 'plot_script.py')
const wrapperPath = join(outputDir, 'plot_executor.py')
await writeFile(sourcePath, input.code, 'utf8')
await writeFile(wrapperPath, buildExecutorScript(), 'utf8')
const { stdout, stderr } = await runPython(wrapperPath, [sourcePath, outputDir, matplotlibConfigDir], input.signal)
const parsedImagePaths = parseJsonLine(stdout, 'PLOT_OUTPUTS_JSON=') as string[] | undefined
const imagePaths = Array.isArray(parsedImagePaths) && parsedImagePaths.length > 0
? parsedImagePaths
: await findPngOutputs(outputDir)
if (imagePaths.length === 0) {
throw new Error(stderr.trim() || 'Matplotlib execution finished without producing any image output')
}
const imageDataUris = await Promise.all(imagePaths.map(async (imagePath) => {
const bytes = await readFile(imagePath)
return `data:image/png;base64,${bytes.toString('base64')}`
}))
return {
outputDir,
scriptPath: sourcePath,
imageDataUris,
imagePaths,
stdout,
stderr,
}
}
async function findPngOutputs(outputDir: string): Promise<string[]> {
const entries = await readdir(outputDir, { withFileTypes: true })
return entries
.filter((entry) => entry.isFile() && /\.png$/i.test(entry.name))
.map((entry) => join(outputDir, entry.name))
.sort((a, b) => a.localeCompare(b))
}
async function runPython(scriptPath: string, args: string[], signal?: AbortSignal): Promise<{ stdout: string; stderr: string }> {
const candidates = [
{ command: 'python', args: [scriptPath, ...args], matplotlibConfigDirIndex: 2 },
{ command: 'py', args: ['-3', scriptPath, ...args], matplotlibConfigDirIndex: 4 },
]
const failures: string[] = []
for (const candidate of candidates) {
try {
return await spawnProcess(candidate.command, candidate.args, candidate.matplotlibConfigDirIndex, signal)
} catch (error) {
const message = error instanceof Error ? error.message : String(error)
failures.push(`${candidate.command} failed: ${message}`)
}
}
throw new Error(`Unable to execute Python for matplotlib render. ${failures.join(' | ')}`)
}
function spawnProcess(
command: string,
args: string[],
matplotlibConfigDirIndex: number,
signal?: AbortSignal,
): Promise<{ stdout: string; stderr: string }> {
return new Promise((resolve, reject) => {
if (signal?.aborted) {
reject(new StudioRunCancelledError(readAbortReason(signal)))
return
}
const matplotlibConfigDir = args[matplotlibConfigDirIndex]
const child = spawn(command, args, {
stdio: ['ignore', 'pipe', 'pipe'],
env: {
...process.env,
MPLCONFIGDIR: matplotlibConfigDir ?? process.env.MPLCONFIGDIR,
},
})
let stdout = ''
let stderr = ''
let finished = false
const cleanupAbort = () => {
signal?.removeEventListener('abort', handleAbort)
}
const settleReject = (error: Error) => {
if (finished) {
return
}
finished = true
cleanupAbort()
reject(error)
}
const settleResolve = (value: { stdout: string; stderr: string }) => {
if (finished) {
return
}
finished = true
cleanupAbort()
resolve(value)
}
const handleAbort = () => {
child.kill('SIGTERM')
settleReject(new StudioRunCancelledError(readAbortReason(signal)))
}
signal?.addEventListener('abort', handleAbort, { once: true })
child.stdout.on('data', (chunk) => {
stdout += String(chunk)
})
child.stderr.on('data', (chunk) => {
stderr += String(chunk)
})
child.on('error', (error) => {
settleReject(error instanceof Error ? error : new Error(String(error)))
})
child.on('close', (code) => {
if (finished) {
return
}
if (code === 0) {
settleResolve({ stdout, stderr })
return
}
settleReject(new Error(stderr.trim() || `Python process exited with code ${code}`))
})
})
}
function parseJsonLine(stdout: string, prefix: string): unknown {
const line = stdout.split(/\r?\n/).find((entry) => entry.startsWith(prefix))
if (!line) {
return undefined
}
return JSON.parse(line.slice(prefix.length))
}
function buildExecutorScript(): string {
return [
'import json',
'import os',
'import sys',
'import matplotlib',
"matplotlib.use('Agg')",
'import matplotlib.pyplot as plt',
'',
'source_path = sys.argv[1]',
'output_dir = sys.argv[2]',
'mpl_config_dir = sys.argv[3] if len(sys.argv) > 3 else None',
'if mpl_config_dir:',
' os.makedirs(mpl_config_dir, exist_ok=True)',
' os.environ["MPLCONFIGDIR"] = mpl_config_dir',
'os.makedirs(output_dir, exist_ok=True)',
'os.chdir(output_dir)',
"namespace = {'plt': plt, '__name__': '__main__', '__file__': source_path}",
'',
'with open(source_path, "r", encoding="utf-8") as f:',
' source = f.read()',
'',
'exec(compile(source, source_path, "exec"), namespace)',
'',
'figure_numbers = plt.get_fignums()',
'outputs = []',
'for index, figure_number in enumerate(figure_numbers, start=1):',
' figure = plt.figure(figure_number)',
' output_path = os.path.join(output_dir, f"plot_{index}.png")',
' figure.savefig(output_path, dpi=160, bbox_inches="tight")',
' outputs.append(output_path)',
'',
'if not outputs:',
' outputs = [',
' os.path.join(output_dir, name)',
' for name in sorted(os.listdir(output_dir))',
' if name.lower().endswith(".png")',
' ]',
'',
'if not outputs:',
' raise RuntimeError("No matplotlib figures or PNG outputs were produced by the script")',
'',
'print("PLOT_OUTPUTS_JSON=" + json.dumps(outputs, ensure_ascii=False))',
].join('\n')
}
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