Uploading

Upload files from your local filesystem to sandboxes. This is useful for transferring data files, scripts, or any local files you want to use in your sandbox.

Overview

File uploading is ideal for:

Transferring local data files to sandboxes
Uploading scripts and code files
Moving configuration files
Transferring datasets or models

Upload supports both text and binary files. Large files may take longer to upload - set appropriate timeouts for large transfers.

Basic Upload

Upload a file from local to sandbox:

Python
JavaScript

from hopx_ai import Sandbox

sandbox = Sandbox.create(template="code-interpreter")

# Upload a local file
sandbox.files.upload('./local_data.csv', '/workspace/data.csv')
print("File uploaded successfully")

# Verify upload
if sandbox.files.exists('/workspace/data.csv'):
    content = sandbox.files.read('/workspace/data.csv')
    print(f"Uploaded content: {content[:100]}...")

sandbox.kill()

import { Sandbox } from '@hopx-ai/sdk';

const sandbox = await Sandbox.create({ template: 'code-interpreter' });

// Note: JavaScript SDK upload may require FormData implementation
// For now, use write() with file content
import * as fs from 'fs';

const localContent = fs.readFileSync('./local_data.csv', 'utf-8');
await sandbox.files.write('/workspace/data.csv', localContent);
console.log('File uploaded successfully');

// Verify upload
const exists = await sandbox.files.exists('/workspace/data.csv');
if (exists) {
  const content = await sandbox.files.read('/workspace/data.csv');
  console.log(`Uploaded content: ${content.substring(0, 100)}...`);
}

await sandbox.kill();

Upload with Timeout

Set timeout for large file uploads:

Python
JavaScript

from hopx_ai import Sandbox

sandbox = Sandbox.create(template="code-interpreter")

# Upload large file with extended timeout
sandbox.files.upload('./large_dataset.zip', '/workspace/dataset.zip', timeout=300)
print("Large file uploaded")

# Verify
files = sandbox.files.list('/workspace')
for f in files:
    if f.name == 'dataset.zip':
        print(f"Uploaded: {f.name} ({f.size_mb:.2f} MB)")

sandbox.kill()

import { Sandbox } from '@hopx-ai/sdk';
import * as fs from 'fs';

const sandbox = await Sandbox.create({ template: 'code-interpreter' });

// Upload large file (use writeBytes for binary)
const largeContent = fs.readFileSync('./large_dataset.zip');
await sandbox.files.writeBytes('/workspace/dataset.zip', largeContent);
console.log('Large file uploaded');

// Verify
const files = await sandbox.files.list('/workspace');
const datasetFile = files.find(f => f.name === 'dataset.zip');
if (datasetFile) {
  console.log(`Uploaded: ${datasetFile.name} (${(datasetFile.size / 1024 / 1024).toFixed(2)} MB)`);
}

await sandbox.kill();

Upload Multiple Files

Upload multiple files in a loop:

Python
JavaScript

from hopx_ai import Sandbox
import os

sandbox = Sandbox.create(template="code-interpreter")

# List of files to upload
files_to_upload = [
    ('./config.json', '/workspace/config.json'),
    ('./data.csv', '/workspace/data.csv'),
    ('./script.py', '/workspace/script.py')
]

# Upload all files
for local_path, remote_path in files_to_upload:
    if os.path.exists(local_path):
        sandbox.files.upload(local_path, remote_path)
        print(f"✅ Uploaded: {local_path} → {remote_path}")
    else:
        print(f"⚠️  File not found: {local_path}")

# Verify all uploads
files = sandbox.files.list('/workspace')
print(f"\nUploaded {len(files)} files")

sandbox.kill()

import { Sandbox } from '@hopx-ai/sdk';
import * as fs from 'fs';
import * as path from 'path';

const sandbox = await Sandbox.create({ template: 'code-interpreter' });

// List of files to upload
const filesToUpload = [
  ['./config.json', '/workspace/config.json'],
  ['./data.csv', '/workspace/data.csv'],
  ['./script.py', '/workspace/script.py']
];

// Upload all files
for (const [localPath, remotePath] of filesToUpload) {
  try {
    if (fs.existsSync(localPath)) {
      const content = fs.readFileSync(localPath, 'utf-8');
      await sandbox.files.write(remotePath, content);
      console.log(`✅ Uploaded: ${localPath} → ${remotePath}`);
    } else {
      console.log(`⚠️  File not found: ${localPath}`);
    }
  } catch (error) {
    console.error(`Error uploading ${localPath}: ${error.message}`);
  }
}

// Verify all uploads
const files = await sandbox.files.list('/workspace');
console.log(`\nUploaded ${files.length} files`);

await sandbox.kill();

Upload Binary Files

Upload binary files (images, PDFs, etc.):

Python
JavaScript

from hopx_ai import Sandbox

sandbox = Sandbox.create(template="code-interpreter")

# Upload image file
sandbox.files.upload('./image.png', '/workspace/image.png', timeout=60)
print("Image uploaded")

# Upload PDF
sandbox.files.upload('./document.pdf', '/workspace/document.pdf', timeout=60)
print("PDF uploaded")

# Verify binary files
files = sandbox.files.list('/workspace')
for f in files:
    if f.name.endswith(('.png', '.pdf')):
        print(f"Binary file: {f.name} ({f.size_kb:.2f} KB)")

sandbox.kill()

import { Sandbox } from '@hopx-ai/sdk';
import * as fs from 'fs';

const sandbox = await Sandbox.create({ template: 'code-interpreter' });

// Upload image file
const imageData = fs.readFileSync('./image.png');
await sandbox.files.writeBytes('/workspace/image.png', imageData);
console.log('Image uploaded');

// Upload PDF
const pdfData = fs.readFileSync('./document.pdf');
await sandbox.files.writeBytes('/workspace/document.pdf', pdfData);
console.log('PDF uploaded');

// Verify binary files
const files = await sandbox.files.list('/workspace');
for (const f of files) {
  if (f.name.endsWith('.png') || f.name.endsWith('.pdf')) {
    console.log(`Binary file: ${f.name} (${(f.size / 1024).toFixed(2)} KB)`);
  }
}

await sandbox.kill();

Upload to Specific Directory

Upload files to specific directories:

Python
JavaScript

from hopx_ai import Sandbox

sandbox = Sandbox.create(template="code-interpreter")

# Create directory structure
sandbox.files.mkdir('/workspace/project')
sandbox.files.mkdir('/workspace/project/data')
sandbox.files.mkdir('/workspace/project/src')

# Upload to specific directories
sandbox.files.upload('./dataset.csv', '/workspace/project/data/dataset.csv')
sandbox.files.upload('./main.py', '/workspace/project/src/main.py')
sandbox.files.upload('./config.json', '/workspace/project/config.json')

# Verify structure
print("Project structure:")
for path in ['/workspace/project', '/workspace/project/data', '/workspace/project/src']:
    files = sandbox.files.list(path)
    print(f"\n{path}:")
    for f in files:
        print(f"  {f.name}")

sandbox.kill()

import { Sandbox } from '@hopx-ai/sdk';
import * as fs from 'fs';

const sandbox = await Sandbox.create({ template: 'code-interpreter' });

// Create directory structure
await sandbox.files.mkdir('/workspace/project');
await sandbox.files.mkdir('/workspace/project/data');
await sandbox.files.mkdir('/workspace/project/src');

// Upload to specific directories
const datasetContent = fs.readFileSync('./dataset.csv', 'utf-8');
await sandbox.files.write('/workspace/project/data/dataset.csv', datasetContent);

const mainContent = fs.readFileSync('./main.py', 'utf-8');
await sandbox.files.write('/workspace/project/src/main.py', mainContent);

const configContent = fs.readFileSync('./config.json', 'utf-8');
await sandbox.files.write('/workspace/project/config.json', configContent);

// Verify structure
console.log('Project structure:');
for (const dirPath of ['/workspace/project', '/workspace/project/data', '/workspace/project/src']) {
  const files = await sandbox.files.list(dirPath);
  console.log(`\n${dirPath}:`);
  for (const f of files) {
    console.log(`  ${f.name}`);
  }
}

await sandbox.kill();

Error Handling

Handle upload errors:

Python
JavaScript

from hopx_ai import Sandbox
from hopx_ai.errors import FileOperationError
import os

sandbox = Sandbox.create(template="code-interpreter")

local_file = './data.csv'

try:
    # Check if local file exists
    if not os.path.exists(local_file):
        print(f"Local file not found: {local_file}")
    else:
        # Upload with error handling
        sandbox.files.upload(local_file, '/workspace/data.csv', timeout=120)
        print("Upload successful")
        
except FileOperationError as e:
    print(f"Upload failed: {e}")
except Exception as e:
    print(f"Error: {e}")

sandbox.kill()

import { Sandbox } from '@hopx-ai/sdk';
import * as fs from 'fs';
import { FileOperationError } from '@hopx-ai/sdk';

const sandbox = await Sandbox.create({ template: 'code-interpreter' });

const localFile = './data.csv';

try {
  // Check if local file exists
  if (!fs.existsSync(localFile)) {
    console.error(`Local file not found: ${localFile}`);
  } else {
    // Upload with error handling
    const content = fs.readFileSync(localFile, 'utf-8');
    await sandbox.files.write('/workspace/data.csv', content);
    console.log('Upload successful');
  }
} catch (error) {
  if (error instanceof FileOperationError) {
    console.error(`Upload failed: ${error.message}`);
  } else {
    console.error(`Error: ${error.message}`);
  }
}

await sandbox.kill();

Complete Example

Here’s a complete upload workflow:

Python
JavaScript

from hopx_ai import Sandbox
import os

sandbox = Sandbox.create(template="code-interpreter")

# Create project structure
sandbox.files.mkdir('/workspace/ml-project')
sandbox.files.mkdir('/workspace/ml-project/data')
sandbox.files.mkdir('/workspace/ml-project/models')

# Upload project files
files_to_upload = {
    './train.py': '/workspace/ml-project/train.py',
    './data/train.csv': '/workspace/ml-project/data/train.csv',
    './data/test.csv': '/workspace/ml-project/data/test.csv',
    './config.yaml': '/workspace/ml-project/config.yaml'
}

print("📤 Uploading files...")
for local_path, remote_path in files_to_upload.items():
    if os.path.exists(local_path):
        try:
            sandbox.files.upload(local_path, remote_path, timeout=120)
            file_size = os.path.getsize(local_path) / 1024
            print(f"  ✅ {local_path} → {remote_path} ({file_size:.2f} KB)")
        except Exception as e:
            print(f"  ❌ Failed to upload {local_path}: {e}")
    else:
        print(f"  ⚠️  File not found: {local_path}")

# Verify uploads
print("\n📋 Verifying uploads...")
files = sandbox.files.list('/workspace/ml-project')
total_size = 0
for f in files:
    if f.is_file:
        total_size += f.size
        print(f"  📄 {f.path} ({f.size_kb:.2f} KB)")

print(f"\n✅ Total uploaded: {total_size / 1024:.2f} KB")

sandbox.kill()

import { Sandbox } from '@hopx-ai/sdk';
import * as fs from 'fs';
import * as path from 'path';

const sandbox = await Sandbox.create({ template: 'code-interpreter' });

// Create project structure
await sandbox.files.mkdir('/workspace/ml-project');
await sandbox.files.mkdir('/workspace/ml-project/data');
await sandbox.files.mkdir('/workspace/ml-project/models');

// Upload project files
const filesToUpload = {
  './train.py': '/workspace/ml-project/train.py',
  './data/train.csv': '/workspace/ml-project/data/train.csv',
  './data/test.csv': '/workspace/ml-project/data/test.csv',
  './config.yaml': '/workspace/ml-project/config.yaml'
};

console.log('📤 Uploading files...');
let totalSize = 0;

for (const [localPath, remotePath] of Object.entries(filesToUpload)) {
  try {
    if (fs.existsSync(localPath)) {
      const stats = fs.statSync(localPath);
      const content = fs.readFileSync(localPath, 'utf-8');
      await sandbox.files.write(remotePath, content);
      const fileSize = stats.size / 1024;
      console.log(`  ✅ ${localPath} → ${remotePath} (${fileSize.toFixed(2)} KB)`);
      totalSize += stats.size;
    } else {
      console.log(`  ⚠️  File not found: ${localPath}`);
    }
  } catch (error) {
    console.error(`  ❌ Failed to upload ${localPath}: ${error.message}`);
  }
}

// Verify uploads
console.log('\n📋 Verifying uploads...');
const files = await sandbox.files.list('/workspace/ml-project');
for (const f of files) {
  if (f.isFile) {
    console.log(`  📄 ${f.path} (${(f.size / 1024).toFixed(2)} KB)`);
  }
}

console.log(`\n✅ Total uploaded: ${(totalSize / 1024).toFixed(2)} KB`);

await sandbox.kill();

Best Practices

1. Check Local File Existence

Always verify local files exist before attempting upload to avoid errors.

2. Set Appropriate Timeouts

For large files, set extended timeouts (60+ seconds) to avoid connection timeouts.

3. Create Directories First

Use files.mkdir() to create target directories before uploading files.

4. Handle Errors Gracefully

Wrap uploads in try/catch blocks to handle network errors, file not found, etc.

5. Verify Uploads

After uploading, verify files exist and check their sizes to ensure successful transfer.

Writing Files - Write files directly in sandboxes
Downloading Files - Download files from sandboxes
Listing Files - List directory contents
SDK: sandbox.files.upload() - Python SDK method
CLI File Operations - File operations from CLI

Next Steps

Learn about Downloading Files to retrieve files from sandboxes
Explore Writing Files for programmatic file creation
Review Listing Files to browse uploaded files

Home

Get Started

Sandboxes

Code Execution

Filesystem

Commands

Environment Variables

Templates

Desktop Automation

Terminal

Observability

Cache

Overview

Basic Upload

Upload with Timeout

Upload Multiple Files

Upload Binary Files

Upload to Specific Directory

Error Handling

Complete Example

Best Practices

Next Steps

Home

Get Started

Sandboxes

Code Execution

Filesystem

Commands

Environment Variables

Templates

Desktop Automation

Terminal

Observability

Cache

​Overview

​Basic Upload

​Upload with Timeout

​Upload Multiple Files

​Upload Binary Files

​Upload to Specific Directory

​Error Handling

​Complete Example

​Best Practices

​Related

​Next Steps

Overview

Basic Upload

Upload with Timeout

Upload Multiple Files

Upload Binary Files

Upload to Specific Directory

Error Handling

Complete Example

Best Practices

Related

Next Steps