anyenv 2.0.5

Compatibility layer for some basic operations to allow painless operation in PyOdide and Python pre-releases

AnyEnv

Read the documentation!

Overview

AnyEnv provides a unified interface for executing code across different environments - local, subprocess, Docker containers, remote sandboxes, and more. Choose the right execution environment for your needs without changing your code.

Getting Started

HTTP Downloads

AnyEnv provides a unified interface for HTTP requests that works across different environments (including PyOdide):

from anyenv import get, post, download, get_json, get_text, get_bytes

# Simple GET request
response = await get("https://api.example.com/data")
print(response.status_code, response.text)

# Get JSON data directly
data = await get_json("https://api.example.com/users")
print(data)  # Parsed JSON object

# Get text content
text = await get_text("https://example.com/page.html")

# Get binary data
data = await get_bytes("https://example.com/image.png")

# Download files
await download("https://example.com/file.zip", "local_file.zip")

# POST requests
response = await post("https://api.example.com/create", json={"name": "test"})

# POST JSON data directly
result = await post_json("https://api.example.com/api", {"key": "value"})

Synchronous Versions

All async functions have synchronous counterparts:

from anyenv import get_sync, get_json_sync, download_sync

# Synchronous versions (useful in non-async contexts)
response = get_sync("https://api.example.com/data")
data = get_json_sync("https://api.example.com/users")
download_sync("https://example.com/file.zip", "local_file.zip")

Error Handling

from anyenv import get, HttpError, RequestError, ResponseError

try:
    response = await get("https://api.example.com/data")
except RequestError as e:
    print(f"Request failed: {e}")
except ResponseError as e:
    print(f"Server error: {e}")
except HttpError as e:
    print(f"HTTP error: {e}")

JSON Tools

Cross-platform JSON handling that works in all environments:

from anyenv import load_json, dump_json, JsonLoadError, JsonDumpError

# Load JSON from various sources
data = load_json('{"key": "value"}')  # From string
data = load_json(Path("config.json"))  # From file
data = load_json(b'{"key": "value"}')  # From bytes

# Dump JSON to various targets
json_str = dump_json(data)  # To string
dump_json(data, Path("output.json"))  # To file
json_bytes = dump_json(data, return_bytes=True)  # To bytes

# Error handling
try:
    data = load_json('invalid json')
except JsonLoadError as e:
    print(f"Failed to parse JSON: {e}")

try:
    dump_json(set())  # Sets aren't JSON serializable
except JsonDumpError as e:
    print(f"Failed to serialize: {e}")

Package Installation

Programmatically install Python packages across environments:

from anyenv import install, install_sync

# Install packages asynchronously
await install("requests")
await install(["numpy", "pandas"])
await install("package>=1.0.0")

# Synchronous installation
install_sync("matplotlib")
install_sync(["scipy", "sklearn"])

# Install with specific options
await install("package", upgrade=True, user=True)

Async Utilities

Utilities for running async/sync code and managing concurrency:

from anyenv import run_sync, run_sync_in_thread, gather, call_and_gather

# Run async function from sync context
result = run_sync(async_function())

# Run sync function in thread from async context
result = await run_sync_in_thread(sync_function, arg1, arg2)

# Enhanced gather with better error handling
results = await gather(
    async_func1(),
    async_func2(),
    async_func3(),
    return_exceptions=True
)

# Call function and gather results
func_results = await call_and_gather(
    my_function,
    [arg1, arg2, arg3],  # Arguments to call function with
    max_workers=5
)

Threading and Concurrency

Manage concurrent operations with ThreadGroup and spawners:

from anyenv import ThreadGroup, function_spawner, method_spawner

# ThreadGroup for managing multiple concurrent operations
async with ThreadGroup() as group:
    # Add functions to run concurrently
    group.spawn(some_function, arg1, arg2)
    group.spawn(another_function, arg3)

    # Wait for all to complete
    results = await group.gather()

# Function spawner for reusable concurrent execution
spawner = function_spawner(my_function, max_workers=10)
results = await spawner([arg1, arg2, arg3, arg4])

# Method spawner for object methods
obj_spawner = method_spawner(my_object.method, max_workers=5)
results = await obj_spawner([data1, data2, data3])

Testing Utilities

Tools for testing and development:

from anyenv import open_in_playground

# Open interactive playground for testing (where supported)
await open_in_playground(locals())

Backend Selection

Choose HTTP backends based on environment:

from anyenv import get_backend, HttpBackend

# Get the best available backend for current environment
backend = get_backend()

# Use specific backend
backend = get_backend("httpx")  # or "urllib", "requests"
response = await backend.get("https://example.com")

Environment Compatibility

All functionality automatically adapts to the execution environment:

• PyOdide: Uses browser-compatible implementations
• Standard Python: Uses optimal libraries (httpx, etc.)
• Limited environments: Falls back to stdlib implementations
• Async contexts: Provides async implementations
• Sync contexts: Provides synchronous alternatives

This ensures your code works consistently across web browsers, Jupyter notebooks, serverless functions, and traditional Python environments.