Install & Compatibility
Where this runs
tested against v0.3.18 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.95 runs
build_error
glibcpy 3.10–3.95 runs
installs and imports cleanly · install 20.5s · import 0.000s · 536MB
544MB installed
● package 544MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
IOHandler
✓ from iotools import IOHandler
✗ from pyiotools import IOHandler
This quickstart demonstrates the core `IOHandler` for defining and (simulated) parsing arguments, and the `Cache` utility for simple persistent key-value storage. It uses environment variables to make the example interactive and runnable.
import os
from iotools import IOHandler, Cache
# 1. Using IOHandler (similar to argparse)
# Create an IOHandler instance for input collection
program_io = IOHandler(
'my_app',
'A simple application demonstrating iotools input handling.'
)
program_io.add_argument('--name', help='Your name', default='Guest')
program_io.add_argument('--verbose', action='store_true', help='Enable verbose output')
# In a real script, this would parse sys.argv.
# For programmatic quickstart, we simulate parsed arguments.
class MockArgs:
def __init__(self, name, verbose):
self.name = name
self.verbose = verbose
# Use environment variables to make it runnable for testing
args = MockArgs(
name=os.environ.get('IOT_NAME', 'User'),
verbose=os.environ.get('IOT_VERBOSE', 'False').lower() == 'true'
)
print(f"Hello, {args.name}!")
if args.verbose:
print("Verbose output enabled.")
# 2. Using Cache for persistent data storage
cache_name = os.environ.get('IOT_CACHE_NAME', 'my_app_data')
my_cache = Cache(cache_name)
# Put and get data
my_cache.put('favorite_color', os.environ.get('IOT_COLOR', 'blue'))
print(f"Favorite color from cache: {my_cache.get('favorite_color')}")
# Update data
my_cache.put('favorite_color', 'red')
print(f"Updated favorite color: {my_cache.get('favorite_color')}")
# Pop data
popped_color = my_cache.pop('favorite_color')
print(f"Popped favorite color: {popped_color}")
print(f"Is favorite_color still in cache? {my_cache.get('favorite_color', 'Not Found')}")
pyio --version
Debug
Known issues
breakingThe `pyiotools` library is explicitly stated as being 'under development'. Its API will likely undergo significant changes that may break existing code, and documentation may not always be up-to-date with the latest changes.fixUsers should expect frequent API changes and be prepared to update their code with each new release. Monitor the GitHub repository for updates and review release notes carefully.
affects: 0.x.x (all current versions)
gotchaThe `Cache` and `Serializer` classes utilize `dill` for serialization. While `pyiotools` itself does not list `dill` as a direct dependency on PyPI, it is an implicit dependency for these features. If you use `Cache` or `Serializer`, you might need to install `dill` explicitly.fixEnsure `dill` is installed: `pip install dill` if you plan to use `Cache` or `Serializer` features.
affects: 0.x.x (all versions using Cache/Serializer)
gotchaNaming your Python script the same as the imported module (e.g., `iotools.py` importing `from iotools import IOHandler`) can lead to import errors or circular import issues, as Python might try to import your local file instead of the installed package.fixAlways use a different name for your script files than the libraries you are importing (e.g., `my_script.py` instead of `iotools.py`).
affects: All versions of Python
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Version history
0.3.18latest on PyPI · released Feb 1, 2021
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Dependencies
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