[](https://opensource.org/licenses/Apache-2.0) 
# async_obj
A minimalist and lightweight Python wrapper to make any function -standalone or within an object- asynchronous.
If you are also tired of adding a whole bunch of code for every single case of simple threading, this small wrapper is my remedy. Requires >=Python 3.8.
`async obj` enables:
- Simply running a function in a dedicated thread.
- Check for completion of the function.
- Block until the function finishes.
- Receiving the returned result.
- In case of an exception, raising the exception on demand (whenever the result is requested).
Advantages:
- No compatibility concerns (e.g., `asyncio`), only depends on a few standard Python libraries.
- Essentially a 2 liner, no decorators or keywords.
- Mimics an object or a function and does not create a copy, hence minimum impact on memory and performance.
## Installation
Easiest way is to use `pip`, only requirement is Python >=3.8.
```bash
pip install async_obj
```
## Examples
- Run a function asynchronous and check for completion. Then collect the result.
```python
from async_obj import async_obj
from time import sleep
def dummy_func(x:int):
sleep(3)
return x * x
#define the async version of the dummy function
async_dummy = async_obj(dummy_func)
print("Starting async function...")
async_dummy(2) # Run dummy_func asynchronously
print("Started.")
while True:
print("Checking whether the async function is done...")
if async_dummy.async_obj_is_done():
print("Async function is done!")
print("Result: ", async_dummy.async_obj_get_result(), " Expected Result: 4")
break
else:
print("Async function is still running...")
sleep(1)
```
---
- Alternatively, block until the function is completed, also retrieve any results.
```python
print("Starting async function...")
async_dummy(4) # Run dummy_func asynchronously
print("Started.")
print("Blocking until the function finishes...")
result = async_dummy.async_obj_wait()
print("Function finished.")
print("Result: ", result, " Expected Result: 16")
```
---
- Raise propagated exceptions, whenever the result is requested either with `async_obj_get_result()` or with `async_obj_wait()`.
```python
print("Starting async function with an exception being expected...")
async_dummy(None) # pass an invalid argument to raise an exception
print("Started.")
print("Blocking until the function finishes...")
try:
result = async_dummy.async_obj_wait()
except Exception as e:
print("Function finished with an exception: ", str(e))
else:
print("Function finished without an exception, which is unexpected.")
```
---
- Same functionalities are available for functions within class instances.
```python
class dummy_class:
x = None
def __init__(self):
self.x = 5
def dummy_func(self, y:int):
sleep(3)
return self.x * y
dummy_instance = dummy_class()
#define the async version of the dummy function within the dummy class instance
async_dummy = async_obj(dummy_instance)
print("Starting async function...")
async_dummy.dummy_func(4) # Run dummy_func asynchronously
print("Started.")
print("Blocking until the function finishes...")
result = async_dummy.async_obj_wait()
print("Function finished.")
print("Result: ", result, " Expected Result: 20")
```
## To Do
1. Providing same concurrency functionalities for `getter`, `setter` and similar extension.
2. Improve autocompletion support for better IDE convenience.
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"description": "[](https://opensource.org/licenses/Apache-2.0) \r\n\r\n# async_obj\r\n\r\nA minimalist and lightweight Python wrapper to make any function -standalone or within an object- asynchronous.\r\n\r\nIf you are also tired of adding a whole bunch of code for every single case of simple threading, this small wrapper is my remedy. Requires >=Python 3.8.\r\n\r\n`async obj` enables:\r\n- Simply running a function in a dedicated thread.\r\n- Check for completion of the function.\r\n- Block until the function finishes.\r\n- Receiving the returned result.\r\n- In case of an exception, raising the exception on demand (whenever the result is requested).\r\n\r\nAdvantages:\r\n- No compatibility concerns (e.g., `asyncio`), only depends on a few standard Python libraries.\r\n- Essentially a 2 liner, no decorators or keywords.\r\n- Mimics an object or a function and does not create a copy, hence minimum impact on memory and performance.\r\n\r\n## Installation\r\nEasiest way is to use `pip`, only requirement is Python >=3.8.\r\n\r\n```bash\r\npip install async_obj\r\n```\r\n\r\n## Examples\r\n\r\n- Run a function asynchronous and check for completion. Then collect the result.\r\n```python\r\nfrom async_obj import async_obj\r\nfrom time import sleep\r\n\r\ndef dummy_func(x:int):\r\n sleep(3)\r\n return x * x\r\n\r\n#define the async version of the dummy function\r\nasync_dummy = async_obj(dummy_func)\r\n\r\nprint(\"Starting async function...\")\r\nasync_dummy(2) # Run dummy_func asynchronously\r\nprint(\"Started.\")\r\n\r\nwhile True:\r\n print(\"Checking whether the async function is done...\")\r\n if async_dummy.async_obj_is_done():\r\n print(\"Async function is done!\")\r\n print(\"Result: \", async_dummy.async_obj_get_result(), \" Expected Result: 4\")\r\n break\r\n else:\r\n print(\"Async function is still running...\")\r\n sleep(1)\r\n```\r\n\r\n---\r\n- Alternatively, block until the function is completed, also retrieve any results.\r\n\r\n```python\r\nprint(\"Starting async function...\")\r\nasync_dummy(4) # Run dummy_func asynchronously\r\nprint(\"Started.\")\r\nprint(\"Blocking until the function finishes...\")\r\nresult = async_dummy.async_obj_wait()\r\nprint(\"Function finished.\")\r\nprint(\"Result: \", result, \" Expected Result: 16\")\r\n```\r\n\r\n---\r\n- Raise propagated exceptions, whenever the result is requested either with `async_obj_get_result()` or with `async_obj_wait()`.\r\n\r\n```python\r\nprint(\"Starting async function with an exception being expected...\")\r\nasync_dummy(None) # pass an invalid argument to raise an exception\r\nprint(\"Started.\")\r\nprint(\"Blocking until the function finishes...\")\r\ntry:\r\n result = async_dummy.async_obj_wait()\r\nexcept Exception as e:\r\n print(\"Function finished with an exception: \", str(e))\r\nelse:\r\n print(\"Function finished without an exception, which is unexpected.\")\r\n```\r\n---\r\n- Same functionalities are available for functions within class instances.\r\n```python\r\nclass dummy_class:\r\n x = None\r\n\r\n def __init__(self):\r\n self.x = 5\r\n\r\n def dummy_func(self, y:int):\r\n sleep(3)\r\n return self.x * y\r\n\r\ndummy_instance = dummy_class()\r\n#define the async version of the dummy function within the dummy class instance\r\nasync_dummy = async_obj(dummy_instance)\r\n\r\nprint(\"Starting async function...\")\r\nasync_dummy.dummy_func(4) # Run dummy_func asynchronously\r\nprint(\"Started.\")\r\nprint(\"Blocking until the function finishes...\")\r\nresult = async_dummy.async_obj_wait()\r\nprint(\"Function finished.\")\r\nprint(\"Result: \", result, \" Expected Result: 20\")\r\n```\r\n\r\n## To Do\r\n1. Providing same concurrency functionalities for `getter`, `setter` and similar extension.\r\n2. Improve autocompletion support for better IDE convenience.\r\n",
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