| Name | psygnal JSON |
| Version |
0.12.0
JSON |
| download |
| home_page | None |
| Summary | Fast python callback/event system modeled after Qt Signals |
| upload_time | 2025-02-03 15:53:24 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | BSD 3-Clause License |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# psygnal
[](https://github.com/pyapp-kit/psygnal/raw/master/LICENSE)
[](https://pypi.org/project/psygnal)
[](https://github.com/conda-forge/psygnal-feedstock)
[](https://python.org)
[](https://github.com/pyapp-kit/psygnal/actions/workflows/test.yml)
[](https://codecov.io/gh/pyapp-kit/psygnal)
[](https://psygnal.readthedocs.io/en/latest/?badge=latest)
[](https://codspeed.io/pyapp-kit/psygnal)
Psygnal (pronounced "signal") is a pure python implementation of the [observer
pattern](https://en.wikipedia.org/wiki/Observer_pattern), with the API of
[Qt-style Signals](https://doc.qt.io/qt-5/signalsandslots.html) with (optional)
signature and type checking, and support for threading. It has no dependencies.
> This library does ***not*** require or use Qt in any way, It simply implements
> a similar observer pattern API.
## Documentation
https://psygnal.readthedocs.io/
### Install
```sh
pip install psygnal
```
```sh
conda install -c conda-forge psygnal
```
## Usage
The [observer pattern](https://en.wikipedia.org/wiki/Observer_pattern) is a software design pattern in which an object maintains a list of its dependents ("**observers**"), and notifies them of any state changes – usually by calling a **callback function** provided by the observer.
Here is a simple example of using psygnal:
```python
from psygnal import Signal
class MyObject:
# define one or more signals as class attributes
value_changed = Signal(str)
# create an instance
my_obj = MyObject()
# You (or others) can connect callbacks to your signals
@my_obj.value_changed.connect
def on_change(new_value: str):
print(f"The value changed to {new_value}!")
# The object may now emit signals when appropriate,
# (for example in a setter method)
my_obj.value_changed.emit('hi') # prints "The value changed to hi!"
```
Much more detail available in the [documentation](https://psygnal.readthedocs.io/)!
### Evented Dataclasses
A particularly nice usage of the signal pattern is to emit signals whenever a
field of a dataclass changes. Psygnal provides an `@evented` decorator that will
emit a signal whenever a field changes. It is compatible with `dataclasses`
from [the standard library](https://docs.python.org/3/library/dataclasses.html),
as well as [attrs](https://www.attrs.org/en/stable/), and
[pydantic](https://pydantic-docs.helpmanual.io):
```python
from psygnal import evented
from dataclasses import dataclass
@evented
@dataclass
class Person:
name: str
age: int = 0
person = Person('John', age=30)
# connect callbacks
@person.events.age.connect
def _on_age_change(new_age: str):
print(f"Age changed to {new_age}")
person.age = 31 # prints: Age changed to 31
```
See the [dataclass documentation](https://psygnal.readthedocs.io/en/latest/dataclasses/) for more details.
### Evented Containers
`psygnal.containers` provides evented versions of mutable data structures
(`dict`, `list`, `set`), for cases when you need to monitor mutation:
```python
from psygnal.containers import EventedList
my_list = EventedList([1, 2, 3, 4, 5])
my_list.events.inserted.connect(lambda i, val: print(f"Inserted {val} at index {i}"))
my_list.events.removed.connect(lambda i, val: print(f"Removed {val} at index {i}"))
my_list.append(6) # Output: Inserted 6 at index 5
my_list.pop() # Output: Removed 6 at index 5
```
See the
[evented containers documentation](https://psygnal.readthedocs.io/en/latest/API/containers/)
for more details.
## Benchmark history
https://pyapp-kit.github.io/psygnal/
and
https://codspeed.io/pyapp-kit/psygnal
## Developers
### Compiling
While `psygnal` is a pure python package, it is compiled with mypyc to increase
performance. To test the compiled version locally, you can run:
```bash
make build
```
(which is just an alias for `HATCH_BUILD_HOOKS_ENABLE=1 pip install -e .`)
### Debugging
To disable all compiled files and run the pure python version,
you may run:
```bash
python -c "import psygnal.utils; psygnal.utils.decompile()"
```
To return the compiled version, run:
```bash
python -c "import psygnal.utils; psygnal.utils.recompile()"
```
The `psygnal._compiled` variable will tell you if you're using the compiled
version or not.
Raw data
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"description": "# psygnal\n\n[](https://github.com/pyapp-kit/psygnal/raw/master/LICENSE)\n[](https://pypi.org/project/psygnal)\n[](https://github.com/conda-forge/psygnal-feedstock)\n[](https://python.org)\n[](https://github.com/pyapp-kit/psygnal/actions/workflows/test.yml)\n[](https://codecov.io/gh/pyapp-kit/psygnal)\n[](https://psygnal.readthedocs.io/en/latest/?badge=latest)\n[](https://codspeed.io/pyapp-kit/psygnal)\n\nPsygnal (pronounced \"signal\") is a pure python implementation of the [observer\npattern](https://en.wikipedia.org/wiki/Observer_pattern), with the API of\n[Qt-style Signals](https://doc.qt.io/qt-5/signalsandslots.html) with (optional)\nsignature and type checking, and support for threading. It has no dependencies.\n\n> This library does ***not*** require or use Qt in any way, It simply implements\n> a similar observer pattern API.\n\n## Documentation\n\nhttps://psygnal.readthedocs.io/\n\n### Install\n\n```sh\npip install psygnal\n```\n\n```sh\nconda install -c conda-forge psygnal\n```\n\n## Usage\n\nThe [observer pattern](https://en.wikipedia.org/wiki/Observer_pattern) is a software design pattern in which an object maintains a list of its dependents (\"**observers**\"), and notifies them of any state changes \u2013 usually by calling a **callback function** provided by the observer.\n\nHere is a simple example of using psygnal:\n\n```python\nfrom psygnal import Signal\n\nclass MyObject:\n # define one or more signals as class attributes\n value_changed = Signal(str)\n\n# create an instance\nmy_obj = MyObject()\n\n# You (or others) can connect callbacks to your signals\n@my_obj.value_changed.connect\ndef on_change(new_value: str):\n print(f\"The value changed to {new_value}!\")\n\n# The object may now emit signals when appropriate,\n# (for example in a setter method)\nmy_obj.value_changed.emit('hi') # prints \"The value changed to hi!\"\n```\n\nMuch more detail available in the [documentation](https://psygnal.readthedocs.io/)!\n\n### Evented Dataclasses\n\nA particularly nice usage of the signal pattern is to emit signals whenever a\nfield of a dataclass changes. Psygnal provides an `@evented` decorator that will\nemit a signal whenever a field changes. It is compatible with `dataclasses`\nfrom [the standard library](https://docs.python.org/3/library/dataclasses.html),\nas well as [attrs](https://www.attrs.org/en/stable/), and\n[pydantic](https://pydantic-docs.helpmanual.io):\n\n```python\nfrom psygnal import evented\nfrom dataclasses import dataclass\n\n@evented\n@dataclass\nclass Person:\n name: str\n age: int = 0\n\nperson = Person('John', age=30)\n\n# connect callbacks\n@person.events.age.connect\ndef _on_age_change(new_age: str):\n print(f\"Age changed to {new_age}\")\n\nperson.age = 31 # prints: Age changed to 31\n```\n\nSee the [dataclass documentation](https://psygnal.readthedocs.io/en/latest/dataclasses/) for more details.\n\n### Evented Containers\n\n`psygnal.containers` provides evented versions of mutable data structures\n(`dict`, `list`, `set`), for cases when you need to monitor mutation:\n\n```python\nfrom psygnal.containers import EventedList\n\nmy_list = EventedList([1, 2, 3, 4, 5])\n\nmy_list.events.inserted.connect(lambda i, val: print(f\"Inserted {val} at index {i}\"))\nmy_list.events.removed.connect(lambda i, val: print(f\"Removed {val} at index {i}\"))\n\nmy_list.append(6) # Output: Inserted 6 at index 5\nmy_list.pop() # Output: Removed 6 at index 5\n```\n\nSee the\n[evented containers documentation](https://psygnal.readthedocs.io/en/latest/API/containers/)\nfor more details.\n\n## Benchmark history\n\nhttps://pyapp-kit.github.io/psygnal/\n\nand\n\nhttps://codspeed.io/pyapp-kit/psygnal\n\n## Developers\n\n### Compiling\n\nWhile `psygnal` is a pure python package, it is compiled with mypyc to increase\nperformance. To test the compiled version locally, you can run:\n\n```bash\nmake build\n```\n\n(which is just an alias for `HATCH_BUILD_HOOKS_ENABLE=1 pip install -e .`)\n\n### Debugging\n\n To disable all compiled files and run the pure python version,\nyou may run:\n\n```bash\npython -c \"import psygnal.utils; psygnal.utils.decompile()\"\n```\n\nTo return the compiled version, run:\n\n```bash\npython -c \"import psygnal.utils; psygnal.utils.recompile()\"\n```\n\nThe `psygnal._compiled` variable will tell you if you're using the compiled\nversion or not.\n",
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