Implementation of the Observer pattern for NumPy arrays.
Example
from numpy import array
from ndarray_listener import ndarray_listener as ndl
a = ndl(array([-0.5, 0.1, 1.1]))
class Observer(object):
def __init__(self):
self.called_me = False
def __call__(self, _):
self.called_me = True
o = Observer()
a.talk_to(o)
print(o.called_me)
a[0] = 1.2
print(o.called_me)The output should be
False
TrueInstall
The recommended way of installing it is via conda
conda install -c conda-forge ndarray-listenerAn alternative way would be via pip
pip install ndarray-listenerRunning the tests
After installation, you can test it
python -c "import ndarray_listener; ndarray_listener.test()"as long as you have pytest.
License
This project is licensed under the MIT License - see the License file for details.
1 maintainer
Release files for ndarray-listener 1.0.26
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ndarray-listener-1.0.26.tar.gz | 5.3 kB | Details |
Release files / ndarray-listener-1.0.26.tar.gz
| Download URL | ndarray-listener-1.0.26.tar.gz |
|---|---|
| Size | 5.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
44a18bba0a6353440f7831782e01ede253078144d17b8b8a48a8936347e1538d
|
|
BLAKE2b-256 checksum How to use checksums |
e7614c80218e4e3aec0474dcf94a43ef704510f39e628f27cec761c18a8b49b8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
