semvec/pypi-packages huggingface dataset:
pyntfy 0.2.1
A module for interacting with ntfy.sh notifications.
Requires Python: >=3.6
Keywords: notification notify ntfy toast


# pyntfy

A module for interacting with [ntfy.sh](https://ntfy.sh/) notifications.

------------------------------------------------------------------  
### Installation
You can install pyntfy via pip.
```
$ pip install pyntfy
```

------------------------------------------------------------------  
### Usage
```py
import pyntfy

# Send a sample notification.
notif = pyntfy.Notification('test_notification', 'Hello, world!', title='Notification Title')
notif.send()

# Send a timed notification.
timed_notif = pyntfy.Notification('test_notification', 'Hello, world!', title='Notification Title', delay='1m')
timed_notif.send()
```

#### Actions
```py
import pyntfy

notif = pyntfy.Notification('test_actions', 'Hello, world!')
notif.add_action(pyntfy.actions.ViewAction('Label', 'https://www.example.com/'))
notif.send()
```

------------------------------------------------------------------  
### Planned Features
- Webhook support.
- Allow for JSON data as input.
- Proper tests.

<!-- TODO: README -->
lockable.dev 0.1.2
Official Python client for https://lockable.dev
Requires Python: >=3.6

# Lockable-dev
Official Python client for https://lockable.dev

Lockable is an easy-to-use, language-independent locking mechanism for multi-process workloads. Think of it as `flock`, but for distributed systems which may not be sharing a filesystem.

## Learn more

* Lockable website: https://lockable.dev
* Lockable Python client on GitHub: https://github.com/lockable-dev/lockable-py
* Docs: https://docs.lockable.dev
* Docs on GitHub: https://github.com/lockable-dev/lockable-docs

## Installation
```
pip install lockable-dev
```

## Usage
```
from lockable import Lock
with Lock('my-lock-name'):
    #do stuff
```
## Development

### Testing
```
make test
```

### Building and pushing changes
If you want to push to PiPy, credentials go in `.env.local`. See `.env.example` for a template.
```
# Just build
make build

#Build and upload latest version to TestPyPi
make test-publish

#Build and upload latest version to TestPyPi
make publish
```
AttentionLSTM 0.1
Combining LSTM with attention

[![Documentation Status](https://readthedocs.org/projects/attentionlstm/badge/?version=latest)](https://attentionlstm.readthedocs.io/en/latest/?badge=latest)

comibining SelfAttention mechnism with LSTM

```python
import numpy as np
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input, Dense
from atten_lstm import AttentionLSTM
seq_len = 20
num_inputs = 2
inp = Input(shape=(seq_len, num_inputs))
outs = AttentionLSTM(num_inputs, 16)(inp)
outs = Dense(1)(outs)

model = Model(inputs=inp, outputs=outs)
model.compile(loss="mse")

print(model.summary())
# define input
x = np.random.random((100, seq_len, num_inputs))
y = np.random.random((100, 1))
h = model.fit(x=x, y=y)
```

For more comprehensive illustration see [examples](https://attentionlstm.readthedocs.io/en/latest/auto_examples/index.html)