semvec/pypi-packages huggingface dataset:
collections-mapping 0.0.1
Specialized container datatypes providing dict-like key-value mapping objects
License: MIT
Keywords: key-value,dict,collections,mapping,serialization

# collections-mapping

collections-mapping are

* specialized container datatypes providing dict-like key-value mapping objects



## Quickstart

```python
import collections_mapping

m = collections_mapping.Mapping()

m['key'] = 'value'
```



### Install collections-mapping

```python
$ pip install collections-mapping
```
pyfzf 0.3.1
Python wrapper for junegunn's fuzzyfinder (fzf)
License: MIT

pyfzf
=====

![](https://img.shields.io/badge/license-MIT-green.svg?style=flat)
![https://pypi.python.org/pypi/pyfzf](https://img.shields.io/pypi/dm/pyfzf.svg?style=flat)
   
##### A python wrapper for *junegunn*'s awesome [fzf](https://github.com/junegunn/fzf).

![](https://raw.githubusercontent.com/nk412/pyfzf/master/pyfzf.gif)

Requirements
------------

* Python 3.6+
* [fzf](https://github.com/junegunn/fzf)

*Note*: fzf must be installed and available on PATH.

Installation
------------
	pip install pyfzf

Usage
-----
    >>> from pyfzf.pyfzf import FzfPrompt
    >>> fzf = FzfPrompt()

If `fzf` is not available on PATH, you can specify a location

    >>> fzf = FzfPrompt('/path/to/fzf')

Simply pass a list of options to the prompt function to invoke fzf.

    >>> fzf.prompt(range(0,10))

You can pass additional arguments to fzf as a second argument

    >>> fzf.prompt(range(0,10), '--multi --cycle')

Input items are written to a temporary file which is then passed to fzf.
The items are delimited with `\n` by default, you can also change the delimiter
(useful for multiline items)

    >>> fzf.prompt(range(0,10), '--read0', '\0')

License
-------
MIT

Thanks
------
@brookite for adding Windows support in v0.3.0
CHANGES
=======

2015.11.16: Initial release
notipy-py 1.0.8
Windows notifier for 9-hours working day using Pomadoro technique (50 minutes work and 10 minutes rest) with lunch break
License: MIT

# Notifier
Simple Windows notifier for tracking working hours. Since start you have 8 work periods for 50 minutes and 10 minutes of rest after each working session. This is so-called Pomadoro technique. There is also a lunch breack for an hour. 

# Install

### Using  `pip`
```
pip install notipy-py
```

### Build from source
```
git clone https://github.com/VladaZakharova/Notifier.git
cd notifier
python setup.py install
```

# Usage

### Work notification
![image](https://user-images.githubusercontent.com/80038284/156029428-1cdf96e0-318b-4dc3-a0dd-4766cf26e7d5.png)

### Break notification
![image](https://user-images.githubusercontent.com/80038284/156030264-75650415-c912-4c78-8367-e8617c0f1318.png)

### Lunch time notification
![image](https://user-images.githubusercontent.com/80038284/156031185-6f9706ee-3ac5-4c18-bf17-0c5702052db0.png)

### End of work notification
![image](https://user-images.githubusercontent.com/80038284/156032207-ba31a8af-2767-4fc0-a0d1-9ecf4894cd7f.png)

### Not a working day notification
![image](https://user-images.githubusercontent.com/80038284/156032749-906f905e-a5a6-4fc2-b744-2c43a45177ad.png)
stoy 0.0.16
Jupyter Server auto stop
License: MIT
Requires Python: >=3.6

# stoy
Application for shutting down kernels in Jupyter Lab after they were idle for a specified period of time.
The jupyter instance itself is terminated when no kernels were open for some time.


# Usage

Add the following to `on_start.sh` script of your Sagemaker instance:
```commandline
pip3 install stoy
export TOKEN=`generate-token`
echo -e '\nc.NotebookApp.token="'$TOKEN'"\n' >> /home/ec2-user/.jupyter/jupyter_notebook_config.py 
stoy --kernel-idle=3600 --server-idle=1800 --token=$TOKEN --url="https://localhost:8443" --log="/var/log" &
```
`generate-token` is a script installed with `stoy` that uses `uuid.uuid4` to generate a unique token. The token is saved in 
an environment variable. The `echo` command adds the token to Jupyter notebook configuration file. Finally,
`stoy` is started as a background script and the token is passed to it.


# Troubleshooting

The application saves logs in `stoy.log` located in the directory specified by the `--log` argument.
The default location is `~/.stoy/stoy.log`.  
To access the logs open jupyter lab terminal and run `tail`, for example:
```commandline
tail -f /var/log/stoy.log
```
or 
```commandline
tail -f ~/.stoy/stoy.log
```
Use `Control-C` to stop watching the logs.