semvec/pypi-packages huggingface dataset:
smc 0.5.3
A python driver library for Pololu's Simple Motor Controllers
License: MIT
Requires Python: >=3.6
Keywords: framework,robotic,robot,motor controller

![](https://raw.githubusercontent.com/MomsFriendlyRobotCompany/smc/master/docs/pics/smc.jpg)

# Pololu Simple Motor Controller

[![image](https://img.shields.io/pypi/v/smc.svg)](https://github.com/MomsFriendlyRobotCompany/smc)
[![image](https://img.shields.io/pypi/l/smc.svg)](https://github.com/MomsFriendlyRobotCompany/smc)
[![image](https://img.shields.io/pypi/pyversions/smc.svg)](https://pypi.python.org/pypi/smc/)

This is a python driver library for the Pololu series of Simple Motor
Controllers.

## Install

    pip install smc

## Usage

``` python
from smc import SMC
import time

mc = SMC('/dev/ttyUSB0', 115200)
# open serial port and exit safe mode
mc.init()

# drive using 12b mode
mc.speed(1000)
time.sleep(3)
mc.speed(-1000)
time.sleep(3)

# drive using 7b mode
mc.speed7b(100)
time.sleep(3)
mc.speed7b(-100)
time.sleep(3)

# and stop motor
mc.stop()
```

## Board

![](https://raw.githubusercontent.com/MomsFriendlyRobotCompany/smc/master/docs/pics/smc-back.jpg)

![](https://raw.githubusercontent.com/MomsFriendlyRobotCompany/smc/master/docs/pics/smc-io.jpg)

![](https://raw.githubusercontent.com/MomsFriendlyRobotCompany/smc/master/docs/pics/smc-wiring.jpg)

## MIT License

**Copyright (c) 2017 Kevin J. Walchko**

Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:

The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
pysabertooth 0.4.0
A python driver library for Dimension Engineering's Sabertooth Motor Controllers
License: MIT
Requires Python: >=3.6
Keywords: framework,robotic,robot,motor controller

.. figure:: https://raw.githubusercontent.com/MomsFriendlyRobotCompany/pysabertooth/master/docs/pics/Sabertooth2x32Big.jpg
	:target: https://www.dimensionengineering.com/products/sabertooth2x32


PySabertooth
==============


.. image:: https://img.shields.io/pypi/l/pysabertooth.svg
	:target: https://github.com/MomsFriendlyRobotCompany/pysabertooth
.. image:: https://img.shields.io/pypi/pyversions/pysabertooth.svg
	:target: https://github.com/MomsFriendlyRobotCompany/pysabertooth
.. image:: https://img.shields.io/pypi/wheel/pysabertooth.svg
	:target: https://github.com/MomsFriendlyRobotCompany/pysabertooth
.. image:: https://img.shields.io/pypi/v/pysabertooth.svg
	:target: https://github.com/MomsFriendlyRobotCompany/pysabertooth


Install
----------

::

	pip install pysabertooth

Usage
--------

.. code-block:: python

	from pysabertooth import Sabertooth

	saber = Sabertooth('/dev/tty.usbserial', baudrate=115200, address=128, timeout=0.1)

	# drive(number, speed)
	# number: 1-2
	# speed: -100 - 100
	saber.drive(1, 50)
	saber.drive(2, -75)
	saber.stop()


MIT License
-------------

**Copyright (c) 2017 Kevin J. Walchko**

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
PyloXyloto 1.0
PyloXyloto is a simple Deep learning framework built from scratch with python
License: MIT
Keywords: DeepLearning,FrameWork,NeuralNetworks,TensorFlow,Pytorch,Python

# PyloXyloto
PyloXyloto is a simple Deep learning framework built from scratch with python that supports the main functionalities needed for a deep learning project
## Design:
![Design](https://user-images.githubusercontent.com/35659429/105618653-83d25300-5df2-11eb-97c6-0d5df8f1a114.png)
writer-cm 1.0.9
`writer-cm` is a context manager allowing you to atomically write files given a file path.
License: MIT
Requires Python: >=3.7

`writer-cm` is a context manager allowing you to atomically write files given a
file path.

## Features

- Cross-platform atomic file writes powered by
  [python-atomicwrites](https://github.com/untitaker/python-atomicwrites).
- Interface using a file path instead of a file handle, for more compatibility
  with external libraries (e.g. `pandas.to_pickle`).
- Automatically create missing directories and set their permissions.
- Automatically set the file permissions.

## Installation

```bash
pip install writer-cm
```

## Usage

Import and invoke `writer_cm` as a context manager to obtain a `pathlib.Path`
object to which you can atomically write to:

```python
from writer_cm import writer_cm

with writer_cm("file.txt") as temp:
    # `temp` is a `pathlib.Path` object

    with open(temp, mode="w") as fh:
        fh.write("foo")

# file.txt is atomically written to upon leaving the context manager

with open("file.txt") as fh:
    assert fh.read() == "foo"
```

`writer_cm` can also automatically create missing directories and set their
permissions (which is done carefully as opposed to relying on
[`Path.mkdir`](https://docs.python.org/3/library/pathlib.html#pathlib.Path.mkdir),
which itself notes that "\[parents\] are created with the default permissions
without taking _mode_ into account"). Analogously, `writer_cm` can also set the
file permissions too.

```python
from stat import S_IRWXU, S_IRWXG, S_IRUSR, S_IWUSR

with writer_cm("dir1/dir2/dir3/file.txt",
               dir_perms=S_IRWXU | S_IRWXG,   # the default
               file_perms=S_IRUSR | S_IWUSR,  # the default
               ) as temp:
    with open(temp, mode="w") as fh:
        fh.write("foo")

# now `dir1/dir2/dir3`          has been created with u=rwx,g=rwx permissions
#     `dir1/dir2/dir3.file.txt` has been created with u=rw        permissions
```

For more info on `stat`, see the
[official docs](https://docs.python.org/3/library/stat.html).

Finally, pass `overwrite=True` to overwrite an already existing file; an error
is thrown otherwise:

```python
with writer_cm("file.txt", overwrite=True) as temp:
    with open(temp, mode="w") as fh:
        fh.write("bar")

with open("file.txt") as fh:
    assert fh.read() == "bar"
```
covid19umbria 0.0.6
Covid-19 statistics for Regione Umbria, based on the public API
License: MIT
Requires Python: >=3.6

# Covid19Umbria

![PyPI](https://img.shields.io/pypi/v/covid19umbria)

Covid-19 statistics for Regione Umbria, based on the [public API](https://apistore.regione.umbria.it/store/apis/info?name=COVID-19&version=1.0.0&provider=admin&tag=Agenda%20digitale-group).

Cf. also the [Dashboard COVID-19 Regione Umbria](https://github.com/Regione-Umbria/coronavirus).

Partially inspired by the [covid](https://github.com/ahmednafies/covid) package.

## Installation

    pip install covid19umbria

## Usage

See the [example](example.py).

### Get All Data

```python
from covid19umbria import Covid19Umbria

covid19 = Covid19Umbria()
covid19.get_data()
```

### Get Currently Active cases

```python
current_active = covid19.get_current_active_cases()
```

### Get Total Confirmed cases

```python
new_active = covid19.get_total_confirmed_cases()
```

### Get Total Recovered cases

```python
recovered = covid19.get_total_recovered()
```

### Get Total Deaths

```python
deaths = covid19.get_total_deaths()
```
shattered 0.5.0
STOMP meets bottle.py
License: MIT
Requires Python: >=3.6,<4.0

# Shattered

STOMP meets `bottle.py`

[![Build Status](https://travis-ci.com/bradshjg/shattered.svg?branch=master)](https://travis-ci.com/bradshjg/shattered)

## Getting Started

### Installation

`pip install shattered`

### CLI

`shattered run` will run a Shattered app, using one of the following (in order):

1. The `--app` flag.
2. The `SHATTERED_APP` environment variable.
3. `app.py` as the application module name.

Use `shattered config` to see the current configuration (same app resolution as `run` command).

### Echo Server

`app.py`

```python
import logging

from shattered import Shattered


logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

app = Shattered(host="rabbitmq")


@app.subscribe("/queue/echo")
def echo(headers, body, conn):
    logger.info("%s %s", headers, body)


@app.subscribe("/queue/echo")
def echo_fancy(headers, body, conn):
    logger.info("✨✨✨%s %s✨✨✨", headers, body)


app.run()
```

#### Running the Demo

Start up RabbitMQ using `docker-compose up`

In another shell, run `docker-compose run shattered python examples/echo/echo.py`

In another shell, run `docker-compose run shattered python examples/echo/send.py`
Terminatetensorflow 0.0.8
A very basic NN framework
License: MIT
Keywords: layer

1. Dense Module
This module contain the parameters initialization, layer forward propogation, layer backward propogation and also parameters update.
2. Viz Module
this module contain all vizualization technique used inside our framework, All built with matplotlib
3. Saver module
This module save the model parameters to be used for predection.
The model is built upon pickle implementation for save and restoring model
4. Metrics module
This module contains all the accuracy Metrics that are used to evaluate the model, include but not limited to absolute_metrics, F1_score
5. Preprocessing module
This module contain all data preprocessing from reading and cutting the data into the required ratios.

Mainly the input data is divided into test data and training data

6. Loss module
this module contain all the implemented loss functions include but not limited to multiclass loss
7. Actvfn module
This module contain all activation functions implemented for our model and also their derivatves.
8. Live animation
This module is for live plotting of both training loass and accuracy, Saved as a gif.

change log
==========

0.0.1(24/01/2021)
-----------------
First Release