semvec/pypi-packages huggingface dataset:
timeflux-upsidedownlabs 0.1.4
Connect to Upside Down Labs devices using Timeflux
License: MIT
Keywords: timeflux

Connect Upside Down Labs devices with Timeflux
==============================================

This plugin allows you to stream data from `Upside Down Labs <https://upsidedownlabs.tech/>`__ BioAmp. Two modes are proposed: through the audio interface and through the USB interface.

Installation
------------

First, make sure that `Timeflux <https://github.com/timeflux/timeflux>`__ is installed. You can then install this plugin in the `timeflux` environment:

::

    $ conda activate timeflux
    $ pip install timeflux_upsidedownlabs

Audio interface
---------------

Look at this `example graph <https://github.com/timeflux/timeflux_upsidedownlabs/blob/master/examples/audio.yaml>`__.
You can run it like this:

::

    $ conda activate timeflux
    $ timeflux -d examples/audio.yaml

The signal can be visualized `here <http://localhost:8000>`__.

USB interface
-------------

First, you must install the firmware on the board.

Download the `Arduino IDE <https://www.arduino.cc/en/Main/Software>`__ on your computer, and then:

 - Start the Arduino IDE
 - Select the serial port under "Tools"
 - Select your Arduino board under "Tools"
 - Upload the standard firmata sketch to your Arduino with:

::

    File -> Examples -> Firmata -> Standard Firmata

You're all set!

With `this example graph <https://github.com/timeflux/timeflux_upsidedownlabs/blob/master/examples/uart.yaml>`__, you can autodetect all the available analog ports and start streaming data.

You can run this graph like this:

::

    $ conda activate timeflux
    $ timeflux -d examples/uart.yaml

For an example of filtering and renaming the channels, see `this graph <https://github.com/timeflux/timeflux_upsidedownlabs/blob/master/examples/channels.yaml>`__.
wsterm 0.7.1
Websocket remote debug terminal (auto sync workspace).
License: MIT
Requires Python: >=3.5

# WSTerm

使用Websocket协议实现的远程终端，可以用于远程调试（支持自动同步本地工作区文件到远程机器）

## 支持环境

操作系统：

* Linux
* Windows
* MacOS

Python `3.5`以上版本

## 功能特性

* 远程终端
* 自动监听、同步工作区文件

## 为什么要使用WSTerm？

相比于SSH，Websocket协议具有更好的可访问性，很多场景下SSH服务不会被暴露出来，但是一般会暴露出Websocket服务。

SSH服务通常只支持Linux和MacOS，Windows需要安装独立的应用；而WSTerm可以直接运行在以上三种系统，使用更加方便。

自动同步本地工作区文件，可以实现本地修改代码，直接远程执行的特性，大大降低远程编写、执行代码的复杂性。

## 使用方式

### 安装方法

```bash
$ python3 -m pip install wsterm
```

### 服务端

```bash
$ wsterm --url ws://0.0.0.0:8080/terminal/ --server
```

此时，服务端会监听在本地的`0.0.0.0:8080`地址；如果只想监听在回环地址，可以将`0.0.0.0`替换成`127.0.0.1`。

服务端还支持以下可选参数：

`--token`: 指定鉴权使用的Token

`--log-level`: 日志级别，默认为`info`

`--log-file`: 日志保存文件路径

`-d/--daemon`: 是否以daemon方式启动，默认为`False`

### 客户端

```bash
$ wsterm --url ws://1.2.3.4:8080/terminal/
```

客户端支持的可选参数：

`--workspace`: 需要同步的工作区目录

`--token`、`--log-level`、`--log-file`等参数与服务端相同

> 服务端与客户端需要指定相同的`Token`才能正常连接
pyhedron 0.1.5
A Polyhedron implemented in Python
License: MIT

#################################################
Pyhedron - a polyhedron implemented in Python
#################################################

There are a lot if implementations of Polyhedrons available.
Most of them are implemented in C++ because of efficiency reason.
Sometimes they offer a Python API and maybe a pip installation package.

**But:** Because these Packages are implemented in C++,
they are often difficult to install and offer a API that is not very Pythish or even ugly.

This implementation wants to solve these problems:
 * Pyhedron is implemented in pure Python
 * There is a standard pip installation Package that is easy to install.
 * It only depends on Numpy
 * It is easy to use, understand and maintain
stream-converter 1.0.0
A package for applying real-time transformations on streaming data.
License: MIT
Requires Python: >=3.8

A simple package for applying transformations to streaming data.

# Stream Conversion

This package can handle stream functions and stream generators.

Here's an example with functions:

```python
from random import randint
from stream_converter.converter import convert_function_stream


def get_random_number() -> int:
    return randint(0, 100)


converted_stream = convert_function_stream(
    stream_function=get_random_number,
    conversion_function=lambda byte: str(byte),
)
for converted_chunk in converted_stream:
    print(converted_chunk)
```

And here's an example with generators:

```python
from random import randint
from typing import Generator
from stream_converter.converter import convert_generator_stream


def get_random_number_generator() -> Generator[int, None, None]:
    while True:
        yield randint(0, 100)


converted_stream = convert_generator_stream(
    stream_generator=get_random_number_generator(),
    conversion_function=lambda int: "odd" if int % 2 else "even"
)
for converted_chunk in converted_stream:
    print(converted_chunk)
```

# Built-In Stream Support

## Microphone via PyAudio

```python
from stream_converter.converter import convert_generator_stream, convert_function_stream
from stream_converter.microphone_stream import get_microphone_stream_generator, MicrophoneStream


# generator
converted_stream = convert_generator_stream(
    stream_generator=get_microphone_stream_generator(),
    conversion_function=lambda byte: str(byte),
)
for converted_chunk in converted_stream:
    print(converted_chunk)


# function
with MicrophoneStream() as microphone_stream:
    converted_stream = convert_function_stream(
        stream_function=microphone_stream.read,
        conversion_function=lambda byte: str(byte),
    )
    for converted_chunk in converted_stream:
        print(converted_chunk)
```