semvec/pypi-packages huggingface dataset:
emsg 0.0.4
An ISO BMFF emsg atom generator

# emsg

An ISO BMFF emsg atom generator.  This cli generates an emsg atom file with any given parameters.  You can insert it into an mp4 file by using an mp4 file editor such as Bento4's [mp4edit](https://www.bento4.com/documentation/mp4edit/) to deliver in-band media timed event data for MPEG-DASH, HLS, and so on.

## Installation

```sh
$ pip install --upgrade emsg
```

## Usage

```sh
$ emsg --help
usage: emsg [-h] [-o OUT] [-s SCHEME_ID_URI] [--box_version {0,1}] [-i ID] [--value VALUE] [-m MESSAGE_DATA]
            [--presentation_time PRESENTATION_TIME] [--presentation_time_delta PRESENTATION_TIME_DELTA]
            [--timescale TIMESCALE] [--event_duration EVENT_DURATION]

options:
  -h, --help            show this help message and exit
  -o OUT, --out OUT     set file name to output (default=./emsg.atom)
  -s SCHEME_ID_URI, --scheme_id_uri SCHEME_ID_URI
                        set scheme id uri to identify the message scheme (default=https://aomedia.org/emsg/ID3)
  --box_version {0,1}   set emsg box version (default=1)
  -i ID, --id ID        set id (default=0)
  --value VALUE         set value for event stream elements (default=1)
  -m MESSAGE_DATA, --message_data MESSAGE_DATA
                        set message data
  --presentation_time PRESENTATION_TIME
                        set presentation time for emsg version 1 (default=450000)
  --presentation_time_delta PRESENTATION_TIME_DELTA
                        set presentation time delta for emsg version 0 (default=450000)
  --timescale TIMESCALE
                        set timescale (default=90000)
  --event_duration EVENT_DURATION
                        set event duration (default=270000)
```

### Examples

To generate an emsg box file named "sample-emsg.atom" containing the metadata below:

- timescale = 90000
- presentation time = 270000
- event duration = 180000
- id = 0
- scheme id uri = "urn:mpeg:dash:event:2012"
- value = "1"
- message data = "A sample message data"

Run the command below:

```sh
$ emsg -o sample-emsg.atom --timescale 90000 --presentation_time 270000 --event_duration 180000 -i 0 -s urn:mpeg:dash:event:2012 --value 1 -m "A sample message data"
```

## Format support

| Format | Supports |
| --- | --- |
| emsg version 0 | Y |
| emsg version 1 | Y |
| ID3 Metadata in emsg (version 1) | Y |
tutor-keyterms-api 0.1.1
keyterms plugin for Tutor
Requires Python: >=3.6

keyterms plugin for `Tutor <https://docs.tutor.overhang.io>`__
===================================================================================

This is a plugin for `Tutor <https://docs.tutor.overhang.io>`_ to easily add the key terms api to an Open edX platform.

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

::

    pip install tutor-keyterms-api


Usage
-----

::

    tutor plugins enable keyterms

Pull the latest image for edx_key_terms_api, run::

    tutor images pull keyterms

To create the keyterms container, run::

    tutor local start

Initialize the service, create the database and run migrations, run::

    tutor local init --limit=keyterms


Configuration
-------------

- ``KEYTERMS_DOCKER_REGISTRY`` (default: ``"589371489025.dkr.ecr.us-east-2.amazonaws.com/"``)
- ``KEYTERMS_DOCKER_IMAGE`` (default: ``"{{ KEYTERMS_DOCKER_REGISTRY }}edx_key_terms_api:{{ KEYTERMS_VERSION }}"``)
- ``KEYTERMS_HOST`` (default: ``"keyterms.{{ LMS_HOST }}"``)
- ``KEYTERMS_MYSQL_DATABASE`` (default: ``"keyterms"``)
- ``KEYTERMS_MYSQL_USERNAME`` (default: ``"keyterms"``)

These values can be modified with ``tutor config save --set PARAM_NAME=VALUE`` commands.
roland-piano 0.4.0
A library to interface with Roland FP pianos over midi
Requires Python: >=3.7

# Roland Piano
Library for interfacing with Roland FP pianos over midi. Tested on both Mac and Linux.

# Installation
Run:
```bash
python3 -m pip install roland-piano
```

# How this started
I found the button only interface on my Roland FP-10 somewhat limiting. The app would give more insight, but was a bit too buggy IMO. Hence I decided to reverse engineer the Roland specific midi messages and create a Python API so that people can build their own interface. Feel free to contribute!

# Examples
Please look at the unit tests on how to use the library. The main difference is that the imports are handled as if you installed the library with Pip:

```python
from roland_piano import RolandPiano, discover, RolandAddressMap, Instruments
```

# Limitations
- Doesn't trigger events (e.g. volume changed) over midi when changing many of the piano settings. Connecting with the app enables this, so I  (or you😃) need to do some digging on how this is achieved. Contact me for more information on what I have tried so far.
- API is quite limited at the moment, but there is some low hanging fruit for more functionality.
parrot-feeder 0.12.0
Advanced multi-channel file-sharing tool
Requires Python: >=3.6, <4
Keywords: file-sharing,ngrok,flask

## General Information
Advanced multichannel file sharing web server.

See also:
- https://hub.docker.com/r/lep0puglabs/parrot-feeder
- https://pypi.org/project/parrot-feeder/

Parrot-feeder is an all-in-one combination of the following tools:

- https://github.com/cyberhexe/ngflask
- https://github.com/mtalimanchuk/flask-filebox
- https://github.com/mtalimanchuk/file-squire-bot

It makes file transferring over Internet easier by giving you a tool to share a local directory through the Ngrok network. 
It lists the given directory, creates a local web server with Flask, make this server sharing the listed files and creates an Ngrok tunnel to the port used by the Flask server. 

In other words, parrot-feeder temporarily exposes your files for downloading on the Internet. 
Once you stop parrot-feeder, your files stop being shared over Ngrok.

It also exposes an HTML page under the `/api/upload` path with a form for uploading files to the remote machine.

If you supply the tool with a telegram bot token via the `--telegram-bot-token` argument or 
via the `TELEGRAM_BOT_TOKEN` env variable, 
you will also activate a telegram bot that will `/fetch` or `/tail` files for you from remote.


*Note-1: you also need to supply the `--telegram-bot-whitelist` or `TELEGRAM_BOT_WHITELIST` 
env variable to specify the users allowed to interact with the bot.*

*Note-2: you may need to sign up for Ngrok for tunneling HTML pages.*


## Screenshots or it didn't happen.
![image info](https://i.imgur.com/nZfsTEH.png)


## Installation

Download the Docker image:

```bash
docker pull lep0puglabs/parrot-feeder:latest
```

or build the Docker image yourself:

```bash
docker build -t parrot-feeder -f ./Dockerfile .
```

Run the Docker image:

```bash
docker run --rm -it -p 4200:4200 parrot-feeder
```

Or install the package using PyPI:

```bash
sudo pip3 install parrot-feeder
```

After starting the server, you can navigate to the following URLs:

- / - for seeing the listing
- /api/upload - for accessing the API for uploading files

## Usage

Serve files and folder from the current working directory 

`parrot-feeder`

or 

`docker run --rm -it -p 4200:4200 parrot-feeder`

Serve files and folders from the /tmp directory 

`parrot-feeder --directory /tmp`

Print served files to the console on startup 

`parrot-feeder --directory /tmp -pf`

Bind the server to the given address 

`parrot-feeder --ip 10.10.10.10 --port 5050`

Print help

`parrot-feeder -h`

On startup print the actual files being shared over Ngrok

`parrot-feeder -pf`

Use a telegram bot to serve you files from the remote server:

`parrot-feeder --telegram-bot-token token --telegram-bot-whitelist username1,username2`