semvec/pypi-packages huggingface dataset:
vidispine-adapter 0.0.6
Python Vidispine API Adapter
License: MIT
Requires Python: >=3.6,<4.0

# Python Vidispine Adapter

A python (3.6+) wrapper around the [Vidispine API](https://apidoc.vidispine.com//latest/)

Note: This is a work in progress and not all of the vidispine endpoints have been implemented yet.

Full documentation can be found [here](https://vidispine-adapter.readthedocs.io/en/stable/).

## Quick start

### Installation

```bash
pip install vidispine-adapter
```

### Basic Usage

To use the Vidispine API you will need a to know the URL, user and password. The user does not need to be the admin user but does need the correct roles for any API call you make

```python
from vidispine import Vidispine

vs = Vidispine(url='http://localhost:8080', user='admin', password='admin')
vs.collection.create({'name': 'test_collection_1'})
```

If `url`, `user` and `password` are not passed through when initialising, Vidispine will fall back and try and use environmental variables called `VIDISPINE_URL`, `VIDISPINE_USER` and `VIDISPINE_PASSWORD`
```bash
export VIDISPINE_URL="http://localhost:8080"
export VIDISPINE_USER="admin"
export VIDISPINE_PASSWORD="admin"
```

```python
from vidispine import Vidispine

vs = Vidispine()
vs.collection.create({'name': 'test_collection_1'})
```


## Contributing

All contributions are welcome and appreciated. Please see [CONTRIBUTING.md](https://github.com/newmediaresearch/vidispine-adapter/blob/master/docs/source/contributing.md) for more details including details on how to run tests etc.



## Running tests

This package is setup to use the Pytest framework for testing.
To run tests, simply execute:
```bash
pytest tests/
```
A coverage report will displayed in the shell on each test run as well as written to `htmlcov/` and can be viewed with `open htmlcov/index.html`


Calls to Vidispine are mocked using [VCR.py](https://vcrpy.readthedocs.io/en/latest/index.html) by default but mocks can easily be refreshed and kept up to date. For more information on how to create and refresh mocks please see the `Running tests` section in [CONTRIBUTING.md](https://github.com/newmediaresearch/vidispine-adapter/blob/master/docs/source/contributing.md).
threedboard 0.0.8
Web Interface to visualize the results of 3DB experiments
License: MIT

# dashboard
Dashboard to explore 3DB experiments

## Install

`pip install threedboard`

## Run the dasboard

`python -m threedboard EXPERIMENT_FOLDER`

## Build from source

When cloning the repo directory the source code for the website has to be built. You will require `node` and `npm` and then run:

`python setup.py build_dashboard`

**Note:** This is not necessary if you install via `pip` it ships with everything built for you out of the box. No external dependencies required to run the dashboard.
retrieve 0.0.8
Retrieve pre-trained models and cache it locally
License: MIT

# retrieve

![Code Sample](https://i.imgur.com/2vSkGIB.png)

No-frills library to download pre-trained models, cache it and return the local path.

## Installation
```bash
pip install -U retrieve
```

## Motivation
When using pre-trained ML models in your projects, majority of them require you to manually download the data/model weights and then specify the path in your code. Everyone in your team has to go through the same trouble of manually setting this up before they can run your models.

The idea with this library is automate this and make using pre-trained models as easy as possible.

## Usage
Pass the pre-trained model path to the retrieve.url(...) method and it will return you a filepath to the file. If the file is not already download, it is fetched and shows a progress of download.
```python
import retrieve

# URL for the pre-trained model
pretrained_model_url = '...'

# Get local path to the pre-trained model
path = retrieve.url(pretrained_model_url)
```
If source is a zip file, it's automatically extracted out and the extracted folder path is returned.