semvec/pypi-packages huggingface dataset:
constructor-io 1.9.0
Constructor.io Python Client
License: MIT

# Constructor.io Python Client

[![Version](https://img.shields.io/pypi/v/constructor-io.svg)](https://pypi.python.org/pypi/constructor-io)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)

A Python client for [Constructor.io](http://constructor.io/). [Constructor.io](http://constructor.io/) provides search as a service that optimizes results using artificial intelligence (including natural language processing, re-ranking to optimize for conversions, and user personalization).

## Documentation
Full API documentation is available on [Github Pages](https://constructor-io.github.io/constructorio-python)

## Requirements

Requesting results from your back-end can be useful in order to control result rendering logic on your server, or augment/hydrate results with data from another system. However, a back-end integration has additional requirements compared to a front-end integration. Please review the [Additional Information For Backend Integrations](https://github.com/Constructor-io/constructorio-python/wiki/Additional-Information-for-Backend-Integrations) article within the wiki for more detail.

## 1. Install

```
pip install constructor-io
```

## 2. Retrieve an API key and token

You can find this in your [Constructor.io dashboard](https://constructor.io/dashboard). Contact sales if you'd like to sign up, or support if you believe your company already has an account.

## 3. Implement the Client

Once imported, an instance of the client can be created as follows:

```python
from constructor_io.constructor_io import ConstructorIO

constructorio = ConstructorIO({
    "api_key": "YOUR API KEY",
})
```

## 4. Retrieve Results

After instantiating an instance of the client, four modules will be exposed as properties to help retrieve data from Constructor.io: `search`, `browse`, `autocomplete`, and `recommendations`.

## Development

```bash
make install                            # install dependencies
pipenv run pylint constructor_io  # run lint
pipenv run pytest .                     # run tests with coverage report
make docs                               # output documentation to `./docs` directory
```
faceware-pyportal 1.1.1
Allow programmatic access to Faceware Cloud Portal via Python library
License: MIT
Requires Python: <4.0,>=3.8


This is a python library for submitting new jobs & downloading results of processed jobs from Faceware Portal.


## Installation and Prerequisites

This library requires 
- Faceware Portal Account and Access Token
- python >= 3.8

```bash
  pip install faceware-pyportal
```
    
## Usage

You can find general usage documentation at [https://docs.facewaretech.com/](https://docs.facewaretech.com).


```python
import logging
from faceware.pyportal.job import TrackingModel
from faceware.pyportal.job_result import JobStatus
from faceware.pyportal import PortalClient

# set your desired logging level
logging.basicConfig(level=logging.INFO)

client = PortalClient(
    access_token="{YOUR-ACCESS-TOKEN}",
    organization_id="{YOUR-ORGANIZATION-ID}"
    parent_logger=logging.getLogger('pyportal') # Optional
)

project = await client.get_project("{PROJECT-ID}")

job = await project.submit_job(
    actor_name="Sample"
    tracking_model=TrackingModel.STATIC_CAM,
    video_file_path="samples/Video.mp4",
    calibration_image_file_path="samples/Calibration.jpg"
)

while await job.get_status() not in [JobStatus.COMPLETED, JobStatus.FAILED]:
    print("waiting for job status to change")

if job.status is JobStatus.COMPLETED:
    await job.download_retargeting_file('samples/tracked.fwr')
```

### Support

For support, email support@facewaretech.com
GDOES-EvaluationSuite 1.0.0
A package for analyzing and visualizing GDOES depth profile data.
License: MIT
Requires Python: >=3.7

# GDOES Depth Profile Analysis Suite

This repository contains tools for analyzing and visualizing GDOES depth profile data.

## Contents

### Jupyter Notebook

- [notebook.ipynb](notebook.ipynb): Main interactive notebook for data import, visualization, and integration.

### Python Package

All package code is located in the `package/` directory:

- [package/__init__.py](package/__init__.py): Initializes the package and imports submodules.
- [package/measurement.py](package/measurement.py): Contains the `Measurement` class for loading, processing, plotting, and integrating measurement data.
- [package/utils.py](package/utils.py): Utility functions, such as importing data files from a folder.
- [package/__pycache__/](package/__pycache__/): Directory for Python bytecode cache files (auto-generated).

## Getting Started

1. Install dependencies from [requirements.txt](requirements.txt).
2. Open [notebook.ipynb](notebook.ipynb) and follow the instructions in each cell to analyze your data.

## License

See [CODEOWNERS](CODEOWNERS) for code ownership information.