semvec/pypi-packages huggingface dataset:
ourskyai_node_platform_api 1.3.9953
OurSky
Requires Python: >=3.9
Keywords: OpenAPI, OpenAPI-Generator, OurSky

# ourskyai-node-platform-api
Node Platform API

This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:

- API version: &lt;VERSION&gt;
- Package version: 1.3.9953
- Build package: org.openapitools.codegen.languages.PythonClientCodegen

## Requirements.

Python 3.9+

## Installation & Usage
### pip install

```sh
pip install ourskyai_node_platform_api
```
(you may need to run `pip` with root permission: `sudo pip install ourskyai_node_platform_api`)

### Poetry install
If you manage dependencies with [poetry](https://python-poetry.org/) then you can add the SDK with:

```sh
poetry add ourskyai_node_platform_api
```

### Import the package

Then import the package:
```python
import ourskyai_node_platform_api
```

## Getting Started

Please follow the [installation procedure](#installation--usage) and then run the following:

```python

import os
import ourskyai_node_platform_api
from ourskyai_node_platform_api.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://api.prod.oursky.ai
# See configuration.py for a list of all supported configuration parameters.
configuration = ourskyai_node_platform_api.Configuration(
    host = "https://api.prod.oursky.ai"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization: BearerToken
configuration = ourskyai_node_platform_api.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# Enter a context with an instance of the API client
with ourskyai_node_platform_api.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ourskyai_node_platform_api.DefaultApi(api_client)
    v1_cancel_all_tasks_request = ourskyai_node_platform_api.V1CancelAllTasksRequest() # V1CancelAllTasksRequest | 
    lineage_id = UUID('38400000-8cf0-11bd-b23e-10b96e4ef00d') # UUID | Lineage ID required when requesting data from the cloud platform (optional)

    try:
        api_response = api_instance.v1_cancel_all_tasks(v1_cancel_all_tasks_request, lineage_id=lineage_id)
        print("The response of DefaultApi->v1_cancel_all_tasks:\n")
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling DefaultApi->v1_cancel_all_tasks: %s\n" % e)

```

## Documentation for API Endpoints

All URIs are relative to *https://api.prod.oursky.ai/docs/node_platform*

<a id="documentation-for-authorization"></a>
## Documentation For Authorization


Authentication schemes defined for the API:
<a id="BearerToken"></a>
### BearerToken

- **Type**: Bearer authentication

<a id="Roles"></a>
### Roles



## Author
ezmsg-learn 1.4.1
ezmsg namespace package for machine learning
Requires Python: >=3.10

# ezmsg-learn

This repository contains a Python package with modules for machine learning (ML)-related processing in the [`ezmsg`](https://www.ezmsg.org) framework. As ezmsg is intended primarily for processing unbounded streaming signals, so are the modules in this repo.

> If you are only interested in offline analysis without concern for reproducibility in online applications, then you should probably look elsewhere.

Processing units include dimensionality reduction, linear regression, and classification that can be initialized with known weights, or adapted on-the-fly with incoming (labeled) data. Machine-learning code depends on `river`, `scikit-learn`, `numpy`, and `torch`.

## Getting Started

This ezmsg namespace package is still highly experimental and under active development. It is not yet available on PyPI, so you will need to install it from source. The easiest way to do this is to use the `pip` command to install the package directly from GitHub:

```bash
pip install git+https://github.com/ezmsg-org/ezmsg-learn
```
matplotlib-sankey 0.3.2
Create Sankey diagrams with Matplotlib.
Requires Python: >=3.11

# matplotlib-sankey

[![codecov](https://codecov.io/gh/harryhaller001/matplotlib-sankey/graph/badge.svg?token=SPSPC7MSV0)](https://codecov.io/gh/harryhaller001/matplotlib-sankey)
[![Version](https://img.shields.io/pypi/v/matplotlib-sankey)](https://pypi.org/project/matplotlib-sankey/)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/matplotlib-sankey)
![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/harryhaller001/matplotlib-sankey/testing.yml)
[![DOI](https://zenodo.org/badge/893904012.svg)](https://doi.org/10.5281/zenodo.15420062)

[Documentation](https://harryhaller001.github.io/matplotlib-sankey/) | [PyPI](https://pypi.org/project/matplotlib-sankey/) | [Github repository](https://github.com/harryhaller001/matplotlib-sankey) | [Codecov](https://codecov.io/gh/harryhaller001/matplotlib-sankey)

Sankey plot for matplotlib

### Installation

Install with `pip`:

`pip install matplotlib-sankey`

Install with `uv`:

`uv add matplotlib-sankey`

Install from source:

```bash
git clone https://github.com/harryhaller001/matplotlib-sankey
cd matplotlib-sankey
pip install -e .
```


### Example

```python
data = [
    # (source index, target index, weight)
    [(0, 2, 20), (0, 1, 10), (3, 4, 15), (3, 2, 10), (5, 1, 5), (5, 2, 50)],
    [(2, 6, 40), (1, 6, 15), (2, 7, 40), (4, 6, 15)],
    [(7, 8, 5), (7, 9, 5), (7, 10, 20), (7, 11, 10), (6, 11, 55), (6, 8, 15)],
]

fig, ax = plt.subplots(figsize=(10, 5))
fig.tight_layout()
sankey(
    data=data,
    cmap="tab20",
    annotate_columns=True,
    ax=ax,
    spacing=0.03,
)
```

![Sankey plot example](./docs/source/_static/images/example_sankey_plot.jpg)



### Development

```bash
git clone https://github.com/harryhaller001/matplotlib-sankey
cd matplotlib-sankey

# Create virtual env with uv
uv venv

# Install dev dependencies
make install

# Run all checks
make check
```