semvec/pypi-packages huggingface dataset:
netspeech 0.0.1
在不需要密钥的情况下语音合成（注意：该效果与用Key的效果可能不同），暂时无暇维护
Requires Python: >=3.2

<h1>Freetts</h1>
<p>这个模块可以在不使用Key的情况下爬取各大网站的密钥。</p>
<p><strong>注意：</strong>实际效果可能与使用Key的情况下不同。</p>
<p><strong>警告：</strong>仅用于学习和交流用，请勿用于商业和非法用途！</p>
<p><strong>注意：</strong>只在中国大陆测试过。在国外可能超时。</p>
pickle-data 0.0.1
A simple tool for pickling data to a file.

# Pickle Data
This is an extremely short and simple project with just two functions, one to pickle data to a file, and one to load pickled data from a file.

This project serves more as an introduction for me to learn how to use PyPi.

## Installation
Use the following command in a command line to install this project:

```python
pip install pickle_data
```

## Basic Usage

```python
from pickle_data import load_data
from pickle_data import save_data

# Save something to a file:
save_data('./MyFile.pickle', 'Example Text')

# Load something from a pickled file:
load_data('./MyFile.pickle')
```


# Development Dependencies
To install pickle_data in its development environment to build on it and run tests yourself, run the following command:

```bash
$ pip install -e . [dev]
```
webcandy-client 0.1.5
Client-side code for communicating with a Webcandy server.

# Webcandy Client
Client-side code for communicating with the Webcandy server and controlling
lighting configuration. This should be run by the machine with LEDs connected to
it via Fadecandy.

## Installation
The easiest way to install is to run `pip install webcandy-client`. If you want
the absolute latest code, you can clone this repository and run
`pip install -e .` from the root directory.

### Development
This project uses [Pipenv](https://docs.pipenv.org/en/latest/) for dependancy
management. If you want to set up a development environment, make sure you have
Pipenv installed and run `pipenv install` from the root directory.

## Running
To run the client in order to receive lighting change requests from the server,
use the `wc-client` executable:

`$ wc-client <username> <password> <client_id>`.

To manually change the lighting configuration offline, use the `wc-controller`
executable:

`$ wc-controller --file <config JSON path>`

For usage information on either script, pass `--help`.
coach-ml 0.22
Python client for coach

# Coach Python SDK

Coach is an end-to-end Image Recognition platform, we provide the tooling to do effective data collection, training, and on-device parsing of Image Recognition models.

See https://coach.lkuich.com for more information!

## Installing
Install and update using [pip](https://pip.pypa.io/en/stable/quickstart/):
```bash
pip install coach-ml
```

## Usage
Coach can be initialized 2 different ways. If you are only using the offline model parsing capabilities and already have a model package on disk, you can initialize like so:

```python
coach = CoachClient()

# We already had the `flowers` model on disk, no need to authenticate:
result = coach.get_model('flowers').predict('rose.jpg')
```

However, in order to download your trained models, you must authenticate with your API key:
```python
coach = CoachClient().login('myapikey')

# Now that we're authenticated, we can cache our models for future use:
coach.cache_model('flowers')

# Evaluate with our cached model:
result = coach.get_model('flowers').predict('rose.jpg')
```

## API Breakdown

### CoachClient
`__init__(is_debug=False)`  
Optional `is_debug`, if `True`, additional logs will be displayed

`login(apiKey) -> CoachClient`  
Authenticates with Coach service and allows for model caching. Accepts API Key as its only parameter. Returns its own instance.

`cache_model(model_name, path='.', skip_match=False, model_type='frozen')`
Downloads model from Coach service to disk. Specify the name of the model, and the path to store it. This will create a new directory in the specified path and store any model related documents there.
By default, if a model already exists with the same version, in the same path, caching will be skipped. Set `skip_match` to `False` to override this behaviour.
`model_type` can be one of: `frozen`, `unity`, `mobile`, and can be useful if you're interested in caching a specific version of your model.

`get_model(path='.') -> CoachModel`
Loads model into memory. Specify the path of the cached models directory. Returns a `CoachModel`

`get_model_remote(model_name, path='.') -> CoachModel`
Downloads and loads model into memory. Specify the path of the cached models directory. Returns a `CoachModel`

### CoachModel
`__init__(graph, labels, base_module)`  
Initializes a new instance of `CoachModel`, accepts a loaded `tf.Graph()`, array of `labels`, and the `base_module` the graph was trained off of.

`predict(image, input_name="input", output_name="output") -> dict`  
Specify the directory of an image file or the image as a byte array. Parses the specified image into memory and runs it through the loaded model. Returns a dict of its predictions in order of confidence.
If you have a pretrained frozen graph with different Tensor input/output names, you can specify them with `input_name` and `output_name` respectfully.
django-colorinput 0.2
Color fields for Django models and forms using HTML5 native color type input elements
Requires Python: >=3.6

=============================
django-colorinput
=============================

Color fields for forms and models using HTML5's native input element of type color.


Quickstart
----------

Install `django-colorinput` and add it to your `INSTALLED_APPS`:

.. code-block:: python

    INSTALLED_APPS = (
        …
        'colorinput.apps.ColorInputConfig',
        …
    )

Now you can use `ColorField` in your models:

.. code-block:: python

    from django.db import models

    from colorinput.models import ColorField

    class MyModel(models.Model):
        …
        color = ColorField(default="d0d0d0")
	…

In forms, the color field will be displayed using HTML5's native color type
input element. In your own templates, you could use the value stored in the
field like this:

.. code-block:: HTML

    <span style="color: #{{ object.color }}">

… or however you want, really. Just keep in mind that the value is stored as
RGB in triple HEX format *without* the leading "#" (hash symbol).