semvec/pypi-packages huggingface dataset:
python-lyric 1.1.6
Python API for talking to the Honeywell Lyric™ Thermostat
Keywords: honeywell lyric thermostat

=========================================================
Python API for the Honeywell Lyric™ Thermostat
=========================================================


History
=======

This module was based on `python-nest http://github.com/technicalpickles/python-nest` 
That module was originally a fork of `nest_thermostat <https://github.com/FiloSottile/nest_thermostat>`
which was a fork of `pynest <https://github.com/smbaker/pynest`
prsample 0.0.5
A pseudo-random data sampler
Requires Python: >=3.7

# prsample

Inplementation of pseudo-random sampling from a 

# Installation

```sh
pip3 install prsample
```
or
```sh
pip3 install --user prsample
```

# Example usage

The minimum required to 

```
class Example():
    def __init__(self, ... ):
    	# State to describe an example
        return

    def __hash__(self): 
        return super.__hash__((self.class_a, self.a, self.class_b, self.b))

    def __str__(self): 
        return str(self.class_a)  + '(' + str(self.a) + ') ' + str(self.class_b) + '(' +str(self.b) + ')'

    def is_valid(self, class_list):
    	# Optional checks go here
        return True

    def get(self):
        return (self.class_a, self.a, self.class_b, self.b)
```
nlp-annotations 1.0.1
NLP Annotation Helpers
Requires Python: >=3.6

# NLP Annotations

A simple python package for dealing with different nlp annotation styles.
No dependencies, and is very fast due to only using regular expressions.

You can install it with:

```bash
pip3 install nlp-annotations
```

## Annotation Types

The following are the annotation types we support and how to convert it to
another type.

### Markdown Links

(Used by Rasa, etc...), these are in the form:

```markdown
The weather is [sunny](weather) and the sky is [blue](color).
```

To convert this to an _entity list_ you can:

```python
from nlp_annotations import markdown_links2entity_list
markdown_links2entity_list("The weather is [sunny](weather) and the sky is [blue](color).")
# ('The weather is sunny and the sky is blue.', {'entities': [(15, 20, 'weather'), (36, 40, 'color')]})
```

For other situations that you may wish to add extra logic, there is also a generator:

```python
from nlp_annotations import markdown_string_link_generator

for link in markdown_string_link_generator("The weather is [sunny](weather) and the sky is [blue](color)."):
    print(f"- word={link.word}, entity={link.entity}, start={link.start}, end={link.end}")

# - word=sunny, entity=weather, start=15, end=31
# - word=blue, entity=color, start=47, end=60
```

### Entity List

(Used by Spacy, etc...), these are in the form:

```python
('The weather is sunny and the sky is blue.', {'entities': [(15, 20, 'weather'), (36, 40, 'color')]})
```

To convert this to a _markdown links_ string, you can:

```python
from nlp_annotations import entity_list2markdown_links
entity_list2markdown_links("The weather is sunny and the sky is blue.", [(15, 20, 'weather'), (36, 40, 'color')])
# 'The weather is [sunny](weather) and the sky is [blue](color).'
```
scpmanWechat 1.0.3
Send Message to Wechat Application
Requires Python: >=3.0

This is Send message to Wechat application package. You can use
[Github](https://github.com/freeddser/scpmanWechat)

### pip install scpmanWechat
### demo
    from scpmanWechat import QYWeChatBot

    CORPID = 'XXX'
    CORPSECRET = 'XXXX'
    AGENTID = '1000002'
    Tag = "1"
    msg = "hello world"
    wx_bot = QYWeChatBot(CORPID, CORPSECRET, AGENTID, Tag)
    wx_bot.send_msg_to_tag_group("xxx")