semvec/pypi-packages huggingface dataset:
podcast-recommendation 0.1.8
Podcast recommendation algorithm in Neo4j
Requires Python: >=3.6

# PodcastRecommendation 
### ```0.1.6``` 
Podcast Recommendation Algorithm <br>
[Documentación completa](https://manuelalejandromartinezflores.github.io/PodcastRecommendation)


## Instalar

```
python3 -m pip install podcast-recommendation
```
```
pip install podcast-recommendation
```
```
pip install podcast-recommendation==0.1.6

```

## Uso
### Import
```py
from podcast_recommendation.algorithm import PodcastRecommendation
```

### Crear objeto
Para utilizarlo debe tener una DataBase abierta en Neo4j con el plugin de Data Science
![db](https://github.com/ManuelAlejandroMartinezFlores/PodcastRecommendation/blob/main/img/neo4j-db.png)
```py
pr = PodcastRecommendation('bolt://localhost:7687', ('neo4j', 'password'), verbose=True)
```
```
Reading x_train
Reading y_train
Training model
Training complete
```

### Generar grafo
```py
pr.build_graph(verbose=True)
```
```
Reading categories
Reading ratings
Creating categories, categories and IsA
Creating users, categories and ratings
Build complete
```

Se genera un grafo como el siguiente:
![grafo](https://github.com/ManuelAlejandroMartinezFlores/PodcastRecommendation/blob/main/img/neo4j-graph.png)

### Generar recomendaciones
Para recomendar podcast al usuario ```6C561484AED5C02```
```py
pr.recommend(user_id='6C561484AED5C02')
```
```
                          podcast_id     proba
47  b4c3c3ebdd76e284f7d9fa358ac82030  0.999225
31  c9add5e9e81a4b3ca963adab5b87083f  0.999216
30  a37fb116709bfdb2dd58ea4f784cb815  0.999042
42  a3a535f66c7e8004e7dc54c2b2829a9e  0.999038
43  b70d658c901897359bb848cf876cbcbc  0.998779
...
```
### Eliminar el grafo
```py
pr.delete_all()
```

### Eliminar rating
Eliminar rating entre usuario ```6C561484AED5C02``` y podcast ```a3a535f66c7e8004e7dc54c2b2829a9e```
```py
pr.delete_rtg(user_id='6C561484AED5C02', podcast_id='a3a535f66c7e8004e7dc54c2b2829a9e')
```

### Crear rating
Crear rating de 5 entre usuario ```6C561484AED5C02``` y podcast ```a3a535f66c7e8004e7dc54c2b2829a9e```
```py
pr.create_rtg(user_id='6C561484AED5C02', podcast_id='a3a535f66c7e8004e7dc54c2b2829a9e', rating=5)
```

### Crear usuario
Crear usuario de id ```A1A1A1A1A1A1A1```
```py
pr.create_user(user_id='A1A1A1A1A1A1A1')
```

### Crear podcast
Crear podcast de id ```a1a1a1a1a1a1a1a1a1a1a1```
```py
pr.create_podcast(podcast_id='a1a1a1a1a1a1a1a1a1a1a1')
```

### Crear categoria
Crear categoria de nombre ```cat``` e id ```99``` 
```py
pr.create_category(category='cat', category_id=99)
```

### Crear relación IsA
Crear relación podcast de id ```a1a1a1a1a1a1a1a1a1a1a1``` IsA categoria de nombre ```cat```
```py
pr.create_IsA(podcast_id='a1a1a1a1a1a1a1a1a1a1a1', category='cat')
```

### Cerrar driver
```py
pr.close()
```
credict 0.1.2
Python interface for Credict smart contracts on Ethereum.
Requires Python: >=3.8

# credict-py

Python interface for smoother interaction with the Credict Ethereum smart contract, namely encryption and watermark mechanisms.

## Install

`pip install credict`

## Sample Usage 

Please refer to [`Credict.ipynb`](Credict.ipynb) for sample code and [`local_config.py`](local_config.py) for configurations.
django-counts-ds 1.1.1
counts part for demiansoft
Requires Python: >=3.8

django-counts_ds
==========

django-counts_ds is a Django app to use for demiansoft. 

Quick start
------------

1. Add "counts" to your INSTALLED_APPS setting like this
```python
INSTALLED_APPS = [
    ...
    'counts',
]
```

2. 코드를 넣고자 하는 위치에 다음을 추가 한다.
```html
{% load counts_tags %}
{% make_counts %}
```

* context example
```python
# 문자열을 | 으로 나누면 medicio 템플릿에서 나눠서 사용한다.
context = {
    "theme": "mentor_ds",
    "counts": [
        ["fa-map-pin", "누적 임플란트 식립|임플란트는 어떻게", 17862, "#link"],
        ["fa-thumbs-up", "누적 교정 케이스|교정은 어떻게", 3345, "#link"],
        ["fa-user-md", "의료진", 3, "#link"],
        ["fa-tooth", "누적 사랑니 발치", 16678, "#link"]
    ],
}
```

* Required vendor - purecounter
serializer-data 2.0.0
serialize and deserialize objects
Requires Python: >=3.8

# serializer_data
serialize and deserialize objects in a simple way

there are two classes Serializer and Serializable, the first uses static methods while the other does not (see examples)

# Test 0
from serializer_data.serializable import Serializable

data_set = {"key1": 3, "key2": 5}

serial = Serializable("fileBinary.mm")

serial.serialize(data_set)

new_data_set = serial.deserialize()

print(new_data_set)

# Test 1
from serializer_data.serializer import Serializer

data_set = {"key1": 3, "key2": 5}

serial = Serializer.serialize(data_set, "fileBinary.mm")

new_data_set = Serializer.deserialize("fileBinary.mm")

print(new_data_set)

# Installation

pip install serializer_data

# Authors
Buscarino Antonino

# License

 GNU General Public License v3
guyamoe-api-types 1.0
Types for the api at guya.moe
Requires Python: >=3.6

guyamoe Python API Types
------------------------

This package contains the Python types for the ``guyamoe`` API.

View the `generated Python documentation <https://typedapis.github.io/guyamoe/index.html>`_.

View the `generated TypeScript documentation <https://typedapis.github.io/guyamoe/js/index.html>`_.

View the `TypeScript code <https://github.com/TypedAPIs/guyamoe/tree/main/js>`_.