semvec/pypi-packages huggingface dataset:
vuv 0.0.4
comparing effects on mortality between fully vaccinated and unvaccinated
Requires Python: >=3.8

# vuv
[![Open in Code Ocean](https://codeocean.com/codeocean-assets/badge/open-in-code-ocean.svg)](https://codeocean.com/capsule/1476065/tree)

Takefuji, Y. (2023). vuv: vaccine effects on mortality between fully vaccinated and unvaccinated [Source Code]. https://doi.org/10.24433/CO.1329228.v1

Takefuji Y. (2023). Effectiveness of vaccination with symptoms by age groups. International immunopharmacology, 116, 109823. Advance online publication. https://doi.org/10.1016/j.intimp.2023.109823

vuv is a PyPI application to evaluate the vaccine effects on mortality by age group 
between fully vaccinated and unvaccinated. 
CDC dataset is automatically downloaded from the following site:

https://data.cdc.gov/api/views/3rge-nu2a/rows.csv

Five age groups include 18-29,30-49,50-64,65-79, and 80+. 
Choose one of five age groups and enter the age group with vuv command.

To install vuv, 

$ pip install vuv

To run vuv, enter one of five age groups.

$ vuv 80+

This command generates 80+.png image file.

<img src=https://github.com/y-takefuji/vuv/raw/main/80%2B.png  width=350 height=280>
easy-notion-api 0.1.5
Unofficial Python API client for Notion
Requires Python: >=3.11

# easy-notion-api
Use __easy-notion-api__ for handy Notion API!<br/>
Unofficial Python 3 client for Notion API

# English
## Installation
```
pip install easy-notion-api
```

## Before Start
To use Notion API, you must get api key from [notion integrations page](https://www.notion.so/my-integrations).<br/>
And then, create new database in your notion workspace.<br/>
Click the database's setting and click 'copy link to view'<br/>
Get database id from copied link before '?v='

`https://www.notion.so/__here_is_database_id__?v=uuid&pvs=4`


## Usage
### Start
```
from notion import Notion

client = Notion("your_api_key", "database_id")
```

### Create new page in your db
```
data = {
    "school": "maycan_school", # school column type in notion is title
    "message": "example message" # message column type in notion is rich_text
    "students": ["Hans", "Woody"] # students column type in notion is people
}
client.create_page_in_db(data)
```

create_page_in_db method returns dictionary like
```
{
    is_created: bool,
    page_id: str, # if is_created is False, then page_id is not given and 'detail' key returned with error message
}
```

- data format

    - title, rich_text, number, selecet, status
        - key: value
        - Be careful! status value must be predefined in notion app.

    - multi_select, people
        - key: [value1, value2 ...]   (value must be user's nickname if people)

    - date
        - key: [value1, value2]
        - The second value(value2) means the end date. If None, only the start date is registered.
        - value format -> "YYYY-MM-DD" or "YYYY-MM-DD hh:mm:ss"

### Update page
```
data = {
    "message": "i want to go home"
}
client.update_page("page_id", data)
```

update_page method returns True (when success), else raise Error with message from Notion

### Retrieve page properties
```
client.get_page_properties("page_id") # returns dictionary
```


## Features
- [X] Create page in Database
- [X] Update page
- [X] Retrieve page properties
- [ ] Query Database
mqttthreaddatalogger 1.6.0
Connexion mqtt et enregistrement des données dans un fichier csv
Requires Python: >=3.4

#mqttdatalogger

Enregistrement des données issues d'un serveur MQTT dans un fichier csv.<br />

Exemple d'utilisation : <br />


import getpass<br />
import mqttthreaddatalogger as MQTT<br />

Username = input('Entrez votre identifiant MQTT : ') <br />
pwd = getpass.getpass('Entrez votre mot de passe MQTT :')<br />

auth = {<br />
    'username':Username,<br />
    'password':pwd<br />
}
# crée le thread transport tcp ou websockets <br />
m = MQTT.mqttthreaddatalogger("url_mqtt",portmqtt,auth["username"],auth["password"],"tcp")   <br /> 
# topics auquel on s'abonne<br />
m.selectTopic(["node_iot2020/arduino/out/"])  <br />
# selection des clés des données voulues , les données seront dans m.data[0], m.data[1],... <br />
m.selectKey(["['ecl']","['temps']"])<br />
# ou pour Lorawan, après le # se trouve le nom du champ qui sera utilisé dans le fichier csv,... <br />
m.selectKey(["['uplink_message']['decoded_payload']['temperature']#temp","['uplink_message']['rx_metadata'][0]['gateway_ids']['gateway_id']#Id_gateway","['end_device_ids']['device_id']#ID_device"])
<br />Après le # on rajoute le nom de la 1ère ligne du fichier de données</br>>
 
m.selectNomFichier("testdonnees.csv")<br />
# pour afficher ou non les info sur la console <br />
m.affichage_console(True) <br />
# démarre le thread, (exécution indépendante du programme principal)<br />
m.start()   <br />               
time.sleep(1)<br />
#publication d'un message vers MQTT  <br />
#m.client.publish("votretopic/test/in/",payload="{\"pression\":1024}",qos=0)<br />
<br />