semvec/pypi-packages huggingface dataset:
databricks-google-sheets 0.8.0
Interact with Google Sheets from Databricks
Requires Python: >=3.6

# databricks-google-sheets

Interact with Google Sheets from Databricks. 

Please follow these steps. Be sure to replace all {{PLACEHOLDERS}} with appropriate values:

1. Create a spreadsheet in Google Sheets, and note the spreadsheet_id (You can get this from the URL)
2. Go to console.cloud.google.com and create a new project (OR select an existing project)
3. Within this project, create a service account [IAM & Admin --> Service Accounts --> Create], and call it `databricks-google-sheets`. You can skip the optional steps
4. Note down the email address associated with your new service account. Eg. `databricks-google-sheets@{{MY-AWESOME-PROJECT}}.iam.gserviceaccount.com`
5. Switch to the Keys tab and create a new key. Choose JSON as the Key type. This will generate a JSON file and download it locally
6. On your local machine, use the Databricks CLI to create a new secret scope. Eg. `databricks secrets create-scope --scope databricks-google-sheets --profile DEFAULT`
7. Create a new secret within the newly created secret scope. Eg. `databricks secrets put --scope databricks-google-sheets --key "databricks-google-sheets@{{MY-AWESOME-PROJECT}}.iam.gserviceaccount.com" --binary-file {{PATH-TO-JSON-FILE-FROM-STEP-5}} --profile DEFAULT`
8. Share your Google Sheet with the user `databricks-google-sheets@{{MY-AWESOME-PROJECT}}.iam.gserviceaccount.com`, and give Editor privileges



### Usage within Databricks Python notebook

```python
from databricks_google_sheets import DatabricksGoogleSheets
dgs = DatabricksGoogleSheets(dbutils)  # Pass in dbutils from the global scope of your Databricks runtime


# OPTION 1 - Create a Pandas dataframe from a Spark SQL query in Python
df = spark.sql("SELECT 'Hello from databricks-google-sheets' greeting;").toPandas()

# OPTION 2 - Create a dataframe directly in Pandas
import pandas as pd
df = pd.DataFrame({'greeting': ['Hello from databricks-google-sheets']})

# Write this dataframe to Google Sheets
dgs.df_to_sheets(df, spreadsheet_id='{{SPREADSHEET-ID-FROM-STEP-1}}', sheet_name='test', 
    dbsecret_scope='databricks-google-sheets', dbsecret_key='databricks-google-sheets@{{MY-AWESOME-PROJECT}}.iam.gserviceaccount.com')

# Read from Google Sheets into a new dataframe
newdf = dgs.sheets_to_df(spreadsheet_id='{{SPREADSHEET-ID-FROM-STEP-1}}', sheet_name='test', 
    dbsecret_scope='databricks-google-sheets', dbsecret_key='databricks-google-sheets@{{MY-AWESOME-PROJECT}}.iam.gserviceaccount.com')

# Compare the new dataframe to the original to ensure they are the same
assert df.equals(newdf) == True
```
pyroute53myip 0.0.2
This python tool pyroute53myip is useful to allow automate updating of a public DNS record hosted at Internet based in the public internet address from home. It is a quite typical scenario running at a domestic raspberry-pi tiny instance
Requires Python: >=3.7


# pyroute53myip

## Description 

This python tool pyroute53myip is useful to allow automate updating of a public DNS record hosted at Internet based in the public internet address from home. It is a quite typical scenario running at a domestic raspberry-pi tiny instance

## Author

Name: redcorjo 
Email: jordipromotions@gmail.com


## Config file structure

The tool self encrypt the AWS credentials initially added on clear. They are encrypted and useable only from the same host they were encrypted. First time the tool is executed, at command line there is a wizard asking for initial values.


Config file can be defined using env variable PYROUTE53MYIP_CONFIG

```
[aws]
aws_access_key_id = <access_key>
aws_secret_access_key = <secret_key>

[dns]
zoneid = <my_aws_zoneid>
record_set = my.domain.com
public_ip = 1.2.3.4

[scheduler]
frequency = 60

[mqtt]
mqtt_server = 127.0.0.1
mqtt_topic = pyroute53myip
```

## Usage

```sh
python3 -m pip install pyroute53myip
export PYROUTE53MYIP_CONFIG=./pyroute53myip.ini
python3 -m pyroute53myip.pyroute53myip:main
```

Version: 2023012901
textutils3 1.1.0
Recursively check spelling and grammer and other tasks with text documents.
Requires Python: >=3.9
Keywords: spellcheck

# Recursive Spellcheck in Python

[![PyPI Download stats](http://pepy.tech/badge/textutils3)](http://pepy.tech/project/textutils3)

Recursively spellcheck files using aspell or other backend.

Install aspell:

* Mac: `brew install aspell`
* Linux: `apt install aspell`
* Windows: use WSL

from Terminal:

```sh
python -m textutils3.spellcheck

python -m textutils3.latextdiff

python -m textutils3.find_bad_char
```
laboro-ftp 0.0.6
Laboro FTP module
Requires Python: >=3.9

---
gitea: none
include_toc: true
---
![Build Status](https://drone.mcos.nc/api/badges/laboro/laboro_ftp/status.svg) ![License](https://img.shields.io/static/v1?label=license&color=orange&message=MIT) ![Language](https://img.shields.io/static/v1?label=language&color=informational&message=Python)

# laboro_ftp

Laboro FTP module

This module is intended to be used by the [**Laboro** NO-Code / Low-Code workflow manager](https://codeberg.org/laboro/laboro).
laboro-demo 0.0.27
The Laboro demonstration module
Requires Python: >=3.9

---
gitea: none
include_toc: true
---
![Build Status](https://drone.mcos.nc/api/badges/laboro/laboro_demo/status.svg) ![License](https://img.shields.io/static/v1?label=license&color=orange&message=MIT) ![Language](https://img.shields.io/static/v1?label=language&color=informational&message=Python)

# laboro_demo

The Laboro demonstration module.

This module is not intended to be useful other than for test purpose.
laboro-http 0.0.5
The Laboro Http client module
Requires Python: >=3.9

---
gitea: none
include_toc: true
---
![Build Status](https://drone.mcos.nc/api/badges/laboro/laboro_http/status.svg) ![License](https://img.shields.io/static/v1?label=license&color=orange&message=MIT) ![Language](https://img.shields.io/static/v1?label=language&color=informational&message=Python)

# laboro_http

The Laboro Http client module

This module is intended to be used by the [**Laboro** NO-Code / Low-Code workflow manager](https://codeberg.org/laboro/laboro).
laboro-ssh 0.0.8
The Laboro SSH/SFTP client module
Requires Python: >=3.9

---
gitea: none
include_toc: true
---
![Build Status](https://drone.mcos.nc/api/badges/laboro/laboro_ssh/status.svg) ![License](https://img.shields.io/static/v1?label=license&color=orange&message=MIT) ![Language](https://img.shields.io/static/v1?label=language&color=informational&message=Python)

# laboro_ssh

The Laboro SSH/SFTP client module

This module is intended to be used by the [**Laboro** NO-Code / Low-Code workflow manager](https://codeberg.org/laboro/laboro).
laboro-template 0.0.6
Laboro templating module
Requires Python: >=3.9

---
gitea: none
include_toc: true
---
![Build Status](https://drone.mcos.nc/api/badges/laboro/laboro_template/status.svg) ![License](https://img.shields.io/static/v1?label=license&color=orange&message=MIT) ![Language](https://img.shields.io/static/v1?label=language&color=informational&message=Python)

# laboro_template

Laboro templating module

This module is intended to be used by the [**Laboro** NO-Code / Low-Code workflow manager](https://codeberg.org/laboro/laboro).
sonarcloudX1 0.1.0
lib para buscar wrapper SonarCloud

# DevopsX

## General Information
* **Software**: SonarCloud
* **Author**: Carlos Henrique Maulaz de Freitas
* **Author's e-mail**:carlosmaulaz@gmail.com
* **Source Repository**: [https://gitlab.com/immigrant-data-driven-development/libs/application/sonarcloud](https://gitlab.com/immigrant-data-driven-development/libs/application/sonarcloud.git)  

## Goal
O SonarCloud é um serviço de análise de códifo desenvolvido para detectar problemas em 25 diferentes linguagens de programação. O objetivo da lib é extrair os dados de uma organização na ferramenta.

	
## Instalation

To install sonarcloudX, run this command in your terminal:
```bash
pip install sonarcloudX
```

## Usage

```python

from sonarcloudX import factories
from pprint import pprint 

sonar_url = "https://sonarcloud.io"
personal_access_token =  "sonarcloud_token"

service = factories.ProjectFactory(personal_access_token=personal_access_token,sonar_url=sonar_url)
service.set_organization_name(organization_name = 'organization_name')
results = service.get_all(today=False)

print(results)

pprint (len(results))

for item in results:
    pprint (item.__dict__)

```
devopsX 0.0.17
DevOps é um produto da Microsoft que fornece controle de versão, relatórios, gerenciamento de requisitos, gerenciamento de projetos, compilações automatizadas, gerenciamento de laboratório, recursos de gerenciamento de testes e versões.

# DevopsX

## General Information
* **Software**:DevopsX
* **Author**:Paulo Sérgio dos Santos Júnior
* **Author's e-mail**:paulossjunior@gmail.com
* **Source Repository**: [https://gitlab.com/immigrant-data-driven-development/libs/application/azuredevops](https://gitlab.com/immigrant-data-driven-development/libs/application/azuredevops)  

## Goal
DevOps é um produto da Microsoft que fornece controle de versão, relatórios, gerenciamento de requisitos, gerenciamento de projetos, compilações automatizadas, gerenciamento de laboratório, recursos de gerenciamento de testes e versões.

## Documentation

The Documentation can be found in this [link](./docs/documentation.md)

## Generate documentation

To create the code documentation:
```bash
pdoc --html --force devopsX/ --output docs

```
### Acess code documentation	

To accesss the documenation, go to folder docs/devopsX and open index.html 
	
## Instalation

To install devopsX, run this command in your terminal:
```bash
pip install devopsX
```

## Usage

```python

from devopsX import factories
from pprint import pprint 
organization_url = "<DEVOPS URL>"
personal_access_token =  "<personal code access>"

project_service = factories.ProjectFactory(personal_access_token=personal_access_token,
                                            organization_url=organization_url)
projects = project_service.get_projects()

for project in projects:
    pprint(project.__dict__)

```
pyeasyencrypt 0.1.0
Your easy tool to encrypt and decrypt strings with a password
Requires Python: >=3.7


# pyeasyencrypt

## Description 

The purpose of this module is to simplify the way of encrypting and decrypting strings at python with a simple password

## Example of Python code
```python
import logging, os
# pip install pyeasyencrypt
from pyeasyencrypt.pyeasyencrypt import encrypt_string, decrypt_string

level = os.getenv("LOGGER", "INFO")
logging.basicConfig(level=level)
logger = logging.getLogger(__name__)

def main():
    logger.info("Example")
    clear_string = 'stringA'
    password = "my password"
    encrypted_string = encrypt_string(clear_string, password)
    decrypted_string = decrypt_string(encrypted_string, password)
    logger.info(f"clear_string={clear_string} decrypted_string={decrypt_string} password={password}  encrypted_string={encrypted_string}")
    logger.debug("Done")

if __name__ == '__main__':
    main()
```

## Author

Name: Jordi Redondo 
Email: jordipromotions@gmail.com
git repo: https://github.com/redcorjo/pyeasyencrypt.git

## Install

pip install pyeasyencrypt


Version: 2023010803