semvec/pypi-packages huggingface dataset:
bangla-python 1.9
bangla-python
Keywords: bangla-python,bangla language processing,bangla tokenizer,remove bangla punctuation,remove foreign words from bangla text,remove bangla stop words,bangla number to word from text,find bangla numbers from text,bangla to english number conversion,english to bangla number conversion,bangla number to word conversion

A comprehensive package for bangla language processing in python.<br> Find full documentation here: http://www.nahid.org/bangla-python
pingen 2023.3.26
Pingen client for Python

# Pingen Python
This is the repository that contains the API client for pingen.com

The quickest way to get going is:
```bash
pip install pingen
# or (depending on your system)
python3 -m pip install pingen
```

### Sending a single pdf file
Below shows a minimal way of interacting with the Pingen Python client.
It instantiates the client, and uploads a file called example.pdf
```python
import pingen

# Fill in your client id and secret when creating the Pingen Client
# It's recommended not to ship these with your code, but use a secret manager
pingen_client = pingen.PingenClient(client_id=..., secret=...)

pingen_client.create_letter(
    *pingen_client.file_upload('example.pdf'),
    auto_send=False,  # set this to True to immediately send this letter
)
```

### Sending a templated letter
If you wish to do some templating before sending each letter, this is how you could do that with `weasyprint`.
Ensure that you have `weasyprint` installed as a package before continuing.

This example also presumes the presence of this template file:

```html

```

```python
import weasyprint
```
surquest-GCP-secret-assessor 0.0.4
Utility package for assessing Google Cloud Platform (GCP) secrets uniformly

![GitHub](https://img.shields.io/github/license/surquest/python-gcp-secrets-assessor?style=flat-square)
![GitHub Workflow Status (with branch)](https://img.shields.io/github/actions/workflow/status/surquest/python-gcp-secrets-assessor/test.yml?branch=main&style=flat-square)
![Coverage](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/surquest/6e25c317000917840152a5e702e71963/raw/python-gcp-secrets-assessor.json&style=flat-square)
![PyPI - Downloads](https://img.shields.io/pypi/dm/surquest-GCP-secret-assessor?style=flat-square)

# Introduction

This project is designed to simplify access to the secrets stored in the Secret Manager within Google Cloud Platform (GCP) during the development life cycle of Python apps.

Let's imagine you are working on a Python-based application running in Google Cloud Run as part of a team. In this case:

* Development is done locally on your machine,
* Code versioning and CI/CD pipelines are orchestrated with a Git repository such as GitHub
* The deployed application is running in Cloud Run, where the secrets are mounted as environmental variables.

The problem is that you need to have the secret available in your local environment, as well as in the environment where the application unit and integration tests are running, and finally in the Cloud Run environment.

This Python package unifies access to secrets across all the above-mentioned environments. It first looks if the secret is available as an environmental variable. If not, it tries to load it from the Secret Manager with the help of default application credentials sourced from the `GOOGLE_APPLICATION_CREDENTIALS` environmental variable.

This approach allows you to have the same codebase for all the environments and maintain carefully only the default application credentials.


# Quick start

```python
# import the Secret Assessor class
from surquest.GCP.secret_assessor import Secret

secret = Secret.get("MY_SECRET") # returns the secret value

# If your secret is a JSON string, you can load it as a dictionary
secret = Secret.get("MY_SECRET", parse="JSON") # returns the secret value as a dictionary

# If your secret is a YAML string, you can load it as a dictionary
secret = Secret.get("MY_SECRET", parse="YAML") # returns the secret value as a dictionary
```

# Local development

You are more than welcome to contribute to this project. To make your start easier we have prepared a docker image with all the necessary tools to run it as interpreter for Pycharm or to run tests.


## Build docker image
```
docker build `
     --tag surquest/gcp/secretassessor `
     --file package.base.dockerfile `
     --target test .
```

## Run tests
```
docker run --rm -it `
 -v "${pwd}:/opt/project" `
 -e "GOOGLE_APPLICATION_CREDENTIALS=/opt/project/credentials/keyfile.json" `
 -w "/opt/project/test" `
 surquest/gcp/secretassessor pytest
```