semvec/pypi-packages huggingface dataset:
fastapi-aad-auth 0.0.1
Adding Azure Active Directory Authentication for FastAPI

************************
fastapi_aad_auth
************************

Adding Azure Active Directory Authentication for FastAPI

Using it
--------

The configuration is defined in ``src/fastapi_aad_auth/config.py``, and includes options for configuring
the AAD config, the login UI and the routes.

You can initialise it with::

    from fastapi_aad_auth import AADAuth, AuthenticationState, Config
    auth_provider = AADAuth()

    # If you had a config that wasn't set in the environment, you could use 
    # auth_provider = AADAuth(Config(<my config kwargs>)


You can use it for fastapi routes::

    from fastapi import APIRouter, Depends


    # Use the auth_provider.api_auth_scheme for fastapi authentication

    router = APIRouter()

    @router.get('/hello')
    async def hello_world(auth_state: AuthenticationState =D epends(auth_provider.api_auth_scheme)):
        print(auth_state)
        return {'hello': 'world'}

For starlette routes (i.e. interactive/HTML pages), use the auth_provider.auth_required for authentication::

    from starlette.responses import PlainTextResponse

    @auth_provider.auth_required()
    async def test(request):
        if request.user.is_authenticated:
            return PlainTextResponse('Hello, ' + request.user.display_name)

This middleware will set the request.user object and request.credentials object::

    async def homepage(request):
        if request.user.is_authenticated:
            return PlainTextResponse('Hello, ' + request.user.display_name)
        return PlainTextResponse(f'Hello, you')


You can set the swagger_ui_init_oauth using auth_provider.api_auth_scheme.init_oauth::

    from fastapi import FastAPI
    app = FastAPI(title='fastapi_aad_auth test app',
                  description='Adding Azure Active Directory Authentication for FastAPI',
                  version='0.1.0',
                  openapi_url=f"/api/v0/openapi.json",
                  docs_url='/api/docs',
                  swagger_ui_init_oauth=auth_provider.api_auth_scheme.init_oauth,
                  redoc_url='/api/redoc',
                  routes=routes)


To add the required middleware to the fastapi app use::

    auth_provider.configure_app(app)



(Built from `package-template <https://github.com/djpugh/package-template>`_ version 1.0.0)
nidhichaudharygsmtpd007 1.0.6
A library to convert the google sheets into pandas df and plot the graphs accordingly
Keywords: GoogleSheets,Plotting

Library: nidhichaudharygsmtpd007

This library helps in taking the google sheets and can even convert the sheets into the pandas dataframe and then it can use this dataframe to plot it into 3 different forms of graphs:
1. Bar plot
2. Line Plot with markers and dotted line
3. Scatter Plot with the mean line and the color.

** Details of each functions are described below

1. To call the google spreadsheet:
    - Use createcredentials() for this purpose:
            
            createcredentials('your api json filename', 'spreadsheet to be called')
        Put the full path for the api json filename
    - It returns the list of the dictionary from the called spreadsheet.

2. To convert the list of dictionary returned from the createcredentials() to dataframe:
    - Use createDF() for this purpose:
            
            createDF(d) 
                - d: the returned list of dictionary
    - Returns the dataframe that can be used for plotting.

3. To plot the graphs of your choice:
    - Currently the library provides you to plot 3 graphs: Bar Plot, Line Plot, Scatter Plot.
   
    - For Barlplot you need to call:
          
            plotBar(dataframe, 'column name for the x axis', 'column name for the y axis')
        - The function automatically plots the graph for you.
    
    - For Lineplot you need to call:
            
            plotLine(dataframe, 'column name for the x axis', 'column name for the y axis')
         - The function plots the graph which is represented by the dotted line and the points are marked by the '>' symbol.

    - For Scatterplot you need to call:
            
            plotScatter(dataframe, 'column name for the x axis', 'column name for the y axis', colors)
            colors: Array for designing the colorbar.
        - The function returns the Scatterplot which is represented by the green color and along with it there shall be a color bar which describes the  variation of color throughout the plotting of graph. Along with that mean is also plotted with that.

    Note: All figures can be easily saved.

    Pre-Requisites:
    1. Google API for spreadsheets

    For creating this library I have used gspread for calling the google spreadsheet api.
speed-reader 1.0.3
A speed reader implemented in Python
Requires Python: >=3.6

# speed-reader

This is a simple speed reader that takes input from a TXT file and reads through it, word by word.

## Installation

### git

```$ git clone https://github.com/h5law/speed-reader.git```

```$ cd speed-reader```

```$ pip install .```


### pip

```$ pip install --user speed-reader```


## Usage

```$ speed-reader --help```


```Usage: speed-reader [OPTIONS] PATH```

```Options:```
```  --version      Show the version and exit.```
```  --wpm INTEGER  Read at specified WPM, defaults to 160```
```  --help         Show this message and exit.```


## Other
You can find the project homepage on [GitHub](https://github.com/h5law/speed-reader)
As well as on [PyPi](https://pypi.org/project/speed-reader/)

## Author
###### h5law