semvec/pypi-packages huggingface dataset:
covid19forecast 1.1.0
Python Package to get Covid19  Forecasting For all Cases Every Country in future using FBProphet Model
Requires Python: >=3.6
Keywords: Covid19,CoronaVirus,Forecasting

# Covid19  Forecasting For all Cases in future using fbprophet model

## about

Python Package to get Covid19  Forecasting For all Cases  in future



# Installation

```
pip install covid19forecast
or in colab google cloud
!pip install covid19forecast
```

## Usage for get first cases (confirmed,recoverd,deaths for any countery)

```
from covid19forecast import cases 
```
```
# country name
country='Iraq'
#path for covide19 dataset   
path_csv='covid_19_data.csv'
#name of  folder  
dir_name='Iraq'
# name of out result for all cases in new dataset 
out_csv='iraq.csv'
# what days number to forecasting for any case 
next_periods=10
# what name of dataset for all forecasting for any case
csv_name='iraq.csv'

```

```
# to get all cases for country 
all=cases.all_cases(country,path_csv,dir_name,out_csv)

# to get confirmed cases for country 
confirmed=cases.confirmed_case(country,path_csv,dir_name,out_csv)
#to get deaths  cases for country 
deaths=cases.deaths_case(country,path_csv,dir_name,out_csv)

#to get recoverd cases for country 
recoverd=cases.recoverd_case(country,path_csv,dir_name,out_csv)


```

## Usage for get Forcasting for all  cases (confirmed,recoverd,deaths for any countery)

```
from covid19forecast import forecast 
```
```
# to get forecasting for country confirmed case
forecast.confirmed_forecast(confirmed,next_periods,dir_name,csv_name,country)
# to get forecasting for country deaths case
forecast.deaths_forecast(deaths,next_periods,dir_name,csv_name,country)
# to get forecasting for country recoverd case
forecast.recoverd_forecast(recoverd,next_periods,dir_name,csv_name,country)
```
## Checking

To verify the retrieved data within this library
go to web site to get download new covid19 dataset

https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset

## Tutorial 
u can see tutorial in colab 

https://colab.research.google.com/drive/12TnzM0E-oZgsrwlaQ5vYCdhsym6UDNUa
lookml 2.0.0
A pythonic api for programatically manipulating LookML

pyLookML allows you to fetch, parse and program lookml very easily. 
It is an object oriented metaprogramming interface built on top of the AWESOME lkml parsing library which you can check out here: https://github.com/joshtemple/lkml. But extends it by adding convenience to it's json structure and more advanced integrations and object oriented behaviors.
Check out the full documentation for pyLookml project here: https://lookml.readthedocs.io/en/latest/

In the meantime here are some very basic examples for getting started:

get started fast:
`pip install lookml`

Connect to a lookml github project:
```
   import lookml
   proj = lookml.Project(
         repo= "llooker/russ_sandbox",
         access_token="your_github_access_token",
   )
   viewFile = proj.getFile('01_order_items.view.lkml')
   orderItems = viewFile.views.order_items
   print(orderItems.id)
```

Pure lookml generation:
```
import lookml

#create a new view
order_items = lookml.View('order_items')

# add a couple fields
order_items + 'id' + 'value'

# add a sum measure
order_itmems.addSum('id')

# order_items.view.lkml will be written in working directory
order_items.write()

```