semvec/pypi-packages huggingface dataset:
alphav 1.0.5
alpha vantage api wrapper
Requires Python: >=3.7

# alphav

alpha vantage api wrapper 

# Description
using a symbol object that pulls the data once the property is accessed.   

The data is then saved for the next property calls.     

# Example
```python
from alphav import Symbol
import os

# generate symbol
apikey = os.environ.get('API_KEY')
s = Symbol('IBM', apikey)

# print the data it provides
print(s.balance_sheet)
print(s.earnings)
print(s.income_statement)
print(s.cash_flow)
print(s.overview)
print(s.global_quote)
print(s.time_series_daily)
print(s.time_series_monthly)
print(s.time_series_monthly_adjusted)
print(s.time_series_weekly)
print(s.time_series_weekly_adjusted)
```


The properties are of data object, supporting
```python
# for balance sheet data
prop.main # the main data slice, annual by default
prop.annual # annual data when provieded
prop.quarterly # quarterly data when provided
prop.set_main('quarterly')
prop.main # will be prop.annual

# for the rest of the data
prop.main # only
```
Geometric-Mean-Method 0.0.0
Pi value approximation algorithm with Geometric Mean Method
Requires Python: >=3.6

# Pi value approximation algorithm with Geometric Mean Method

![image](https://user-images.githubusercontent.com/64249907/161782722-0b5c48e0-a723-4db0-b47c-14b9cf7c16db.png)

```Python
from math import sqrt

if __name__ == "__main__":

    p = 5
    n = pow(10, p)

    Aa = 0
    for i in range(0, n+1):
        H = sqrt(i*(n-i))
        Aa = Aa + H

    Aa = 8*Aa/n/n
    print(f"{Aa:.6}")
```


I am God once zero times •
xbench 0.0.3
Document Extraction Benchmark (xbench)
Requires Python: >=3.8

# EXtraction BENCHmark (xbench)

**XBench** is a Swiss Army Knife for working with document processing tools on the command line. It is developed by [Impira](https://www.impira.com/) but strives to be neutral and support a wide variety of platforms over time. It includes utilities for generating synthetic documents, evaluating documents against different services, saving their results, recreating them in other services, and comparing (benchmarking) their results.

See the [XBench docs](https://impira.github.io/xbench/index.html) for more information on how to install and use XBench.