su79eu7k su79eu7k

## asnyc_sqlalchemy_core_on_fastapi.py
import asyncio
from fastapi import FastAPI
from pydantic import BaseModel
from typing import List
import sqlalchemy
from sqlalchemy.ext.asyncio import create_async_engine

engine = create_async_engine(
    "sqlite+aiosqlite:///simulations.db", echo=True, future=True
)

## sap_bapi.py
import pandas as pd
from pyrfc import Connection, ABAPApplicationError, ABAPRuntimeError, LogonError, CommunicationError


class RFC_Handle(object):
    def __init__(self):
        self.conn = None

    def login(self, sap_id, sap_pwd):
        try:

## sap_table_access_and_report_generation.py
import pandas as pd
from pyrfc import Connection, ABAPApplicationError, ABAPRuntimeError, LogonError, CommunicationError


class RFC_Handle(object):
    def __init__(self):
        self.conn = None

    def login(self, sap_id, sap_pwd):
        try:

## sap_login.py
from pyrfc import Connection, ABAPApplicationError, ABAPRuntimeError, LogonError, CommunicationError


class RFC_Handle(object):
    def __init__(self):
        self.conn = None

    def login(self, sap_id, sap_pwd):
        try:
            self.sap_id = sap_id

## handle_last_index.py
def handle_last_index(elements, last_index):
    grouped = []
    for i, _ in enumerate(last_index):
        if i == 0:
            grouped.append(' '.join(elements[:last_index[i] + 1]))
        elif i == len(last_index) - 1:
            grouped.append(' '.join(elements[last_index[i - 1] + 1:]))
        else:
            grouped.append(' '.join(elements[last_index[i - 1] + 1:last_index[i] + 1]))

## pmml_bayesnet.ipynb

      
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                su79eu7k
                / pmml_bayesnet.ipynb
            
            
              Created
              December 6, 2018 12:51
                — forked from rtbs-dev/pmml_bayesnet.ipynb
            
              
                Bayesian Network Models in PyMC3 and NetworkX
              
          
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## distcorr.py
from scipy.spatial.distance import pdist, squareform
import numpy as np

from numbapro import jit, float32

def distcorr(X, Y):
    """ Compute the distance correlation function

    >>> a = [1,2,3,4,5]
    >>> b = np.array([1,2,9,4,4])
	import asyncio
	from fastapi import FastAPI
	from pydantic import BaseModel
	from typing import List
	import sqlalchemy
	from sqlalchemy.ext.asyncio import create_async_engine

	engine = create_async_engine(
	"sqlite+aiosqlite:///simulations.db", echo=True, future=True
	)
	import pandas as pd
	from pyrfc import Connection, ABAPApplicationError, ABAPRuntimeError, LogonError, CommunicationError


	class RFC_Handle(object):
	def __init__(self):
	self.conn = None

	def login(self, sap_id, sap_pwd):
	try:
	def handle_last_index(elements, last_index):
	grouped = []
	for i, _ in enumerate(last_index):
	if i == 0:
	grouped.append(' '.join(elements[:last_index[i] + 1]))
	elif i == len(last_index) - 1:
	grouped.append(' '.join(elements[last_index[i - 1] + 1:]))
	else:
	grouped.append(' '.join(elements[last_index[i - 1] + 1:last_index[i] + 1]))
	from scipy.spatial.distance import pdist, squareform
	import numpy as np

	from numbapro import jit, float32

	def distcorr(X, Y):
	""" Compute the distance correlation function

	>>> a = [1,2,3,4,5]
	>>> b = np.array([1,2,9,4,4])