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# Load the Pandas libraries with alias 'pd' 
import pandas as pd 

from matplotlib import pyplot as plt
from scipy.cluster.hierarchy import dendrogram, linkage
from sklearn import datasets
import numpy as np

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#https://github.com/delip/blog-stuff/blob/master/tensorflow_ufp.ipynb

#https://github.com/delip/blog-stuff/blob/master/tensorflow_ufp.ipynb

import tensorflow as tf
import numpy as np
import math, random


np.random.seed(100)

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#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <stdlib.h>
#include <string.h>
#include <sys/types.h>
#include <wait.h>
#include <signal.h>

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#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <stdlib.h>
#include <string.h>
#include <sys/types.h>
#include <wait.h>

void cerrar (int pipe1[2], int pipe2[2])
{

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select 'type ' ||  table_name || '_T is 
record (' || chr(13) || listagg(column_name || ' ' || 
table_name ||'.'||column_name || '%type',','||chr(13)) 
within group (order by column_id)  
|| '); ' || CHR(13) ||
'type '||TABLE_NAME||'_T_C is table of '||TABLE_NAME||'_T;' || CHR(13) ||
'T '||TABLE_NAME|| '_T_C;'
from user_tab_columns 
where table_name = '<PONER EL NOMBRE DE LA TABLA>'
group by table_name

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create type t_flavio as object(c1 varchar2(100), c2 number);

create type t_flavio_c as table of t_flavio;

declare
  tabla t_flavio_c;
begin
with c1 as
(
select xmlelement("root",