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{ | |
"medical_agreement" : { | |
"client" : "ECR Salud", | |
"care_provider" : [ | |
"ECR Salud", | |
"Inmunomedica", | |
"Centro Médico de Quilicura", | |
"UCM", | |
"Medismart", | |
"Teledoc", |
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{ | |
"fonasa": [ | |
{ | |
"group": "01", | |
"items": [ | |
{ | |
"subgroup": "0101", | |
"description": "ATENCION ABIERTA", | |
"items": [ | |
{ |
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{ | |
"fonasa": [ | |
{ | |
"group": "29", | |
"items": [ | |
{ | |
"subgroup": "2904", | |
"description": "POR ESPECIALISTA EN ONCOLOGIA Y HEMATOONCOLOGOS.", | |
"items": [ | |
{ |
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""" | |
Description: Compose a CSV object. | |
Example execution: | |
python3 python_pipeline.py > output.csv | |
""" | |
import csv | |
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INPUT_DATA_BACK = [ | |
{ | |
"weekDayName": 3, | |
"scheduleBlocks": [ | |
{ | |
"startWorkingTime": 480, | |
"endWorkingTime": 720, | |
"tag": null, | |
"description": null | |
}, |
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{ | |
"region": { | |
"01": { "code": "01", "name": "Tarapacá", "abreviation": "TPCA" } | |
}, | |
"province": { | |
"011": { "code": "011", "name": "Iquique"} | |
}, | |
"comune": { | |
"01101": { "code": "01101", "code_comune_2018": "01101", "name": "Iquique"}, | |
} |
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""" | |
November 9th, 2021 | |
Naive Implmementation | |
Exacution example | |
> python3 string_match.py | |
""" | |
class StringMatch(): | |
text: str |
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#!/usr/bin/env jjs | |
/*#################################################################################################################################### | |
# As Nashorn does not have http capabilities through XMLHttpRequest (DOM API), we have to use regular Java classes instead. | |
# This sample shows how this can be acheived without depending on any third party libraries. Just a standard Java 8 JDK. | |
# Make sure to have JAVA_HOME/bin on your PATH for the shebang to work. Then just chmod +x away and run... | |
# Alternatively if you're on a non *nix OS, start with jjs -scritping httpsample.js | |
####################################################################################################################################*/ | |
var url = "https://api.github.com/users/billybong/repos"; | |
var response; |
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// Naive Graph Traversing. | |
console.log("edit a property from a relation"); | |
$("#id-733e2449d19b455db12241633b28cdab").prop("top_bottom", 0); | |
$("#id-733e2449d19b455db12241633b28cdab").prop("bottom_top", 0); | |
console.log("every input relation from the current element"); | |
$(ID).inRels().each(function(relation) { | |
if (relation.name){ | |
console.log(relation); |
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from math import ceil | |
import random | |
import pytz | |
from datetime import date | |
import pandas as pd | |
def dates_gen(cases: int = 1000) -> list: | |
return [random.randint(0, 1639758915) for _ in range(0, cases)] |