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import csv | |
import requests | |
import time | |
from lxml import html | |
title_list = [] | |
author_list = [] | |
def get_authors(element): |
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{ | |
"version": "0.2.0", | |
"configurations": [ | |
{ | |
"type": "node", | |
"request": "launch", | |
"name": "nodemon", | |
"runtimeExecutable": "nodemon", | |
"program": "${workspaceFolder}/server.js", | |
"restart": true, |
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import requests | |
from py2neo import Graph, Node | |
from time import time | |
import json | |
import re | |
def main(): | |
t1 = time() | |
connection = connect_database() |
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import boto3 | |
import uuid | |
def create_bucket_name(bucket_prefix): | |
# The generated bucket name must be between 3 and 63 chars long | |
return ''.join([bucket_prefix, str(uuid.uuid4())]) | |
def create_bucket(bucket_prefix, s3_connection): |
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def remove_lines(image, colors): | |
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
bin_image = cv2.threshold( | |
gray_image, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1] | |
h_contours = get_contours(bin_image, (25, 1)) | |
v_contours = get_contours(bin_image, (1, 25)) | |
for contour in h_contours: | |
cv2.drawContours(image, [contour], -1, colors[0][0], 2) |
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from nkocr import OcrTable | |
text = OcrTable("paste_image_url_here") | |
print(text) # or print(text.text) |
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import os | |
import glob | |
import pandas as pd | |
def main(): | |
data = pd.read_csv('/path/of/txt/', sep=" ", header=None)[0].values.tolist() | |
caminho = "/path/of/files" | |
finded = 0 | |
deleted = 0 | |
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import sklearn.datasets as datasets | |
import pandas as pd | |
from sklearn.tree import DecisionTreeClassifier | |
from sklearn.externals.six import StringIO | |
from IPython.display import Image | |
from sklearn.tree import export_graphviz | |
import pydotplus | |
iris = datasets.load_iris() | |
df = pd.DataFrame(iris.data, columns=iris.feature_names) |
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__author__ = 'sidharthgoyal' | |
import math | |
increment = 0.1 | |
startingPoint = [1, 1] | |
point1 = [1,5] | |
point2 = [6,4] | |
point3 = [5,2] | |
point4 = [2,1] |
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def gerar_nos(seq, arr= []): | |
seq = list(seq) | |
saida_array = seq[:3] | |
arr.append(''.join(saida_array)) | |
if len(seq) == 3: | |
return arr | |
seq.pop(0) | |
return gerar_nos(seq) | |