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istioctl --kubeconfig=kubeconfig pc log $pod --level grpc:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level hc:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level health_checker:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level http:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level http2:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level hystrix:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level init:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level io:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level jwt:debug | |
istioctl --kubeconfig=kubeconfig pc log $pod --level kafka:debug |
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import requests | |
import json | |
import subprocess | |
from collections import namedtuple | |
import time | |
PieceOfArts = namedtuple('PieceOfArt', ['id', 'variant']) | |
arts = { | |
'robust_statue': PieceOfArts('3865006808', '3072656478'), |
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package functionalkubs | |
/** | |
* Implement part 1 of http://adventofcode.com/2017/day/1. | |
* See https://github.com/raphait/kotlin-functional-kubs for instructions. | |
*/ | |
object Part1 { | |
fun captcha(input: String): Int { |
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instructions = "L5, R1, L5, L1, R5, R1, R1, L4, L1, L3, R2, R4, L4, L1, L1, R2, R4, R3, L1, R4, L4, L5, " \ | |
"L4, R4, L5, R1, R5, L2, R1, R3, L2, L4, L4, R1, L192, R5, R1, R4, L5, L4, R5, L1, L1, R48, " \ | |
"R5, R5, L2, R4, R4, R1, R3, L1, L4, L5, R1, L4, L2, L5, R5, L2, R74, R4, L1, R188, R5, L4, L2, " \ | |
"R5, R2, L4, R4, R3, R3, R2, R1, L3, L2, L5, L5, L2, L1, R1, R5, R4, L3, R5, L1, L3, R4, L1, L3, " \ | |
"L2, R1, R3, R2, R5, L3, L1, L1, R5, L4, L5, R5, R2, L5, R2, L1, L5, L3, L5, L5, L1, R1, L4, L3, L1, " \ | |
"R2, R5, L1, L3, R4, R5, L4, L1, R5, L1, R5, R5, R5, R2, R1, R2, L5, L5, L5, R4, L5, L4, L4, R5, L2, R1, " \ | |
"R5, L1, L5, R4, L3, R4, L2, R3, R3, R3, L2, L2, L2, L1, L4, R3, L4, L2, R2, R5, L1, R2".split(", ") | |
instructions = [[x[0], int(x[1:])] for x in instructions] |
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file = open("recommendations.txt") | |
recommendation = {} | |
for line in file: | |
# print(line) | |
if line == "": | |
pass | |
else: | |
if line in recommendation: | |
recommendation[line] += 1 |
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""" | |
The account was scraped using the following Twitter library: https://github.com/sixohsix/twitter | |
I prefer this library over Tweepy as it is much "closer" to the API (less abstraction). | |
The way the following script works is basically as follows: | |
- First, I get all of the user's friend (I get max 200 friend per call) and store their the friends' names in a list | |
- Once I have the list of all the user's friends, I iterate through it to get the friends of the friends | |
- In a second script, I count the number of times a particular username occurs, and then return the sorted list of | |
friends (the most followed ones). | |
- That's it, more or less |
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from PIL import Image | |
''' | |
Based on a script by BigglesZX: https://gist.github.com/BigglesZX/4016539 | |
BigglesZX was adapted as follows: | |
- Updated to be compatible with Python 3. | |
- The original function 'processImage' was renamed 'extract_and_resize_frames' and was adapted as follows: | |
- It resizes each frames as it extracts them | |
- It saves all the frames to an array |
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import functools | |
number = '''73167176531330624919225119674426574742355349194934 | |
96983520312774506326239578318016984801869478851843 | |
85861560789112949495459501737958331952853208805511 | |
12540698747158523863050715693290963295227443043557 | |
66896648950445244523161731856403098711121722383113 | |
62229893423380308135336276614282806444486645238749 | |
30358907296290491560440772390713810515859307960866 | |
70172427121883998797908792274921901699720888093776 |