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| FROM ubuntu:12.04 | |
| # Install dependencies | |
| RUN apt-get update -y | |
| RUN apt-get install -y apache2 | |
| # Install apache and write hello world message | |
| RUN echo "Hello Cloud Gurus!!!! This web page is running in a Docker container!" > /var/www/index.html | |
| # Configure apache | |
| RUN a2enmod rewrite |
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| version: 0.0 | |
| os: linux | |
| files: | |
| - source: /index.html | |
| destination: /var/www/html/ | |
| hooks: | |
| BeforeInstall: | |
| - location: scripts/install_dependencies.sh | |
| timeout: 300 | |
| runas: root |
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| import csv | |
| import datetime | |
| import json | |
| import logging | |
| import os | |
| from google.cloud import storage | |
| from twitter_scraper import get_tweets | |
| log = logging.getLogger() |
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| # Using @property decorator | |
| # Source - https://www.programiz.com/python-programming/property | |
| class Celsius: | |
| def __init__(self, temperature=0): | |
| self.temperature = temperature | |
| def to_fahrenheit(self): | |
| return (self.temperature * 1.8) + 32 | |
| @property |
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| def windowed_dataset(series, window_size, batch_size, shuffle_buffer): | |
| """Function for creating a windowed dataset for sequence training""" | |
| dataset = tf.data.Dataset.from_tensor_slices(series) | |
| dataset = dataset.window(window_size + 1, shift=1, drop_remainder=True) | |
| dataset = dataset.flat_map(lambda window: window.batch(window_size + 1)) | |
| dataset = dataset.shuffle(shuffle_buffer).map(lambda window: (window[:-1], window[-1])) | |
| dataset = dataset.batch(batch_size).prefetch(1) | |
| return dataset |
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| import numpy as np | |
| for i in list_vals: | |
| print('Anshaj') |
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