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import click
from pathlib import Path
from subprocess import call, check_output
from tqdm import tqdm

@click.command()
@click.argument('directory', type=click.Path(exists=True))
@click.option('--recursive', is_flag=True, help='Recursive')
@click.option('--file-ext', help='File format to process')
def main(directory, file_ext='mp4', recursive=False):

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from typing import Optional, Union
import numpy as np
import pandas as pd

from sklearn.linear_model import LinearRegression, LogisticRegression
from sklearn.base import BaseEstimator
from sklearn.utils.estimator_checks import check_estimator
from sklearn.utils.validation import check_X_y, check_array, check_is_fitted
from lightgbm import LGBMClassifier, LGBMRegressor

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/* 
Render embeds inline in Live Preview mode
Source: https://gist.github.com/asdfgeoff/e6116873daa81ae92a6755af1d3c19e5
*/

/***********
BLOCK EMBEDS
************/

/* Make a bunch of block-level elements involved in embed display as inline */

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from typing import Callable, Union
import numpy as np
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.utils.validation import check_X_y, check_array
from IPython.display import display

array_like = Union[list, np.ndarray]
matrix_like = Union[np.ndarray, pd.DataFrame]

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from airflow.operators.python_operator import PythonOperator


class SQLTemplatedPythonOperator(PythonOperator):
    """ Extend PythonOperator to receive a templated SQL query and also to display it in the "Rendered Template" tab in Airflow's UI.

    This is very helpful for troubleshooting specific task instances, since you can copy a propertly formatted query directly from
    the web UI rather than copying the contents of "templates_dict" and parsing it manually.

    Args:

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{%- extends 'full.tpl' -%}
// Source: http://damianavila.github.io/blog/posts/mimic-the-ipython-notebook-cell-execution.html

{% block input_group -%}/Users/geoffruddock/Library/Jupyter/nbconvert/templates
<div class="input_hidden">
{{ super() }}
</div>
{% endblock input_group %}

{%- block header -%}

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import datetime as dt
from typing import List, Tuple
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as plticker
from scipy.stats import norm


plt.rcParams['figure.facecolor'] = 'white'

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Packages

• lxml - Pythonic binding for the C libraries libxml2 and libxslt.
• boto - Python interface to Amazon Web Services
• Django - Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.
• Fabric - Library and command-line tool for streamlining the use of SSH for application deployment or systems administration task.
• PyMongo - Tools for working with MongoDB, and is the recommended way to work with MongoDB from Python.
• Celery - Task queue to distribute work across threads or machines.
• pytz - pytz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.4 or higher.

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