EricSchles

from datetime import datetime, timedelta
from textwrap import dedent
from functor import my_function

# The DAG object; we'll need this to instantiate a DAG
from airflow import DAG

# Operators; we need this to operate!
from airflow.operators.bash import BashOperator

EricSchles

from pyspark.sql.functions import col

def groupby(df, columns):
  sdf = df.to_spark()
  _groups = sdf.select(*columns).distinct().collect()
  _groups = [group.asDict() for group in _groups]
  groups = []
  for group in _groups:
    tmp = []
    for column in columns:

EricSchles

from tensorflow.keras import Model
import tensorflow as tf
import numpy as np
import pandas as pd
import random

class ReluDense(tf.Module):
    def __init__(self, in_features, out_features, name=None):
        super().__init__(name=name)
        self.w = tf.Variable(

EricSchles

from tensorflow.keras import Model
import tensorflow as tf
import numpy as np
import pandas as pd
import random

class ReluDense(tf.Module):
    def __init__(self, in_features, out_features, name=None):
        super().__init__(name=name)
        self.w = tf.Variable(

EricSchles

from tensorflow.keras import Model
import tensorflow as tf
import numpy as np
import pandas as pd
import random

class ReluDense(tf.Module):
    def __init__(self, in_features, out_features, name=None):
        super().__init__(name=name)
        self.w = tf.Variable(

EricSchles

import tensorflow as tf
import numpy as np
import pandas as pd

class ReluDense(tf.Module):
    def __init__(self, in_features, out_features, name=None):
        super().__init__(name=name)
        self.w = tf.Variable(
            tf.random.normal([out_features, out_features]), name='w'
        )

EricSchles

pyramid_sum = lambda n: (2*(n**2) - (2*n - 1))

EricSchles

from glob import glob
from json import load

def loc(nb):
    cells = load(open(nb))["cells"]
    return sum(len(c["source"]) for c in cells)

root_folder = "~"
summation = 0
for File in glob(root_folder+"/**/*.ipynb", recursive=True):

EricSchles

python setup.py sdist bdist_wheel
python -m twine upload --repository-url https://test.pypi.org/legacy/ dist/*
python -m twine upload dist/*

EricSchles

import numpy as np
import pandas as pd
from sklearn import linear_model
from sklearn.model_selection import train_test_split

# In general for the way to do type hinting is very straight forward.
# simply don't instantiate the class to use it as a 'type'

# Here's a generic example: