christinebuckler

##
# Usage:
# python wordle_csv_upload.py /tmp/file.csv
##

import webbrowser
import sys, os

filename = sys.argv[1]
csv_file = open(filename)

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#!/usr/bin/python
"""
cPickle works well and it is very flexible, but if array only data are available
numpy's save features can provide better read speed
"""

import pickle,os
import numpy as np

#######################################

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'''
To run test files, type the following into the terminal
py.test file.py –vv
'''

import unittest as unittest
from folder.file import MyClass

class TestMyClass(unittest.TestCase):

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def flatten_json(y):
    out = {}

    def flatten(x, name=''):
        if type(x) is dict:
            for a in x:
                flatten(x[a], name + a + '_')
        elif type(x) is list:
            i = 0
            for a in x:

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import numpy 

array_2d = np.array([1, 2, 3]).reshape(-1,1)
array_2d.shape # (3,1)

array_1d = array_2d.flatten()
array_1d.shape # (3,)


# and from 1d back to 2d...

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def precision(y_true, y_pred):
    i = set(y_true).intersection(y_pred)
    len1 = len(y_pred)
    if len1 == 0:
        return 0
    else:
        return len(i) / len1

def recall(y_true, y_pred):
    i = set(y_true).intersection(y_pred)

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# Normalize Discounted Communicative Gain  
# NDCG evaluated within list impression for top n items (where NCG is actually ranking and IDCG is the ideal ranking). 
# Relevance score is generally related to funnel metrics.

def dcg(data, n):
    rel = data['relevance_score']
    dcg = sum((rel/np.log2(i + 1)) for i in range(1, n+1)])
    return dcg

def ndcg(dcg, idcg):

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def func(arg1, arg2):
    """Summary line.

    Extended description of function.

    Parameters
    ----------
    arg1 : int
        Description of arg1
    arg2 : str

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# https://pypi.org/project/runipy

# To save the output of each cell back to the notebook file, run:
runipy -o MyNotebook.ipynb

# To save the notebook output as a new notebook, run:
runipy MyNotebook.ipynb OutputNotebook.ipynb

# To run a .ipynb file and generate an HTML report, run:
runipy MyNotebook.ipynb --html report.html

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Use example code to join all cell values in column A, separated by a comma. 
=TEXTJOIN(",",TRUE,A:A)