howardhamilton

#!/usr/bin/python
#
# run 'python num_line.py -v' to see doctest results.
# Howard Hamilton
# 17 March 2014

def number_line(L, I):
    '''
    Update number line intervals with addition of new interval.  
    

howardhamilton

#
# trie.py
#
# create trie data structure
#


class Node(object):
    """
    Node element of trie data structure.

howardhamilton

#
# commit_transfer.py
#
# I wrote this script in order to transfer commits between branches in a less painful way.  The use
# case is rebasing a working branch on its parent in order to use changes that have been pushed there.
# Yes, a rebase does preserve history, but only if you haven't already pushed the branch to a remote.
# If you have, it's best to create a fresh branch from the parent and transfer the commits there.
#
# My tasks are tracked in JIRA, so I write all of my commits with the following convention:
#

howardhamilton

"""
An outline for identifying N players with similar summary statistics to a player of interest.
A list of candidate players is compiled by filtering on position and end-of-season age.
Summary statistics are scaled to z-scores, which are the inputs to the machine learning model.
This algorithm uses K-Nearest Neighbor, but other algorithms (eg K-Means Clustering) can be substituted.

(c) 2015 Soccermetrics Research LLC
This code is licensed under the terms of the MIT License (http://choosealicense.com/licenses/mit/)
"""
from sklearn.neighbors import NearestNeighbors

howardhamilton

"""A Python context to move in and out of directories.

Copyright 2016-2020, Howard Hamilton.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and 
associated documentation files (the "Software"), to deal in the Software without restriction, in-
cluding without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, 
and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do 
so, subject to the following conditions:

howardhamilton

class RegexpReplacer(object):
    """
    Take in list or dictionary of regex patterns and substitutes, and apply them to text with a map.
    """

    def __init__(self, patterns):
        if type(patterns) is dict:
            self.patterns = [(re.compile(r"{}".format(regex)), patterns['replace'])
                             for regex in patterns['pattern']]
        else:

howardhamilton

import logging
import subprocess
from io import BytesIO


def execute_command(cmd, ns=__name__, shell_flag=False):
    """
    Execute command using a subprocess, and write streaming output to the screen.

    :param cmd: Command-line statement

howardhamilton

from lxml import etree
from lxml.builder import E


if __name__ == "__main__":
    with open('sample.xml') as f:
        xml = f.read()
        new_xml = E.Wrapper(etree.XML(xml))
        print(etree.tostring(new_xml, pretty_print=True))
        

howardhamilton

{
  "version": 1,
  "disable_existing_loggers": false,
  "formatters": {
    "default": {
      "format": "%(asctime)s - %(name)s - %(levelname)s: %(message)s"
    },
    "console": {
      "format": "%(name)-12s: %(message)s"
    }

howardhamilton

# unique list of dictionaries
# ---------------------------
# This problem comes up when I bulk insert records into databases
# because I can't check for existence of records (they don't exist yet, too slow, etc)
#
# I typically use a set to make list elements unique, but dicts and lists themselves
# can't be inserted in sets because they're mutable and thus unhashable.
#
# Solution is to make a tuple of the dict's items and insert it in set,
# then create dicts from each member of the set.