python: Write totals at different indentation levels

"""
ReportWithLevels
__author__ = 'Margery Harrison'
__license__ = "Public Domain"
__version__ = "1.0"
"""

import sys

class ReportWithLevels():

    def __init__(self):
        """
        Sets the default values for the class
        """
        self.fdout=sys.stdout  #default - writes report to stdout
        self.number_width=10
        self.level_indent=2
        self.total_width=30
        self.debug = True
        self.min_level = 1
        self.max_level = 4

        #levels before which to print a newline
        self.newline_before = [1]

    # open the input path as file to write to
    def open_outfile(self,path):
        try:
            self.fdout = open(path,'w')
        except IOError:
            msg="{0:s} Can't open and write to {1:s}".format(self.__class__.__name__,path)
            sys.stderr.write(msg)

    # print debug statement if debugging turned on
    def debugPrint(self,message):
        if self.debug:
            print(message)

    # Write a line out to the output file with newline at end
    def writeLine(self,message):
        self.fdout.write(message + '\n')

    # Print message and total with indentation set by input level
    def printLevel(self, level, message, total):
        lev=int(level)
        assert lev >= self.min_level and lev <= self.max_level,\
            "input level not within current limits"

        #skip a space before level 1 statements
        if lev in self.newline_before:
            self.writeLine('')

        #s1 and s2 are number of spaces for formatting
        s1 = lev * self.level_indent
        s2 = self.total_width - s1

        #initialize fstr to the correct number of spaces
        fstr='{{0:{0:d}s}} {{1:{1:d}s}}'.format(s1,s2)

        # Number format string is right justified within number_width
        number_format='{{2:-{0:d}d}}'.format(self.number_width)
        fstr+=number_format
        self.debugPrint('level {0:d} format str= {1:s}'.format(lev,fstr))

        self.writeLine(fstr.format(' ', message, int(total)))


if __name__ == '__main__':
    print "Testing ReportWithLevels.printLevel()"
    pl=ReportWithLevels()
    pl.open_outfile("testout.txt")
    pl.writeLine("This is my report")
    pl.number_width=12
    tot=7
    for level in [1,2,3,2,2,3,4,3,1]:  #range(1,4):
        msg='level {0:d} msg'.format(level)
        tot=tot * 12
        pl.printLevel(level,msg,tot)


    #pl.printLevel(8,"level 8 msg",88)  #test assert error


assert isinstance() not for file stream parameters?

I'm writing methods in PyCharm, and I'd like to follow its hints for the way I should be structuring my code. Here I'm passing in a parameter of type file stream, could be sys.out or a file descriptor. It prompted me to include an "assert isinstance()" for the input parameter. 

    def set_stream(self,fdout):
        """
        :param fdout: 
        """ 
        assert isinstance(fdout,...) 

I was looking up what type to call it for the purposes of isinstance() and I came across  http://dobesland.wordpress.com/2007/10/07/python-isinstance-considered-useful/:

The classic example of this is python’s famous “file-like objects”, which typically implement read and/or write in the same way and are accepted by various python functions.  I believe the DB API is another well-used example of this.  In both cases, there is no common base-class, so it’s impossible to use isinstance() to check whether a particular object is, in fact, file-like or a database object.

I guess I'll leave that assert() out. The code will break reliably enough when someone tries to write to an fdout that isn't the right sort of object.

python: CSV analysis using Counter and DictReader and format

Here is a simple CSV file:

name,color,size,shape,number
tom,red,big,square,3
mary,blue,big,triangle,5
sally,green,small,square,2
edith,blue,small,triangle,1
wally,red,big,square,7
jon,blue,small,triangle,3

This code reads in the simple CSV and reports on it:


import os.path 
import csv 
import collections


def printLevel(level, message, total):
""" Print message and totals, with spacing determined by level
   

    Keyword arguments:

    level   -- integer from 1 to 4

    message -- string, e.g. "Number of happy tomcats"

    total   -- for this version, should be an integer count 

"""
    lev=int(level)
        
    if lev==1:
        print("")
    #fstr1='{0:5s} {1:35s} {2:-3d}'
    #fstr2='{0:10s} {1:30s} {2:-3d}'
    s1=5*lev  #5 or 10
    s2=40-s1
    fstr='{{0:{0:d}s}} {{1:{1:d}s}}'.format(s1,s2)
    fstr+=' {2:-3d}'
    print fstr.format(' ', message, int(total))

def print_colors_shapes(c):
"""Prints report on number of shapes of different colors
    keyword argument:
    c -- collection that includes values in shape_list, color_list below
"""
    shape_list= ['square', 'triangle','circle']
    color_list= ['red', 'blue', 'green','yellow']
    #first print shapes
    for shape in shape_list:
        msg = 'Number of '+ shape + 's'
        tot=c.get(shape,"0")
        printLevel(1, msg,tot)
        if int(tot) > 0:
            for color in color_list:
                msg = "Number of " + color + " " + shape + 's'
                tot=c.get(color + '_' + shape,"0")
                printLevel(2, msg, tot)
    for color in color_list:
        msg = 'Total {0} shapes'.format(color)
        tot = c.get(color,'0')
        printLevel(1,msg,tot)


def count_color_shape(my_reader):
""" create counters for colors and shapes separate and combined
    keyword argument:
    my_reader -- of type csv.DictReader
"""
    c = collections.Counter()
    for row in my_reader:
        print row
        color = row['color']
        shape = row['shape']
        c[color] += 1
        c[shape] += 1
        c[color + '_' + shape] += 1
    return c


def read_dict(path):
    with open(path) as csv_file:
        my_reader = csv.DictReader(csv_file)
        print my_reader.fieldnames
        #now have the read_dict() method return the Counter datastructure
        c = count_color_shape(my_reader)
        print c
        print_colors_shapes(c)

def test_dict():
    datadir = "/Users/margery/Documents/pystuff/pyGotham/demo/data"
    csv_file = 'simpleCSV.txt'
    path = os.path.join(datadir, csv_file)
    print path
    read_dict(path)

test_dict()
 
Here is the output:
/usr/bin/python /Users/margery/PycharmProjects/proj3/TestDict1.py
/Users/margery/Documents/pystuff/pyGotham/demo/data/simpleCSV.txt
['name', 'color', 'size', 'shape', 'number']
{'color': 'red', 'shape': 'square', 'number': '3', 'name': 'tom', 'size': 'big'}
{'color': 'blue', 'shape': 'triangle', 'number': '5', 'name': 'mary', 'size': 'big'}
{'color': 'green', 'shape': 'square', 'number': '2', 'name': 'sally', 'size': 'small'}
{'color': 'blue', 'shape': 'triangle', 'number': '1', 'name': 'edith', 'size': 'small'}
{'color': 'red', 'shape': 'square', 'number': '7', 'name': 'wally', 'size': 'big'}
{'color': 'blue', 'shape': 'triangle', 'number': '3', 'name': 'jon', 'size': 'small'}
Counter({'blue': 3, 'square': 3, 'triangle': 3, 'blue_triangle': 3, 'red_square': 2, 'red': 2, 'green': 1, 'green_square': 1})

      Number of squares                     3
           Number of red squares            2
           Number of blue squares           0
           Number of green squares          1
           Number of yellow squares         0

      Number of triangles                   3
           Number of red triangles          0
           Number of blue triangles         3
           Number of green triangles        0
           Number of yellow triangles       0

      Number of circles                     0

      Total red shapes                      2

      Total blue shapes                     3

      Total green shapes                    1

      Total yellow shapes                   0


python: csv.dictreader - That's what I should have been using

I learned late Wednesday that I'm supposed to give a talk at PyGotham about my forays into python dictionary land. So I did some research. And what I really should have been using is a csv reader flavor called dictreader. This does exist in python 2.6, so being stuck there is no excuse.

There's a good explanation at http://pymotw.com/2/csv/#using-field-names

And great examples at:

http://www.youlikeprogramming.com/2013/11/python-csv-reader-dictreader-quick-reference/

python: Links to my posts about python dictionary objects

purpose

The reason for my interest is that we generate output tab-separated files containing values that need to be tabulated into reports. I was looking for a way to generalize the code for creating these reports. In other words:

Given a list of strings describing the counts saved in each column of a CSV file, what would be the best way to automate the creation of reports of counts for individual and common categories?

For example, if a list of voters had values like Party Affiliation (D/R/O/U), Gender, Zip Code, etc, I should be able to feed in these values and get a report listing totals for Female Republicans voters[R][F], Male Democrats with Zip Code 12345 voters[D][M][12345], total unaffiliated voters voters[U], etc. And then I should be able to use the same tool to automate reports for my next list of zoo animals, with columns tabulating Species, Location, Diet...

input

1. list of column ID's
2. dictionary mapping column ID's to corresponding strings to use in report
3. collection of totals desired for the report

output

1. From input 1. and the CSV file you should be able to produce the dictionary structure containing all the totals.
2. From 1 and 2 you should be able to produce a function to generate strings for a report line
3. From 1, 2, 3 you should be able to produce a general sort of report. (I haven't bothered with that yet.)

links

I know there is a better way to organize this blog to enable easier searching by topic but I haven't investigated how yet. Until then, collected here are the posts where I was exploring the use of multidimensional dictionaries:

• Monday, November 28, 2011
  python: 2-D dictionary, somewhat dynamically filled
• Tuesday, March 11, 2014 6pm
  python: building 3-D dictionary
• Tuesday, March 11, 2014 7pm
  Python: build and initialize a dictionary from a list of lists
• Friday, March 28, 2014
  python: 1-d dictionary for counting hierarchical attributes
• Thursday, May 23, 2013
  Python: given two lists of strings, create 2-d dictionary to hold int values, initialized to 0

At some point I thought I had been clever, and posted the way to nest dictionaries. Later, I found that it did not work--my test data had had too many 1's and I hadn't caught that I was adding up the wrong values.

I ended up using a 1-D dictionary to save my multidimensional values. This worked so long as I could use a single character to express all the possibilities for each dimension, with no re-use.

python: 1-d dictionary for counting heirarchical attributes

This dictionary method uses concatenated characters instead of sub-dictionaries to track the hierarchical counts. e.g Number of Dogs could be pets['D'], Number of red dogs could be pets['DR']. Number of red dogs living in Cambridge could be pets['DRC'].

What follows is the general dictionary-building method, followed by a method written to illustrate how it could be used, followed by the printout from the test method.

# Given a list of lists, build a set of keys that combine fields from each list
# return a 1-d dictionary of these keys initialized to input_default
#
# @param list_of_lists = list of key-lists - Should be single unique characters.
# @param input_default [optional] Value to initialize each dictionary entry
# if input_default parameter not given, then 0 is used
def build1Dictionary(list_of_lists,input_default=0):
    number_of_lists=len(list_of_lists)
    if number_of_lists==0:
        return dict()
    keylist=list_of_lists[0]
    if number_of_lists==1:
        return dict.fromkeys(keylist,input_default)
    for next_list in list_of_lists[1:]:
        new_list=list(keylist)
        for key in keylist:
            for xkey in next_list:
                new_list.append(key+xkey)
        keylist=new_list
    return dict.fromkeys(keylist,input_default)

# Here is a method to test the dictionary:
def count_pets():
    #Create the dictionary
    pets=['D','C','F','B']
    gender=['g','b']
    home=['R','S','U']
    words=dict(D="Dog",C="Cat",F="Fish",B="Bird",\
       g="Girl",b="Boy",R="Rural",S="Suburban",U="City")
    pets_dict=build1Dictionary([pets,gender,home])
   
    #fill the dictionary with some counts
    data=["DgS","DgS","DbR","CgU","FgS","CgR","BbR"]
    for pet in data:
        p=pet[0:1]
        g=pet[1:2]
        h=pet[2:3]
        pets_dict[p]+=1
        pets_dict[p+g]+=1
        pets_dict[p+g+h]+=1
   
    #Print the counts indented by level of heiarchy
    for p in pets:
        print ("%d %s(s)" % (pets_dict[p],words[p]))
        for g in gender:
            if pets_dict[p+g]>0:
                print ("  %d owned by a %s" % \
                   (pets_dict[p+g],words[g]))
                for h in home:
                    if pets_dict[p+g+h] > 0:
                        print("    %d in %s environment." % \
                            (pets_dict[p+g+h],words[h]))
   

if __name__ == '__main__':
    count_pets()

Then when I run it, it prints out:

3 Dog(s)
  2 owned by a Girl
    2 in Suburban environment.
  1 owned by a Boy
    1 in Rural environment.
2 Cat(s)
  2 owned by a Girl
    1 in Rural environment.
    1 in City environment.
1 Fish(s)
  1 owned by a Girl
    1 in Suburban environment.
1 Bird(s)
  1 owned by a Boy
    1 in Rural environment.

Python: build and initialize a dictionary from a list of lists

OK, so building on the last post. Here's a general purpose function that takes a list of desired key-lists, and returns a multi-dimensional data dictionary.

##
## Takes dictionary and a list of desired keys
## adds the keys to the dictionary, initializing them to input parameter
#
# @param input_dictionary Name of input dictionary
# @param input_keys List of desired keys
# @param input_default [optional] Value to initialize each dictionary entry
# if input_default parameter not given, then 0 is used
#
#
def setDictionaryDefaults(input_dictionary,input_keys,input_default=0):
    for key in input_keys:
      input_dictionary.setdefault(key,input_default)


##
# Given a list of lists, build a multidimensional dictionary, initialized to optional input parameter
#
# @param list_of_lists = list of key-lists
# @param input_default [optional] Value to initialize each dictionary entry
# if input_default parameter not given, then 0 is used
def buildDictionary(list_of_lists,input_default=0):
    d=dict()
    number_of_lists=len(list_of_lists)
    if number_of_lists==0:
        return d
    setDictionaryDefaults(d,list_of_lists[0],input_default)
    if number_of_lists==1:
        return d
    next_d=dict()
    for next_list in list_of_lists[1:]:
        setDictionaryDefaults(next_d,next_list,d)
        d=next_d
        next_d=dict()
    return d

Here I test it:

 Python 2.4.1 (#2, Jul 24 2007, 12:14:31)
[GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-34)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from lists_to_dict import buildDictionary
>>> a=['a','b']
>>> c=[a]
>>> d=buildDictionary(c,1)
>>> d
{'a': 1, 'b': 1}
>>> q=['R','S','T']
>>> x=['X','XX','XXX']
>>> y=['Y','YY']
>>> c=[a,q,x,y]
>>> c
[['a', 'b'], ['R', 'S', 'T'], ['X', 'XX', 'XXX'], ['Y', 'YY']]
>>> d=buildDictionary(c,1)
>>> d
{'Y': {'X': {'S': {'a': 1, 'b': 1}, 'R': {'a': 1, 'b': 1}, 'T': {'a': 1, 'b': 1}}, 'XX': {'S': {'a': 1, 'b': 1}, 'R': {'a': 1, 'b': 1}, 'T': {'a': 1, 'b': 1}}, 'XXX': {'S': {'a': 1, 'b': 1}, 'R': {'a': 1, 'b': 1}, 'T': {'a': 1, 'b': 1}}}, 'YY': {'X': {'S': {'a': 1, 'b': 1}, 'R': {'a': 1, 'b': 1}, 'T': {'a': 1, 'b': 1}}, 'XX': {'S': {'a': 1, 'b': 1}, 'R': {'a': 1, 'b': 1}, 'T': {'a': 1, 'b': 1}}, 'XXX': {'S': {'a': 1, 'b': 1}, 'R': {'a': 1, 'b': 1}, 'T': {'a': 1, 'b': 1}}}}
>>>
>>> c=[]
>>> d=buildDictionary(c,1)
>>> d
{}
>>> a=['q','r']
>>> c=[a]
>>> buildDictionary(c)
{'q': 0, 'r': 0}
>>> d=buildDictionary(c)
>>> d
{'q': 0, 'r': 0}
>>>

python: building 3-D dictionary

We're using 2.4 so don't have defaultdict. Her's a way to create one using dict() and setdefault():

>>> hid=dict()
>>> hid.setdefault('H',0)
0
>>> hid.setdefault('I',0)
0
>>> bkd=dict()
>>> bkd
{}
>>> bkd.setdefault('Z',hid)
{'I': 0, 'H': 0}
>>> bkd
{'Z': {'I': 0, 'H': 0}}
>>> bkd.setdefault('CH',hid)
{'I': 0, 'H': 0}
>>> bkd
{'CH': {'I': 0, 'H': 0}, 'Z': {'I': 0, 'H': 0}}
>>> epd=dict()
>>> epd.setdefault('E',bkd)
{'CH': {'I': 0, 'H': 0}, 'Z': {'I': 0, 'H': 0}}
>>> epd.setdefault('P',bkd)
{'CH': {'I': 0, 'H': 0}, 'Z': {'I': 0, 'H': 0}}
>>> epd
{'P': {'CH': {'I': 0, 'H': 0}, 'Z': {'I': 0, 'H': 0}}, 'E': {'CH': {'I': 0, 'H': 0}, 'Z': {'I': 0, 'H': 0}}}

Now use it:

>>> ep=['E','P']
>>> bk=['Z','CH']
>>> hi=['H','I']
>>> i=0
>>> for e in ep:
...   for b in bk:
...     for h in hi:
...       epd[e][b][h]=i
...       i+=1
...
>>> epd
{'P': {'CH': {'I': 7, 'H': 6}, 'Z': {'I': 7, 'H': 6}}, 'E': {'CH': {'I': 7, 'H': 6}, 'Z': {'I': 7, 'H': 6}}}

>>> epd['E']['Z']['H']
6

I want to start with lists and build dictionaries from there. Here's the start of that automation:

>>> def setDefaults(k,d):
...   for key in k:
...     d.setdefault(key,0)
...
>>> kay=['A','B','C','D']
>>> dee=dict()
>>> setDefaults(kay,dee)
>>> dee
{'A': 0, 'C': 0, 'B': 0, 'D': 0}

Now update setDefaults to take the default initializer as a parameter:

>>> def setDefaults(k,d,i):
...   for key in k:
...     d.setdefault(key,i)
...
>>> kay
['A', 'B', 'C', 'D']
>>> d2=dict()
>>> setDefaults(kay,d2,2)
>>> d2
{'A': 2, 'C': 2, 'B': 2, 'D': 2}

OK, now here we start with three lists and build a 3-d dictionary using the setDefaults() method:

>>> kay
['A', 'B', 'C', 'D']
>>> ell=['X','Y','Z']
>>> grk=['pi','ro','lamtha','tau']
>>> kay_ell=dict()
>>> kay_d=dict()
>>> setDefaults(kay,kay_d,0)
>>> kay_d
{'A': 0, 'C': 0, 'B': 0, 'D': 0}
>>> setDefaults(ell,kay_ell,kay_d)
>>> ell
['X', 'Y', 'Z']
>>> kay_ell
{'Y': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'X': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'Z': {'A': 0, 'C': 0, 'B': 0, 'D': 0}}
>>> kay_ell_grk=dict()
>>> setDefaults(grk,kay_ell_grk,kay_ell)
>>> kay_ell_grk
{'tau': {'Y': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'X': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'Z': {'A': 0, 'C': 0, 'B': 0, 'D': 0}}, 'pi': {'Y': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'X': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'Z': {'A': 0, 'C': 0, 'B': 0, 'D': 0}}, 'ro': {'Y': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'X': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'Z': {'A': 0, 'C': 0, 'B': 0, 'D': 0}}, 'lamtha': {'Y': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'X': {'A': 0, 'C': 0, 'B': 0, 'D': 0}, 'Z': {'A': 0, 'C': 0, 'B': 0, 'D': 0}}}
>>>

python: "splat" operator * to unpack a list to use it as method parameters

I had a long list of parameters to be re-used in different methods. 

if condition1:
    method1( a,b,c,d,e,f,g,h,i,j)
elif condition2:
    method2( a,b,c,d,e,f,g,h,i,j)

I wanted to define the list only once.

 parameter_list=a,b,c,d,e,f,g,h,i,j

I didn't know how to use the values in the method call. If you use it directly, i.e.

method1(parameter_list) <- br="" nope="">

it's only one parameter, instead of the number of parameters in the list.

I found the answer in:
http://stackoverflow.com/questions/4979542/python-use-list-as-function-parameters

Apply the "splat" operator (*) to the parameter list, and it will work.
Here's an example:

>>> def sum(a,b,c):
...   print a+b+c
...
>>> sum(1,2,3)
6
>>> q=1,2,3
>>> sum(q)
Traceback (most recent call last):
  File "", line 1, in ?
TypeError: sum() takes exactly 3 arguments (1 given)
>>> sum(*q)
6
 

gnu's 30th