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Working with PDF and Word Documents

317

8. What is the difference between a

Paragraph

object and a

Run

object?

9. How do you obtain a list of

Paragraph

objects for a

Document

object that’s

stored in a variable named

doc

10. What type of object has

bold

underline

italic

strike

, and

outline

variables?

11. What is the difference between setting the

bold

variable to

True

False

None

12. How do you create a

Document

object for a new Word document?

13. How do you add a paragraph with the text

'Hello there!'

to a

Document

object stored in a variable named

doc

14. What integers represent the levels of headings available in Word

documents?

Practice Projects

For practice, write programs that do the following.

PDF Paranoia

Using the

os.walk()

function from Chapter 9, write a script that will go

through every PDF in a folder (and its subfolders) and encrypt the PDFs

using a password provided on the command line. Save each encrypted

PDF with an _encrypted.pdf sufﬁx added to the original ﬁlename. Before

deleting the original ﬁle, have the program attempt to read and decrypt

the ﬁle to ensure that it was encrypted correctly.

Then, write a program that ﬁnds all encrypted PDFs in a folder (and its

subfolders) and creates a decrypted copy of the PDF using a provided pass-

word. If the password is incorrect, the program should print a message to

the user and continue to the next PDF.

Custom Invitations as Word Documents

Say you have a text ﬁle of guest names. This guests.txt ﬁle has one name per

line, as follows:

Prof. Plum

Miss Scarlet

Col. Mustard

Al Sweigart

RoboCop

Write a program that would generate a Word document with custom

invitations that look like Figure 13-11.

Since Python-Docx can use only those styles that already exist in the

Word document, you will have to ﬁrst add these styles to a blank Word ﬁle

and then open that ﬁle with Python-Docx. There should be one invitation

per page in the resulting Word document, so call

add_break()

to add a page

break after the last paragraph of each invitation. This way, you will need to

open only one Word document to print all of the invitations at once.

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318

Chapter 13

Figure 13-11: The Word document generated by your custom invite script

You can download a sample guests.txt ﬁle from http://nostarch.com/

automatestuff/.

Brute-Force PDF Password Breaker

Say you have an encrypted PDF that you have forgotten the password to,

but you remember it was a single English word. Trying to guess your forgot-

ten password is quite a boring task. Instead you can write a program that will

decrypt the PDF by trying every possible English word until it ﬁnds one

that works. This is called a brute-force password attack. Download the text ﬁle

dictionary.txt from http://nostarch.com/automatestuff/. This dictionary ﬁle con-

tains over 44,000 English words with one word per line.

Using the ﬁle-reading skills you learned in Chapter 8, create a list of

word strings by reading this ﬁle. Then loop over each word in this list, passing

it to the

decrypt()

method. If this method returns the integer

, the pass-

word was wrong and your program should continue to the next password.

decrypt()

returns

, then your program should break out of the loop and

print the hacked password. You should try both the uppercase and lower-

case form of each word. (On my laptop, going through all 88,000 uppercase

and lowercase words from the dictionary ﬁle takes a couple of minutes. This

is why you shouldn’t use a simple English word for your passwords.)

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wo r k i n g w i t h C S v f i l e S

An D j S o n D A t A

In Chapter 13, you learned how to extract

text from PDF and Word documents. These

ﬁles were in a binary format, which required

special Python modules to access their data.

CSV and JSON ﬁles, on the other hand, are just plain-

text ﬁles. You can view them in a text editor, such as

IDLE’s ﬁle editor. But Python also comes with the

special

csv

and

json

modules, each providing func-

tions to help you work with these ﬁle formats.

CSV stands for “comma-separated values,” and CSV ﬁles are simpliﬁed

spreadsheets stored as plaintext ﬁles. Python’s

csv

module makes it easy to

parse CSV ﬁles.

JSON (pronounced “JAY-sawn” or “Jason”—it doesn’t matter how

because either way people will say you’re pronouncing it wrong) is a for-

mat that stores information as JavaScript source code in plaintext ﬁles.

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320

Chapter 14

(JSON is short for JavaScript Object Notation.) You don’t need to know the

JavaScript programming language to use JSON ﬁles, but the JSON format

is useful to know because it’s used in many web applications.

the csv module

Each line in a CSV ﬁle represents a row in the spreadsheet, and commas

separate the cells in the row. For example, the spreadsheet example.xlsx from

http://nostarch.com/automatestuff/ would look like this in a CSV ﬁle:

4/5/2015 13:34,Apples,73

4/5/2015 3:41,Cherries,85

4/6/2015 12:46,Pears,14

4/8/2015 8:59,Oranges,52

4/10/2015 2:07,Apples,152

4/10/2015 18:10,Bananas,23

4/10/2015 2:40,Strawberries,98

I will use this ﬁle for this chapter’s interactive shell examples. You can

download example.csv from http://nostarch.com/automatestuff/ or enter the text

into a text editor and save it as example.csv.

CSV ﬁles are simple, lacking many of the features of an Excel spread-

sheet. For example, CSV ﬁles

• Don’t have types for their values—everything is a string

• Don’t have settings for font size or color

• Don’t have multiple worksheets

• Can’t specify cell widths and heights

• Can’t have merged cells

• Can’t have images or charts embedded in them

The advantage of CSV ﬁles is simplicity. CSV ﬁles are widely supported

by many types of programs, can be viewed in text editors (including IDLE’s

ﬁle editor), and are a straightforward way to represent spreadsheet data.

The CSV format is exactly as advertised: It’s just a text ﬁle of comma-

separated values.

Since CSV ﬁles are just text ﬁles, you might be tempted to read them in

as a string and then process that string using the techniques you learned

in Chapter 8. For example, since each cell in a CSV ﬁle is separated by a

comma, maybe you could just call the

split()

method on each line of text to

get the values. But not every comma in a CSV ﬁle represents the boundary

between two cells. CSV ﬁles also have their own set of escape characters to

allow commas and other characters to be included as part of the values. The

split()

method doesn’t handle these escape characters. Because of these

potential pitfalls, you should always use the

csv

module for reading and

writing CSV ﬁles.

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Working with CSV Files and JSON Data

321

Reader Objects

To read data from a CSV ﬁle with the

csv

module, you need to create a

Reader

object. A

Reader

object lets you iterate over lines in the CSV ﬁle. Enter the

following into the interactive shell, with example.csv in the current working

directory:

u >>> import csv

v >>> exampleFile = open('example.csv')

w >>> exampleReader = csv.reader(exampleFile)

x >>> exampleData = list(exampleReader)

y >>> exampleData

[['4/5/2015 13:34', 'Apples', '73'], ['4/5/2015 3:41', 'Cherries', '85'],

['4/6/2015 12:46', 'Pears', '14'], ['4/8/2015 8:59', 'Oranges', '52'],

['4/10/2015 2:07', 'Apples', '152'], ['4/10/2015 18:10', 'Bananas', '23'],

['4/10/2015 2:40', 'Strawberries', '98']]

The

csv

module comes with Python, so we can import it u without hav-

ing to install it ﬁrst.

To read a CSV ﬁle with the

csv

module, ﬁrst open it using the

open()

function v, just as you would any other text ﬁle. But instead of calling the

read()

readlines()

method on the

File

object that

open()

returns, pass it

to the

csv.reader()

function w. This will return a

Reader

object for you to

use. Note that you don’t pass a ﬁlename string directly to the

csv.reader()

function.

The most direct way to access the values in the

Reader

object is to con-

vert it to a plain Python list by passing it to

list()

x. Using

list()

on this

Reader

object returns a list of lists, which you can store in a variable like

exampleData

. Entering

exampleData

in the shell displays the list of lists y.

Now that you have the CSV ﬁle as a list of lists, you can access the value

at a particular row and column with the expression

exampleData[row][col]

where

row

is the index of one of the lists in

exampleData

, and

col

is the index

of the item you want from that list. Enter the following into the interactive

shell:

>>> exampleData[0][0]

'4/5/2015 13:34'

>>> exampleData[0][1]

'Apples'

>>> exampleData[0][2]

'73'

>>> exampleData[1][1]

'Cherries'

>>> exampleData[6][1]

'Strawberries'

exampleData[0][0]

goes into the ﬁrst list and gives us the ﬁrst string,

exampleData[0][2]

goes into the ﬁrst list and gives us the third string, and

so on.

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322

Chapter 14

Reading Data from Reader Objects in a for Loop

For large CSV ﬁles, you’ll want to use the

Reader

object in a

for

loop. This

avoids loading the entire ﬁle into memory at once. For example, enter the

following into the interactive shell:

>>> import csv

>>> exampleFile = open('example.csv')

>>> exampleReader = csv.reader(exampleFile)

>>> for row in exampleReader:

print('Row #' + str(exampleReader.line_num) + ' ' + str(row))

Row #1 ['4/5/2015 13:34', 'Apples', '73']

Row #2 ['4/5/2015 3:41', 'Cherries', '85']

Row #3 ['4/6/2015 12:46', 'Pears', '14']

Row #4 ['4/8/2015 8:59', 'Oranges', '52']

Row #5 ['4/10/2015 2:07', 'Apples', '152']

Row #6 ['4/10/2015 18:10', 'Bananas', '23']

Row #7 ['4/10/2015 2:40', 'Strawberries', '98']

After you import the

csv

module and make a

Reader

object from the

CSV ﬁle, you can loop through the rows in the

Reader

object. Each row is

a list of values, with each value representing a cell.

The

print()

function call prints the number of the current row and the

contents of the row. To get the row number, use the

Reader

object’s

line_num

variable, which contains the number of the current line.

The

Reader

object can be looped over only once. To reread the CSV ﬁle,

you must call

csv.reader

to create a

Reader

object.

Writer Objects

Writer

object lets you write data to a CSV ﬁle. To create a

Writer

object, you

use the

csv.writer()

function. Enter the following into the interactive shell:

>>> import csv

u >>> outputFile = open('output.csv', 'w', newline='')

v >>> outputWriter = csv.writer(outputFile)

>>> outputWriter.writerow(['spam', 'eggs', 'bacon', 'ham'])

>>> outputWriter.writerow(['Hello, world!', 'eggs', 'bacon', 'ham'])

>>> outputWriter.writerow([1, 2, 3.141592, 4])

>>> outputFile.close()

First, call

open()

and pass it

'w'

to open a ﬁle in write mode u. This will

create the object you can then pass to

csv.writer()

v to create a

Writer

object.

On Windows, you’ll also need to pass a blank string for the

open()

func-

tion’s

newline

keyword argument. For technical reasons beyond the scope

of this book, if you forget to set the

newline

argument, the rows in output.csv

will be double-spaced, as shown in Figure 14-1.

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Working with CSV Files and JSON Data

323

Figure 14-1: If you forget the newline='' keyword argument in open(), the CSV ﬁle

will be double-spaced.

The

writerow()

method for

Writer

objects takes a list argument.

Each value in the list is placed in its own cell in the output CSV ﬁle. The

return value of

writerow()

is the number of characters written to the ﬁle

for that row (including newline characters).

This code produces an output.csv ﬁle that looks like this:

spam,eggs,bacon,ham

"Hello, world!",eggs,bacon,ham

1,2,3.141592,4

Notice how the

Writer

object automatically escapes the comma in the

value

'Hello, world!'

with double quotes in the CSV ﬁle. The

csv

module

saves you from having to handle these special cases yourself.

The delimiter and lineterminator Keyword Arguments

Say you want to separate cells with a tab character instead of a comma and

you want the rows to be double-spaced. You could enter something like the

following into the interactive shell:

>>> import csv

>>> csvFile = open('example.tsv', 'w', newline='')

u >>> csvWriter = csv.writer(csvFile, delimiter='\t', lineterminator='\n\n')

>>> csvWriter.writerow(['apples', 'oranges', 'grapes'])

>>> csvWriter.writerow(['eggs', 'bacon', 'ham'])

>>> csvWriter.writerow(['spam', 'spam', 'spam', 'spam', 'spam', 'spam'])

>>> csvFile.close()

324

Chapter 14

This changes the delimiter and line terminator characters in your

ﬁle. The delimiter is the character that appears between cells on a row. By

default, the delimiter for a CSV ﬁle is a comma. The line terminator is the

character that comes at the end of a row. By default, the line terminator

is a newline. You can change characters to different values by using the

delimiter

and

lineterminator

keyword arguments with

csv.writer()

Passing

delimeter='\t'

and

lineterminator='\n\n'

u changes the charac-

ter between cells to a tab and the character between rows to two newlines.

We then call

writerow()

three times to give us three rows.

This produces a ﬁle named example.tsv with the following contents:

apples oranges grapes

eggs bacon ham

spam spam spam spam spam spam

Now that our cells are separated by tabs, we’re using the ﬁle extension

.tsv, for tab-separated values.

Project: removing the header from cSV files

Say you have the boring job of removing the ﬁrst line from several hundred

CSV ﬁles. Maybe you’ll be feeding them into an automated process that

requires just the data and not the headers at the top of the columns. You

could open each ﬁle in Excel, delete the ﬁrst row, and resave the ﬁle—but

that would take hours. Let’s write a program to do it instead.

The program will need to open every ﬁle with the .csv extension in the

current working directory, read in the contents of the CSV ﬁle, and rewrite

the contents without the ﬁrst row to a ﬁle of the same name. This will

replace the old contents of the CSV ﬁle with the new, headless contents.

wA r nin g

As always, whenever you write a program that modiﬁes ﬁles, be sure to back up the

ﬁles, ﬁrst just in case your program does not work the way you expect it to. You don’t

want to accidentally erase your original ﬁles.

At a high level, the program must do the following:

• Find all the CSV ﬁles in the current working directory.

• Read in the full contents of each ﬁle.

• Write out the contents, skipping the ﬁrst line, to a new CSV ﬁle.

At the code level, this means the program will need to do the following:

• Loop over a list of ﬁles from

os.listdir()

, skipping the non-CSV ﬁles.

• Create a CSV

Reader

object and read in the contents of the ﬁle, using

the

line_num

attribute to ﬁgure out which line to skip.

• Create a CSV

Writer

object and write out the read-in data to the new ﬁle.

Working with CSV Files and JSON Data

325

For this project, open a new ﬁle editor window and save it as

removeCsvHeader.py.

Step 1: Loop Through Each CSV File

The ﬁrst thing your program needs to do is loop over a list of all CSV ﬁle-

names for the current working directory. Make your removeCsvHeader.py look

like this:

#! python3

# removeCsvHeader.py - Removes the header from all CSV files in the current

# working directory.

import csv, os

os.makedirs('headerRemoved', exist_ok=True)

# Loop through every file in the current working directory.

for csvFilename in os.listdir('.'):

if not csvFilename.endswith('.csv'):

u continue # skip non-csv files

print('Removing header from ' + csvFilename + '...')

# TODO: Read the CSV file in (skipping first row).

# TODO: Write out the CSV file.

The

os.makedirs()

call will create a

headerRemoved

folder where all the head-

less CSV ﬁles will be written. A

for

loop on

os.listdir('.')

gets you partway

there, but it will loop over all ﬁles in the working directory, so you’ll need

to add some code at the start of the loop that skips ﬁlenames that don’t end

with

.csv

. The

continue

statement u makes the

for

loop move on to the next

ﬁlename when it comes across a non-CSV ﬁle.

Just so there’s some output as the program runs, print out a message

saying which CSV ﬁle the program is working on. Then, add some

TODO

com-

ments for what the rest of the program should do.

Step 2: Read in the CSV File

The program doesn’t remove the ﬁrst line from the CSV ﬁle. Rather, it

creates a new copy of the CSV ﬁle without the ﬁrst line. Since the copy’s

ﬁlename is the same as the original ﬁlename, the copy will overwrite the

original.

The program will need a way to track whether it is currently looping on

the ﬁrst row. Add the following to removeCsvHeader.py.

#! python3

# removeCsvHeader.py - Removes the header from all CSV files in the current

# working directory.

--snip--

326

Chapter 14

# Read the CSV file in (skipping first row).

csvRows = []

csvFileObj = open(csvFilename)

readerObj = csv.reader(csvFileObj)

for row in readerObj:

if readerObj.line_num == 1:

continue # skip first row

csvRows.append(row)

csvFileObj.close()

# TODO: Write out the CSV file.

The

Reader

object’s

line_num

attribute can be used to determine which

line in the CSV ﬁle it is currently reading. Another

for

loop will loop over

the rows returned from the CSV

Reader

object, and all rows but the ﬁrst will

be appended to

csvRows

As the

for

loop iterates over each row, the code checks whether

readerObj.line_num

is set to

. If so, it executes a

continue

to move on to the

next row without appending it to

csvRows

. For every row afterward, the

condition will be always be

False

, and the row will be appended to

csvRows

Step 3: Write Out the CSV File Without the First Row

Now that

csvRows

contains all rows but the ﬁrst row, the list needs to be

written out to a CSV ﬁle in the headerRemoved folder. Add the following

to removeCsvHeader.py:

#! python3

# removeCsvHeader.py - Removes the header from all CSV files in the current

# working directory.

--snip--

# Loop through every file in the current working directory.

u for csvFilename in os.listdir('.'):

if not csvFilename.endswith('.csv'):

continue # skip non-CSV files

--snip--

# Write out the CSV file.

csvFileObj = open(os.path.join('headerRemoved', csvFilename), 'w',

newline='')

csvWriter = csv.writer(csvFileObj)

for row in csvRows:

csvWriter.writerow(row)

csvFileObj.close()

The CSV

Writer

object will write the list to a CSV ﬁle in

headerRemoved

using

csvFilename

(which we also used in the CSV reader). This will over-

write the original ﬁle.

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