Category: Coding

Being a freelancer is an interesting role. You come across a variety of projects. I recently worked on a project involving replacing images in a PDF which taught me a couple of things.

1. While there are a number of tools to deal with PDF in Python, the general purpose tools can only do so much because… reason 2
2. PDF is a dump of instructions to put things in specific places. There is no logical way it is done that make general purposes tools manipulate the PDF in a consistent way.
3. Not everything is bad. Almost all positive changes like adding text or image and whole page changes like rotating, cropping are usually possible and so are all read operations like text, image extraction ..etc.,
4. The issue is when you want to delete something and replace it with something else.

With that learnt, I set out to achieve the goal anyway.

Step 1 – Understanding the format

Humans invented the PDF format, which means they used words to describe things in the file, which means we can read them. So opening a PDF file in a text editor like VIM will show something like this.

Without getting into the entirety of the PDF spec, let us see what this means. PDF is a collection of objects. There is usually an identifier like int int obj followed by some metadata and then a stream of binary information starting with stream and ends with endstream and endobj. A image in our case would be represented as

16 0 obj
<< /Length 17 0 R /Type /XObject /Subtype /Image /Width 242 /Height 291 /Interpolate
true /ColorSpace 7 0 R /Intent /Perceptual /BitsPerComponent 8 /Filter /DCTDecode
>>
stream
Image binary data here like ÿØÿá^@VExif^@^@MM^@*^@^@^@^H^@^D^A^Z^@^E^@^@
endstream
endobj

So to successfully replace an image we will have to replace the image binary data and the metadata like width and height.

Step 2 – Uncompressing the PDF and extracting the images

Use a PDF manipulation called toolkit called PDFtk.

pdftk sample.pdf output uncompressed.pdf uncompress

What this command does is, it uncompresses the file and makes it easier to read and manipulate. Let us open the uncompressed.pdf in VIM to see the difference.

Step 3 – Identifying the image to replace

PDF is essentially a collection of objects and a PDF file might contain multiple images, there is no way to identify a particular image in the binary data of the PDF file (unless you are from Matrix). We will have to first extract the images from the PDF and match the PDF object to the image using its metadata like height and width. To do that install pdfimages command-line tool (part of poppler-utils) and run pdfimages -list uncompressed.pdf. This will list all the images in the PDF with their metadata.

page   num  type   width height color comp bpc  enc interp  object ID x-ppi y-ppi size ratio
--------------------------------------------------------------------------------------------
   1     0 image     277   185  icc     3   8  jpeg   yes       11  0   113   113 69.2K  46%
   1     1 image     277   185  icc     3   8  jpeg   yes       10  0   113   113 31.9K  21%
   1     2 image     242   291  icc     3   8  jpeg   yes       12  0   112   112 55.2K  27%

Next extract all the images in their original formats using

pdfimages -all uncompressed.pdf image

That extracts the files and names them after the prefix we provided like this image-000.jpg image-001.jpg image-002.jpg.

Now open your images check their file’s height, width and file size and mark the details for the one to replace. In my case the file details were:

• height – 185
• width – 277
• size – 70836

There are two images which matches the height and width, thankfully they have different file sizes.

Step 4 – Identifying the object in PDF that represents the image

I opened the uncompressed.pdf in VIM and searched for the most unique value I have found for the image – its size.

Now we can identify the object identifier, in this case it is 11 0 obj.

Step 5 – Replacing the image with another image

Now the job is to switch the object 11’s image data with our image’s data. You can use the following Python script to achieve that.

Download the file, change the OBJECT_ID value, save the file and run:

python process.py <your pdf> <new image>

I just used the one of the extracted images to replace another one. So here are the before and after images.

Step 6 – Compressing the file back (OPTIONAL)

Do this only if you really need to do it for some reason. It is usually cool to just use the uncompressed file.

pdftk uncompressed.pdf output replaced.pdf compress

Sorting is simplified in Python with sorted(). You can even sort with complex rules.

>>> strings = ['alice', 'bob', 'donald', 'cathy']
>>> sorted(strings)
['alice', 'bob', 'cathy', 'donald']

>>> sorted(strings, key=len)
['bob', 'alice', 'cathy', 'donald']

>>> def secondchar(word):
...    return word[1]

>>> sorted(strings, key=secondchar)
['cathy', 'alice', 'bob', 'donald']

In situations where you have a list of objects and have to retrieve then in random order, dictionaries can act as lookup tables.

users = list of class User 

# Get users one by one by looking up ids
user_1 = next((u for u in users if u.id == user_1_id), None)
user_2 = next((u for u in users if u.id == user_2_id), None)
...

# Simpler solution using lookup table
lookup = dict((u.id, user) for u in users)
user_1 = lookup[user_1_id]
user_2 = lookup[user_2_id]
...

This tip is not very obvious, hence this explanation:

user_1 = next((u for u in users if u.id == user_1_id), None)

This method employs a iterator looping through the list of users every time we have to find a user, which means we have to run this loop a hundred times. This poses a complexity of O(N²).

lookup = dict((u.id, user) for u in users)
user_1 = lookup[user_1_id]

This method on the other hand iterates through the users list one time and create a lookup table that we can again and again without having to iterate through the list every time. This reduces the complexity to O(N) which could theoretically lead up to 10 times faster execution of the program.

Sometimes we have to deal with external objects and their attributes. getattr() can save you at those times.

# Get the attribute name
name = obj.name  # AttributeError if name is not present

# Check if the attribute is present before fetching
try:
    name = obj.name
except AttributeError:
    name = "Guest"

# Simpler solution
name = obj.name if hasattr(obj, "name") else "Guest"

# Simplest Solution
name = getattr(obj, "name", "Guest")

Merge or combine dictionaries

d1 = { "a": 1 }
d2 = { "b": 2 }

# Adding elements of one dictionary to another
d1.update(d2)  # d1 => { "a": 1, "b": 2 }

# Create a new dict with values from other dictionaries
d3 = { **d1, **d2 }  # d3 => { "a": 1, "b": 2 }
d4 = { **d3, "c": 3 }  # d4 => { "a": 1, "b": 2, "c": 3 }

** is the unpacking operator

Check for existence of a key in dictionary and retrieve its value if present.

dictionary = { "key": "value" }

# checking for the presence and key and getting the value
wanted = None
if "key" in dictionary:
    wanted = dictionary["key"]

# Simpler version
wanted = dictionary.get("key", None)

What if you want to find the first item that matches the condition instead of getting a list of items?

selected = None
for i in items:
if condition:
selected = i
break

# Simpler version using next()
selected = next((i for i in items if condition), None)

next() is a built in function which is not that well known.