- Background and Lesson Goals
- Recursive Retrieval and Sequential URLs: The Library and Archives Canada Example
- A Second Example: The National Archives of Australia
- Recursive Retrieval and Wget’s ‘Accept’ (-A) Function
- More Complicated Recursive Retrieval: A Python Script for Leading Zeros
Background and Lesson Goals
Now that you have learned how Wget can be used to mirror or download specific files from websites like ActiveHistory.ca via the command line, it’s time to expand your web-scraping skills through a few more lessons that focus on other uses for Wget’s recursive retrieval function. The following tutorial provides three examples of how Wget can be used to download large collections of documents from archival websites with assistance from the Python programing language. It will teach you how to parse and generate a list of URLs using a simple Python script, and will also introduce you to a few of Wget’s other useful features. Similar functions to the ones demonstrated in this lesson can be achieved using curl, an open-source software capable of performing automated downloads from the command line. For this lesson, however, we will focus on Wget and building your Python skills.
Archival websites offer a wealth of resources to historians, but increased accessibility does not always translate into increased utility. In other words, while online collections often allow historians to access hitherto unavailable or cost-prohibitive materials, they can also be limited by the manner in which content is presented and organized. Take for example the Indian Affairs Annual Reports database hosted on the Library and Archives Canada [LAC] website. Say you wanted to download an entire report, or reports for several decades. The current system allows a user the option to read a plaintext version of each page, or click on the “View a scanned page of original Report” link, which will take the user to a page with LAC’s embedded image viewer. This allows you to see the original document, but it is also cumbersome because it requires you to scroll through each individual page. Moreover, if you want the document for offline viewing, the only option is to right click –> save as each image to a directory on your computer. If you want several decades’ worth of annual reports, you can see the limits to the current means of presentation pretty easily. This lesson will allow you to overcome such an obstacle.
Recursive Retrieval and Sequential URLs: The Library and Archives Canada Example
Let’s get started. The first step involves building a script to generate sequential URLs using Python’s ForLoop function. First, you’ll need to identify the beginning URL in the series of documents that you want to download. Because of its smaller size we’re going to use the online war diary for No. 14 Canadian General Hospital as our example. The entire war diary is 80 pages long. The URL for page 1 is http://data2.archives.ca/e/e061/e001518029.jpg and the URL for page 80 is ‘http://data2.archives.ca/e/e061/e001518109.jpg. Note that they are in sequential order. We want to download the .jpeg images for all of the pages in the diary. To do this, we need to design a script to generate all of the URLs for the pages in between (and including) the first and last page of the diary.
Open your preferred text editor (such as Komodo Edit) and enter the code below. Where it says ‘integer 1′ type in ‘8029′, where it says ‘integer 2′, type ‘8110’. The ForLoop will generate a list of numbers between ‘8029’ and ‘8110’, but it will not print the last number in the range (i.e. 8110). To download all 80 pages in the diary you must add one to the top-value of the range because it is at this integer where the ForLoop is told to stop. This applies for any sequence of numbers you generate with this function. Additionally, the script will not properly execute if leading zeros are included in the range of integers, so you must exclude them by leaving them in the string (the URL). In this example I have parsed the URL so that only the last four digits of the string are being manipulated by the ForLoop.
#URL-Generator.py urls = ''; f=open('urls.txt','w') for x in range('integer1', 'integer2'): urls = 'http://data2.collectionscanada.ca/e/e061/e00151%d.jpg\n' % (x) f.write(urls) f.close
Now replace ‘integer1′ and ‘integer2′ with the bottom and top ranges of URLs you want to download. The final product should look like this:
#URL-Generator.py urls = ''; f=open('urls.txt','w') for x in range(8029, 8110): urls = 'http://data2.collectionscanada.ca/e/e061/e00151%d.jpg\n' % (x) f.write(urls) f.close
Save the program as a .py file, and then click run the Python script.
The ForLoop will automatically generate a sequential list of URLs
between the range of two integers that you specified in the brackets,
and will write them to a .txt file that will be saved in your
Programming Historian directory. The
%d appends each sequential number
generated by the ForLoop to the exact position you place it in the
\n to the end of the string removes line-breaks,
allowing Wget to read the .txt file.
You do not need to use all of the digits in the URL to specify the range
– just the ones between the beginning and end of the sequence you are
interested in. This is why only the last 4 digits of the string were
00151 was left intact.
Before moving on to the next stage of the downloading process, make sure you have created a directory where you would like to save your files, and, for ease of use, locate it in the main directory where you keep your documents. For both Mac and Windows users this will normally be the ‘Documents’ folder. For this example, we’ll call our folder ‘LAC’. You should move the urls.txt file your Python script created in to this directory. To save time on future downloads, it is advisable to simply run the program from the directory you plan to download to. This can be achieved by saving the URL-Generator.py file to your ‘LAC’ folder.
For Mac users, under your applications list, select Utilities -> Terminal. For Windows Users, you will need to open your system’s Command Line utility.
Once you have a shell open, you need to ‘call’ the directory you want to save your downloaded .jpeg files to. Type:
and hit enter. Then type:
and press enter again. You now have the directory selected and are ready to begin downloading.
Based on what you have learned from Ian Milligan’s Wget lesson, enter the following into the command line (note you can choose whatever you like for your ‘limit rate’, but be a responsible internet citizen and keep it under 200kb/s!):
wget -i urls.txt -r --no-parent -nd -w 2 --limit-rate=100k
(Note: including ‘-nd’ in the command line will keep Wget from automatically mirroring the website’s directories, making your files easier to access and organize).
Within a few moments you should have all 80 pages of the war diary downloaded to this directory. You can copy and move them into a new folder as you please.
A Second Example: The National Archives of Australia
After this lesson was originally published, the National Archvies of Australia changed their URL patterns and broke the links provided here. We are preserving the original text for reference, however you may wish to skip to the next section.
Let’s try one more example using this method of recursive retrieval. This lesson can be broadly applied to numerous archives, not just Canadian ones!
Say you wanted to download a manuscript from the National Archives of Australia, which has a much more aesthetically pleasing online viewer than LAC, but is still limited by only being able to scroll through one image at a time. We’ll use William Bligh’s “Notebook and List of Mutineers, 1789” which provides an account of the mutiny aboard the HMS Bounty. On the viewer page you’ll note that there are 131 ‘items’ (pages) to the notebook. This is somewhat misleading. Click on the first thumbnail in the top right to view the whole page. Now, right-click -> view image. The URL should be ‘http://nla.gov.au/nla.ms-ms5393-1-s1-v.jpg’. If you browse through the thumbnails, the last one is ‘Part 127’, which is located at ‘http://nla.gov.au/nla.ms-ms5393-1-s127-v.jpg’. The discrepancy between the range of URLs and the total number of files means that you may miss a page or two in the automated download – in this case there are a few URLs that include a letter in the name of the .jpeg (‘s126a.v.jpg’ or ‘s126b.v.jpg’ for example). This is going to happen from time to time when downloading from archives, so do not be surprised if you miss a page or two during an automated download.
Note that a potential workaround could include using regular expressions to make more complicated queries if appropriate (for more, see the Understanding Regular Expressions lesson).
Let’s run the script and Wget command once more:
#Bligh.py urls = ''; f=open('urls.txt','w') for x in range(1, 128): urls = 'http://www.nla.gov.au/apps/cdview/?pi=nla.ms-ms5393-1-s%d-v.jpg\n' % (x) f.write(urls) f.close
wget -i urls.txt -r --no-parent -nd -w 2 --limit-rate=100k
You now have a (mostly) full copy of William Bligh’s notebook. The missing pages can be downloaded manually using right-click -> save image as.
Recursive Retrieval and Wget’s ‘Accept’ (-A) Function
Sometimes automated downloading requires working around coding barriers. It is common to encounter URLs that contain multiple sets of leading zeros, or URLs which may be too complex for someone with a limited background in coding to design a Python script for. Thankfully, Wget has a built-in function called ‘Accept’ (expressed as ‘-A’) that allows you to define what type of files you would like to download from a specific webpage or an open directory.
For this example we will use one of the many great collections available through the Library of Congress website: The Thomas Jefferson Papers. As with LAC, the viewer for these files is outdated and requires you to navigate page by page. We’re going to download a selection from Series 1: General Correspondence. 1651-1827. Open the link and then click on the image (the .jpeg viewer looks awful familiar doesn’t it?) The URL for the image also follows a similar pattern to the war diary from LAC that we downloaded earlier in the lesson, but the leading zeros complicate matters and do not permit us to easily generate URLs with the first script we used. Here’s a workaround. Click on this link:
The page you just opened is a sub-directory of the website that lists the .jpeg files for a selection of the Jefferson Papers. This means that we can use Wget’s ‘–A’ function to download all of the .jpeg images (100 of them) listed on that page. But say you want to go further and download the whole range of files for this set of dates in Series 1 – that’s 1487 images. For a task like this where there are relatively few URLs you do not actually need to write a script (although you could using my final example, which discusses the problem of leading zeros). Instead, simply manipulate the URLs in a .txt file as follows:
… all the way up to
This is the last sub-directory on the Library of Congress site for these dates in Series 1. This last URL contains images 1400-1487.
Your completed .txt file should have 15 URLs total. Before going any further, save the file as ‘Jefferson.txt’ in the directory you plan to store your downloaded files in.
Now, run the following Wget command:
wget -i Jefferson.txt -r --no-parent -nd -w 2 -A .jpg, .jpeg --limit-rate=100k
Voila, after a bit of waiting, you will have 1487 pages of presidential papers right at your fingertips!
More Complicated Recursive Retrieval: A Python Script for Leading Zeros
The Library of Congress, like many online repositories, organizes their collections using a numbering system that incorporates leading zeros within each URL. If the directory is open, Wget’s –A function is a great way to get around this without having to do any coding. But what if the directory is closed and you can only access one image at a time? This final example will illustrate how to use a Python script to incorporate leading into a list of URLs. For this example we will be using the Historical Medical Poster Collection, available from the Harvey Cushing/Jack Hay Whitney Medical Library (Yale University).
First, we’ll need to identify the URL of the first and last files we want to download. We also want the high-resolution versions of each poster. To locate the URL for the high res image click on the first thumbnail (top left) then look below the poster for the link that says ‘Click HERE for Full Image’. If you follow the link, a high-resolution image with a complex URL will appear. As was the case in the Australian Archives example, to get the simplified URL you must right-click -> view image using your web-browser. The URL for the first poster should be:
Follow the same steps for the last poster in the gallery – the URL should be:
The script we used to download from LAC will not work because the range function cannot comprehend leading zeros. The script below provides an effective workaround that runs three different ForLoops and exports the URLs to a .txt file in much the same way as our original script. This approach would also work with the Jefferson Papers, but I chose to use the –A function to demonstrate its utility and effectiveness as a less complicated alternative.
In this script the poster URL is treated in much the same way as the URL in our LAC example. The key difference is that the leading zeros are included as part of the string. For each loop, the number of zeros in the string decreases as the digits increase from single, to double, to triple. The script can be expanded or shortened as needed. In this case we needed to repeat the process three times because we were moving from three leading zeros to one leading zero. To ensure that the script iterates properly, a ‘+’ should be added to each ForLoop as in the example below.
We do not recommend actually performing this download because of the size and extent of the files. This example is merely intended to illustrate the how to build and execute the Python script.
#Leading-Zeros.py urls = ''; f=open('leading-zeros.txt','w') for x in range(1,10): urls += 'http://cushing.med.yale.edu/images/mdposter/full/poster000%d.jpg\n' % (x) for y in range(10,100): urls += 'http://cushing.med.yale.edu/images/mdposter/full/poster00%d.jpg\n' % (y) for z in range(100,638): urls += 'http://cushing.med.yale.edu/images/mdposter/full/poster0%d.jpg\n' % (z) f.write(urls) f.close
These three examples only scratch the surface of Wget’s potential. Digital archives organize, store, and present their content in a variety of ways, some of which are more accessible than others. Indeed, many digital repositories store files using URLs that must be manipulated in several different ways to utilize a program like Wget. Wherever your downloading may take you, new challenges and opportunities await. This tutorial has provided you with the core skills for further work in the digital archive and, hopefully, will lead you to undertake your own experiments in an effort to add new tools to the digital historian’s toolkit. As new methods for scraping online repositories become available, we will continue to update this lesson with additional examples of Wget’s power and potential.