Today I figured out how to use this Gmail Python Library to fetch Gmail data for my ITP listserv visualization. First up, I installed the Gmail Python library by cloning the GitHub repo to a folder on my local computer.
Clone Python Gmail Repo
1
2
3
git clonegit://github.com/charlierguo/gmail.git
In Terminal, I changed directories so I was in the directory where I saved the library.
Change Directories
1
2
3
cd/Users/michellechandra/rwet/gmail
I then installed the GMail Python library:
Install GMail Python Library
1
2
3
python setup.py
And opened the Python Interpreter in Terminal:
Python Interpreter
1
2
3
python
and ran these commands to log-in to my Gmail Account:
GMail Python Library Install
1
2
3
import gmail
GMail Python Log-In
1
2
3
g=gmail.login('username'.'password')
This command accesses messages labeled “ITP” in my Inbox: → Read more
I am tackling what at times feels like a herculean Data Representation project, although on paper it sounds easy: visualize the connections between folks who use the ITP student listserv. In 2007, Joshua Knowles did just that.
This post is about how to not tackle this project.
For my first attempt at getting my gmail data, I ran this Python script and downloaded 6,126 emails (as separate text files) sent to the ITP listserv from Sept 5, 2013-Present. Luckily, Gmail has been archiving these emails for me in a separate folder in my Inbox (plus one for me!) I then attempted to adapt one of Dan O’Sullivan’s Gmail Word Count Processing sketches in order to loop through each text file, grab the From and Subject line and write to a CSV file. This turns out to be exactly the kind of sketch that crashes Processing. It’s just too much data for Processing + my computer to manage given I do not need each email (and all of that data including attachments) for this project. → Read more
For Recurring Concepts in Art, Joelle and I are taking my Instacollages and remaking them without technology. The process of deconstructing my original project has forced me several times over to reflect on the motivations and process that led to Instacollage.
Joelle found this great quote which sums up collage and juxtaposition quite nicely:
“In nature we never see anything isolated, but everything in connection with something else which is before it, beside it, under it, and over it.” Johann Goethe
One of the things you learn as photographer is that there is a process that happens by which we become familiar with our surroundings to the point we stop “seeing.”
“Before you have focused your thoughts you are all over the place, because you are searching. You are feeling. You are looking for things. You do not know what you are doing. You are lost. You are in a maze. So thinking is number one in the design process. The design is the product of your thinking.”
-Paul Rand
For my second pass at my Corporate Motto mashups, I recombined mottos by splitting each motto based on a certain number of words and recombining the mottos into a new motto.
The first round of mashups returned some funny results, but mainly mottos that almost sounded like they could be real mottos. Some of my favorite ones:
Even your best friends won’t tell you!
Snap! Crackle! Pop! just one!
You’ve come a long way, baby.
We Help You life.
It looks good, it cleans your teeth.
I then took the first results, and passed them back into my corporate motto program. Round two returned much more ridiculous mashups: → Read more
For this week’s Coding for Emotional Impact class, I adapted Mimi’s sin/cos/tan wave code to a sketch I wrote that draws circles and lines in spirograph-like patterns.
I discovered through this process that cos and sin waves create very fluid motion and patterns, which can be especially dreamy when drawn slowly.
Tan waves create abrupt change and surprise, which can be interesting especially if the desired effect is meant to be jittery, confused or manic. Tan also creates much more variation and randomness, and is therefore less repetitive and a little bit more interesting.
Combining and contrasting speed using sin/cos/tan waves also creates interesting variation. → Read more
For my first Python program that mashes up text, I chose to work with corporate mottos. I first manually copied over 400 corporate mottos from this pdf file into a text file. I then used Adam’s Cowboy.py program, which replaces common words (you, I, the, etc) with cowboy slang. However, I chose to replace those words with California slang (dude, hella, totally, whatever, etc).
Here is the text replacement program:
Text Replacement with Surf Slang
1
2
3
4
5
6
7
8
9
10
11
import sys
forline insys.stdin:
line=line.strip()
line=line.replace("the ","hella ")
line=line.replace("and ","like yeah, ")
line=line.replace(" a "," like whatever ")
line=line.replace("!",". Dude.")
line=line.replace(","," totally ")
print line
And a few examples of the result with this initial translation:
Ace is hella place for hella helpful hardware man.
