A couple of thoughts so far:
1. The author is really dedicated to his book and audience, evident in his responsiveness in answering my question (#7 below).
2. The VM experience is totally awesome.
3. Each of the topic covered can be expanded into a whole book by itself. We are scratching only the surface.
4. For me, when writing a script on a new topic, finding the right library is typically half of the battle. Nothing is more frustrating when you are already going down the path of using a library only to find a better one (or worse, nothing at all). The book gave you a nice list of best-of-breed libraries for each topic, which in itself is worth every penny of buying the book.
Here is more detail about my experience:
1. I reran the exercise I did in previous post via IPython notebook via the VM. The three top trending corresponds to the bombing in Russia and the NFL game that was on at the time:
2013-12-29T18:48:48Z
set([u'AJ Green', u'Volgograd', u'Andy Dalton'])
2. I ran the rest of the code from the VM because I was short on time:
+----------------+-------+ | Screen Name | Count | +----------------+-------+ | justinbieber | 6 | | Kid_Charliej | 2 | | Cavillafuerte | 2 | | touchmestyles_ | 1 | | aliceorr96 | 1 | | gymleeam | 1 | | fienas | 1 | | nayely_1D | 1 | | angelchute | 1 | +----------------+-------+
3. I was really glad I used virtualenv to isolate each of the chapters as each of them reuqire a different Python package. There was no problem installing any of the packages and run the scripts that I tried on the Win8.1 platform.
4. Facebook Graph API is a beast. It really require more reading and understanding in order to fully grasp the depth and what you can do with it. Here is a partial list of my friend's top interest list:
Top likes amongst friends +----------------------------------------+------+ | Name | Freq | +----------------------------------------+------+ | Amazon.com | 9 | | Python for Network Engineering | 5 | | George Takei | 4 | | West Seattle Rolfing | 4 | | Photography on Facebook | 3 | | Music on Facebook | 3 | +----------------------------------------+------+
5. D3 looks really awesome, but there is a learning curve to it that I will need to come back to.
1. First file to get the connection file:
from linkedin import linkedin
import json
consumer_key = ''
consumer_secret = ''
user_token = ''
user_secret = ''
return_url = ''
auth = linkedin.LinkedInDeveloperAuthentication(consumer_key, consumer_secret,
user_token, user_secret, return_url,
permissions=linkedin.PERMISSIONS.enums.values())
app = linkedin.LinkedInApplication(auth)
# Get you own profile
#print app.get_profile()
# Getting connections as a ego point
#print app.get_connections()
# A good idea to get connections and store them in file to save API calls
connections = app.get_connections()
f = open('linkedin_connections.json', 'w')
f.write(json.dumps(connections, indent=1))
f.close()
for line in open('linkedin_connections.json', 'r'):
print line
import json
consumer_key = ''
consumer_secret = ''
user_token = ''
user_secret = ''
return_url = ''
auth = linkedin.LinkedInDeveloperAuthentication(consumer_key, consumer_secret,
user_token, user_secret, return_url,
permissions=linkedin.PERMISSIONS.enums.values())
app = linkedin.LinkedInApplication(auth)
# Get you own profile
#print app.get_profile()
# Getting connections as a ego point
#print app.get_connections()
# A good idea to get connections and store them in file to save API calls
connections = app.get_connections()
f = open('linkedin_connections.json', 'w')
f.write(json.dumps(connections, indent=1))
f.close()
for line in open('linkedin_connections.json', 'r'):
print line
2. Second file to do the parsing:
from prettytable import PrettyTable
import json
f = open('linkedin_connections.json', 'r')
connections = json.loads(f.read())
f.close()
# PrettyTable Print
pt = PrettyTable(field_names=['Name', 'Location'])
pt.align = 'l'
for c in connections['values']:
if c.has_key('location'):
pt.add_row([c['firstName'] + ' ' + c['lastName'], c['location']['name']])
print pt
import json
f = open('linkedin_connections.json', 'r')
connections = json.loads(f.read())
f.close()
# PrettyTable Print
pt = PrettyTable(field_names=['Name', 'Location'])
pt.align = 'l'
for c in connections['values']:
if c.has_key('location'):
pt.add_row([c['firstName'] + ' ' + c['lastName'], c['location']['name']])
print pt
I am enjoying the experience very much and feel like I am learning a lot. Again, the biggest difference for me is the author's dedication to his audience as well as the VM experience.
Happy coding!
