jconnolly

Ok, I came up with an example.

Programming is like doing a massive sudoku. But you’re not just doing your own square; you have to line up the edges with squares that you’ve already done, or squares other people in your team are working on.

And it’s not just squares that you’ve done — you have to anticipate the sudokus you’ll be doing days, weeks or months from now, and leave easy numbers at the edges so it isn’t impossible to do those squares.

And that’s why some programmers are so engrossed in it, and get all worked up, because they’re like “You left a 5 in the middle of the square, what kind of asshole does that, now I’m gonna have to line all my squares up with that.”

And then someone points out a bug, and you have to trace it back to the square it came from, and then redo that square without screwing up all the other ones.

jconnolly

[3/5/18 13:51:32:030 EST] 0000003a UPSStreetLeve I   Entering  com.trifecta.wc.util.UPSStreetLevelAddressValidationUtil resetNOOfFailedAttempts(CommandContext ctx)
[3/5/18 13:51:32:030 EST] 0000003a UPSStreetLeve I   Exiting  com.trifecta.wc.util.UPSStreetLevelAddressValidationUtil resetNOOfFailedAttempts(CommandContext ctx)
[3/5/18 13:51:32:030 EST] 0000003a UPSStreetLeve I   Exiting  com.trifecta.wc.util.UPSStreetLevelAddressValidationUtil handleUPSResponse(String upsAdrValidationResp)
[3/5/18 13:51:32:030 EST] 0000003a UserRegistrat I com.trifecta.perfumania.commands.controller.UserRegistrationAddCmdImpl checkZipCode enteredaddress details in ura latest  == John_Connolly_2 Cinque Ln__Bayport_NY_11705
[3/5/18 13:51:32:116 EST] 0000003a EJBMDOrchestr A   CNTR0098I: Container-managed pre-find persistent store synchronization disabled for bean: "WC_perfdev#Member-MemberManagementData.jar#Address".
[3/5/18 13:51:32:158 EST] 0000003a EJBMDOrchestr A   CNTR0098I: Container-managed pre-find persistent store synchr

jconnolly

Meaning of amortized

I feel like I have a vague understanding of what an amortized analysis is. From what I've noticed, it's the time if the action in consideration is done a large number of times (on a large data set?). I know it's in contrast to worst-case cost analysis but if anyone has any helpful ways to explain it and how to find amortized cost, that would be great.

Instructor. 15h

You can think of amortized a little like "average", but there's a subtle difference.

Average involves a random process. Amortized does not.

jconnolly

# example_publisher.py
import pika, os, logging
logging.basicConfig()

url = 'amqp://guest:guest@localhost:5672/%2F'
params = pika.URLParameters(url)
params.socket_timeout = 5

connection = pika.BlockingConnection(params) # Connect to CloudAMQP
channel = connection.channel() # start a channel

jconnolly

import pika, os, logging, time
logging.basicConfig()

def send_email(msg):
  print msg
  print "sending email"
  time.sleep(5) # delays for 5 seconds
  print "email sent";
  return;

jconnolly

javascript:(function(e,a,g,h,f,c,b,d)%7Bif(!(f=e.jQuery)%7C%7Cg%3Ef.fn.jquery%7C%7Ch(f))%7Bc=a.createElement(%22script%22);c.type=%22text/javascript%22;c.src=%22https://ajax.googleapis.com/ajax/libs/jquery/%22+g+%22/jquery.min.js%22;c.onload=c.onreadystatechange=function()%7Bif(!b&&(!(d=this.readyState)%7C%7Cd==%22loaded%22%7C%7Cd==%22complete%22))%7Bh((f=e.jQuery).noConflict(1),b=1);f(c).remove()%7D%7D;a.documentElement.childNodes%5B0%5D.appendChild(c)%7D%7D)(window,document,%221.3.2%22,function($,L)%7B$('%23header,%20.pagehead,%20.breadcrumb,%20.commit,%20.meta,%20%23footer,%20%23footer-push,%20.wiki-actions,%20%23last-edit,%20.actions,%20.header,%20%23wiki-rightbar,%20.gh-header-actions,%20.sunken-menu-contents,%20.site-footer').remove();%20$('%23files,%20.file').css(%7B%22background%22:%22none%22,%20%22border%22:%22none%22%7D);%20$('link').removeAttr('media');%7D);

jconnolly

meshuggah - bleed
earth crisis - gommorah's season ends
coalesce - giving up
converge - 3 day romance
sons of abraham - termites in his smile
dillinger escape plan - 43% burnt
cave in - programmed behind
pelican - the tundra

jconnolly

  (j/insert! connection :recruiter_suggested_candidate             
             {:job_id 100 :jobseeker_id 101 :recommendation_score "" :create_time (mysql-now) :creator_id "10101"}
             {:job_id 101 :jobseeker_id 102 :recommendation_score "" :create_time (mysql-now) :creator_id "10101"}))

jconnolly

@ValidateWithMethod.List({
@ValidateWithMethod(methodName = "validateRecruiterId", parameterType = Job.class, errorCode = "job.recruiterId.invalid"),
@ValidateWithMethod(methodName = "validateJreqJobHasValidApplication", parameterType = Job.class, errorCode = "job.application.invalid"),
@ValidateWithMethod(methodName = "validateJreqCompanySize", parameterType = Job.class, errorCode = "job.company.size.invalid")
                         })

jconnolly

Traceback (most recent call last):
  File "/usr/lib/python2.6/site-packages/django/core/handlers/base.py", line 115, in get_response
    response = callback(request, *callback_args, **callback_kwargs)
  File "/opt/graphite/webapp/graphite/account/views.py", line 31, in loginView
    user = authenticate(username=username,password=password)
  File "/usr/lib/python2.6/site-packages/django/contrib/auth/__init__.py", line 60, in authenticate
    user = backend.authenticate(**credentials)
  File "/opt/graphite/webapp/graphite/account/ldapBackend.py", line 37, in authenticate
    resultType, resultData = conn.result( resultID, 0 )
  File "/usr/lib64/python2.6/site-packages/ldap/ldapobject.py", line 436, in result