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MacBooks-MacBook-Pro:web-blackjack tim$ heroku logs --app guarded-island-9684. | |
Your version of git is 1.9.3. Which has serious security vulnerabilities. | |
More information here: https://blog.heroku.com/archives/2014/12/23/update_your_git_clients_on_windows_and_os_x | |
! App not found. | |
MacBooks-MacBook-Pro:web-blackjack tim$ |
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[5] pry(#<PostsController>)> @post.update(post_params) | |
(0.1ms) begin transaction | |
Category Load (0.4ms) SELECT "categories".* FROM "categories" WHERE "categories"."id" IN (1, 2, 3) | |
Category Load (0.1ms) SELECT "categories".* FROM "categories" INNER JOIN "post_categories" ON "categories"."id" = "post_categories"."category_id" WHERE "post_categories"."post_id" = ? [["post_id", 1]] | |
SQL (0.4ms) INSERT INTO "post_categories" ("category_id", "post_id") VALUES (?, ?) [["category_id", 3], ["post_id", 1]] | |
(31.3ms) rollback transaction | |
NoMethodError: undefined method `name' for nil:NilClass | |
from /Users/tim/.rvm/gems/ruby-2.2.0/gems/activerecord-4.0.0/lib/active_record/associations/has_many_association.rb:80:in `cached_counter_attribute_name' | |
[6] pry(#<PostsController>)> |
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# amazon_api.rb | |
# ENV variables are configured with figaro locally and directly on Amazon Elastic Beanstalk in production | |
Amazon::Ecs.configure do |options| | |
options[:AWS_access_key_id] = ENV["AWS_ACCESS_KEY_ID"] | |
options[:AWS_secret_key] = ENV["AWS_SECRET_KEY"] | |
options[:associate_tag] = ENV["associate_tag"] | |
options[:version] = "2013-08-01" | |
end |
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# User.rb | |
class User <ActiveRecord::Base | |
before_save :generate_slug | |
# [...] | |
def self.from_omniauth(auth) | |
where(provider: auth.provider, uid: auth.uid).first_or_create do |user| | |
user.provider = auth.provider |
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Intern Talk | |
1. Searching for an internship | |
1. www.intern.supply | |
2. Sent your resume & never heard back? | |
1. Focus on what you want to do (ex: Data, PM, Front-end, Back-end) | |
1. Try to apply to second tier companies that match what you want to do (ex: me at 1010data) - You will gain “experience”! | |
2. Talk with people who are working at your dream company | |
1. Screenshot of Google Tweet: https://twitter.com/AdamSinger/status/765591442500620288 | |
2. Cold emails on linkedin: http://imgur.com/a/DsbwP |
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Exception in thread "main" java.lang.NoClassDefFoundError: org/slf4j/LoggerFactory | |
at edu.stanford.nlp.parser.common.ParserGrammar.<clinit>(ParserGrammar.java:46) | |
Caused by: java.lang.ClassNotFoundException: org.slf4j.LoggerFactory | |
at java.net.URLClassLoader.findClass(URLClassLoader.java:381) | |
at java.lang.ClassLoader.loadClass(ClassLoader.java:424) | |
at java.lang.ClassLoader.loadClass(ClassLoader.java:357) | |
... 1 more | |
Traceback (most recent call last): | |
File "test.py", line 11, in <module> |
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Traceback (most recent call last): | |
File "test.py", line 11, in <module> | |
sentences = parser.raw_parse_sents(("Hello, My name is Melroy.", "What is your name?")) | |
File "/Library/Python/2.7/site-packages/nltk/parse/stanford.py", line 153, in raw_parse_sents | |
return self._parse_trees_output(self._execute(cmd, '\n'.join(sentences), verbose)) | |
File "/Library/Python/2.7/site-packages/nltk/parse/stanford.py", line 219, in _execute | |
stdout=PIPE, stderr=PIPE) | |
File "/Library/Python/2.7/site-packages/nltk/internals.py", line 136, in java | |
raise OSError('Java command failed : ' + str(cmd)) | |
OSError: Java command failed : ['/Library/Java/JavaVirtualMachines/jdk1.8.0_60.jdk/Contents/Home/bin/java', |
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Input: Bob brought the pizza to Alice because she was cold . | |
Parse: | |
brought VBD ROOT | |
+-- Bob NNP nsubj | |
+-- pizza NN dobj | |
| +-- the DT det | |
+-- to IN prep | |
| +-- Alice NNP pobj | |
+-- cold JJ advcl | |
| +-- because IN mark |
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Input: Bob brought the pizza to Alice because she was cold . | |
Parse: | |
brought VBD ROOT | |
+-- Bob NNP nsubj | |
+-- pizza NN dobj | |
| +-- the DT det | |
+-- to IN prep | |
| +-- Alice NNP pobj | |
+-- cold JJ advcl | |
| +-- because IN mark |
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INFO:tensorflow:Total processed documents: 7 | |
INFO:tensorflow:num correct tokens: 14 | |
INFO:tensorflow:total tokens: 47 | |
INFO:tensorflow:Seconds elapsed in evaluation: 1.16, eval metric: 29.79% |
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