I wasn't able to retrieve PDD puzzles from the code base and submit them to GitHub. If you think that it's a bug on our side, please submit it to [yegor256/0pdd](https://github.com/yegor256/0pdd/issues):

> set -x && set -e && set -o pipefail && cd /tmp/0pdd20181015-4-1bxobtk/skapral/puzzlerbot && pdd -v -f /tmp/20181015-6626-1q2fbf2 [1]: bash: warning: setlocale: LC_ALL: cannot change locale (UTF-8) + set -e + set -o pipefail + cd /tmp/0pdd20181015-4-1bxobtk/skapral/puzzlerbot + pdd -v -f...

Please, copy and paste this stack trace to GitHub:

```
UserError
set -x && set -e && set -o pipefail && cd /tmp/0pdd20181015-4-1bxobtk/skapral/puzzlerbot && pdd -v -f /tmp/20181015-6626-1q2fbf2 [1]:
bash: warning: setlocale: LC_ALL: cannot change locale (UTF-8)
+ set -e
+ set -o pipefail
+ cd /tmp/0pdd20181015-4-1bxobtk/skapral/puzzlerbot
+ pdd -v -f /tmp/20181015-6626-1q2fbf2

Found 2 lines in /tmp/0pdd20181015-4-1bxobtk/skapral/puzzlerbot/.pdd
My version is 0.20.3
Ruby version is 2.5.1 at x86_64-linux
Reading .
Excluding **/target/**/*
162 file(s) found, 112 excluded
/tmp/0pdd20181015-4-1bxobtk/skapral/puzzlerbot/.mvn/wrapper/maven-wrapper.jar is a binary file (48336 bytes)
Reading .travis.yml...
Reading .mvn/wrapper/maven-wrapper.properties...
Reading .mvn/wrapper/MavenWrapperDownloader.java...
Reading Procfile...
Reading LICENSE...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/config/Cp_PORT.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/config/package-info.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/jersey/GitlabHookEndpoint.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/jersey/StatusEndpoint.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/jersey/AuthenticationExceptionMapper.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/jersey/package-info.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/jersey/PuzzlerAPI.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/jersey/DefaultExceptionMapper.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/jersey/GithubHookEndpoint.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/Server.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/package-info.java...
Reading puzzler-web/src/main/java/com/github/skapral/puzzler/web/SrvGrizzlyWithJersey.java...
Reading puzzler-web/pom.xml...
Reading checkstyle.xml...
Reading DEPLOYMENT.md...
Reading .pdd...
Reading .github/ISSUE_TEMPLATE.md...
Reading .github/PULL_REQUEST_TEMPLATE.md...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/config/Cp_GITHUB_HOOK_SECRET.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/config/package-info.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/config/Cp_GITHUB_AUTH_TOKEN.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/text/threepars/TwPuzzlerbotUser.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/text/threepars/package-info.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/source/PsrcFromGithubEvent.java...
Puzzle 27-7995c0a8 0/DEV at puzzler-github/src/main/java/com/github/skapral/puzzler/github/source/PsrcFromGithubEvent.java
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/source/package-info.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/source/PsrcFromGithubComments.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/operation/OpValidatingGithubEventSignature.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/operation/package-info.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/operation/OpIgnoringUnprivildgedEventSender.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/puzzle/package-info.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/project/GprjFromGithubEvent.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/project/GithubProject.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/project/package-info.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/location/GhapiProduction.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/location/package-info.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/location/GhapiStatic.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/location/GithubAPI.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/itracker/package-info.java...
Reading puzzler-github/src/main/java/com/github/skapral/puzzler/github/itracker/ItGithubIssues.java...
Reading puzzler-github/src/test/resources/testComments.json...
Reading puzzler-github/src/test/resources/testPullRequestEvent.json...
Reading puzzler-github/src/test/resources/com/github/skapral/puzzler/github/operation/signedBody...
Reading puzzler-github/src/test/resources/com/github/skapral/puzzler/github/operation/ownerIsNotSender...
Reading puzzler-github/src/test/resources/com/github/skapral/puzzler/github/operation/ownerIsSender...
Reading puzzler-github/src/test/resources/testIssueEvent.json...
Reading puzzler-github/src/test/java/com/github/skapral/puzzler/github/source/PsrcFromGithubCommentsTest.java...
Reading puzzler-github/src/test/java/com/github/skapral/puzzler/github/source/PsrcFromGithubEventTest.java...
Reading puzzler-github/src/test/java/com/github/skapral/puzzler/github/source/package-info.java...
Reading puzzler-github/src/test/java/com/github/skapral/puzzler/github/operation/OpValidatingGithubEventSignatureTest.java...
Reading puzzler-github/src/test/java/com/github/skapral/puzzler/github/operation/package-info.java...
Reading puzzler-github/src/test/java/com/github/skapral/puzzler/github/operation/OpIgnoringUnprivildgedEventSenderTest.java...
Reading puzzler-github/src/test/java/com/github/skapral/puzzler/github/itracker/ItGithubIssuesTest.java...
Reading puzzler-github/src/test/java/com/github/skapral/puzzler/github/itracker/package-info.java...
Reading puzzler-github/pom.xml...
Reading deploy.sh...
Reading puzzler-app/src/main/java/com/github/skapral/puzzler/app/Bootstrap.java...
Reading puzzler-app/src/main/java/com/github/skapral/puzzler/app/package-info.java...
Reading puzzler-app/pom.xml...
Reading .0pdd.yml...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/config/package-info.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/config/Cp_GITLAB_HOOK_SECRET.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/config/Cp_GITLAB_AUTH_TOKEN.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/text/threepars/TwPuzzlerbotUser.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/text/threepars/package-info.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/source/PsrcFromGitlabNotes.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/source/PsrcFromGitlabEvent.java...
Puzzle 27-7995c0a8 0/DEV at puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/source/PsrcFromGitlabEvent.java
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/source/package-info.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/operation/OpValidatingGitlabEventToken.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/operation/package-info.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/project/GitlabProject.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/project/package-info.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/project/GprjFromGitlabEvent.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/location/GitlabAPI.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/location/GlapiProduction.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/location/GlapiStatic.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/location/package-info.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/itracker/ItGitlabIssues.java...
Reading puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/itracker/package-info.java...
Reading puzzler-gitlab/src/test/resources/testMergeRequestEvent.json...
Reading puzzler-gitlab/src/test/resources/testComments.json...
Reading puzzler-gitlab/src/test/resources/testIssueEvent.json...
Reading puzzler-gitlab/src/test/java/com/github/skapral/puzzler/gitlab/source/PsrcFromGitlabEventTest.java...
Reading puzzler-gitlab/src/test/java/com/github/skapral/puzzler/gitlab/source/package-info.java...
Reading puzzler-gitlab/src/test/java/com/github/skapral/puzzler/gitlab/operation/OpValidatingGitlabEventTokenTest.java...
Reading puzzler-gitlab/src/test/java/com/github/skapral/puzzler/gitlab/operation/package-info.java...
Reading puzzler-gitlab/pom.xml...
Reading mvnw.cmd...
Reading README.md...
Puzzle 31-c7cfd7be 0/DEV at README.md
Reading mvnw...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/config/CpMissingValue.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/config/CpEnvironment.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/config/AssertConfigPropertyHasValue.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/config/package-info.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/config/AssertConfigPropertyIsUnitialized.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/config/CpStatic.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/config/ConfigProperty.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/config/CpOneOf.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/TwStatic.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/Text.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/Paragraph.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/AssertTextInstanceProducesCertainParagraphs.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/TxtStatic.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/TxtStandard.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/TxtBase.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/package-info.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/TriggerWord.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/TxtTrim.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/text/threepars/ParStatic.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/PuzzleSource.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/IssueTracker.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/source/PsrcCombined.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/source/PsrcFromComments.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/source/AssertPuzzleSourceProducesNoPuzzles.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/source/PsrcInferred.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/source/PsrcStatic.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/source/package-info.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/source/AssertPuzzleSourceProducesCertainPuzzles.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/Puzzle.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/operation/AssertOperationFails.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/operation/OpDoNothing.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/operation/AssertOperationMakesHttpCallsOnMockServer.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/operation/package-info.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/operation/AssertOperationSuccessful.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/operation/OpPersistAllPuzzles.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/operation/OpFail.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/package-info.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/puzzle/PzlStatic.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/puzzle/package-info.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/puzzle/AssertPuzzleHasCertainTitleAndDescription.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/puzzle/PzlUsingThreeParsText.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/itracker/package-info.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/itracker/ItToList.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/core/Operation.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/mock/MockServer.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/mock/AssertAssumingMockServer.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/mock/MockSrvImplementation.java...
Puzzle 69-9dd0b135 0/DEV at puzzler-core/src/main/java/com/github/skapral/puzzler/mock/MockSrvImplementation.java
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/mock/package-info.java...
Reading puzzler-core/src/main/java/com/github/skapral/puzzler/mock/AssertHttpEndpointProducesExpectedResponse.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/config/package-info.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/config/CpOneOfTest.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/text/threepars/package-info.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/text/threepars/TxtStandardTest.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/text/threepars/AssertTextInstanceProducesCertainParagraphsTest.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/source/PsrcFromCommentsTest.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/source/package-info.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/source/AssertPuzzleSourceProducesCertainPuzzlesTest.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/operation/AssertOperationMakesHttpCallsOnMockServerTest.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/operation/package-info.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/puzzle/AssertPuzzleHasCertainTitleAndDescriptionTest.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/core/puzzle/package-info.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/mock/package-info.java...
Reading puzzler-core/src/test/java/com/github/skapral/puzzler/mock/MockSrvImplementationTest.java...
Reading puzzler-core/pom.xml...
Reading .gitignore...
Reading appveyor.yml...
Reading pom.xml...
ERROR: there are 2 duplicate(s) of the same puzzle: puzzler-github/src/main/java/com/github/skapral/puzzler/github/source/PsrcFromGithubEvent.java:67-67, puzzler-gitlab/src/main/java/com/github/skapral/puzzler/gitlab/source/PsrcFromGitlabEvent.java:67-67, while maximum 1 duplicate is allowed
ERROR: 1 errors, see log above. If you can't understand the cause of this issue or you don't know how to fix it, please submit a GitHub issue, we will try to help you: https://github.com/yegor256/pdd/issues. This tool is still in its beta version and we will appreciate your feedback. Here is where you can find more documentation: https://github.com/yegor256/pdd/blob/master/README.md.
Exit code is 1

/app/objects/git_repo.rb:66:in `rescue in block in xml'
/app/objects/git_repo.rb:63:in `block in xml'
/app/vendor/ruby-2.5.1/lib/ruby/2.5.0/tempfile.rb:295:in `open'
/app/objects/git_repo.rb:62:in `xml'
/app/objects/puzzles.rb:36:in `deploy'
/app/objects/job.rb:38:in `proceed'
/app/objects/job_starred.rb:33:in `proceed'
/app/objects/job_recorded.rb:32:in `proceed'
/app/objects/job_emailed.rb:35:in `proceed'
/app/objects/job_commiterrors.rb:36:in `proceed'
/app/objects/job_detached.rb:48:in `exclusive'
/app/objects/job_detached.rb:36:in `block in proceed'
/app/objects/job_detached.rb:36:in `fork'
/app/objects/job_detached.rb:36:in `proceed'
/app/0pdd.rb:346:in `block in <top (required)>'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1635:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1635:in `block in compile!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:992:in `block (3 levels) in route!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1011:in `route_eval'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:992:in `block (2 levels) in route!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1040:in `block in process_route'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1038:in `catch'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1038:in `process_route'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:990:in `block in route!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:989:in `each'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:989:in `route!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1097:in `block in dispatch!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1076:in `block in invoke'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1076:in `catch'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1076:in `invoke'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1094:in `dispatch!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:924:in `block in call!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1076:in `block in invoke'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1076:in `catch'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1076:in `invoke'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:924:in `call!'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:913:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-protection-2.0.4/lib/rack/protection/xss_header.rb:18:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-protection-2.0.4/lib/rack/protection/path_traversal.rb:16:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-protection-2.0.4/lib/rack/protection/json_csrf.rb:26:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-protection-2.0.4/lib/rack/protection/base.rb:50:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-protection-2.0.4/lib/rack/protection/base.rb:50:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-protection-2.0.4/lib/rack/protection/frame_options.rb:31:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-2.0.5/lib/rack/logger.rb:15:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-2.0.5/lib/rack/common_logger.rb:33:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:231:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:224:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-2.0.5/lib/rack/head.rb:12:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-2.0.5/lib/rack/method_override.rb:22:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:194:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1957:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1502:in `block in call'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1729:in `synchronize'
/app/vendor/bundle/ruby/2.5.0/gems/sinatra-2.0.4/lib/sinatra/base.rb:1502:in `call'
/app/vendor/bundle/ruby/2.5.0/gems/rack-2.0.5/lib/rack/handler/webrick.rb:86:in `service'
/app/vendor/ruby-2.5.1/lib/ruby/2.5.0/webrick/httpserver.rb:140:in `service'
/app/vendor/ruby-2.5.1/lib/ruby/2.5.0/webrick/httpserver.rb:96:in `run'
/app/vendor/ruby-2.5.1/lib/ruby/2.5.0/webrick/server.rb:307:in `block in start_thread'
```


# Specs execution successful
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refs #647


Hey, wäre gut wenn du mir bei Gelegenheit mal genau sagst, was ich falsch gemacht habe. Ich war etwas sehr verwirrt und hab ab einen Punkt nicht mehr weiter gemacht, weil ich nichts kaputt machen wollte. Das mit der Einrückung hab ich auch bemerkt, weiß aber nicht wie ich das abstellen kann. Anscheinend macht das mein Tex-Editor automatisch? Über jede Hilfe würde ich mich freuen.


Yeah, looks good to me.


Лаба 3 отчет Фролов


So, we should still process the data message and show it? I'm not sure whether that's good or not. What's your thinking here? (If a corrupted TLV arrives, should we trust ANYTHING in the data message?)


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So, `add_private_key_v4_to` is only called in one place, inside of `otrng_global_state_private_key_v4_write_to`. This sends it to `global_state_write_to` which gives it the name `fn`. Basically, this line is the loop:
```
  otrng_list_foreach(gs->clients, fn, f);
```
Now, when `add_private_key_v4_to` is finished, the loop will continue, no matter what. So no failure will happen. Which I think is the right behavior.

The point is just that the `return` is completely useless, and so is the `if` - the behavior of the function and the code is exactly the same with and without them.


började på #2


I think the typo should be fixed in this readme


Danke

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>
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It's just about not using not existing concepts in C :p
Tuples do not exist, so you either create a type specifying a tuple or just don't xD

Short said: you've been trolled :D


Отчет Маши


this changeset also needs to be applied at other places where similar operations are performed. @mohammedzee1000


En realidad este commit es de las US 0042-D 0043-D 0044-D , los issues son #23 #24 #25


Info. Objects in java do not need to initialize null. Their default value is null.


@sasensi Using `TypeScript` correctly would probably mean we'd abandon the argument reading tricks and everything would have to be provided as `Point`, `Size`, `Color`, etc. arguments all the time? Not sure what to think of it?

We can use `Babel`, with the goal to drop it once JS tech has caught up and is sufficiently far progressed? I don't really like the JS code it produces, as it looks very convoluted and sometimes inefficient to me. I'm oretty sure that Babel + Webpack would increase the size of the library quite a bit.

What's more important probably is to build the library in a modular way, probably in a Lerna monorepo, instead of one monolithic output, then let people decide which features they need. Maybe support tree-shacking as well... And then it's probably fine to go with Babel + Webpack, since most people now load a whole lot of paper.js stuff they never use (e.g. Boolean Operations, etc.)


@wzul why not `$rbody = array()`? to show that your define a variable name with empty array.


Fixes Issues #9


谢谢啦 看到效果了


At the time I merged `frodo_sn` into `_dev`, SHA3 was verifying fully. The version [here](https://github.com/project-everest/hacl-star/tree/frodo_sn/code/experimental/sha3) should verify.

I don't mind either switching to a different style as long as we have good reasons to do so. My preference is to optimize for clarity of the specification rather than for shorter proofs of implementations, but I agree clarity is sometimes subjective.


Info. If you know that the parameters that you pass to the function will not be changed, they should be marked final. This is good practice.


Thinking more about `TypeScript` and argument reading: If we go the `TypeScript` route, it would mean we'd have proper typing formation for the full API, which would be really great for lots of things, e.g. code completion.

We could then use this information to move the argument reading tricks from the core of the library to `PaperScript` instead? It would mean that we could keep writing things like the following code as long as we're in `PaperScript`:

```js
new Path.Circle({
   center: [100, 100],
   radius: 100,
   strokeColor: [1, 1, 0]
})
```

While in normal JS, it would have to be:

```js
new Path.Circle({
   center: new Point(100, 100),
   radius: 100,
   strokeColor: new Color(1, 1, 0)
})
```

Sounds massively complex to implement that though.


#Getting index error while attaching png file with mdf.  I used

mdf1=MDF()
with open('Ideas.jpg','rb') as img1:
    mdf1.attach(
        data=img1.read(),
        file_name='asdmmdf1.jpg',
        comment='logo',
        compression=True,
    )
    mdf1.save('CI.mf4')
# I am getting index error when I save the mdf1 file


update: remove action folder & add reducer in index page


Agreed on `$rbody = array()`. Btw, why we need variable assignment when it will not be used? Is that for easier reading?


Info. Use import instead writing the full package name.


Info. In all places should be use logger instead console entries


you could move the import inside the UFOConverter.open method. It's better than a NameError, I think.


@sushantdhiman sure!


I know why you're doing that. Definitely I do.
But.

Are we sure that we want to really pass a function pointer to the threadman function? It's ugly...

IMHO, it would be way cleaner if we specify a structure containing the pthread and thread function instead, so that we pass THREAD_BLAH as threadno.

Example:
ucithreads[threadno]->running = true;
And
pthread_create(&ucithreads[threadno]->phtread, NULL, ucithreads[threadno]->threadfunc, NULL);


Probably will need to revert this commit - GNOME have realised that the pathbar styling messed up 3rd party themes - they have a fix coming out with the 3.30.2 version of GNOME Files.


I am not sure I understand the question.  But Petalisp strided arrays are not limited by ARRAY-TOTAL-SIZE-LIMIT.  They are logical entities that do not correspond to memory locations.  They could be distributed across many machines.  Even a single machine can work on a strided array that is larger than ARRAY-TOTAL-SIZE-LIMIT, if one broadcasts a small array to a large space, but immediately reduces that array to another small array.  Then one would have an iteration space that exceeds the limit, but using only arrays below the limit.


Info. No need for brackets.


apapun itu


@wzul Yes. I personally thinks for user experience purpose. When defining a function, i usually name the variable same as supplied by `do_action` or `apply_filters`. To keep them look the same and easy to understand.

Because, we can see that there's another filter, with same name, but has another parameter. If we write and display them the same way, that would help developer to understand how to use the filter?

Any personal thought on this?


The function had cryptic variable names. Now it's more readable.

Also a main function was added that can be used to run the example.


About TypeScript making us abandon argument reading trick, I think it would still be possible with method overloading (see example [here](https://www.bennadel.com/blog/3339-using-method-and-function-overloading-in-typescript.htm)).
I don't think actual code have to change much, it's just a matter of helping TypeScript detect the right type.


[Facebook Pixel Code.docx](https://github.com/477447/-xxx/files/2478036/Facebook.Pixel.Code.docx)


Well, for me this is weird. So, in the unlike case that TLVs are corrupted but the rest of the message is not, you will have already decrypted the message and derive the keys already. So this will mean that the data message was correctly created with the corrupted TLV and not modified in transit (otherwise the MAC or the decryption would have failed). So, in this case, I'll say yes, we should still take the rest of the data message as valid.


what do you think?


Info. I think should be  better to keep this info in constants.


Fixes Issue #10


Would a clever use of git allow to automate this? Or can we have a common prefix listed somewhere to only have to change one instance?


Well,  Then I can only wait for the news of gnome.


Thanks again @phyy-nx. I just ran the faster set of xfel_regression tests here. There was a lot of output, but each ended with "OK" so I assume all is good ;-)


@sheikalthaf hey, could we use isFirst && isLast instead of the length of pointNumbers ? Would that work ?


Is there a special reason for not allowing bug fixes on fog-core build level releases like 2.1.1 and 2.1.2? Maybe `"<2.2"` or even `"<3"` would be better here?


*@ryanb


This commit has been mentioned on **Discourse Meta**. There might be relevant details there:

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What was the motivation for this change? The comment says one thing and the change reflects the opposite - or is it meant to support those non-current specifications which supported more elements?

With the latest mapbox-gl typings, Position can no longer be used as LatLonLike, which would be reasonable.


update


Successfully aliased the URL <https://hasura-github-bot-oelphmckjx.now.sh> to the following alias.

* https://hasura-github-bot.now.sh


Oui c'est suremement plus explicite


Info. I think better keep all scripts in separate files.


почему ты QueryHandler заставила возвращать dynamic, если так против него выступала?


Fix_isshutDown_ on _isShutDown_ - Idea generated incorrect getter for this fields.


Nothing to changes


## Major Changes

### src/main.js
- Import and use [portal-vue](https://github.com/LinusBorg/portal-vue) to render our only player on-demand

###  src/App.vue
- Add event listener on window resizing
> - Because of the special layout design of the mobile use case, we can't simply use CSS @media to decide when and where to render or player.
> - We need to listen to the resizing event of window to make it controllable by Javascript

- Asynchronously load the IFrame Player API code
> - Follow the guideline of the [offical document](https://developers.google.com/youtube/iframe_api_reference)
> - Commit the onYouTubeIframeAPIReady to vuex to make it accessible globally

### src/views/Timeline.vue
- Import VideoPlayer component

### src/components/VideoPlayer.vue
- It's the only player in the Timeline page. Everytime the nowFocusOn is changed, the portal-vue will dynamically re-render the player to the place we would like it to be.
- Dynamically change the video content by binding the id of nowFocusOn video.
- Create the YT.player to control the exist iframe
> Todo: add handler for the onStateChange event of YT.player

### src/components/TimelineItem.vue
- Set up the portal-target


зачем нужен этот метод, который скрывает нормальный GetType и выглядит одинаково, в каком классе ты бы его не реализовала?


Agree. Will change it to assign $rbody then.


Info. I think all data on the page should be in one language.


@ysangkok why `ensure_future` and not `run_coroutine_threadsafe`? `add_peer` is not guaranteed to run on the event loop thread.

Also maybe `peer` should be defined first, as `_init_peer` already refers to it.


This commit has been mentioned on **Discourse Meta**. There might be relevant details there:

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Why did you comment at here.
Please delete it right now


это очень не полиморфный код, который превратится в огромную неподдерживаемую простыню как только ты начнёшь его повсеместно применять


This commit has been mentioned on **Discourse Meta**. There might be relevant details there:

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How I noted earlier exlude _main method_ from _Server class_.


work in progress. Trying to work on paroller.js to create easy parallax effects on webpages.


Info. One class - one file.


@sapics @sasensi let's only list the issue itself when there is one, not the PR and the issue. But when fix affects multiple issues, we list those. And when a fix doesn't have an issue, then we list the PR. Sounds good?


doesn't this make it dqn instead of ddqn?


You actually rolled-back the driver from 3.18.124. :/


@sasensi good to know! Yeah then maybe that's the way to go!


@xmedeko it makes sense on other platforms, becuase second socket must be IPv6 only on all platforms.


Related to Issue #11


Hello
Am at beginner level at coding..
But want to learn and gain alot in programming.
So am learning :)


alright, you can do that.


Please open a new issue and write there the complete error traceback message


This is not a typo. This is a PR that has been pulled in without testing.


Yes, sounds good to me.


@optimistanoop , Review the code.


You can create _ThreadPoolExecutor pool_, config it, and if any place of code wait _ExecutorService interface_ then simple pass it and _ThreadPoolExecutor_ cast to __ExecutorService _ automatically.


How do i download on android and use it?


Ну сколько можно это повторять Changed вместо Changet


This commit has been mentioned on **Discourse Meta**. There might be relevant details there:

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I'm compiling this in a raspbian-stretch-lite on QUEMU by make (doing some trik),
- Installed vdr-dev (to have vdr header)
- Installed libsigc++-2.0 libsigc++-2.0-dev and pointed it by static include:
                 SIGC2LIBDIR =/usr/include/sigc++-2.0
                 SIGC2LIBDIR2 =/usr/lib/arm-linux-gnueabihf/sigc++-2.0/include
- Copied enigma2/lib on /usr/include/lib (to compile standalone and use enigma2 header)
        cp enigma2/include/* /usr/include/
        and I had to modify /usr/include/lib/python/python.h inserting line:
                                                #include <python2.7/Python.h> (because I'm compiling out of enigma2)

the idea is insert these source as enigma2/lib  (ex enigma2/lib/dvb/ or engima2/lib/driver/ or a new dir engima2/lib/rpihd ) and compile as part of enigma2.

I'm working on removing dependencies by vdr-dev, the target is to merge omxdevice.c with enigma2/lib/dvb/decoder.cpp, maybe we can take some idea from enigma2pc62 patch by 1455
included here [http://gdurl.com/l387o/patches.tar.gz](http://gdurl.com/l387o/patches.tar.gz)


RaisePropertyChanged


`CSS.escape` est utile pour construire des selecteurs, à la construction on peut mettre n'importe quoi (ex: `<p class="14éme"></p>`.

La doc qui m'a éclairée:

> The CSS.escape() static method returns a DOMString containing the escaped string passed as parameter, mostly for use as part of a CSS selector.


Ok that makes sense. Thanks for answer!


Copy of this build can be found at
https://www.mewbuilds.com/build/0733379ba2005b87b56e498fec1de445a3514bd7/index.html
                       https://www.cloudflare-ipfs.com/ipfs/QmZDKM4569SgwKCamN21hS6vMzxmZPusCJ3rDfMetkzu1j


I already have Server class, there will be conflict


Dear binfalse,
I have used your LaTeX text and then printed it. I expected to have a black output (like when one copy the banknotes). But strangely it printed normally.
Actually several times I tried to do this test but didn't work for me. For example, I used exactly the EUrion symbol on the banknotes (using photoshop) and after that it is possible to copy/scan it.


Если ты редактируешь текущий лист, его имя может не измениться, значит проврка твоя не пройдет хотя должна, здесь нужна еще проверка на идентификатор самого листа


This will cause a memory leak on C Python < 3.4.

On C Python < 3.4, **a cycle of objects with finalizers**, its **\_\_del\_\_** method will never be executed.  https://docs.python.org/2/library/gc.html#gc.garbage
>Because, in general, it isn’t possible for Python to guess a safe order in which to run the __del__() methods.

 [PEP 442](https://www.python.org/dev/peps/pep-0442/)  solved this problem on C Python 3.4.
You can also see discuss on pypy's GC https://morepypy.blogspot.com/2008/02/python-finalizers-semantics-part-1.html


Le seul saut à la ligne que je vois est pour l'url JO, ce saut disparaît mais le résultat est pas mal:

![image](https://user-images.githubusercontent.com/1469823/46941596-c598be80-d06b-11e8-97ff-01096607fdff.png)


<Шутка>
Почему не используешь  Equals? Equals это же круто!
</Шутка>


Modif à virer


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I understand as below, sounds good 👍

- PR only -> Add PR number to CHANGELOG.md.
- Exist issues which explain the PR -> Add only issue numbers to CHANGELOG.md.


음... 좋은 practice라면 아마도 game state에서 입력 처리기와 출력 처리기를 분리하는 것이겠죠.
그래야 game state 자체만으로 입력/출력에 관계 없이 로직을 실행해볼 수 있으니까요.
더군다나 AI를 통한 게임 시뮬레이션을 해보려면 더더욱이요.

이 경우 출력은 단순히 현재 state를 화면으로 번역만하면 되니까 비교적 쉽지만 입력은 까다롭죠.

러프하게 이렇게 생각해볼 수 있을거에요.
'입력처리기'라는 추상적인 인터페이스가 있다고 하죠.
입력처리는 키보드, 네트워크, 랜덤값, 파일 등등 다양한 수단으로부터 현재 상태에서 필요로 하는 조건에 맞는 입력을 처리하겠죠.
예를 들어 duel 상황에서 입력은 어떤 플레이어가 DARE, DIE, DONE을 입력했거나 혹은 둘 다 timeout된 경우겠고, 이 결과를 어떤 상태 process의 입력 파라미터로 호출하도록 하면 상태와 process(method)는 완전히 코드만으로 동작이 가능하겠죠.

결국 극단적으로 요소를 줄이자면,
```
game = NewGame()
while not game.over:
  actualInput = game.waitForExpectedInput()
  game.process(actualInput)
  game.display()
```
와 같은 형식이 될 수 있죠.

여기에서 심지어 입/출력을 더 분리할 수도 있고요.
```
game = NewGame()
a = NewKeyboardInputHandler()
b = NewAIInputHandler()
inputHandler = NewAggregateInputHandler(a, b)
displayHandler = NewDisplayHandler()
while not game.over:
  actualInput = inputHandler.waitForExpectedInput(game)
  game.process(actualInput)
  displayHandler.Display(game)
```
또한 입력 핸들러에 game전체를 던지는게 아니라 game.getExpectedInputSpec() 처럼 추상화된 입력 기대값을 명시적으로 전달하게 하는 방법도 있겠죠.

어찌되었건 game이 입출력과 분리되면 game 로직만 가지고 테스트를 돌릴 수 있으니 심지어는 그냥 유닛테스트 짜듯이 알고리듬을 테스트해볼 수도 있겠죠.


Might be a good idea to add a test for `= NULL` also.


add some info in views.rst


Ich bin jetzt endlich dazu gekommen mir das anzusehen.
Imo ist das nicht ok so. Es ist kein false negative, es ist ein negative. Wenn wir dadurch in der App die falschen Daten anzeigen ist das nicht gut. Das eigentliche Problem ist die Verwendung von float, das macht einfach keinen Sinn. Ich hab das eher "der Vollständigkeit halber" eingebaut. Wir sollten überall doubles hernehmen, und das hier reverten.


Thanks to everyone for helping with this.

Paul - I've pushed a small change to 'ardour/session.h' to use a forward
declaration, rather than an unnecessary #include. If necessary, I could
tweak MSVC to accept the #include but there's an underlying problem
whereby (directly or indirectly) 'session.h' itself seems to get
#included by almost every source file being compiled. So in this
particular case, adding a #include which isn't strictly needed just
complicates (and lengthens) the build. Hopefully this should be okay for
the gcc builds.


You can do all static fields non-static and in Servlet Context Listener create Server object, build it and start. That will simple your code.


updatat textul


 Dear Martin,
I appreciate for your prompt reply.Yeah I printed in color, next time,I thought maybe color is not much in the page, so I have added a picture  ( please find the attached file, the page I printed and then copied) I didn't work. When I print banknote the output is black. I expected to have dark or black output too.

    On Monday, October 15, 2018, 12:25:23 PM GMT+3, Tom Theile <notifications@github.com> wrote:

Did you print it in color?
Try to print it in color and scan it then. Scanning shouldn't work.

—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub, or mute the thread.


It was tested but this particular error, which does not affect any functionality, is a bit hard to spot.


Hmmmmmm, so another force push then ._.


[R/berekenLSVIbasis.R:121:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L121) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>        "Aggregatiemethode moet een van de volgende waarden zijn: 'RapportageHR' of '1-out-all-out'",
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[R/berekenLSVIbasis.R:434:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L434) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>                                         (sum(.data$Status_indicator, na.rm = na.rm) > sum(!is.na(.data$Status_indicator))/2.0) & (sum((.data$Status_indicator == FALSE) * (.data$Belang == "zb"), na.rm = na.rm) == 0),
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[R/berekenLSVIbasis.R:434:123:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L434) *style:* **Put spaces around all infix operators.**
```r
<U+200B>                                         (sum(.data$Status_indicator, na.rm = na.rm) > sum(!is.na(.data$Status_indicator))/2.0) & (sum((.data$Status_indicator == FALSE) * (.data$Belang == "zb"), na.rm = na.rm) == 0),
                                                                                ~^~
```
[R/berekenLSVIbasis.R:434:136:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L434) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>                                         (sum(.data$Status_indicator, na.rm = na.rm) > sum(!is.na(.data$Status_indicator))/2.0) & (sum((.data$Status_indicator == FALSE) * (.data$Belang == "zb"), na.rm = na.rm) == 0),
                                                                                ^
```
[R/berekenLSVIbasis.R:441:16:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L441) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>          mean(((.data$Verschilscore + 1) / 2) ^ -1,
               ^
```
[R/berekenLSVIbasis.R:441:17:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L441) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>          mean(((.data$Verschilscore + 1) / 2) ^ -1,
                ^
```
[R/berekenLSVIbasis.R:457:31:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L457) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>        Index_min_harm = mean(((.data$Index_min_criterium + 1) / 2) ^ -1,
                              ^
```
[R/berekenLSVIbasis.R:457:32:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L457) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>        Index_min_harm = mean(((.data$Index_min_criterium + 1) / 2) ^ -1,
                               ^
```
[R/berekenLSVIbasis.R:461:16:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L461) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>          mean(((.data$Index_harm_criterium + 1) / 2) ^ -1,
               ^
```
[R/berekenLSVIbasis.R:461:17:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L461) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>          mean(((.data$Index_harm_criterium + 1) / 2) ^ -1,
                ^
```
[R/berekenLSVIbasis.R:479:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L479) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>                                         (sum(.data$Status_indicator, na.rm = na.rm) > sum(!is.na(.data$Status_indicator))/2.0) & (sum((.data$Status_indicator == FALSE) * (.data$Belang == "zb"), na.rm = na.rm) == 0),
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[R/berekenLSVIbasis.R:479:123:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L479) *style:* **Put spaces around all infix operators.**
```r
<U+200B>                                         (sum(.data$Status_indicator, na.rm = na.rm) > sum(!is.na(.data$Status_indicator))/2.0) & (sum((.data$Status_indicator == FALSE) * (.data$Belang == "zb"), na.rm = na.rm) == 0),
                                                                                ~^~
```
[R/berekenLSVIbasis.R:479:136:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/berekenLSVIbasis.R#L479) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>                                         (sum(.data$Status_indicator, na.rm = na.rm) > sum(!is.na(.data$Status_indicator))/2.0) & (sum((.data$Status_indicator == FALSE) * (.data$Belang == "zb"), na.rm = na.rm) == 0),
                                                                                ^
```
[R/combinerenVerschilscore.R:35:6:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/combinerenVerschilscore.R#L35) *warning:* **local variable '%max%' assigned but may not be used**
```r
<U+200B>    `%max%` <- function(a, b) max(a, b)
     ^~~~~
```
[R/combinerenVerschilscore.R:36:6:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/combinerenVerschilscore.R#L36) *warning:* **local variable '%min%' assigned but may not be used**
```r
<U+200B>    `%min%` <- function(a, b) min(a, b)
     ^~~~~
```
[R/combinerenVerschilscore.R:57:17:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/combinerenVerschilscore.R#L57) *style:* **Use <-, not =, for assignment.**
```r
<U+200B>      Resultaat = NA
                ^
```
[R/combinerenVoorwaarden.R:31:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/combinerenVoorwaarden.R#L31) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>    #nog testen of Formule bestaat uit EN, OF, haakjes en VoorwaardeID's (en evt. andere tekens die logische berekening toelaten)
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[R/invoercontroleData_voorwaarden.R:66:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/invoercontroleData_voorwaarden.R#L66) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>    #misschien best ook testen dat die indicator-criterium-voorwaarde-combinatie in de databank voorkomt?  En of deze voor dat habitattype voorkomt, maar dat best verderop doen
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[R/s4_aandeel.R:46:36:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeel.R#L46) *style:* **Put spaces around all infix operators.**
```r
<U+200B>      aandeel_min <- min(teller_min/noemer_max, 1)
                                  ~^~
```
[R/s4_aandeel.R:47:36:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeel.R#L47) *style:* **Put spaces around all infix operators.**
```r
<U+200B>      aandeel_max <- min(teller_max/noemer_min, 1)
                                  ~^~
```
[R/s4_aandeelKruidlaag.R:33:7:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeelKruidlaag.R#L33) *style:* **Place a space before left parenthesis, except in a function call.**
```r
<U+200B>    if(nrow(vegetatielaag) > 0){
      ^
```
[R/s4_aandeelKruidlaag.R:35:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeelKruidlaag.R#L35) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>      #indien bedekking vegetatielaag is meegegeven wordt deze als noemer gebruikt
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[R/s4_aandeelKruidlaag.R:36:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeelKruidlaag.R#L36) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>      resultaat <- c(teller[1]/vegetatielaag$WaardeMax, teller[2]/vegetatielaag$WaardeMin)
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[R/s4_aandeelKruidlaag.R:36:31:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeelKruidlaag.R#L36) *style:* **Put spaces around all infix operators.**
```r
<U+200B>      resultaat <- c(teller[1]/vegetatielaag$WaardeMax, teller[2]/vegetatielaag$WaardeMin)
                             ~^~
```
[R/s4_aandeelKruidlaag.R:36:66:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeelKruidlaag.R#L36) *style:* **Put spaces around all infix operators.**
```r
<U+200B>      resultaat <- c(teller[1]/vegetatielaag$WaardeMax, teller[2]/vegetatielaag$WaardeMin)
                                                                ~^~
```
[R/s4_aandeelKruidlaag.R:39:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeelKruidlaag.R#L39) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>      #indien bedekking vegetatielaag niet is meegegeven wordt deze berekend op basis van alle soorten in kruidlaag
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[R/s4_aandeelKruidlaag.R:49:31:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeelKruidlaag.R#L49) *style:* **Put spaces around all infix operators.**
```r
<U+200B>      resultaat <- c(teller[1]/BedekkingMax, teller[2]/BedekkingMin)
                             ~^~
```
[R/s4_aandeelKruidlaag.R:49:55:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/s4_aandeelKruidlaag.R#L49) *style:* **Put spaces around all infix operators.**
```r
<U+200B>      resultaat <- c(teller[1]/BedekkingMax, teller[2]/BedekkingMin)
                                                     ~^~
```
[R/zzz.R:31:13:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/R/zzz.R#L31) *warning:* **no visible binding for global variable 'ConnectiePool'**
```r
<U+200B>  poolClose(ConnectiePool)
            ^~~~~~~~~~~~~
```
[inst/tests/testthat/test_berekenLSVIbasis_vegetatielaag.R:24:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/inst/tests/testthat/test_berekenLSVIbasis_vegetatielaag.R#L24) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>      mutate(  #idee is om onderstaande code te wissen zodra de databank/rekenmodule hiervoor aangepast is
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[inst/tests/testthat/test_berekenLSVIbasis_vegetatielaag.R:93:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/inst/tests/testthat/test_berekenLSVIbasis_vegetatielaag.R#L93) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>    # Onderstaande test is zinloos: sleutelsoorten boom - en struiklaag worden op basis van grondvlak berekend en niet op basis van bedekking
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[inst/tests/testthat/test_berekenLSVIbasis_vegetatielaag.R:172:11:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/inst/tests/testthat/test_berekenLSVIbasis_vegetatielaag.R#L172) *style:* **Commented code should be removed.**
```r
<U+200B>    #     Resultaat[["Resultaat_globaal"]]
          ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[inst/tests/testthat/test_berekenLSVIbasis_vegetatielaag.R:193:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/inst/tests/testthat/test_berekenLSVIbasis_vegetatielaag.R#L193) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>      mutate(  #idee is om onderstaande code te wissen zodra de databank/rekenmodule hiervoor aangepast is
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[inst/tests/testthat/test_berekenStatus_RapportageHR.R:25:9:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/inst/tests/testthat/test_berekenStatus_RapportageHR.R#L25) *style:* **Commented code should be removed.**
```r
<U+200B>#       Aggregatiemethode = "RapportageHR"
        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
[inst/tests/testthat/test_berekenStatus_RapportageHR.R:53:4:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/inst/tests/testthat/test_berekenStatus_RapportageHR.R#L53) *error:* **unexpected end of input**
```r
<U+200B>  })
   ^
```
[inst/tests/testthat/test_s4_Aantal.R:199:1:](https://github.com/inbo/LSVI/blob/029fdfcbcc697ec2c89cc835096cbed3a9920662/inst/tests/testthat/test_s4_Aantal.R#L199) *style:* **lines should not be more than 80 characters.**
```r
<U+200B>  #nog toevoegen als het opzoeken van soorten in subniveaus opgelost is: de aggregatie van bedekkingen gebeurt correct
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```


cf  #234


bien vu, je te laisse faire la modif dans le pull request et après je merge.


We are working on different branches.
When you merge tom-dev with metron-ctrl-dev, then servicechains --> serviceChains


Any specific reason why you don't just use `<br>`? I see no need xhtml compability.


Архип, какого хуя ты долбоеб


Hello @rim-odoo, could also be possible apply this change to the previous versione `10.0`?
Indeed in https://github.com/odoo/odoo/blob/10.0/addons/sale/wizard/sale_make_invoice_advance.py#L30 there isn'it. Can I propose a PR?


Once I have these polygons as objects, I can begin constructing the continents and the rest of the program on top of that.

I don't think I'm doing this in the most efficient possible way, but it works and other parts of the program takes significantly longer.


accident said paler speed. should be wave position made more random


Cool. Thank you 👍


This breaks so much stuff


Hi Zeeshan,
hope you are doing well.
I had tried to find the branch but failed. Well I had create a new branch and changes the code and created the pull request. Here is the link to pull request.
https://github.com/YotpoLtd/magento2-plugin/pull/110
Looking forward for your response.
Regards,
Ijaz Ali


Good job :)


カウンタ変数をsize_t型で定義すれば、明示的なキャストは必要なくなるように思います。


Native Storage Plugin for Cordova ADDED


the following is my error.log

```bash
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/ensemble/weight_boosting.py:29: DeprecationWarning: numpy.core.umath_tests is an internal NumPy module and should not be imported. It will be removed in a future NumPy release.
  from numpy.core.umath_tests import inner1d
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/_parallel_backends.py", line 350, in __call__
    return self.func(*args, **kwargs)
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py", line 131, in __call__
    return [func(*args, **kwargs) for func, args, kwargs in self.items]
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py", line 131, in <listcomp>
    return [func(*args, **kwargs) for func, args, kwargs in self.items]
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/model_selection/_validation.py", line 448, in _fit_and_score
    X_train, y_train = _safe_split(estimator, X, y, train)
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/utils/metaestimators.py", line 188, in _safe_split
    if getattr(estimator, "_pairwise", False):
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/pipeline.py", line 499, in _pairwise
    return getattr(self.steps[0][1], '_pairwise', False)
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/pipelinehelper/__init__.py", line 104, in __getattr__
    raise Exception('The method "%s" is not implemented by your model' % name)
Exception: The method "_pairwise" is not implemented by your model

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/multiprocessing/pool.py", line 121, in worker
    result = (True, func(*args, **kwds))
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/_parallel_backends.py", line 359, in __call__
    raise TransportableException(text, e_type)
sklearn.externals.joblib.my_exceptions.TransportableException: TransportableException
___________________________________________________________________________
Exception                                          Mon Oct 15 06:46:47 2018
PID: 18446 Python 3.7.0: /Users/jessequinn/.pyenv/versions/3.7.0/bin/python
...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py in __call__(self=<sklearn.externals.joblib.parallel.BatchedCalls object>)
    126     def __init__(self, iterator_slice):
    127         self.items = list(iterator_slice)
    128         self._size = len(self.items)
    129
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
        self.items = [(<function _fit_and_score>, (Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]),        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, {'score': make_scorer(roc_auc_score, needs_threshold=True)}, array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), array([   0,    1,    2, ..., 4134, 4135, 4137]), 1, {'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})}), {'error_score': 'raise', 'fit_params': {}, 'return_n_test_samples': True, 'return_parameters': False, 'return_times': True, 'return_train_score': 'warn'})]
    132
    133     def __len__(self):
    134         return self._size
    135

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py in <listcomp>(.0=<list_iterator object>)
    126     def __init__(self, iterator_slice):
    127         self.items = list(iterator_slice)
    128         self._size = len(self.items)
    129
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
        func = <function _fit_and_score>
        args = (Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]),        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, {'score': make_scorer(roc_auc_score, needs_threshold=True)}, array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), array([   0,    1,    2, ..., 4134, 4135, 4137]), 1, {'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})})
        kwargs = {'error_score': 'raise', 'fit_params': {}, 'return_n_test_samples': True, 'return_parameters': False, 'return_times': True, 'return_train_score': 'warn'}
    132
    133     def __len__(self):
    134         return self._size
    135

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/model_selection/_validation.py in _fit_and_score(estimator=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]), X=       ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], y=0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, scorer={'score': make_scorer(roc_auc_score, needs_threshold=True)}, train=array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), test=array([   0,    1,    2, ..., 4134, 4135, 4137]), verbose=1, parameters={'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})}, fit_params={}, return_train_score='warn', return_parameters=False, return_n_test_samples=True, return_times=True, error_score='raise')
    443     if parameters is not None:
    444         estimator.set_params(**parameters)
    445
    446     start_time = time.time()
    447
--> 448     X_train, y_train = _safe_split(estimator, X, y, train)
        X_train = undefined
        y_train = undefined
        estimator = Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))])
        X =        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns]
        y = 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64
        train = array([ 3021,  3029,  3040, ..., 19997, 19998, 19999])
    449     X_test, y_test = _safe_split(estimator, X, y, test, train)
    450
    451     is_multimetric = not callable(scorer)
    452     n_scorers = len(scorer.keys()) if is_multimetric else 1

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/utils/metaestimators.py in _safe_split(estimator=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]), X=       ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], y=0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, indices=array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), train_indices=None)
    183
    184     y_sliced : array-like, sparse matrix or list
    185         Sliced targets.
    186
    187     """
--> 188     if getattr(estimator, "_pairwise", False):
        estimator = Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))])
    189         if not hasattr(X, "shape"):
    190             raise ValueError("Precomputed kernels or affinity matrices have "
    191                              "to be passed as arrays or sparse matrices.")
    192         # X is a precomputed square kernel matrix

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/pipeline.py in _pairwise(self=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]))
    494         return self.steps[-1][-1].classes_
    495
    496     @property
    497     def _pairwise(self):
    498         # check if first estimator expects pairwise input
--> 499         return getattr(self.steps[0][1], '_pairwise', False)
        self.steps = [('scaler', PipelineHelper(available_models={'std': Standard...Scaler(copy=True, with_mean=True, with_std=True))), ('classifier', PipelineHelper(available_models={'svm': SVC(C=1....e=None, verbose=0,
            warm_start=False)))]
    500
    501
    502 def _name_estimators(estimators):
    503     """Generate names for estimators."""

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/pipelinehelper/__init__.py in __getattr__(self=PipelineHelper(available_models={'std': Standard...Scaler(copy=True, with_mean=True, with_std=True)), name='_pairwise')
     99         if hasattr(self.selected_model, name):
    100             method = getattr(self.selected_model, name, None)
    101             if callable(method):
    102                 return method
    103         else:
--> 104             raise Exception('The method "%s" is not implemented by your model' % name)
        name = '_pairwise'
    105
    106
    107
    108

Exception: The method "_pairwise" is not implemented by your model
___________________________________________________________________________
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py", line 699, in retrieve
    self._output.extend(job.get(timeout=self.timeout))
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/multiprocessing/pool.py", line 657, in get
    raise self._value
sklearn.externals.joblib.my_exceptions.TransportableException: TransportableException
___________________________________________________________________________
Exception                                          Mon Oct 15 06:46:47 2018
PID: 18446 Python 3.7.0: /Users/jessequinn/.pyenv/versions/3.7.0/bin/python
...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py in __call__(self=<sklearn.externals.joblib.parallel.BatchedCalls object>)
    126     def __init__(self, iterator_slice):
    127         self.items = list(iterator_slice)
    128         self._size = len(self.items)
    129
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
        self.items = [(<function _fit_and_score>, (Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]),        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, {'score': make_scorer(roc_auc_score, needs_threshold=True)}, array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), array([   0,    1,    2, ..., 4134, 4135, 4137]), 1, {'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})}), {'error_score': 'raise', 'fit_params': {}, 'return_n_test_samples': True, 'return_parameters': False, 'return_times': True, 'return_train_score': 'warn'})]
    132
    133     def __len__(self):
    134         return self._size
    135

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py in <listcomp>(.0=<list_iterator object>)
    126     def __init__(self, iterator_slice):
    127         self.items = list(iterator_slice)
    128         self._size = len(self.items)
    129
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
        func = <function _fit_and_score>
        args = (Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]),        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, {'score': make_scorer(roc_auc_score, needs_threshold=True)}, array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), array([   0,    1,    2, ..., 4134, 4135, 4137]), 1, {'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})})
        kwargs = {'error_score': 'raise', 'fit_params': {}, 'return_n_test_samples': True, 'return_parameters': False, 'return_times': True, 'return_train_score': 'warn'}
    132
    133     def __len__(self):
    134         return self._size
    135

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/model_selection/_validation.py in _fit_and_score(estimator=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]), X=       ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], y=0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, scorer={'score': make_scorer(roc_auc_score, needs_threshold=True)}, train=array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), test=array([   0,    1,    2, ..., 4134, 4135, 4137]), verbose=1, parameters={'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})}, fit_params={}, return_train_score='warn', return_parameters=False, return_n_test_samples=True, return_times=True, error_score='raise')
    443     if parameters is not None:
    444         estimator.set_params(**parameters)
    445
    446     start_time = time.time()
    447
--> 448     X_train, y_train = _safe_split(estimator, X, y, train)
        X_train = undefined
        y_train = undefined
        estimator = Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))])
        X =        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns]
        y = 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64
        train = array([ 3021,  3029,  3040, ..., 19997, 19998, 19999])
    449     X_test, y_test = _safe_split(estimator, X, y, test, train)
    450
    451     is_multimetric = not callable(scorer)
    452     n_scorers = len(scorer.keys()) if is_multimetric else 1

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/utils/metaestimators.py in _safe_split(estimator=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]), X=       ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], y=0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, indices=array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), train_indices=None)
    183
    184     y_sliced : array-like, sparse matrix or list
    185         Sliced targets.
    186
    187     """
--> 188     if getattr(estimator, "_pairwise", False):
        estimator = Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))])
    189         if not hasattr(X, "shape"):
    190             raise ValueError("Precomputed kernels or affinity matrices have "
    191                              "to be passed as arrays or sparse matrices.")
    192         # X is a precomputed square kernel matrix

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/pipeline.py in _pairwise(self=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]))
    494         return self.steps[-1][-1].classes_
    495
    496     @property
    497     def _pairwise(self):
    498         # check if first estimator expects pairwise input
--> 499         return getattr(self.steps[0][1], '_pairwise', False)
        self.steps = [('scaler', PipelineHelper(available_models={'std': Standard...Scaler(copy=True, with_mean=True, with_std=True))), ('classifier', PipelineHelper(available_models={'svm': SVC(C=1....e=None, verbose=0,
            warm_start=False)))]
    500
    501
    502 def _name_estimators(estimators):
    503     """Generate names for estimators."""

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/pipelinehelper/__init__.py in __getattr__(self=PipelineHelper(available_models={'std': Standard...Scaler(copy=True, with_mean=True, with_std=True)), name='_pairwise')
     99         if hasattr(self.selected_model, name):
    100             method = getattr(self.selected_model, name, None)
    101             if callable(method):
    102                 return method
    103         else:
--> 104             raise Exception('The method "%s" is not implemented by your model' % name)
        name = '_pairwise'
    105
    106
    107
    108

Exception: The method "_pairwise" is not implemented by your model
___________________________________________________________________________

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "example.py", line 223, in <module>
    print(blight_model())
  File "example.py", line 186, in blight_model
    grid.fit(X, y)
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/model_selection/_search.py", line 640, in fit
    cv.split(X, y, groups)))
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py", line 789, in __call__
    self.retrieve()
  File "/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py", line 740, in retrieve
    raise exception
sklearn.externals.joblib.my_exceptions.JoblibException: JoblibException
___________________________________________________________________________
Multiprocessing exception:
...........................................................................
/Users/jessequinn/github/Coursera/Applied Data Science with Python Specialization/Course 3 - Applied Machine Learning in Python/Week 4/example.py in <module>()
    218     #
    219     # return results
    220
    221
    222 if __name__ == '__main__':
--> 223     print(blight_model())

...........................................................................
/Users/jessequinn/github/Coursera/Applied Data Science with Python Specialization/Course 3 - Applied Machine Learning in Python/Week 4/example.py in blight_model()
    181                 'nb_pipe__nb__fit_prior': [True, False],
    182                 'nb_pipe__nb__alpha': [0.1, 0.2],
    183             })
    184         }
    185         grid = GridSearchCV(pipe, params, scoring='%s'%score, cv=5, verbose=1, n_jobs=-1)
--> 186         grid.fit(X, y)
        grid.fit = <bound method BaseSearchCV.fit of GridSearchCV(c...ore='warn',
       scoring='roc_auc', verbose=1)>
        X =        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns]
        y = 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64
    187         print(grid.best_params_)
    188         print(grid.best_score_)
    189
    190     # remove gb__ prefix from best_params_

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/model_selection/_search.py in fit(self=GridSearchCV(cv=5, error_score='raise',
       e...core='warn',
       scoring='roc_auc', verbose=1), X=       ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], y=0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, groups=None, **fit_params={})
    635                                   return_train_score=self.return_train_score,
    636                                   return_n_test_samples=True,
    637                                   return_times=True, return_parameters=False,
    638                                   error_score=self.error_score)
    639           for parameters, (train, test) in product(candidate_params,
--> 640                                                    cv.split(X, y, groups)))
        cv.split = <bound method StratifiedKFold.split of Stratifie...ld(n_splits=5, random_state=None, shuffle=False)>
        X =        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns]
        y = 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64
        groups = None
    641
    642         # if one choose to see train score, "out" will contain train score info
    643         if self.return_train_score:
    644             (train_score_dicts, test_score_dicts, test_sample_counts, fit_time,

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py in __call__(self=Parallel(n_jobs=-1), iterable=<generator object BaseSearchCV.fit.<locals>.<genexpr>>)
    784             if pre_dispatch == "all" or n_jobs == 1:
    785                 # The iterable was consumed all at once by the above for loop.
    786                 # No need to wait for async callbacks to trigger to
    787                 # consumption.
    788                 self._iterating = False
--> 789             self.retrieve()
        self.retrieve = <bound method Parallel.retrieve of Parallel(n_jobs=-1)>
    790             # Make sure that we get a last message telling us we are done
    791             elapsed_time = time.time() - self._start_time
    792             self._print('Done %3i out of %3i | elapsed: %s finished',
    793                         (len(self._output), len(self._output),

---------------------------------------------------------------------------
Sub-process traceback:
---------------------------------------------------------------------------
Exception                                          Mon Oct 15 06:46:47 2018
PID: 18446 Python 3.7.0: /Users/jessequinn/.pyenv/versions/3.7.0/bin/python
...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py in __call__(self=<sklearn.externals.joblib.parallel.BatchedCalls object>)
    126     def __init__(self, iterator_slice):
    127         self.items = list(iterator_slice)
    128         self._size = len(self.items)
    129
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
        self.items = [(<function _fit_and_score>, (Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]),        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, {'score': make_scorer(roc_auc_score, needs_threshold=True)}, array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), array([   0,    1,    2, ..., 4134, 4135, 4137]), 1, {'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})}), {'error_score': 'raise', 'fit_params': {}, 'return_n_test_samples': True, 'return_parameters': False, 'return_times': True, 'return_train_score': 'warn'})]
    132
    133     def __len__(self):
    134         return self._size
    135

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/externals/joblib/parallel.py in <listcomp>(.0=<list_iterator object>)
    126     def __init__(self, iterator_slice):
    127         self.items = list(iterator_slice)
    128         self._size = len(self.items)
    129
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
        func = <function _fit_and_score>
        args = (Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]),        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, {'score': make_scorer(roc_auc_score, needs_threshold=True)}, array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), array([   0,    1,    2, ..., 4134, 4135, 4137]), 1, {'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})})
        kwargs = {'error_score': 'raise', 'fit_params': {}, 'return_n_test_samples': True, 'return_parameters': False, 'return_times': True, 'return_train_score': 'warn'}
    132
    133     def __len__(self):
    134         return self._size
    135

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/model_selection/_validation.py in _fit_and_score(estimator=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]), X=       ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], y=0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, scorer={'score': make_scorer(roc_auc_score, needs_threshold=True)}, train=array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), test=array([   0,    1,    2, ..., 4134, 4135, 4137]), verbose=1, parameters={'classifier__selected_model': ('rf', {'bootstrap': True, 'max_features': 'auto', 'min_samples_leaf': 1, 'min_samples_split': 2, 'n_estimators': 10}), 'scaler__selected_model': ('std', {'with_mean': True, 'with_std': True})}, fit_params={}, return_train_score='warn', return_parameters=False, return_n_test_samples=True, return_times=True, error_score='raise')
    443     if parameters is not None:
    444         estimator.set_params(**parameters)
    445
    446     start_time = time.time()
    447
--> 448     X_train, y_train = _safe_split(estimator, X, y, train)
        X_train = undefined
        y_train = undefined
        estimator = Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))])
        X =        ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns]
        y = 0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64
        train = array([ 3021,  3029,  3040, ..., 19997, 19998, 19999])
    449     X_test, y_test = _safe_split(estimator, X, y, test, train)
    450
    451     is_multimetric = not callable(scorer)
    452     n_scorers = len(scorer.keys()) if is_multimetric else 1

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/utils/metaestimators.py in _safe_split(estimator=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]), X=       ticket_id  fine_amount  late_fee  discoun...  42.374448 -83.135341

[20000 rows x 22 columns], y=0        0.0
1        1.0
2        0.0
3        ...0
Name: compliance, Length: 20000, dtype: float64, indices=array([ 3021,  3029,  3040, ..., 19997, 19998, 19999]), train_indices=None)
    183
    184     y_sliced : array-like, sparse matrix or list
    185         Sliced targets.
    186
    187     """
--> 188     if getattr(estimator, "_pairwise", False):
        estimator = Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))])
    189         if not hasattr(X, "shape"):
    190             raise ValueError("Precomputed kernels or affinity matrices have "
    191                              "to be passed as arrays or sparse matrices.")
    192         # X is a precomputed square kernel matrix

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/sklearn/pipeline.py in _pairwise(self=Pipeline(memory=None,
     steps=[('scaler', Pip...one, verbose=0,
            warm_start=False)))]))
    494         return self.steps[-1][-1].classes_
    495
    496     @property
    497     def _pairwise(self):
    498         # check if first estimator expects pairwise input
--> 499         return getattr(self.steps[0][1], '_pairwise', False)
        self.steps = [('scaler', PipelineHelper(available_models={'std': Standard...Scaler(copy=True, with_mean=True, with_std=True))), ('classifier', PipelineHelper(available_models={'svm': SVC(C=1....e=None, verbose=0,
            warm_start=False)))]
    500
    501
    502 def _name_estimators(estimators):
    503     """Generate names for estimators."""

...........................................................................
/Users/jessequinn/.pyenv/versions/3.7.0/lib/python3.7/site-packages/pipelinehelper/__init__.py in __getattr__(self=PipelineHelper(available_models={'std': Standard...Scaler(copy=True, with_mean=True, with_std=True)), name='_pairwise')
     99         if hasattr(self.selected_model, name):
    100             method = getattr(self.selected_model, name, None)
    101             if callable(method):
    102                 return method
    103         else:
--> 104             raise Exception('The method "%s" is not implemented by your model' % name)
        name = '_pairwise'
    105
    106
    107
    108

Exception: The method "_pairwise" is not implemented by your model
___________________________________________________________________________
```


can you post your code that produced this error?


dbconfig.example.php is needed in the installation manuals?


```python
import pandas as pd
from pipelinehelper import PipelineHelper
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier
from sklearn.model_selection import GridSearchCV
from sklearn.naive_bayes import MultinomialNB
from sklearn.neighbors import KNeighborsClassifier
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler, MaxAbsScaler, MinMaxScaler
from sklearn.svm import SVC

def blight_model():
    # variables (to be changed if needed)
    train = 'train.csv'
    test = 'test.csv'
    addresses = 'addresses.csv'
    latlons = 'latlons.csv'
    # remove non-existing features from training data or both training and testing data
    features_to_remove_from_train_only = [
        'payment_amount',
        'payment_date',
        'payment_status',
        'balance_due',
        'collection_status',
        'compliance_detail'
    ]
    features_to_remove_general = [
        #         'agency_name',
        'inspector_name',
        'violator_name',
        'violation_street_number',
        'violation_street_name',
        'violation_zip_code',
        'mailing_address_str_number',
        'mailing_address_str_name',
        'city',
        'state',
        'zip_code',
        'non_us_str_code',
        'country',
        'ticket_issued_date',
        'hearing_date',
        'violation_code',
        'violation_description',
        #         'disposition',
        'grafitti_status',
        'state_fee',
        'admin_fee'
    ]

    # https://stackoverflow.com/questions/18171739/unicodedecodeerror-when-reading-csv-file-in-pandas-with-python
    df_train = pd.read_csv(train, encoding="latin-1", low_memory=False)
    df_test = pd.read_csv(test)
    df_addresses = pd.read_csv(addresses)
    df_latlons = pd.read_csv(latlons)

    # remove Null if the violator was found not responsible
    df_train_filtered = df_train[df_train['compliance'].notnull()]
    df_train_filtered = df_train_filtered[df_train_filtered['hearing_date'].notnull()]
    #     df_test_filtered =  df_test[df_test['hearing_date'].notnull()]

    # hot one encode agency_name and disposition
    df_train_filtered = pd.get_dummies(df_train_filtered, columns=['agency_name'])
    df_train_filtered = pd.get_dummies(df_train_filtered, columns=['disposition'])
    df_test = pd.get_dummies(df_test, columns=['agency_name'])
    df_test = pd.get_dummies(df_test, columns=['disposition'])

    # add non existing columns will default value of 0
    df_test['agency_name_Health Department'] = 0
    df_test['agency_name_Neighborhood City Halls'] = 0
    df_train_filtered['disposition_Responsible (Fine Waived) by Admis'] = 0
    df_train_filtered['disposition_Responsible - Compl/Adj by Default'] = 0
    df_train_filtered['disposition_Responsible - Compl/Adj by Determi'] = 0
    df_train_filtered['disposition_Responsible by Dismissal'] = 0

    # fix dates
    df_train_filtered['ticket_issued_date'] = pd.to_datetime(df_train_filtered['ticket_issued_date'])
    df_test['ticket_issued_date'] = pd.to_datetime(df_test['ticket_issued_date'])
    df_train_filtered['hearing_date'] = pd.to_datetime(df_train_filtered['hearing_date'])
    df_test['hearing_date'] = pd.to_datetime(df_test['hearing_date'])
    df_train_filtered['days_between_ticket'] = df_train_filtered['hearing_date'] - df_train_filtered[
        'ticket_issued_date']
    df_test['days_between_ticket'] = df_test['hearing_date'] - df_test['ticket_issued_date']
    df_train_filtered['days_between_ticket'] = df_train_filtered['days_between_ticket'].dt.days
    df_test['days_between_ticket'] = df_test['days_between_ticket'].dt.days
    df_test['days_between_ticket'].fillna(0, inplace=True)
    df_train_filtered['days_between_ticket'].fillna(0, inplace=True)

    # drop features from training data
    df_train_filtered = df_train_filtered.drop(features_to_remove_from_train_only, axis=1)
    df_train_filtered = df_train_filtered.drop(features_to_remove_general, axis=1)
    df_test_filtered = df_test.drop(features_to_remove_general, axis=1)

    # join addresses and latlons together based on common column of address
    # https://stackoverflow.com/questions/45068584/merge-two-csv-files-into-one-with-pandas-by-id
    df_locations = pd.merge(df_addresses, df_latlons, how='inner', on=['address', 'address'])

    # join addresses to train and test dataframe
    df_train_filtered = pd.merge(df_train_filtered, df_locations, how='inner', on=['ticket_id', 'ticket_id'])
    df_test_filtered = pd.merge(df_test_filtered, df_locations, how='inner', on=['ticket_id', 'ticket_id'])

    df_train_filtered = df_train_filtered.drop('address', axis=1)
    df_test_filtered = df_test_filtered.drop('address', axis=1)

    # fill NaN values
    df_train_filtered.lat.fillna(method='pad', inplace=True)
    df_train_filtered.lon.fillna(method='pad', inplace=True)
    df_test_filtered.lat.fillna(method='pad', inplace=True)
    df_test_filtered.lon.fillna(method='pad', inplace=True)
    df_train_filtered.lat.fillna(method='bfill', inplace=True)
    df_train_filtered.lon.fillna(method='bfill', inplace=True)
    df_test_filtered.lat.fillna(method='bfill', inplace=True)
    df_test_filtered.lon.fillna(method='bfill', inplace=True)

    #     df_train_filtered = df_train_filtered.reindex(sorted(df_train_filtered.columns), axis=1)
    #     df_test_filtered = df_test_filtered.reindex(sorted(df_test_filtered.columns), axis=1)

    #     print(df_train_filtered.shape)
    #     print()
    #     print(df_test_filtered.shape)

    y = df_train_filtered.compliance[:20000]
    X = df_train_filtered.drop('compliance', axis=1)[:20000]
    X_test = df_test_filtered

    scores = ['roc_auc']

    for score in scores:
        print("# Tuning hyper-parameters for %s" % score)
        pipe = Pipeline([
            ('scaler', PipelineHelper([
                ('std', StandardScaler()),
                ('max', MaxAbsScaler()),
            ], include_bypass=True)),  # this will produce one setting without scaler
            ('classifier', PipelineHelper([
                ('svm', SVC()),
                ('rf', RandomForestClassifier()),
                ('ada', AdaBoostClassifier()),
                ('gb', GradientBoostingClassifier()),
                ('knn', KNeighborsClassifier()),

                ('nb_pipe', Pipeline([
                    # Naivie Bayes needs positive numbers
                    ('scaler', MinMaxScaler()),
                    ('nb', MultinomialNB())
                ])),
            ])),
        ])

        params = {
            'scaler__selected_model': pipe.named_steps['scaler'].generate({
                'std__with_mean': [True, False],
                'std__with_std': [True, False],
                # no params for 'max' leads to using standard params
            }),
            'classifier__selected_model': pipe.named_steps['classifier'].generate({
                # too slow!
                # 'svm__C': [0.1, 1.0, 10, 100, 1000],
                # 'svm__gamma': [0.0001, 0.001, 0.01, 0.05, 0.1, 1, 10, 100],
                # 'svm__kernel': ['linear', 'rbf'],

                'rf__n_estimators': [10, 20, 50, 100, 150],
                'rf__max_features': ['auto', 'sqrt', 'log2'],
                'rf__min_samples_split': [2, 5, 10],
                'rf__min_samples_leaf': [1, 2, 4],
                'rf__bootstrap': [True, False],

                'ada__n_estimators': [10, 20, 40, 100],
                'ada__algorithm': ['SAMME', 'SAMME.R'],

                'gb__n_estimators': [10, 20, 50, 100],
                'gb__criterion': ['friedman_mse', 'mse', 'mae'],
                'gb__max_features': ['auto', 'sqrt', None],
                'gb__max_depth': [3, 4, 5, 6, 7],

                'knn__n_neighbors': [2, 3, 5, 7, 10],
                'knn__leaf_size': [1, 2, 3, 5],
                'knn__weights': ['uniform', 'distance'],
                'knn__algorithm': ['auto', 'ball_tree', 'kd_tree', 'brute'],

                'nb_pipe__nb__fit_prior': [True, False],
                'nb_pipe__nb__alpha': [0.1, 0.2],
            })
        }
        grid = GridSearchCV(pipe, params, scoring='%s'%score, cv=5, verbose=1, n_jobs=-1)
        grid.fit(X, y)
        print(grid.best_params_)
        print(grid.best_score_)

    # remove gb__ prefix from best_params_
    # new_gb_best_params_ = dict((key.replace('gb__', ''), value) for (key, value) in estimator.best_params_.items())
    # new_gb_best_params_ = {'criterion': 'friedman_mse', 'max_depth': 6, 'max_features': 'sqrt', 'n_estimators': 10}
    # new_nb_best_params_ = {'fit_prior': True, 'alpha': 0.1}
    # new_std_best_params_ = {'with_mean': True, 'with_std': True}

    # scaler = StandardScaler(**new_std_best_params_)
    #
    # X_scaled = scaler.fit_transform(X)
    #
    # X_test_scaled = scaler.transform(X_test)

    # scaler = MinMaxScaler()
    #
    # X_scaled = scaler.fit_transform(X)
    #
    # X_test_scaled = scaler.transform(X_test)
    #
    # estimator3 = MultinomialNB(**new_nb_best_params_)
    #
    # estimator3.fit(X_scaled, y)
    #
    # yhat_prob = estimator3.predict_proba(X_test_scaled)[:,1]
    #
    # results = pd.DataFrame(columns=['ticket_id','compliance'])
    # results['ticket_id'] = df_test_filtered.ticket_id
    # results['compliance'] = yhat_prob
    # results.set_index('ticket_id', inplace=True)
    #
    # return results

if __name__ == '__main__':
    blight_model()
```


interesting vars to vals in a few paces


master


new branch