Results for better-ids

A gem that makes better dependent error messages telling exactly which relationship tree failed with which ID's.

GraphQL IDE for better development workflows (GraphQL Subscriptions, interactive docs)

Pass in an Airbrake id to visualize and diagnose errors better.

Stop hitting the DB with every secure-token submission. Encoded Tokens have the ID, or UUID, encoded within the token itself - increasing both security and performance. Coded in plain Ruby, EncodedToken is framework agnostic.

This gem encrypt the url id and provide better security from accessing web pages.

With Docker's syslog log-driver the log entries contain just container ID, but seeing the name is even better

Adds better functionality for writing raw sql. Adds hashed global id reference string for database records. This can help with the flexibility and speed of handling records.

convert Selenium tests to ruby/rspec for running against a Grid. Performs much better translation than the Selenium IDE, and a harness for running the resulting specs.

== README.md: #ScheduledResource This gem is for displaying how things are used over time -- a schedule for a set of "resources". You can configure the elements of the schedule and there are utilities and protocols to connect them: - Configuration (specification and management), - Query interfaces (a REST-like API and internal protocols to query the models), and - A basic Rails controller implementation. We have a way to configure the schedule, internal methods to generate the data, and a way to retrieve data from the client. However this gem is largely view-framework agnostic. We could use a variety of client-side packages or even more traditional Rails view templates to generate HTML. In any case, to get a good feel in a display like this we need some client-side code. The gem includes client-side modules to: - Manage <b>time and display geometries</b> with "infinite" scroll along the time axis. - <b>Format display cells</b> in ways specific to the resource models. - <b>Update text justification</b> as the display is scrolled horizontally. ## Configuration A **scheduled resource** is something that can be used for one thing at a time. So if "Rocky & Bullwinkle" is on channel 3 from 10am to 11am on Saturday, then 'channel 3' is the <u>resource</u> and that showing of the episode is a <u>resource-use</u> block. Resources and use-blocks are typically Rails models. Each resource and its use-blocks get one row in the display. That row has a label to the left with some timespan visible on the rest of the row. Something else you would expect see in a schedule would be headers and labels -- perhaps one row with the date and another row with the hour. Headers and labels also fit the model of resources and use-blocks. Basic timezone-aware classes (ZTime*) for those are included in this gem. ### Config File The schedule configuration comes from <tt>config/resource_schedule.yml</tt> which has three top-level sections: - ResourceKinds: A hash where the key is a Resource and the value is a UseBlock. (Both are class names), - Resources: A list where each item is a Resource Class followed by one or more resource ids, and - visibleTime: The visible timespan of the schedule in seconds. The example file <tt>config/resource_schedule.yml</tt> (installed when you run <tt>schedulize</tt>) should be enough to display a two-row schedule with just the date above and the hour below. Of course you can monkey-patch or subclass these classes for your own needs. ### The schedule API The 'schedule' endpoint uses parameters <tt>t1</tt> and <tt>t2</tt> to specify a time interval for the request. A third parameter <tt>inc</tt> allows an initial time window to be expanded without repeating blocks that span those boundaries. The time parameters _plus the configured resources_ define the data to be returned. ### More About Configuration Management The <b>ScheduledResource</b> class manages resource and use-block class names, id's and labels for a schedule according to the configuration file. A ScheduledResource instance ties together: 1. A resource class (eg TvStation), 2. An id (a channel number in this example), and 3. Strings and other assets that will go into the DOM. The id is used to - select a resource _instance_ and - select instances of the _resource use block_ class (eg Program instances). The id _could_ be a database id but more often is something a little more suited to human use in the configuration. In any case it is used by model class method <tt>(resource_use_block_class).get_all_blocks()</tt> to select the right use-blocks for the resource. A resource class name and id are are joined with a '_' to form a tag that also serves as an id for the DOM. Once the configuration yaml is loaded that data is maintained in the session structure. Of course having a single configuration file limits the application's usefulness. A more general approach would be to have a user model with login and configuration would be associated with the user. ## Installation Add this line to your application's Gemfile: ```ruby gem 'scheduled_resource' ``` And then execute: $ bundle Or install it yourself as: $ gem install scheduled_resource Then from your application's root execute: $ schedulize . This will install a few image placeholders, client-side modules and a stylesheet under <tt>vendor/assets</tt>, an example configuration in <tt>config/resource_schedule.yml</tt> and an example controller in <tt>app/controllers/schedule_controller.rb</tt>. Also, if you use $ bundle show scheduled_resource to locate the installed source you can browse example classes <tt>lib/z_time_*.rb</tt> and the controller helper methods in <tt>lib/scheduled_resource/helper.rb</tt> ## Testing This gem also provides for a basic test application using angularjs to display a minimal but functional schedule showing just the day and hour headers in two different timezones (US Pacific and Eastern). Proceed as follows, starting with a fresh Rails app: $ rails new test_sr As above, add the gem to the Gemfile, then $ cd test_sr $ bundle $ schedulize . Add lines such as these to <tt>config/routes.rb</tt> get "/schedule/index" => "schedule#index" get "/schedule" => "schedule#schedule" Copy / merge these files from the gem source into the test app: $SR_SRC/app/views/layouts/application.html.erb $SR_SRC/app/views/schedule/index.html.erb $SR_SRC/app/assets/javascripts/{angular.js,script.js,controllers.js} and add <tt>//= require angular</tt> to application.js just below the entries for <tt>jquery</tt>. After you run the server and browse to http://0.0.0.0:3000/schedule/index you should see the four time-header rows specified by the sample config file. ## More Examples A better place to see the use of this gem is at [tv4](https://github.com/emeyekayee/tv4). Specifically, models <tt>app/models/event.rb</tt> and <tt>app/models/station.rb</tt> give better examples of implementing the ScheduledResource protocol and adapting to a db schema organized along somewhat different lines. ## Contributing 1. Fork it ( https://github.com/emeyekayee/scheduled_resource/fork ) 2. Create your feature branch (`git checkout -b my-new-feature`) 3. Commit your changes (`git commit -am 'Add some feature'`) 4. Push to the branch (`git push origin my-new-feature`) 5. Create a new Pull Request

README ====== This is a simple API to evaluate information retrieval results. It allows you to load ranked and unranked query results and calculate various evaluation metrics (precision, recall, MAP, kappa) against a previously loaded gold standard. Start this program from the command line with: retreval -l <gold-standard-file> -q <query-results> -f <format> -o <output-prefix> The options are outlined when you pass no arguments and just call retreval You will find further information in the RDOC documentation and the HOWTO section below. If you want to see an example, use this command: retreval -l example/gold_standard.yml -q example/query_results.yml -f yaml -v INSTALLATION ============ If you have RubyGems, just run gem install retreval You can manually download the sources and build the Gem from there by `cd`ing to the folder where this README is saved and calling gem build retreval.gemspec This will create a gem file called which you just have to install with `gem install <file>` and you're done. HOWTO ===== This API supports the following evaluation tasks: - Loading a Gold Standard that takes a set of documents, queries and corresponding judgements of relevancy (i.e. "Is this document relevant for this query?") - Calculation of the _kappa measure_ for the given gold standard - Loading ranked or unranked query results for a certain query - Calculation of _precision_ and _recall_ for each result - Calculation of the _F-measure_ for weighing precision and recall - Calculation of _mean average precision_ for multiple query results - Calculation of the _11-point precision_ and _average precision_ for ranked query results - Printing of summary tables and results Typically, you will want to use this Gem either standalone or within another application's context. Standalone Usage ================ Call parameters --------------- After installing the Gem (see INSTALLATION), you can always call `retreval` from the commandline. The typical call is: retreval -l <gold-standard-file> -q <query-results> -f <format> -o <output-prefix> Where you have to define the following options: - `gold-standard-file` is a file in a specified format that includes all the judgements - `query-results` is a file in a specified format that includes all the query results in a single file - `format` is the format that the files will use (either "yaml" or "plain") - `output-prefix` is the prefix of output files that will be created Formats ------- Right now, we focus on the formats you can use to load data into the API. Currently, we support YAML files that must adhere to a special syntax. So, in order to load a gold standard, we need a file in the following format: * "query" denotes the query * "documents" these are the documents judged for this query * "id" the ID of the document (e.g. its filename, etc.) * "judgements" an array of judgements, each one with: * "relevant" a boolean value of the judgment (relevant or not) * "user" an optional identifier of the user Example file, with one query, two documents, and one judgement: - query: 12th air force germany 1957 documents: - id: g5701s.ict21311 judgements: [] - id: g5701s.ict21313 judgements: - relevant: false user: 2 So, when calling the program, specify the format as `yaml`. For the query results, a similar format is used. Note that it is necessary to specify whether the result sets are ranked or not, as this will heavily influence the calculations. You can specify the score for a document. By "score" we mean the score that your retrieval algorithm has given the document. But this is not necessary. The documents will always be ranked in the order of their appearance, regardless of their score. Thus in the following example, the document with "07" at the end is the first and "25" is the last, regardless of the score. --- query: 12th air force germany 1957 ranked: true documents: - score: 0.44034874 document: g5701s.ict21307 - score: 0.44034874 document: g5701s.ict21309 - score: 0.44034874 document: g5701s.ict21311 - score: 0.44034874 document: g5701s.ict21313 - score: 0.44034874 document: g5701s.ict21315 - score: 0.44034874 document: g5701s.ict21317 - score: 0.44034874 document: g5701s.ict21319 - score: 0.44034874 document: g5701s.ict21321 - score: 0.44034874 document: g5701s.ict21323 - score: 0.44034874 document: g5701s.ict21325 --- query: 1612 ranked: true documents: - score: 1.0174774 document: g3290.np000144 - score: 0.763108 document: g3201b.ct000726 - score: 0.763108 document: g3400.ct000886 - score: 0.6359234 document: g3201s.ct000130 --- **Note**: You can also use the `plain` format, which will load the gold standard in a different way (but not the results): my_query my_document_1 false my_query my_document_2 true See that every query/document/relevancy pair is separated by a tabulator? You can also add the user's ID in the fourth column if necessary. Running the evaluation ----------------------- After you have specified the input files and the format, you can run the program. If needed, the `-v` switch will turn on verbose messages, such as information on how many judgements, documents and users there are, but this shouldn't be necessary. The program will first load the gold standard and then calculate the statistics for each result set. The output files are automatically created and contain a YAML representation of the results. Calculations may take a while depending on the amount of judgements and documents. If there are a thousand judgements, always consider a few seconds for each result set. Interpreting the output files ------------------------------ Two output files will be created: - `output_avg_precision.yml` - `output_statistics.yml` The first lists the average precision for each query in the query result file. The second file lists all supported statistics for each query in the query results file. For example, for a ranked evaluation, the first two entries of such a query result statistic look like this: --- 12th air force germany 1957: - :precision: 0.0 :recall: 0.0 :false_negatives: 1 :false_positives: 1 :true_negatives: 2516 :true_positives: 0 :document: g5701s.ict21313 :relevant: false - :precision: 0.0 :recall: 0.0 :false_negatives: 1 :false_positives: 2 :true_negatives: 2515 :true_positives: 0 :document: g5701s.ict21317 :relevant: false You can see the precision and recall for that specific point and also the number of documents for the contingency table (true/false positives/negatives). Also, the document identifier is given. API Usage ========= Using this API in another ruby application is probably the more common use case. All you have to do is include the Gem in your Ruby or Ruby on Rails application. For details about available methods, please refer to the API documentation generated by RDoc. **Important**: For this implementation, we use the document ID, the query and the user ID as the primary keys for matching objects. This means that your documents and queries are identified by a string and thus the strings should be sanitized first. Loading the Gold Standard ------------------------- Once you have loaded the Gem, you will probably start by creating a new gold standard. gold_standard = GoldStandard.new Then, you can load judgements into this standard, either from a file, or manually: gold_standard.load_from_yaml_file "my-file.yml" gold_standard.add_judgement :document => doc_id, :query => query_string, :relevant => boolean, :user => John There is a nice shortcut for the `add_judgement` method. Both lines are essentially the same: gold_standard.add_judgement :document => doc_id, :query => query_string, :relevant => boolean, :user => John gold_standard << :document => doc_id, :query => query_string, :relevant => boolean, :user => John Note the usage of typical Rails hashes for better readability (also, this Gem was developed to be used in a Rails webapp). Now that you have loaded the gold standard, you can do things like: gold_standard.contains_judgement? :document => "a document", :query => "the query" gold_standard.relevant? :document => "a document", :query => "the query" Loading the Query Results ------------------------- Now we want to create a new `QueryResultSet`. A query result set can contain more than one result, which is what we normally want. It is important that you specify the gold standard it belongs to. query_result_set = QueryResultSet.new :gold_standard => gold_standard Just like the Gold Standard, you can read a query result set from a file: query_result_set.load_from_yaml_file "my-results-file.yml" Alternatively, you can load the query results one by one. To do this, you have to create the results (either ranked or unranked) and then add documents: my_result = RankedQueryResult.new :query => "the query" my_result.add_document :document => "test_document 1", :score => 13 my_result.add_document :document => "test_document 2", :score => 11 my_result.add_document :document => "test_document 3", :score => 3 This result would be ranked, obviously, and contain three documents. Documents can have a score, but this is optional. You can also create an Array of documents first and add them altogether: documents = Array.new documents << ResultDocument.new :id => "test_document 1", :score => 20 documents << ResultDocument.new :id => "test_document 2", :score => 21 my_result = RankedQueryResult.new :query => "the query", :documents => documents The same applies to `UnrankedQueryResult`s, obviously. The order of ranked documents is the same as the order in which they were added to the result. The `QueryResultSet` will now contain all the results. They are stored in an array called `query_results`, which you can access. So, to iterate over each result, you might want to use the following code: query_result_set.query_results.each_with_index do |result, index| # ... end Or, more simply: for result in query_result_set.query_results # ... end Calculating statistics ---------------------- Now to the interesting part: Calculating statistics. As mentioned before, there is a conceptual difference between ranked and unranked results. Unranked results are much easier to calculate and thus take less CPU time. No matter if unranked or ranked, you can get the most important statistics by just calling the `statistics` method. statistics = my_result.statistics In the simple case of an unranked result, you will receive a hash with the following information: * `precision` - the precision of the results * `recall` - the recall of the results * `false_negatives` - number of not retrieved but relevant items * `false_positives` - number of retrieved but nonrelevant * `true_negatives` - number of not retrieved and nonrelevantv items * `true_positives` - number of retrieved and relevant items In case of a ranked result, you will receive an Array that consists of _n_ such Hashes, depending on the number of documents. Each Hash will give you the information at a certain rank, e.g. the following to lines return the recall at the fourth rank. statistics = my_ranked_result.statistics statistics[3][:recall] In addition to the information mentioned above, you can also get for each rank: * `document` - the ID of the document that was returned at this rank * `relevant` - whether the document was relevant or not Calculating statistics with missing judgements ---------------------------------------------- Sometimes, you don't have judgements for all document/query pairs in the gold standard. If this happens, the results will be cleaned up first. This means that every document in the results that doesn't appear to have a judgement will be removed temporarily. As an example, take the following results: * A * B * C * D Our gold standard only contains judgements for A and C. The results will be cleaned up first, thus leading to: * A * C With this approach, we can still provide meaningful results (for precision and recall). Other statistics ---------------- There are several other statistics that can be calculated, for example the **F measure**. The F measure weighs precision and recall and has one parameter, either "alpha" or "beta". Get the F measure like so: my_result.f_measure :beta => 1 If you don't specify either alpha or beta, we will assume that beta = 1. Another interesting measure is **Cohen's Kappa**, which tells us about the inter-agreement of assessors. Get the kappa statistic like this: gold_standard.kappa This will calculate the average kappa for each pairwise combination of users in the gold standard. For ranked results one might also want to calculate an **11-point precision**. Just call the following: my_ranked_result.eleven_point_precision This will return a Hash that has indices at the 11 recall levels from 0 to 1 (with steps of 0.1) and the corresponding precision at that recall level.

Watermark's library for interfacing with Arena ChMS's web API

= dm-is-published This plugin makes it very easy to add different states to your models, like 'draft' vs 'live'. By default it also adds validations of the field value. Originally inspired by the Rails plugin +acts_as_publishable+ by &lt;b&gt;fr.ivolo.us&lt;/b&gt;. == Installation # Add GitHub to your RubyGems sources $ gem sources -a http://gems.github.com $ (sudo)? gem install kematzy-dm-is-published &lt;b&gt;NB! Depends upon the whole DataMapper suite being installed, and has ONLY been tested with DM 0.10.0 (next branch).&lt;/b&gt; == Getting Started First of all, for a better understanding of this gem, make sure you study the '&lt;tt&gt;dm-is-published/spec/integration/published_spec.rb&lt;/tt&gt;' file. ---- Require +dm-is-published+ in your app. require 'dm-core' # must be required first require 'dm-is-published' Lets say we have an Article class, and each Article can have a current state, ie: whether it's Live, Draft or an Obituary awaiting the death of someone famous (real or rumored) class Article include DataMapper::Resource property :id, Serial property :title, String ...&lt;snip&gt; is :published end Once you have your Article model we can create our Articles just as normal Article.create(:title =&gt; 'Example 1') The instance of &lt;tt&gt;Article.get(1)&lt;/tt&gt; now has the following things for free: * a &lt;tt&gt;:publish_status&lt;/tt&gt; attribute with the value &lt;tt&gt;'live'&lt;/tt&gt;. Default choices are &lt;tt&gt;[ :live, :draft, :hidden ]&lt;/tt&gt;. * &lt;tt&gt;:is_live?, :is_draft? or :is_hidden?&lt;/tt&gt; methods that returns true/false based upon the state. * &lt;tt&gt;:save_as_live&lt;/tt&gt;, &lt;tt&gt;:save_as_draft&lt;/tt&gt; or &lt;tt&gt;:save_as_hidden&lt;/tt&gt; converts the instance to the state and saves it. * &lt;tt&gt;:publishable?&lt;/tt&gt; method that returns true for models where &lt;tt&gt;is :published &lt;/tt&gt; has been declared, but &lt;b&gt;false&lt;/b&gt; for those where it has not been declared. The Article class also gets a bit of new functionality: Article.all(:draft) =&gt; finds all Articles with :publish_status = :draft Article.all(:draft, :author =&gt; @author_joe ) =&gt; finds all Articles with :publish_status = :draft and author == Joe Todo Need to write more documentation here.. == Usage Scenarios In a Blog/Publishing scenario you could use it like this: class Article ...&lt;snip&gt;... is :published :live, :draft, :hidden end Whereas in another scenario - like in a MenuItem model for a Restaurant - you could use it like this: class MenuItem ...&lt;snip&gt;... is :published :on, :off # the item is either on the menu or not end == RTFM As I said above, for a better understanding of this gem/plugin, make sure you study the '&lt;tt&gt;dm-is-published/spec/integration/published_spec.rb&lt;/tt&gt;' file. == Errors / Bugs If something is not behaving intuitively, it is a bug, and should be reported. Report it here: http://github.com/kematzy/dm-is-published/issues == Credits Copyright (c) 2009-07-11 [kematzy gmail com] Loosely based on the ActsAsPublishable plugin by [http://fr.ivolo.us/posts/acts-as-publishable] == Licence Released under the MIT license.

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