Results for single-line-string

Generate JSON strings from Ruby objects with flexible formatting options. Key features: keep arrays and objects on a single line when they fit; format floats to specific precision; sort and align object keys; adjust whitespace padding of arrays and objects, inside and around commas and colons. JavaScript version included.

This gem provides a (hopefully) high quality http parser library that can build request information iteratively as data comes over the line without requiring the caller to maintain the entire body of the request as a single string in memory.

Configurable parser for single-line argument strings, returning a structured set of sub-strings representing positional arguments, named arguments and flags.

The input consists of a string containing a sequence of commands, where a command is represented by a single capital letter at the beginning of the line. Parameters of the command are separated by white spaces and they follow the command character. Pixel co-ordinates are a pair of integers: a column number between 1 and 250, and a row number between 1 and 250. Bitmaps starts at coordinates 1,1. Colours are specified by capital letters.

Small, fast and flexible state machines using composition.

== Develop, Decorate and manage Dependencies for C (GNU) Makefiles easily with a Ruby script. Install using the Ruby Gem: > gem install demake To create an example with multiple sample applications: > demake example This will create a directory named example containing the example. To create an example with a single sample application: > demake oreo This will create a directory named oreo containing the example. It requires a demake directory and application file containing the application names followed by depencencies separated by spaces and with a new line to indicate a different application. Something like (from the example): > mkdir demake > echo "hello string" > demake/applications > echo "goodbye string" >> demake/applications > demake For customization, optionally include (see example): demake/settings.rb, demake/test-target.rb, demake/install-target.rb, demake/license The output of the command by itself is a (GNU style) file named Makefile: > demake You can also clone from git: > git clone https://github.com/MinaswanNakamoto/demake.git > chmod +x demake/bin/demake > cd demake > bin/demake example > cd example ; make ; make build ; make test If you have an existing C application and you want to generate a Makefile for it, you might try the gen_application shell script. > ./gen_application myapp

== Easily add colors, boxes, repetitions and emojis to your terminal output using pipes (|). Install using the Ruby Gem: > gem install pipetext Includes a library module which can be included in your code: require 'pipetext' class YellowPrinter include PipeText def print(string) write('|Y' + string + '|n') end end printer = YellowPrinter.new printer.print('This is yellow') The gem includes a command line interface too: > pipetext > pipetext '|Ccyan|n' Easily set your bash prompt colors using pipetext: > PS1=$(pipetext '|$|g\u|n@|g\h|n:|g\w|n$ ') Works with files: > pipetext <filename> Works with pipes too: > echo '|RRed test |u1f49c|n' | pipetext --- | pipe || & ampersand && Toggle (&) background color mode |& smoke |s white |W black text on white background |k&w red |r bright red |R red background &r green |g bright green |G green background &g blue |b bright blue |B blue background &b cyan |c bright cyan |C cyan background &c yellow |y bright yellow |Y yellow background &y magenta |m bright magenta |M magenta background &m --- Hex RGB color codes: Foreground |#RRGGBB Background &#RRGGBB Palette colors (256) using Hex: |p33&pF8 Clear Screen |! black with white background |K&w Blinking |@ white with magenta background |w&m invert |i smoke with green background |s&g Underlined |_ red with cyan background |r&c Italics |~ bright red with blue background |R&b Bold |+ green with yellow background |g&y Faint |. bright green with red background |G&r Crossed out |x normal color and background |n&n Escape Sequence |\ Center text using current position and line end number |{text to center} Add spaces to line end |; Set line end |]# Set current x,y cursor position |[x,y] Terminal bell |[bell] Move cursor up 1 line |^ Hide cursor |h Move cursor down 1 line |v Unhide cursor |H Move cursor forward 1 character |> Sleep timer in seconds |[#s] Move cursor back 1 character |< Sleep timer in milliseconds |[#ms] Capture variable |(variable name=data) Display variable |(variable name) Add to variable |(variable name+=data) Subtract from variable |(variable name-=data) Multiple variable |(variable name*=data) Divide variable |(variable name/=data) Copy variable to current number |(#variable name) |$ toggles [ and ] around empty sequences automatically for bash command prompts --- Emojis: https://unicode.org/emoji/charts/full-emoji-list.html |[Abbreviated CLDR Short Name] 😍 |[smiling face with heart-eyes] or ⚙ |[gear] 💤 |[zzz] 👨 |[man] 😍 |[sm f w he e] ✔ |U2714 ❌ |U274c ☮ |u262E 💎 |u1f48e 💜 |u1f49c --- Single or double line box mode with |- or |= ┌──┬──┐ ╔══╦══╗ +--+--+ <-- Draw this with this: |15 |-[--v--] |=[--v--] |o[--v--] │ │ │ ║ ║ ║ | | | |15 |-! ! ! |=! ! ! |o! ! ! 123456789012345├──┴──┤ ╠══╩══╣ +--+--+ |y1234567890|g12345|n|->--^--< |=>--^--< |o>--^--< 15 Spaces │ │ ║ ║ | | |c15|n Spaces|6 |-! ! |=! ! |o! ! (|15 ) └─────┘ ╚═════╝ +-----+ (||15 )|9 |-{-----} |={-----} |o{-----} ┌──────────────────┐ ╔════════════════════╗ |-[|18-]|4 |g&m|=[|20-]|n&n|O │ │ ║ ║ |-!|18 !|4 |g&m|=!|20 !|n&n|O ├──────────────────┤ ╠════════════════════╣ |->|18-<|4 &m|g|=>|20-<|n&n|O │ │ ║ ║ |-!|18 !|4 |g&m|=!|20 !|n&n|O └──────────────────┘ ╚════════════════════╝ |-{|18-}|4 |g&m|={|20-}|n&n|O --- Repetition using | followed by the number of characters to repeat and then the character to repeat. |15* does the * character 15 times like this: *************** --- ==Use the ++pipetext++ command to see other options and examples.

= TMail http://tmail.rubyforge.org/ Mikel Lindsaar maintainer Trans assitant developer Minero Aoki original developer == NOTE: !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! THIS IS A FORK OF TMAIL HACKED TOGETHER TO WORK WITH RUBY 1.9.1 ! ! USE AT YOUR OWN DISCRETION ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! == DESCRIPTION: TMail is a mail handling library for Ruby. It abstracts a mail message into a usable object allowing you to read, set, add and delete headers and the mail body. TMail is used by the Ruby on Rails web framework as the Email abstraction layer for their ActionMailer module. It is also used by the Nitro framework and many other applications on and off the web. The goal of the TMail handling library is to be able to parse and handle raw Email sources and produce RFC compliant Emails as a result. If you find something that TMail does that violates an RFC, we want to know and we'll get it fixed fast. == DOCUMENTATION: The place you will want to look first is the TMail::Mail class. This has the vast majority of methods you will be using to talk to your TMail object. == FEATURES/PROBLEMS: TMail is fairly RFC compliant on the handling of emails. There are also some problems in the header handling, but for 99.9% of email, you will be fine. Usually, the problems revolve around parsing incomming emails and making sense of them. I really welcome any examples of Emails that "didn't work" with TMail so I can use them as test cases. == SYNOPSIS: TMail is very easy to use. You simply require the library and then pass a raw email text message into the TMail::Mail.parse method. This returns a TMail::Mail object which you can now query and run methods against to modify, inspect or add to the Email. You can find almost all of the methods that you will use to talk to and update a TMail instance in the TMail::Mail class. I am constantly updating this code, with comments, added a fair bit and have a lot more to go!. === Short Version: irb(main):001:0&gt; require 'tmail' irb(main):002:0&gt; raw_email = File.open("my_raw_email", 'r') { |f| @mail = f.read } irb(main):003:0&gt; email = TMail::Mail.parse(raw_email) irb(main):004:0&gt; puts email['to'] mikel@example.com =&gt; nil irb(main):005:0&gt; email['to'] = 'mikel@somewhere.else.com' =&gt; "mikel@somewhere.else.com" irb(main):006:0&gt; puts email['to'] mikel@somewhere.else.com =&gt; nil === Longer Version: Assuming you have a single raw email in the variable my_message, you can do the following: require 'tmail' email = TMail::Mail.parse(my_message) This will give you a TMail::Mail class containing your parsed message. There are other methods of opening emails through Ports. You can view this email by a simple puts: puts email Return-Path: &lt;mikel@nowhere.com&gt; Date: Sun, 21 Oct 2007 19:38:13 +1000 From: Mikel Lindsaar &lt;mikel@nowhere.com&gt; To: mikel@somewhere.com Message-Id: &lt;009601c813c6$19df3510$0437d30a@mikel091a&gt; Subject: Testing Email Hello Mikel Easy right? === Adding a header to the EMail: Say now that you have opened your message, you want to put in a Reply-To field. You do this like so: email['reply-to'] = "My Email Address &lt;my_address@anotherplace.com&gt;" Is it really there? Well, find out with a puts: puts email Return-Path: &lt;mikel@nowhere.com&gt; Date: Sun, 21 Oct 2007 19:38:13 +1000 From: Mikel Lindsaar &lt;mikel@nowhere.com&gt; Reply-To: My Email Address &lt;my_address@anotherplace.com&gt; To: mikel@somewhere.com Message-Id: &lt;009601c813c6$19df3510$0437d30a@mikel091a&gt; Subject: Testing Email Hello Mikel Yup looks good. === Inspecting a header: You can then inspect your added header by doing: email['reply-to'] # =&gt; #&lt;TMail::AddressHeader "My Email Address &lt;my_address@anotherplace.com&gt;"&gt; If you just want to the actual value, not the AddressHeader object, pass to_s to this. email['reply-to'].to_s # =&gt; "My Email Address &lt;my_address@anotherplace.com&gt;" === Deleting a header: One way of deleting a header from an Email is just assigning it nil like so: email['reply-to'] = nil # =&gt; nil If you now puts the email again, it will not be included: puts email Return-Path: &lt;mikel@nowhere.com&gt; Date: Sun, 21 Oct 2007 19:38:13 +1000 From: Mikel Lindsaar &lt;mikel@nowhere.com&gt; To: mikel@somewhere.com Message-Id: &lt;009601c813c6$19df3510$0437d30a@mikel091a&gt; Subject: Testing Email Hello Mikel === Writing out an Email: You can just call to_s on any email to have it serialized out as a single string with the right number of line breaks and encodings. == CONTRIBUTING: You can visit the {Contributing to TMail}[link:http://tmail.rubyforge.org/contributing/] to find out how to contribute to TMail, developers are welcome and wanted! == REQUIREMENTS: * C compiler if you want the Ruby extension for Scanner * Ruby 1.8 or later == INSTALLATION: * sudo gem install tmail Or manually, * sudo script/setup == LICENSE: (The MIT License) Copyright (c) 2007 FIX Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the 'Software'), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED 'AS IS', WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

== 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 &lt;b&gt;time and display geometries&lt;/b&gt; with "infinite" scroll along the time axis. - &lt;b&gt;Format display cells&lt;/b&gt; in ways specific to the resource models. - &lt;b&gt;Update text justification&lt;/b&gt; 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 &amp; Bullwinkle" is on channel 3 from 10am to 11am on Saturday, then 'channel 3' is the &lt;u&gt;resource&lt;/u&gt; and that showing of the episode is a &lt;u&gt;resource-use&lt;/u&gt; 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 &lt;tt&gt;config/resource_schedule.yml&lt;/tt&gt; 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 &lt;tt&gt;config/resource_schedule.yml&lt;/tt&gt; (installed when you run &lt;tt&gt;schedulize&lt;/tt&gt;) 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 &lt;tt&gt;t1&lt;/tt&gt; and &lt;tt&gt;t2&lt;/tt&gt; to specify a time interval for the request. A third parameter &lt;tt&gt;inc&lt;/tt&gt; 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 &lt;b&gt;ScheduledResource&lt;/b&gt; 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 &lt;tt&gt;(resource_use_block_class).get_all_blocks()&lt;/tt&gt; 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 &lt;tt&gt;vendor/assets&lt;/tt&gt;, an example configuration in &lt;tt&gt;config/resource_schedule.yml&lt;/tt&gt; and an example controller in &lt;tt&gt;app/controllers/schedule_controller.rb&lt;/tt&gt;. Also, if you use $ bundle show scheduled_resource to locate the installed source you can browse example classes &lt;tt&gt;lib/z_time_*.rb&lt;/tt&gt; and the controller helper methods in &lt;tt&gt;lib/scheduled_resource/helper.rb&lt;/tt&gt; ## 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 &lt;tt&gt;config/routes.rb&lt;/tt&gt; get "/schedule/index" =&gt; "schedule#index" get "/schedule" =&gt; "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 &lt;tt&gt;//= require angular&lt;/tt&gt; to application.js just below the entries for &lt;tt&gt;jquery&lt;/tt&gt;. 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 &lt;tt&gt;app/models/event.rb&lt;/tt&gt; and &lt;tt&gt;app/models/station.rb&lt;/tt&gt; 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.

Lookout Lookout is a unit testing framework for Ruby¹ that puts your results in focus. Tests (expectations) are written as follows expect 2 do 1 + 1 end expect ArgumentError do Integer('1 + 1') end expect Array do [1, 2, 3].select{ |i| i % 2 == 0 } end expect [2, 4, 6] do [1, 2, 3].map{ |i| i * 2 } end Lookout is designed to encourage – force, even – unit testing best practices such as • Setting up only one expectation per test • Not setting expectations on non-public APIs • Test isolation This is done by • Only allowing one expectation to be set per test • Providing no (additional) way of accessing private state • Providing no setup and tear-down methods, nor a method of providing test helpers Other important points are • Putting the expected outcome of a test in focus with the steps of the calculation of the actual result only as a secondary concern • A focus on code readability by providing no mechanism for describing an expectation other than the code in the expectation itself • A unified syntax for setting up both state-based and behavior-based expectations The way Lookout works has been heavily influenced by expectations², by {Jay Fields}³. The code base was once also heavily based on expectations, based at Subversion {revision 76}⁴. A lot has happened since then and all of the work past that revision are due to {Nikolai Weibull}⁵. ¹ Ruby: http://ruby-lang.org/ ² Expectations: http://expectations.rubyforge.org/ ³ Jay Fields’s blog: http://blog.jayfields.com/ ⁴ Lookout revision 76: https://github.com/now/lookout/commit/537bedf3e5b3eb4b31c066b3266f42964ac35ebe ⁵ Nikolai Weibull’s home page: http://disu.se/ § Installation Install Lookout with % gem install lookout § Usage Lookout allows you to set expectations on an object’s state or behavior. We’ll begin by looking at state expectations and then take a look at expectations on behavior. § Expectations on State: Literals An expectation can be made on the result of a computation: expect 2 do 1 + 1 end Most objects, in fact, have their state expectations checked by invoking ‹#==› on the expected value with the result as its argument. Checking that a result is within a given range is also simple: expect 0.099..0.101 do 0.4 - 0.3 end Here, the more general ‹#===› is being used on the ‹Range›. § Regexps ‹Strings› of course match against ‹Strings›: expect 'ab' do 'abc'[0..1] end but we can also match a ‹String› against a ‹Regexp›: expect %r{a substring} do 'a string with a substring' end (Note the use of ‹%r{…}› to avoid warnings that will be generated when Ruby parses ‹expect /…/›.) § Modules Checking that the result includes a certain module is done by expecting the ‹Module›. expect Enumerable do [] end This, due to the nature of Ruby, of course also works for classes (as they are also modules): expect String do 'a string' end This doesn’t hinder us from expecting the actual ‹Module› itself: expect Enumerable do Enumerable end or the ‹Class›: expect String do String end for obvious reasons. As you may have figured out yourself, this is accomplished by first trying ‹#==› and, if it returns ‹false›, then trying ‹#===› on the expected ‹Module›. This is also true of ‹Ranges› and ‹Regexps›. § Booleans Truthfulness is expected with ‹true› and ‹false›: expect true do 1 end expect false do nil end Results equaling ‹true› or ‹false› are slightly different: expect TrueClass do true end expect FalseClass do false end The rationale for this is that you should only care if the result of a computation evaluates to a value that Ruby considers to be either true or false, not the exact literals ‹true› or ‹false›. § IO Expecting output on an IO object is also common: expect output("abc\ndef\n") do |io| io.puts 'abc', 'def' end This can be used to capture the output of a formatter that takes an output object as a parameter. § Warnings Expecting warnings from code isn’t very common, but should be done: expect warning('this is your final one!') do warn 'this is your final one!' end expect warning('this is your final one!') do warn '%s:%d: warning: this is your final one!' % [__FILE__, __LINE__] end ‹$VERBOSE› is set to ‹true› during the execution of the block, so you don’t need to do so yourself. If you have other code that depends on the value of $VERBOSE, that can be done with ‹#with_verbose› expect nil do with_verbose nil do $VERBOSE end end § Errors You should always be expecting errors from – and in, but that’s a different story – your code: expect ArgumentError do Integer('1 + 1') end Often, not only the type of the error, but its description, is important to check: expect StandardError.new('message') do raise StandardError.new('message') end As with ‹Strings›, ‹Regexps› can be used to check the error description: expect StandardError.new(/mess/) do raise StandardError.new('message') end § Queries Through Symbols Symbols are generally matched against symbols, but as a special case, symbols ending with ‹?› are seen as expectations on the result of query methods on the result of the block, given that the method is of zero arity and that the result isn’t a Symbol itself. Simply expect a symbol ending with ‹?›: expect :empty? do [] end To expect it’s negation, expect the same symbol beginning with ‹not_›: expect :not_nil? do [1, 2, 3] end This is the same as expect true do [].empty? end and expect false do [1, 2, 3].empty? end but provides much clearer failure messages. It also makes the expectation’s intent a lot clearer. § Queries By Proxy There’s also a way to make the expectations of query methods explicit by invoking methods on the result of the block. For example, to check that the even elements of the Array ‹[1, 2, 3]› include ‹1› you could write expect result.to.include? 1 do [1, 2, 3].reject{ |e| e.even? } end You could likewise check that the result doesn’t include 2: expect result.not.to.include? 2 do [1, 2, 3].reject{ |e| e.even? } end This is the same as (and executes a little bit slower than) writing expect false do [1, 2, 3].reject{ |e| e.even? }.include? 2 end but provides much clearer failure messages. Given that these two last examples would fail, you’d get a message saying “[1, 2, 3]#include?(2)” instead of the terser “true≠false”. It also clearly separates the actual expectation from the set-up. The keyword for this kind of expectations is ‹result›. This may be followed by any of the methods • ‹#not› • ‹#to› • ‹#be› • ‹#have› or any other method you will want to call on the result. The methods ‹#to›, ‹#be›, and ‹#have› do nothing except improve readability. The ‹#not› method inverts the expectation. § Literal Literals If you need to literally check against any of the types of objects otherwise treated specially, that is, any instances of • ‹Module› • ‹Range› • ‹Regexp› • ‹Exception› • ‹Symbol›, given that it ends with ‹?› you can do so by wrapping it in ‹literal(…)›: expect literal(:empty?) do :empty? end You almost never need to do this, as, for all but symbols, instances will match accordingly as well. § Expectations on Behavior We expect our objects to be on their best behavior. Lookout allows you to make sure that they are. Reception expectations let us verify that a method is called in the way that we expect it to be: expect mock.to.receive.to_str(without_arguments){ '123' } do |o| o.to_str end Here, ‹#mock› creates a mock object, an object that doesn’t respond to anything unless you tell it to. We tell it to expect to receive a call to ‹#to_str› without arguments and have ‹#to_str› return ‹'123'› when called. The mock object is then passed in to the block so that the expectations placed upon it can be fulfilled. Sometimes we only want to make sure that a method is called in the way that we expect it to be, but we don’t care if any other methods are called on the object. A stub object, created with ‹#stub›, expects any method and returns a stub object that, again, expects any method, and thus fits the bill. expect stub.to.receive.to_str(without_arguments){ '123' } do |o| o.to_str if o.convertable? end You don’t have to use a mock object to verify that a method is called: expect Object.to.receive.name do Object.name end As you have figured out by now, the expected method call is set up by calling ‹#receive› after ‹#to›. ‹#Receive› is followed by a call to the method to expect with any expected arguments. The body of the expected method can be given as the block to the method. Finally, an expected invocation count may follow the method. Let’s look at this formal specification in more detail. The expected method arguments may be given in a variety of ways. Let’s introduce them by giving some examples: expect mock.to.receive.a do |m| m.a end Here, the method ‹#a› must be called with any number of arguments. It may be called any number of times, but it must be called at least once. If a method must receive exactly one argument, you can use ‹Object›, as the same matching rules apply for arguments as they do for state expectations: expect mock.to.receive.a(Object) do |m| m.a 0 end If a method must receive a specific argument, you can use that argument: expect mock.to.receive.a(1..2) do |m| m.a 1 end Again, the same matching rules apply for arguments as they do for state expectations, so the previous example expects a call to ‹#a› with 1, 2, or the Range 1..2 as an argument on ‹m›. If a method must be invoked without any arguments you can use ‹without_arguments›: expect mock.to.receive.a(without_arguments) do |m| m.a end You can of course use both ‹Object› and actual arguments: expect mock.to.receive.a(Object, 2, Object) do |m| m.a nil, 2, '3' end The body of the expected method may be given as the block. Here, calling ‹#a› on ‹m› will give the result ‹1›: expect mock.to.receive.a{ 1 } do |m| raise 'not 1' unless m.a == 1 end If no body has been given, the result will be a stub object. To take a block, grab a block parameter and ‹#call› it: expect mock.to.receive.a{ |&b| b.call(1) } do |m| j = 0 m.a{ |i| j = i } raise 'not 1' unless j == 1 end To simulate an ‹#each›-like method, ‹#call› the block several times. Invocation count expectations can be set if the default expectation of “at least once” isn’t good enough. The following expectations are possible • ‹#at_most_once› • ‹#once› • ‹#at_least_once› • ‹#twice› And, for a given ‹N›, • ‹#at_most(N)› • ‹#exactly(N)› • ‹#at_least(N)› § Utilities: Stubs Method stubs are another useful thing to have in a unit testing framework. Sometimes you need to override a method that does something a test shouldn’t do, like access and alter bank accounts. We can override – stub out – a method by using the ‹#stub› method. Let’s assume that we have an ‹Account› class that has two methods, ‹#slips› and ‹#total›. ‹#Slips› retrieves the bank slips that keep track of your deposits to the ‹Account› from a database. ‹#Total› sums the ‹#slips›. In the following test we want to make sure that ‹#total› does what it should do without accessing the database. We therefore stub out ‹#slips› and make it return something that we can easily control. expect 6 do |m| stub(Class.new{ def slips raise 'database not available' end def total slips.reduce(0){ |m, n| m.to_i + n.to_i } end }.new, :slips => [1, 2, 3]){ |account| account.total } end To make it easy to create objects with a set of stubbed methods there’s also a convenience method: expect 3 do s = stub(:a => 1, :b => 2) s.a + s.b end This short-hand notation can also be used for the expected value: expect stub(:a => 1, :b => 2).to.receive.a do |o| o.a + o.b end and also works for mock objects: expect mock(:a => 2, :b => 2).to.receive.a do |o| o.a + o.b end Blocks are also allowed when defining stub methods: expect 3 do s = stub(:a => proc{ |a, b| a + b }) s.a(1, 2) end If need be, we can stub out a specific method on an object: expect 'def' do stub('abc', :to_str => 'def'){ |a| a.to_str } end The stub is active during the execution of the block. § Overriding Constants Sometimes you need to override the value of a constant during the execution of some code. Use ‹#with_const› to do just that: expect 'hello' do with_const 'A::B::C', 'hello' do A::B::C end end Here, the constant ‹A::B::C› is set to ‹'hello'› during the execution of the block. None of the constants ‹A›, ‹B›, and ‹C› need to exist for this to work. If a constant doesn’t exist it’s created and set to a new, empty, ‹Module›. The value of ‹A::B::C›, if any, is restored after the block returns and any constants that didn’t previously exist are removed. § Overriding Environment Variables Another thing you often need to control in your tests is the value of environment variables. Depending on such global values is, of course, not a good practice, but is often unavoidable when working with external libraries. ‹#With_env› allows you to override the value of environment variables during the execution of a block by giving it a ‹Hash› of key/value pairs where the key is the name of the environment variable and the value is the value that it should have during the execution of that block: expect 'hello' do with_env 'INTRO' => 'hello' do ENV['INTRO'] end end Any overridden values are restored and any keys that weren’t previously a part of the environment are removed when the block returns. § Overriding Globals You may also want to override the value of a global temporarily: expect 'hello' do with_global :$stdout, StringIO.new do print 'hello' $stdout.string end end You thus provide the name of the global and a value that it should take during the execution of a block of code. The block gets passed the overridden value, should you need it: expect true do with_global :$stdout, StringIO.new do |overridden| $stdout != overridden end end § Integration Lookout can be used from Rake¹. Simply install Lookout-Rake²: % gem install lookout-rake and add the following code to your Rakefile require 'lookout-rake-3.0' Lookout::Rake::Tasks::Test.new Make sure to read up on using Lookout-Rake for further benefits and customization. ¹ Read more about Rake at http://rake.rubyforge.org/ ² Get information on Lookout-Rake at http://disu.se/software/lookout-rake/ § API Lookout comes with an API¹ that let’s you create things such as new expected values, difference reports for your types, and so on. ¹ See http://disu.se/software/lookout/api/ § Interface Design The default output of Lookout can Spartanly be described as Spartan. If no errors or failures occur, no output is generated. This is unconventional, as unit testing frameworks tend to dump a lot of information on the user, concerning things such as progress, test count summaries, and flamboyantly colored text telling you that your tests passed. None of this output is needed. Your tests should run fast enough to not require progress reports. The lack of output provides you with the same amount of information as reporting success. Test count summaries are only useful if you’re worried that your tests aren’t being run, but if you worry about that, then providing such output doesn’t really help. Testing your tests requires something beyond reporting some arbitrary count that you would have to verify by hand anyway. When errors or failures do occur, however, the relevant information is output in a format that can easily be parsed by an ‹'errorformat'› for Vim or with {Compilation Mode}¹ for Emacs². Diffs are generated for Strings, Arrays, Hashes, and I/O. ¹ Read up on Compilation mode for Emacs at http://www.emacswiki.org/emacs/CompilationMode ² Visit The GNU Foundation’s Emacs’ software page at http://www.gnu.org/software/emacs/ § External Design Let’s now look at some of the points made in the introduction in greater detail. Lookout only allows you to set one expectation per test. If you’re testing behavior with a reception expectation, then only one method-invocation expectation can be set. If you’re testing state, then only one result can be verified. It may seem like this would cause unnecessary duplication between tests. While this is certainly a possibility, when you actually begin to try to avoid such duplication you find that you often do so by improving your interfaces. This kind of restriction tends to encourage the use of value objects, which are easy to test, and more focused objects, which require simpler tests, as they have less behavior to test, per method. By keeping your interfaces focused you’re also keeping your tests focused. Keeping your tests focused improves, in itself, test isolation, but let’s look at something that hinders it: setup and tear-down methods. Most unit testing frameworks encourage test fragmentation by providing setup and tear-down methods. Setup methods create objects and, perhaps, just their behavior for a set of tests. This means that you have to look in two places to figure out what’s being done in a test. This may work fine for few methods with simple set-ups, but makes things complicated when the number of tests increases and the set-up is complex. Often, each test further adjusts the previously set-up object before performing any verifications, further complicating the process of figuring out what state an object has in a given test. Tear-down methods clean up after tests, perhaps by removing records from a database or deleting files from the file-system. The duplication that setup methods and tear-down methods hope to remove is better avoided by improving your interfaces. This can be done by providing better set-up methods for your objects and using idioms such as {Resource Acquisition Is Initialization}¹ for guaranteed clean-up, test or no test. By not using setup and tear-down methods we keep everything pertinent to a test in the test itself, thus improving test isolation. (You also won’t {slow down your tests}² by keeping unnecessary state.) Most unit test frameworks also allow you to create arbitrary test helper methods. Lookout doesn’t. The same rationale as that that has been crystallized in the preceding paragraphs applies. If you need helpers you’re interface isn’t good enough. It really is as simple as that. To clarify: there’s nothing inherently wrong with test helper methods, but they should be general enough that they reside in their own library. The support for mocks in Lookout is provided through a set of test helper methods that make it easier to create mocks than it would have been without them. Lookout-rack³ is another example of a library providing test helper methods (well, one method, actually) that are very useful in testing web applications that use Rack⁴. A final point at which some unit test frameworks try to fragment tests further is documentation. These frameworks provide ways of describing the whats and hows of what’s being tested, the rationale being that this will provide documentation of both the test and the code being tested. Describing how a stack data structure is meant to work is a common example. A stack is, however, a rather simple data structure, so such a description provides little, if any, additional information that can’t be extracted from the implementation and its tests themselves. The implementation and its tests is, in fact, its own best documentation. Taking the points made in the previous paragraphs into account, we should already have simple, self-describing, interfaces that have easily understood tests associated with them. Rationales for the use of a given data structure or system-design design documentation is better suited in separate documentation focused at describing exactly those issues. ¹ Read the Wikipedia entry for Resource Acquisition Is Initialization at http://en.wikipedia.org/wiki/Resource_Acquisition_Is_Initialization ² Read how 37signals had problems with slow Test::Unit tests at http://37signals.com/svn/posts/2742-the-road-to-faster-tests/ ³ Visit the Lookout-rack home page at http://disu.se/software/lookout-rack/ ⁴ Visit the Rack Rubyforge project page at http://rack.rubyforge.org/ § Internal Design The internal design of Lookout has had a couple of goals. • As few external dependencies as possible • As few internal dependencies as possible • Internal extensibility provides external extensibility • As fast load times as possible • As high a ratio of value objects to mutable objects as possible • Each object must have a simple, obvious name • Use mix-ins, not inheritance for shared behavior • As few responsibilities per object as possible • Optimizing for speed can only be done when you have all the facts § External Dependencies Lookout used to depend on Mocha for mocks and stubs. While benchmarking I noticed that a method in Mocha was taking up more than 300 percent of the runtime. It turned out that Mocha’s method for cleaning up back-traces generated when a mock failed was doing something incredibly stupid: backtrace.reject{ |l| Regexp.new(@lib).match(File.expand_path(l)) } Here ‹@lib› is a ‹String› containing the path to the lib sub-directory in the Mocha installation directory. I reported it, provided a patch five days later, then waited. Nothing happened. {254 days later}¹, according to {Wolfram Alpha}², half of my patch was, apparently – I say “apparently”, as I received no notification – applied. By that time I had replaced the whole mocking-and-stubbing subsystem and dropped the dependency. Many Ruby developers claim that Ruby and its gems are too fast-moving for normal package-managing systems to keep up. This is testament to the fact that this isn’t the case and that the real problem is instead related to sloppy practices. Please note that I don’t want to single out the Mocha library nor its developers. I only want to provide an example where relying on external dependencies can be “considered harmful”. ¹ See the Wolfram Alpha calculation at http://www.wolframalpha.com/input/?i=days+between+march+17%2C+2010+and+november+26%2C+2010 ² Check out the Wolfram Alpha computational knowledge engine at http://www.wolframalpha.com/ § Internal Dependencies Lookout has been designed so as to keep each subsystem independent of any other. The diff subsystem is, for example, completely decoupled from any other part of the system as a whole and could be moved into its own library at a time where that would be of interest to anyone. What’s perhaps more interesting is that the diff subsystem is itself very modular. The data passes through a set of filters that depends on what kind of diff has been requested, each filter yielding modified data as it receives it. If you want to read some rather functional Ruby I can highly recommend looking at the code in the ‹lib/lookout/diff› directory. This lookout on the design of the library also makes it easy to extend Lookout. Lookout-rack was, for example, written in about four hours and about 5 of those 240 minutes were spent on setting up the interface between the two. § Optimizing For Speed The following paragraph is perhaps a bit personal, but might be interesting nonetheless. I’ve always worried about speed. The original Expectations library used ‹extend› a lot to add new behavior to objects. Expectations, for example, used to hold the result of their execution (what we now term “evaluation”) by being extended by a module representing success, failure, or error. For the longest time I used this same method, worrying about the increased performance cost that creating new objects for results would incur. I finally came to a point where I felt that the code was so simple and clean that rewriting this part of the code for a benchmark wouldn’t take more than perhaps ten minutes. Well, ten minutes later I had my results and they confirmed that creating new objects wasn’t harming performance. I was very pleased. § Naming I hate low lines (underscores). I try to avoid them in method names and I always avoid them in file names. Since the current “best practice” in the Ruby community is to put ‹BeginEndStorage› in a file called ‹begin_end_storage.rb›, I only name constants using a single noun. This has had the added benefit that classes seem to have acquired less behavior, as using a single noun doesn’t allow you to tack on additional behavior without questioning if it’s really appropriate to do so, given the rather limited range of interpretation for that noun. It also seems to encourage the creation of value objects, as something named ‹Range› feels a lot more like a value than ‹BeginEndStorage›. (To reach object-oriented-programming Nirvana you must achieve complete value.) § News § 3.0.0 The ‹xml› expectation has been dropped. It wasn’t documented, didn’t suit very many use cases, and can be better implemented by an external library. The ‹arg› argument matcher for mock method arguments has been removed, as it didn’t provide any benefit over using Object. The ‹#yield› and ‹#each› methods on stub and mock methods have been removed. They were slightly weird and their use case can be implemented using block parameters instead. The ‹stub› method inside ‹expect› blocks now stubs out the methods during the execution of a provided block instead of during the execution of the whole except block. When a mock method is called too many times, this is reported immediately, with a full backtrace. This makes it easier to pin down what’s wrong with the code. Query expectations were added. Explicit query expectations were added. Fluent boolean expectations, for example, ‹expect nil.to.be.nil?› have been replaced by query expectations (‹expect :nil? do nil end›) and explicit query expectations (‹expect result.to.be.nil? do nil end›). This was done to discourage creating objects as the expected value and creating objects that change during the course of the test. The ‹literal› expectation was added. Equality (‹#==›) is now checked before “caseity” (‹#===›) for modules, ranges, and regular expressions to match the documentation. § Financing Currently, most of my time is spent at my day job and in my rather busy private life. Please motivate me to spend time on this piece of software by donating some of your money to this project. Yeah, I realize that requesting money to develop software is a bit, well, capitalistic of me. But please realize that I live in a capitalistic society and I need money to have other people give me the things that I need to continue living under the rules of said society. So, if you feel that this piece of software has helped you out enough to warrant a reward, please PayPal a donation to now@disu.se¹. Thanks! Your support won’t go unnoticed! ¹ Send a donation: https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=now%40disu%2ese&item_name=Lookout § Reporting Bugs Please report any bugs that you encounter to the {issue tracker}¹. ¹ See https://github.com/now/lookout/issues § Contributors Contributors to the original expectations codebase are mentioned there. We hope no one on that list feels left out of this list. Please {let us know}¹ if you do. • Nikolai Weibull ¹ Add an issue to the Lookout issue tracker at https://github.com/now/lookout/issues § Licensing Lookout is free software: you may redistribute it and/or modify it under the terms of the {GNU Lesser General Public License, version 3}¹ or later², as published by the {Free Software Foundation}³. ¹ See http://disu.se/licenses/lgpl-3.0/ ² See http://gnu.org/licenses/ ³ See http://fsf.org/

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