TimeDifference is the missing Ruby method to calculate difference between two given time. You can do a Ruby time difference in year, month, week, day, hour, minute, and seconds.

Calculate the difference in time relative to now. Returns readable metrics (e.g. years_ago, days_ago, etc.)

A Rails gem that provides helper methods to display time differences in a human-readable format (e.g., '2 hours ago', '3 days later'). Features include auto-updating timestamps every minute without page reload, no JavaScript imports required, and seamless integration with Rails views. Supports various time units from seconds to years.

PORO to hold a monotonic tick count. Useful for measuring time differences.

A script to check a given Consul key EPOCH for freshness. Good for monitoring cron jobs or batch jobs. Have the last step of the job post the EPOCH time to target Consul key. This script will monitor it for a given freshness value (difference in time now to posted EPOCH)

Profile web applications by noting differences in response times based on input values

Handles time differences.

Making time difference calculations fun

Calculates time difference within 24 hour limit.

Thes gem calculate the difference between two date time values. The output depends on the input given.

It returns a hash file with the difference in terms of year, month, week, day, hour, minute and second

Solves a quirk of rspec --profile in some code bases: result vary with every random spec ordering. This seems to be due to differences in dependency load order, class initialization, and test server startup. This lib runs rspec --profile many times, averaging the results to always give the same (stable) and meaningful result.

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.

A class that wraps the Time class and makes it easy to work with most known time values, including various time strings, automatically converting them to Time values, and perform tolerant comparisons. Several time classes, and the String class, are extended with the ".easy_time" method to perform an auto-conversion. A tolerant comparison allows for times from differing systems to be compared, even when the systems are out of sync, using the relationship operators and methods like "newer?", "older?", "same?" and "between?". A tolerant comparison for equality is where the difference of two values is less than the tolerance value (1 minute by default). The tolerance can be configured, even set to zero. Finally, all of the Time class and instance methods are available on the EasyTime class and instances.

VectorNumber provides a Numeric-like experience for doing arithmetics on heterogeneous objects, with more advanced operations based on real vector spaces available when needed. Features: - Add and subtract (almost) any object, with no setup or declaration. - Multiply and divide vectors by any real number to create 1.35 of an array and -2 of a string. What does that mean? Only you know! - Use vectors instead of inbuilt numbers in most situtations with no difference in behavior. Or, use familiar methods from numerics with sane semantics! - Enumerate vectors in a hash-like fashion, or transform to an array or hash as needed. - Enjoy a mix of vector-, complex- and polynomial-like behavior at appropriate times. - No dependencies, no extensions. It just works!

== ICU4R - ICU Unicode bindings for Ruby ICU4R is an attempt to provide better Unicode support for Ruby, where it lacks for a long time. Current code is mostly rewritten string.c from Ruby 1.8.3. ICU4R is Ruby C-extension binding for ICU library[1] and provides following classes and functionality: * UString: - String-like class with internal UTF16 storage; - UCA rules for UString comparisons (<=>, casecmp); - encoding(codepage) conversion; \ - Unicode normalization; - transliteration, also rule-based; Bunch of locale-sensitive functions: - upcase/downcase; - string collation; \ - string search; - iterators over text line/word/char/sentence breaks; \ - message formatting (number/currency/string/time); - date and number parsing. * URegexp - unicode regular expressions. * UResourceBundle - access to resource bundles, including ICU locale data. * UCalendar - date manipulation and timezone info. * UConverter - codepage conversions API * UCollator - locale-sensitive string comparison == Install and usage > ruby extconf.rb > make && make check > make install Now, in your scripts just require 'icu4r'. To create RDoc, run > sh tools/doc.sh == Requirements To build and use ICU4R you will need GCC and ICU v3.4 libraries[2]. == Differences from Ruby String and Regexp classes === UString vs String 1. UString substring/index methods use UTF16 codeunit indexes, not code points. 2. UString supports most methods from String class. Missing methods are: capitalize, capitalize!, swapcase, swapcase! %, center, ljust, rjust chomp, chomp!, chop, chop! \ count, delete, delete!, squeeze, squeeze!, tr, tr!, tr_s, tr_s! crypt, intern, sum, unpack dump, each_byte, each_line hex, oct, to_i, to_sym reverse, reverse! succ, succ!, next, next!, upto 3. Instead of String#% method, UString#format is provided. See FORMATTING for short reference. 4. UStrings can be created via String.to_u(encoding='utf8') or global u(str,[encoding='utf8']) calls. Note that +encoding+ parameter must be value of String class. 5. There's difference between character grapheme, codepoint and codeunit. See UNICODE reports for gory details, but in short: locale dependent notion of character can be presented using more than one codepoint - base letter and combining (accents) (also possible more than one!), and each codepoint can require more than one codeunit to store (for UTF8 codeunit size is 8bit, though \ some codepoints require up to 4bytes). So, UString has normalization and locale dependent break iterators. 6. Currently UString doesn't include Enumerable module. 7. UString index/[] methods which accept URegexp, throw exception if Regexp passed. 8. UString#<=>, UString#casecmp use UCA rules. === URegexp UString uses ICU regexp library. Pattern syntax is described in [./docs/UNICODE_REGEXPS] and ICU docs. There are some differences between processing in Ruby Regexp and URegexp: 1. When UString#sub, UString#gsub are called with block, special vars ($~, $&, $1, ...) aren't set, as their values are processed through deep ruby core code. Instead, block receives UMatch object, which is essentially immutable array of matching groups: "test".u.gsub(ure("(e)(.)")) do |match| \ puts match[0] # => 'es' <--> $& puts match[1] # => 'e' \ <--> $1 puts match[2] # => 's' <--> $2 end 2. In URegexp search pattern backreferences are in form \n (\1, \2, ...), in replacement string - in form $1, $2, ... NOTE: URegexp considers char to be a digit NOT ONLY ASCII (0x0030-0x0039), but any Unicode char, which has property Decimal digit number (Nd), e.g.: a = [?$, 0x1D7D9].pack("U*").u * 2 puts a.inspect_names <U000024>DOLLAR SIGN <U01D7D9>MATHEMATICAL DOUBLE-STRUCK DIGIT ONE <U000024>DOLLAR SIGN <U01D7D9>MATHEMATICAL DOUBLE-STRUCK DIGIT ONE puts "abracadabra".u.gsub(/(b)/.U, a) abbracadabbra \ 3. One can create URegexp using global Kernel#ure function, Regexp#U, Regexp#to_u, or from UString using URegexp.new, e.g: /pattern/.U =~ "string".u 4. There are differences about Regexp and URegexp multiline matching options: t = "text\ntest" # ^,$ handling : URegexp multiline <-> Ruby default t.u =~ ure('^\w+$', URegexp::MULTILINE) => #<UMatch:0xf6f7de04 @ranges=[0..3], @cg=[\u0074\u0065\u0078\u0074]> t =~ /^\w+$/ => 0 # . matches \n : URegexp DOTALL <-> /m t.u =~ ure('.+test', URegexp::DOTALL) \ => #<UMatch:0xf6fa4d88 ... t.u =~ /.+test/m 5. UMatch.range(idx) returns range for capturing group idx. This range is in codeunits. === References 1. ICU Official Homepage http://ibm.com/software/globalization/icu/ 2. ICU downloads \ http://ibm.com/software/globalization/icu/downloads.jsp 3. ICU Home Page http://icu.sf.net 4. Unicode Home Page http://www.unicode.org ==== BUGS, DOCS, TO DO The code is slow and inefficient yet, is still highly experimental, so can have many security and memory leaks, bugs, inconsistent documentation, incomplete test suite. Use it at your own risk. Bug reports and feature requests are welcome :) === Copying This extension module is copyrighted free software by Nikolai Lugovoi. You can redistribute it and/or modify it under the terms of MIT License. Nikolai Lugovoi <meadow.nnick@gmail.com>

Deliver all master files managed in a single master snapshot directory into the specified directory while maintaining the hierarchy of the master snapshot directory. If the destination file already exists, back it up first and then deliver the master file. The difference with rsync is that master_delivery creates a symlinks instead of copying the master files. They are symlinks, so you have to keep in mind that you have to keep the master files in the same location, but it also has the advantage that the master file is updated at the same time when you directly make changes to the delivered file. Do you have any experience that the master file is getting old gradually? master_delivery can prevent this. If the master directory is git or svn managed, you can manage revisions of files that are delivered here and there at once with commands like git diff and git commit.

The affixapi.com API documentation. # Introduction Affix API is an OAuth 2.1 application that allows developers to access customer data, without developers needing to manage or maintain integrations; or collect login credentials or API keys from users for these third party systems. # OAuth 2.1 Affix API follows the [OAuth 2.1 spec](https://datatracker.ietf.org/doc/html/draft-ietf-oauth-v2-1-08). As an OAuth application, Affix API handles not only both the collection of sensitive user credentials or API keys, but also builds and maintains the integrations with the providers, so you don't have to. # How to obtain an access token in order to get started, you must: - register a `client_id` - direct your user to the sign in flow (`https://connect.affixapi.com` [with the appropriate query parameters](https://github.com/affixapi/starter-kit/tree/master/connect)) - capture `authorization_code` we will send to your redirect URI after the sign in flow is complete and exchange that `authorization_code` for a Bearer token # Sandbox keys (developer mode) ### dev ``` eyJhbGciOiJFUzI1NiIsImtpZCI6Ims5RmxwSFR1YklmZWNsUU5QRVZzeFcxazFZZ0Zfbk1BWllOSGVuOFQxdGciLCJ0eXAiOiJKV1MifQ.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.VLWYjCQvBS0C3ZA6_J3-U-idZj5EYI2IlDdTjAWBxSIHGufp6cqaVodKsF2BeIqcIeB3P0lW-KL9mY3xGd7ckQ ``` #### `employees` endpoint sample: ``` curl --fail \ -X GET \ -H 'Authorization: Bearer eyJhbGciOiJFUzI1NiIsImtpZCI6Ims5RmxwSFR1YklmZWNsUU5QRVZzeFcxazFZZ0Zfbk1BWllOSGVuOFQxdGciLCJ0eXAiOiJKV1MifQ.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.VLWYjCQvBS0C3ZA6_J3-U-idZj5EYI2IlDdTjAWBxSIHGufp6cqaVodKsF2BeIqcIeB3P0lW-KL9mY3xGd7ckQ' \ 'https://dev.api.affixapi.com/2023-03-01/developer/employees' ``` ### prod ``` eyJhbGciOiJFUzI1NiIsImtpZCI6Ims5RmxwSFR1YklmZWNsUU5QRVZzeFcxazFZZ0Zfbk1BWllOSGVuOFQxdGciLCJ0eXAiOiJKV1MifQ.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.2zdpFAmiyYiYk6MOcbXNUwwR4M1Fextnaac340x54AidiWXCyw-u9KeavbqfYF6q8a9kcDLrxhJ8Wc_3tIzuVw ``` #### `employees` endpoint sample: ``` curl --fail \ -X GET \ -H 'Authorization: Bearer eyJhbGciOiJFUzI1NiIsImtpZCI6Ims5RmxwSFR1YklmZWNsUU5QRVZzeFcxazFZZ0Zfbk1BWllOSGVuOFQxdGciLCJ0eXAiOiJKV1MifQ.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.2zdpFAmiyYiYk6MOcbXNUwwR4M1Fextnaac340x54AidiWXCyw-u9KeavbqfYF6q8a9kcDLrxhJ8Wc_3tIzuVw' \ 'https://api.affixapi.com/2023-03-01/developer/employees' ``` # Webhooks An exciting feature for HR/Payroll modes are webhooks. If enabled, your `webhook_uri` is set on your `client_id` for the respective environment: `dev | prod` Webhooks are configured to make live requests to the underlying integration 1x/hr, and if a difference is detected since the last request, we will send a request to your `webhook_uri` with this shape: ``` { added: <api.v20230301.Employees>[ <api.v20230301.Employee>{ ..., date_of_birth: '2010-08-06', display_full_name: 'Daija Rogahn', employee_number: '57993', employment_status: 'pending', employment_type: 'other', employments: [ { currency: 'eur', effective_date: '2022-02-25', employment_type: 'other', job_title: 'Dynamic Implementation Manager', pay_frequency: 'semimonthly', pay_period: 'YEAR', pay_rate: 96000, }, ], first_name: 'Daija', ... } ], removed: [], updated: [ <api.v20230301.Employee>{ ..., date_of_birth: '2009-11-09', display_full_name: 'Lourdes Stiedemann', employee_number: '63189', employment_status: 'leave', employment_type: 'full_time', employments: [ { currency: 'gbp', effective_date: '2023-01-16', employment_type: 'full_time', job_title: 'Forward Brand Planner', pay_frequency: 'semimonthly', pay_period: 'YEAR', pay_rate: 86000, }, ], first_name: 'Lourdes', } ] } ``` the following headers will be sent with webhook requests: ``` x-affix-api-signature: ab8474e609db95d5df3adc39ea3add7a7544bd215c5c520a30a650ae93a2fba7 x-affix-api-origin: webhooks-employees-webhook user-agent: affixapi.com ``` Before trusting the payload, you should sign the payload and verify the signature matches the signature sent by the `affixapi.com` service. This secures that the data sent to your `webhook_uri` is from the `affixapi.com` server. The signature is created by combining the signing secret (your `client_secret`) with the body of the request sent using a standard HMAC-SHA256 keyed hash. The signature can be created via: - create an `HMAC` with your `client_secret` - update the `HMAC` with the payload - get the hex digest -> this is the signature Sample `typescript` code that follows this recipe: ``` import { createHmac } from 'crypto'; export const computeSignature = ({ str, signingSecret, }: { signingSecret: string; str: string; }): string => { const hmac = createHmac('sha256', signingSecret); hmac.update(str); const signature = hmac.digest('hex'); return signature; }; ``` ## Rate limits Open endpoints (not gated by an API key) (applied at endpoint level): - 15 requests every 1 minute (by IP address) - 25 requests every 5 minutes (by IP address) Gated endpoints (require an API key) (applied at endpoint level): - 40 requests every 1 minute (by IP address) - 40 requests every 5 minutes (by `client_id`) Things to keep in mind: - Open endpoints (not gated by an API key) will likely be called by your users, not you, so rate limits generally would not apply to you. - As a developer, rate limits are applied at the endpoint granularity. - For example, say the rate limits below are 10 requests per minute by ip. from that same ip, within 1 minute, you get: - 10 requests per minute on `/orders`, - another 10 requests per minute on `/items`, - and another 10 requests per minute on `/identity`, - for a total of 30 requests per minute.

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/

Inventory Inventory keeps track of the contents of your Ruby¹ projects. Such an inventory can be used to load the project, create gem specifications and gems, run unit tests, compile extensions, and verify that the project’s content is what you think it is. ¹ See http://ruby-lang.org/ § Usage Let’s begin by discussing the project structure that Inventory expects you to use. It’s pretty much exactly the same as the standard Ruby project structure¹: ├── README ├── Rakefile ├── lib │ ├── foo-1.0 │ │ ├── bar.rb │ │ └── version.rb │ └── foo-1.0.rb └── test └── unit ├── foo-1.0 │ ├── bar.rb │ └── version.rb └── foo-1.0.rb Here you see a simplified version of a project called “Foo”’s project structure. The only real difference from the standard is that the main entry point into the library is named “foo-1.0.rb” instead of “foo.rb” and that the root sub-directory of “lib” is similarly named “foo-1.0” instead of “foo”. The difference is the inclusion of the API version. This must be the major version of the project followed by a constant “.0”. The reason for this is that it allows concurrent installations of different major versions of the project and means that the wrong version will never accidentally be loaded with require. There’s a bigger difference in the content of the files. ‹Lib/foo-1.0/version.rb› will contain our inventory instead of a String: require 'inventory-1.0' class Foo Version = Foo.new(1, 4, 0){ authors{ author 'A. U. Thor', 'a.u.thor@example.org' } homepage 'http://example.org/' licenses{ license 'LGPLv3+', 'GNU Lesser General Public License, version 3 or later', 'http://www.gnu.org/licenses/' } def dependencies super + Dependencies.new{ development 'baz', 1, 3, 0 runtime 'goo', 2, 0, 0 optional 'roo-loo', 3, 0, 0, :feature =&gt; 'roo-loo' } end def package_libs %w[bar.rb] end } end We’re introducing quite a few concepts at once, and we’ll look into each in greater detail, but we begin by setting the ‹Version› constant to a new instance of an Inventory with major, minor, and patch version atoms 1, 4, and 0. Then we add a couple of dependencies and list the library files that are included in this project. The version numbers shouldn’t come as a surprise. These track the version of the API that we’re shipping using {semantic versioning}². They also allow the Inventory#to_s method to act as if you’d defined Version as ‹'1.4.0'›. Next follows information about the authors of the project, the project’s homepage, and the project’s licenses. Each author has a name and an email address. The homepage is simply a string URL. Licenses have an abbreviation, a name, and a URL where the license text can be found. We then extend the definition of ‹dependencies› by adding another set of dependencies to ‹super›. ‹Super› includes a dependency on the version of the inventory project that’s being used with this project, so you’ll never have to list that yourself. The other three dependencies are all of different kinds: development, runtime, and optional. A development dependency is one that’s required while developing the project, for example, a unit-testing framework, a documentation generator, and so on. Runtime dependencies are requirements of the project to be able to run, both during development and when installed. Finally, optional dependencies are runtime dependencies that may or may not be required during execution. The difference between runtime and optional is that the inventory won’t try to automatically load an optional dependency, instead leaving that up to you to do when and if it becomes necessary. By that logic, runtime dependencies will be automatically loaded, which is a good reason for having dependency information available at runtime. The version numbers of dependencies also use semantic versioning, but note that the patch atom is ignored unless the major atom is 0. You should always only depend on the major and minor atoms. As mentioned, runtime dependencies will be automatically loaded and the feature they try to load is based on the name of the dependency with a “-X.0” tacked on the end, where ‘X’ is the major version of the dependency. Sometimes, this isn’t correct, in which case the :feature option may be given to specify the name of the feature. You may also override other parts of a dependency by passing in a block to the dependency, much like we’re doing for inventories. The rest of an inventory will list the various files included in the project. This project only consists of one additional file to those that an inventory automatically include (Rakefile, README, the main entry point, and the version.rb file that defines the inventory itself), namely the library file ‹bar.rb›. Library files will be loaded automatically when the main entry point file loads the inventory. Library files that shouldn’t be loaded may be listed under a different heading, namely “additional_libs”. Both these sets of files will be used to generate a list of unit test files automatically, so each library file will have a corresponding unit test file in the inventory. We’ll discuss the different headings of an inventory in more detail later on. Now that we’ve written our inventory, let’s set it up so that it’s content gets loaded when our main entry point gets loaded. We add the following piece of code to ‹lib/foo-1.0.rb›: module Foo load File.expand_path('../foo-1.0/version.rb', __FILE__) Version.load end That’s all there’s to it. The inventory can also be used to great effect from a Rakefile using a separate project called Inventory-Rake³. Using it’ll give us tasks for cleaning up our project, compiling extensions, installing dependencies, installing and uninstalling the project itself, and creating and pushing distribution files to distribution points. require 'inventory-rake-1.0' load File.expand_path('../lib/foo-1.0/version.rb', __FILE__) Inventory::Rake::Tasks.define Foo::Version Inventory::Rake::Tasks.unless_installing_dependencies do require 'lookout-rake-3.0' Lookout::Rake::Tasks::Test.new end It’s ‹Inventory::Rake::Tasks.define› that does the heavy lifting. It takes our inventory and sets up the tasks mentioned above. As we want to be able to use our Rakefile to install our dependencies for us, the rest of the Rakefile is inside the conditional #unless_installing_dependencies, which, as the name certainly implies, executes its block unless the task being run is the one that installs our dependencies. This becomes relevant when we set up Travis⁴ integration next. The only conditional set-up we do in our Rakefile is creating our test task via Lookout-Rake⁵, which also uses our inventory to find the unit tests to run when executed. Travis integration is straightforward. Simply put before_script: - gem install inventory-rake -v '~&gt; VERSION' --no-rdoc --no-ri - rake gem:deps:install in the project’s ‹.travis.yml› file, replacing ‹VERSION› with the version of Inventory-Rake that you require. This’ll make sure that Travis installs all development, runtime, and optional dependencies that you’ve listed in your inventory before running any tests. You might also need to put env: - RUBYOPT=rubygems in your ‹.travis.yml› file, depending on how things are set up. ¹ Ruby project structure: http://guides.rubygems.org/make-your-own-gem/ ² Semantic versioning: http://semver.org/ ³ Inventory-Rake: http://disu.se/software/inventory-rake-1.0/ ⁴ Travis: http://travis-ci.org/ ⁵ Lookout-Rake: http://disu.se/software/lookout-rake-3.0/ § API If the guide above doesn’t provide you with all the answers you seek, you may refer to the API¹ for more answers. ¹ See http://disu.se/software/inventory-1.0/api/Inventory/ § 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&amp;business=now@disu.se&amp;item_name=Inventory § Reporting Bugs Please report any bugs that you encounter to the {issue tracker}¹. ¹ See https://github.com/now/inventory/issues § Authors Nikolai Weibull wrote the code, the tests, the documentation, and this README. § Licensing Inventory 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/