RbPath provides a simple query language for deep Ruby data structures. Similar to XPath and CSS selectors.
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README.md

RbPath

RbPath is a small library for finding and retrieving data in large Ruby collections (Arrays/Hashes) and object graphs, similar to XPath and CSS selectors. You might use it over XPath or something similar because it's super lightweight and may do exactly what you need without the complex semantics of XPath or CSS selectors. It also makes operations such as regular expression filtering much easier to use.

Table of contents

Installation

Add this line to your application's Gemfile:

gem 'rbpath'

And then execute:

$ bundle

Or install it yourself as:

$ gem install rbpath

Usage

Direct

You can use the query engine directly through the Query class.

require 'rbpath'

h = {...}

RbPath::Query.new(...).query(h)

Object Mixin

You can add the query interface to an existing instance of a Hash or Array.

require 'rbpath'

h = {...}
h.extend RbPath

h.query(...)

Class Mixin

You can make your own objects queryable by using the RbPath mixin.

require 'rbpath'

class Person < Struct.new(:first, :middle, :last, :age, :relatives)
  include RbPath

  rbpath :first, :middle, :last, :age, :relatives
end

p = Person.new('john', 'michael', 'doe', 21, [relative1,...])

p.query(...)

Notice that the rbpath attributes must be explicitly listed.

Queries

Queries are similar to XPath expressions. They are used to navigate and find information in tree-like data structures.

class Employee < Struct.new(:first, :last, :position)
  include RbPath
  rbpath :first, :last, :position
end

data = {
  illinois: {
    chicago: {
      inventory: {
        bakery: { white: 220, whole_wheat: 150, multigrain: 72, rye: 27 },
        fish:   { salmon: 110, tuna: 115, flounder: 22, catfish: 90, cod: 15 },
        meat:   { ribeye: 23, pork_chop: 19, pork_loin: 12, beef_brisket: 30 }},
      employees: [
        Employee.new("John", "Sansk",   "General Manager"),
        Employee.new("Gene", "Pollack", "Warehouse Manager"),
        Employee.new("Luke", "Sanders", "Director")],
      address: '101 Big St',
      services: [:pharmacy, :bakery, :groceries, :kids_corner, :pet_grooming]
    },
    springfield: {
      inventory: {
        fish:   { salmon: 101, trout: 97, snapper: 172, catfish: 17, cod: 93 },
        meat:   { ribeye: 13, chuck_roast: 82, flank_steak: 73, beef_brisket: 30 }},
      employees: [
        Employee.new("Kerry",  "Adams",  "General Manager"),
        Employee.new("Sherry", "Nerst",  "Warehouse Manager"),
        Employee.new("Kate",   "Holmes", "Director")],
      address: '220 Small St',
      services: [:groceries, :kids_corner]
    }
  }
}

data.extend RbPath

The sample data above represents a chain of grocery stores and their employees. We will see how RbPath can extract useful information from this set of data.

Literals

The result of a query call will always be a list values that satisfy it, or an empty list if no matching values were found. There is also an analagous pquery interface which, instead of returning the values themselves, will return the paths to the values (or an empty list). Calling path_values on the result of pquery is the same as calling query directly.

To make the examples more concise, only results from the pquery call will be provided in later examples.

# Xpath: /illinois/chicago

> data.query("illinois chicago")
=> [{inventory: {...}, employees: [...], address: "...", services: [...]}]

> data.pquery("illinois chicago")
=> [['illinois','chicago']]

> data.path_values( data.pquery("illinois chicago") )
=> [{inventory: {...}, employees: [...], address: "...", services: [...]}]

# Xpath: /california/san_francisco

> data.query("california san_francisco")
=> []

> data.pquery("california san_francisco")
=> []

Notice that the elements are seperated by spaces instead of slashes, and rbpath queries are absolute by default.

Because the access semantics for Ruby collections (Arrays vs Hashes vs Objects) are inherently different, queries into Arrays will have numerical indices while queries into Hashes and RbPath objects will usually have string indices, much like in XPath.

# Xpath: /illinois/chicago/services[1]

> data.pquery("illinois chicago services 0")
=> [['illinois','chicago','services','0']]

Results to absolute queries aren't very interesting though, since they only return a single match. Other queries can return multiple matching paths.

Wildcards

The star in the query below represents a wildcard match. It allows us to match more than one value at a particular depth in the tree.

# XPath: /illinois/*/employees

> data.pquery("illinois * employees")
=> [['illinois','chicago','employees'],
      ['illinois','springfield','employees']]

Wildcards can also be span across multiple levels of the tree, in case you don't know how deep your value lives. These multi-level wildcards will reach across 0 or more depth levels.

# XPath: //illinois

> data.pquery("** illinois")
=> [['illinois']]

# XPath: //employees

> data.pquery("** employees")
=> [['illinois','employees'],
      ['illinois','chicago','employees'],
      ['illinois','springfield','employees']]

Notice that paths of differnt lengths may be returned in the resulting set when using multi-level wildcards.

Logic Expressions

In addiction to wildcards, there is another, more restrictive, way to match several paths at once using AND and NOR expressions.

# XPath: /illinois/chicago/inventory/*/salmon | /illinois/chicago/inventory/*/pork_chop

> data.pquery("illinois chicago inventory * (salmon,pork_chop)")
=> [['illinois','chicago','inventory','fish','salmon'],
      ['illinois','chicago','inventory','meat','pork_chop']]

The above query will select all the inventory paths in the chicago store that match 'salmon' AND 'pork_chop' for any of the departments. We can also achieve the opposite effect by using a NOR expression and specifying a list of values to avoid matching.

# XPath: /illinois/chicago/inventory/fish[not(contains(salmon)) and not(contains(tuna))]

> data.pquery("illinois chicago inventory fish [salmon,tuna]")
=> [['illinois','chicago','inventory','fish','flounder'],
      ['illinois','chicago','inventory','fish','catfish'],
      ['illinois','chicago','inventory','fish','cod']]

This query gives us all the fish in the chicago store which do not match 'salmon' or 'tuna'.

Regex Matching

It's not always enough to be able to filter on an exact field/key name. Sometimes you only know part of the name or you want to match all the names that match a certain pattern. This is where regular expressions come in handy.

You can include plain old ruby regexes in your quries by splitting the query up into multiple arguments. In this case the query will will still be processed as though it was continuous.

> data.pquery("illinois chicago inventory meat", /(pork.*|beef.*)/)
=> [['illinois','chicago','inventory','meat','pork_chop'],
      ['illinois','chicago','inventory','meat','pork_loin'],
      ['illinois','chicago','inventory','meat','beef_brisket']]

> data.pquery("illinois", /(chi.*|spr.*)/, "inventory *")
=> [['illinois','chicago','inventory','bakery'],
      ['illinois','chicago','inventory','fish'],
      ['illinois','chicago','inventory','meat'],
      ['illinois','springfield','inventory','fish'],
      ['illinois','springfield','inventory','meat']]

XPath 1.0 doesn't actually support regular expressions, but it does provide some specialized functions for partially matching element names such as starts-with() and contains().

Gotchas

Sometimes you may need to find strings with spaces or things which are not strings at all. Here is how you do that.

Single quote your string or use a regex matcher when your filter string contains spaces.

> data.pquery("* * employees * position 'General Manager'")
=> [['illinois','chicago','employees','0','position','General Manager'],
      ['illinois','chicago','employees','0','position','General Manager']]

> data.pquery("* * employees 0 position", /General Manager/)
=> [['illinois','chicago','employees','0','position','General Manager'],
      ['illinois','chicago','employees','0','position','General Manager']]

Split up queries that use non-String filters into multiple arguments, just like we did with regular expressions.

> data.pquery("* * inventory * *", 30)
=> [['illinois','chicago','inventory','meat','beef_brisket',30],
      ['illinois','springfield','inventory','meat','beef_brisket',30]]

Working With JSON/YAML/XML

You can use the rq command (which is installed with the gem) from your shell to query JSON, YAML and XML files using the RbPath engine, but you will not be able to match regular expressions or non-string values due to the limitations of the query parser.

Usage: rq [OPTIONS] QUERY
    -f, --file  [FILE]       File to parse
    -t, --type  [TYPE]       File format
    -p, --paths              Paths only
    -h, --help               Show usage
  • If you don't supply the file option then data will be read from STDIN.
  • The paths option will mimic the pquery interface shown in the examples.
# read from a file
$ rq -f data.json '** john **'

# read from STDIN
$ curl http://myservice.com/api/1.json | rq -t json '** john **'

XML

The xml-simple gem is used to convert xml files to Ruby hashes prior to processing, so it must be installed if you want to query XML files.

gem install xml-simple

Pretty Printer

Installing the hirb gem will tabularize certain types of output, making it much easier to read.

gem install hirb

Contributing

  1. Fork it
  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 new Pull Request