File: README.txt

# README.txt

Path: | README.txt
Last Update: | Mon Aug 09 19:43:50 -0600 2010

# Quick Links

- Setup and Configuration - DataMapper
- Finders and CRUD -
- Properties - DataMapper::Property
- FAQ
- Contact Us
  - Website - www.datamapper.org
  - Bug Reports - datamapper.lighthouseapp.com
  - IRC Channel - `#datamapper` on irc.freenode.net
  - Mailing List - groups.google.com/group/datamapper/

# Why DataMapper?

## Open Development

DataMapper sports a very accessible code-base and a welcoming community. Outside contributions and feedback are welcome and encouraged, especially constructive criticism. Make your voice heard! Submit a ticket or patch, speak up on our mailing-list, chat with us on irc, write a spec, get it reviewed, ask for commit rights. It‘s as easy as that to become a contributor.

## Identity Map

One row in the data-store should equal one object reference. Pretty simple idea. Pretty profound impact. If you run the following code in ActiveRecord you‘ll see all `false` results. Do the same in DataMapper and it‘s `true` all the way down.

      repository do
        @parent = Tree.first(:name => 'bob')

        @parent.children.each do |child|
          puts @parent.equal?(child.parent)  # => true
        end
      end

This makes DataMapper faster and allocate less resources to get things done.

## Dirty Tracking

When you save a model back to your data-store, DataMapper will only write the fields that actually changed. So it plays well with others. You can use it in an Integration data-store without worrying that your application will be a bad actor causing trouble for all of your other processes.

## Eager Loading

Ready for something amazing? The following example executes only two queries regardless of how many rows the inner and outer queries return.

      repository do
        Zoo.all.each { |zoo| zoo.exhibits.to_a }
      end

Pretty impressive huh? The idea is that you aren‘t going to load a set of objects and use only an association in just one of them. This should hold up pretty well against a 99% rule. When you don‘t want it to work like this, just load the item you want in it‘s own set. So the DataMapper thinks ahead. We like to call it "performant by default". This feature single-handedly wipes out the "N+1 Query Problem". No need to specify an `:include` option in your finders.

## Laziness Can Be A Virtue

Text fields are expensive in data-stores. They‘re generally stored in a different place than the rest of your data. So instead of a fast sequential read from your hard-drive, your data-store server has to hop around all over the place to get what it needs. Since ActiveRecord returns everything by default, adding a text field to a table slows everything down drastically, across the board.

Not so with the DataMapper. Text fields are lazily loaded, meaning they only load when you need them. If you want more control you can enable or disable this feature for any field (not just text-fields) by passing a @:lazy@ option to your field mapping with a value of `true` or `false`.

      class Animal
        include DataMapper::Resource

        property :name,  String
        property :notes, Text, :lazy => false
      end

Plus, lazy-loading of Text fields happens automatically and intelligently when working with associations. The following only issues 2 queries to load up all of the notes fields on each animal:

      repository do
        Animal.all.each { |animal| animal.notes.to_a }
      end

Did you notice the the `to_a` call in the above example? That was necessary because even DataMapper collections are lazy. If you don‘t iterate over them, or in this case ask them to become Arrays, they won‘t execute until you need them. We needed to call `to_a` to force the lazy load because without it, the above example would have only executed one query. This extra bit of laziness can come in very handy, for example:

      animals = Animal.all

      unless note.blank?
        animals.each do |animal|
          animal.update(:note => note)
        end
      end

In the above example, the Animals won‘t be retrieved until you actually need them. This comes in handy in cases where you initialize the collection before you know if you need it, like in a web app controller.

## Collection Chaining

DataMapper‘s lazy collections are also handy because you can get the same effect as named scopes, without any special syntax, eg:

      class Animal
        # ... setup ...

        def self.mammals
          all(:mammal => true)
        end

        def self.zoo(zoo)
          all(:zoo => zoo)
        end
      end

      zoo = Zoo.first(:name => 'Greater Vancouver Zoo')

      Animal.mammals.zoo(zoo).to_a  # => executes one query

In the above example, we ask the Animal model for all the mammals, and then all the animals in a specific zoo, and DataMapper will chain the collection queries together and execute a single query to retrieve the matching records. There‘s no special syntax, and no custom DSLs to learn, it‘s just plain ruby all the way down.

You can even use this on association collections, eg:

      zoo.animals.mammals.to_a  # => executes one query

## Plays Well With Others

In ActiveRecord, all your fields are mapped, whether you want them or not. This slows things down. In the DataMapper you define your mappings in your model. So instead of an _ALTER TABLE ADD field_ in your data-store, you simply add a `property :name, String` to your model. DRY. No schema.rb. No migration files to conflict or die without reverting changes. Your model drives the data-store, not the other way around.

Unless of course you want to map to a legacy data-store. Raise your hand if you like seeing a method called `col2Name` on your model just because that‘s what it‘s called in an old data-store you can‘t afford to change right now? In DataMapper you control the mappings:

      class Fruit
        include DataMapper::Resource

        storage_names[:repo] = 'frt'

        property :name, String, :field => 'col2Name'
      end

## All Ruby, All The Time

It‘s great that ActiveRecord allows you to write SQL when you need to, but should we have to so often?

DataMapper supports issuing your own query, but it also provides more helpers and a unique hash-based condition syntax to cover more of the use-cases where issuing your own SQL would have been the only way to go. For example, any finder option that‘s non-standard is considered a condition. So you can write `Zoo.all(:name => ‘Dallas’)` and DataMapper will look for zoos with the name of ‘Dallas’.

It‘s just a little thing, but it‘s so much nicer than writing `Zoo.find(:all, :conditions => [‘name = ?’, ‘Dallas’])`. What if you need other comparisons though? Try these:

      # 'gt' means greater-than. We also do 'lt'.
      Person.all(:age.gt => 30)

      # 'gte' means greather-than-or-equal-to. We also do 'lte'.
      Person.all(:age.gte => 30)

      # 'not' allows you to match all people without the name "bob"
      Person.all(:name.not => 'bob')

      # If the value of a pair is an Array, we do an IN-clause for you.
      Person.all(:name.like => 'S%', :id => [ 1, 2, 3, 4, 5 ])

      # Does a NOT IN () clause for you.
      Person.all(:name.not => [ 'bob', 'rick', 'steve' ])

See? Fewer SQL fragments dirtying your Ruby code. And that‘s just a few of the nice syntax tweaks DataMapper delivers out of the box…

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