Table-Importer

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=== an awesome Table Importer

Importing Legacy Tabluar Data e.g. from cvs Files always sucks. With these Table Importer you are able to import any legacy Data and map it easily to any (e.g.ActiveRecord) Objects

=== Features

• Nested Objects
• Supports Active Record Associations (has_one, belongs_to, has_many
• Easy converting of Data with Procs

=== Usage

• get your Data as nested Array in rows and columns
• build a dictionary to map your data to your Classes {"ClassName"=>attributes} where attributes is a hash of of objects attributes and its corresponding columns attributes = {:attribute=>:col_1}
• you can use number or letters eg. :col1, :col_1, :col_A, :colB, :col_AB, :col_aa etc.
• for pre processing data use array with a lambda as last element :attribute => [:co_l,col_2,lambda{|col1,col2| col1 +" " +col2 }]
• use constant values :attribute=> "My Value"
• for associations user Hashes :association => {:attribute=>:col1}
• Build the Mapper by passing the dictonary mapper = TableImporter::Mapper.new(dictonary)
• Build the Importer by passing the data and the mapper importer = TableImporter:Importer.new(data,mapper)
• build result = importer.build
• you get your result as nested Array [FirstRow [First First Level Object,Second First Level Object],Second Row [...] ]

=== Note

The Objects are only build not saved so you can post process them before saving.

=== Example

Assume you have the follwoing Tabluar Data (e.g. from a CVS File with CSV.read("your_file.csv"))

data= [ # we have only one row in this example ["Bob","Marley","First Avenue 23","12345","New York","Ann","Admins","School","Friends","Private"] ]

And you have the follwoing simple Data Structure

Class Contact < ActiveRecord::Base # first_name String (column1) # last_name String (column2) # full_name String (column1 column2) has_many :tags belongs_to :user has_one :address end

Class Tag < ActiveRecord::Base #tagging String (column 8, 9 and 10) belongs_to :contact end

Class User < ActiveRecord::Base # name String (column 6) has_many :contacts has_one :group end

Class Group # name String (column 7)
end

Class Address # street String (column3) # number Integer (RegEx Number Part of column3) # zip String (column4) # city String (column5) # country String ('USA' constant for the import) belongs_to :contact end

You can build your Data as follows

• first we setup our dictonary hash

  dictonary = {"Contact" =>{:first_name=>:col_1,:last_name=>:col_2,:full_name=>[:col_1,:col_2,lambda{|f,l| "#{v} #{l}"}], # has_many associations you have three tags here :tags=>{:tagging => [:col_8,:col_9,:col_10]}, # nested belongs_to :user => {:name=>:col_6,:group=>{:name=>:col_7}}, # has_one :address => {:street=>[:col_3,lambda{|s| s[/(.?) ([\d]+)/,1]}], :number=>[:col_3,lambda{|s| s[/(.?) ([\d]+)/,2]}], :zip=>:col_4,:city=>:col_5,:country=>"USA" } } }

• now we create a new mapper Object, passing the dictonary

  mapper = TableImporter::Mapper.new(dictonary)

• and an Importer Object passing the data

  importer = TableImporter:Importer.new(data,mapper) result = importer.build

• it should return the processed objects

  => [[#<Contact first_name="Bob",last_name="Marley",full_name="Bob Marley", tags=[#<Tag tagging="Private">,#<Tag tagging="School">,#<Tag tagging="Friends">], address=#<Address street="First Avenue",number=23,zip="12345",city="New York",country="USA"> user =#<User name="Ann",group=#<Group name="Admin"> > ]]

=== License

Copyright (c) 2010 by Manuel Kniep. All rights reserved.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.