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
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Nested Objects
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Supports Active Record Associations (has_one, belongs_to, has_many
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Easy converting of Data with Procs
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get your Data as nested Array in rows and columns
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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}
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you can use number or letters eg. :col1, :col_1, :col_A, :colB, :col_AB, :col_aa etc.
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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"
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for associations user Hashes
:association => {:attribute=>:col1} -
Build the Mapper by passing the dictonary
mapper = TableImporter::Mapper.new(dictonary)
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Build the Importer by passing the data and the mapper
importer = TableImporter:Importer.new(data,mapper)
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build
result = importer.build
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you get your result as nested Array [FirstRow [First First Level Object,Second First Level Object],Second Row […] ]
The Objects are only build not saved so you can post process them before saving.
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
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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" } } }
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now we create a new mapper Object, passing the dictonary
mapper = TableImporter::Mapper.new(dictonary)
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and an Importer Object passing the data
importer = TableImporter:Importer.new(data,mapper) result = importer.build
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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"> > ]]
Copyright © 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.