Daru-IO

A Ruby plugin-gem to daru gem, that extends support for many Import and Export methods of Daru::DataFrame. This gem is intended to help Rubyists who are into Data Analysis or Web Development, by serving as a general purpose conversion library that takes input in one format (say, JSON) and converts it another format (say, Avro) while also making it incredibly easy to getting started on analyzing data with daru.

While supporting various IO modules, daru-io also provides an easier way of adding more Importers / Exporters. It's strongly recommended to have a look at 'Creating your own IO modules' section, if you're interested in creating new Importers / Exporters.

Table of contents

Installation
Importers: ActiveRecord, Avro, CSV, Excel, Excelx, HTML, JSON, Mongo, Plaintext, RData, RDS, Redis, SQL
Exporters: Avro, CSV, Excel, JSON, RData, RDS, SQL
Creating your own IO modules
Contributing
License

Installation

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If you're working with a Gemfile,
- Add this line to your application's Gemfile:
```
gem 'daru-io'
```
- And then execute on your terminal:
```
$ bundle
```
If you're NOT working with a Gemfile, simply install it yourself by executing on your terminal:
```
$ gem install daru-io
```

Require daru-io gem in your application:

require 'daru/io' #! Requires all Importers & Exporters
require 'daru/io/importers' #! Requires all Importers and no Exporters
require 'daru/io/importers/json' #! Requires only JSON Importer

Note: Each IO module has it's own set of dependencies. Have a look at the Importers and Exporters section for dependency-specific information.

Importers

The Daru::IO Importers are intended to return a Daru::DataFrame from the given arguments. Generally, all Importers can be called in two ways - from Daru::IO or Daru::DataFrame.

#! Partially requires Format Importer
require 'daru/io/importers/format'

#! Usage from Daru::IO
instance = Daru::IO::Importers::Format.from(connection)
# or,
instance = Daru::IO::Importers::Format.read(path)
df = instance.call(opts)

#! Usage from Daru::DataFrame
df1 = Daru::DataFrame.from_format(connection, opts)
df2 = Daru::DataFrame.read_format(path, opts)

Note: Please have a look at the respective Importer Doc links below, for having a look at arguments and examples.

ActiveRecord Importer

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Imports a Daru::DataFrame from an ActiveRecord connection.

Docs: rubydoc.info
Gem Dependencies: activerecord gem
Other Dependencies: Install database server(s) such as SQL / Postgresql / etc.

Usage:

#! Partially require just ActiveRecord Importer
require 'daru/io/importers/active_record'

#! Usage from Daru::IO
df = Daru::IO::Importers::ActiveRecord.from(activerecord_relation).call(:field_1, :field_2)

#! Usage from Daru::DataFrame
df = Daru::DataFrame.from_activerecord(activerecord_relation, :field_1, :field_2)

Avro Importer

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Imports a Daru::DataFrame from an .avro file.

Docs: rubydoc.info
Gem Dependencies: avro and snappy gems

Usage:

#! Partially require just Avro Importer
require 'daru/io/importers/avro'

#! Usage from Daru::IO
df = Daru::IO::Importers::Avro.read('path/to/file.avro').call

#! Usage from Daru::DataFrame
df = Daru::DataFrame.read_avro('path/to/file.avro')

CSV Importer

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Imports a Daru::DataFrame from a .csv or .csv.gz file.

Docs: rubydoc.info

Usage:

#! Partially require just CSV Importer
require 'daru/io/importers/csv'

#! Usage from Daru::IO
df1 = Daru::IO::Importers::CSV.read('path/to/file.csv').call(skiprows: 10, col_sep: ' ')
df2 = Daru::IO::Importers::CSV.read('path/to/file.csv.gz').call(skiprows: 10, compression: :gzip)

#! Usage from Daru::DataFrame
df1 = Daru::DataFrame.read_csv('path/to/file.csv', skiprows: 10, col_sep: ' ')
df2 = Daru::DataFrame.read_csv('path/to/file.csv.gz', skiprows: 10, compression: :gzip)

Excel Importer

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Imports a Daru::DataFrame from a .xls file.

Docs: rubydoc.info
Gem Dependencies: spreadsheet gem

Usage:

#! Partially require just Excel Importer
require 'daru/io/importers/excel'

#! Usage from Daru::IO
df = Daru::IO::Importers::Excel.read('path/to/file.xls').call(worksheet_id: 1)

#! Usage from Daru::DataFrame
df = Daru::DataFrame.read_excel('path/to/file.xls', worksheet_id: 1)

Excelx Importer

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Imports a Daru::DataFrame from a .xlsx file.

Docs: rubydoc.info
Gem Dependencies: roo gem

Usage:

#! Partially require just Excel Importer
require 'daru/io/importers/excelx'

#! Usage from Daru::IO
df = Daru::IO::Importers::Excelx.read('path/to/file.xlsx').call(sheet: 2, skiprows: 10, skipcols: 2)

#! Usage from Daru::DataFrame
require 'daru/io/importers/excel'
df = Daru::DataFrame.read_excel('path/to/file.xlsx', sheet: 2, skiprows: 10, skipcols: 2)

HTML Importer

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Note: This module works only for static tables on a HTML page, and won't work in cases where the table is being loaded into the HTML table by inline Javascript. This is how the Nokogiri gem works, and the HTML Importer also follows suit.

Imports an Array of Daru::DataFrames from a .html file or website.

Docs: rubydoc.info
Gem Dependencies: nokogiri gem

Usage:

#! Partially require just HTML Importer
require 'daru/io/importers/html'

#! Usage from Daru::IO
df1 = Daru::IO::Importers::HTML.read('https://some/url/with/tables').call(match: 'market', name: 'Shares analysis')
df2 = Daru::IO::Importers::HTML.read('path/to/file.html').call(match: 'market', name: 'Shares analysis')

#! Usage from Daru::DataFrame
df1 = Daru::DataFrame.read_html('https://some/url/with/tables', match: 'market', name: 'Shares analysis')
df2 = Daru::DataFrame.read_html('path/to/file.html', match: 'market', name: 'Shares analysis')

JSON Importer

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Imports a Daru::DataFrame from a .json file / response.

Docs: rubydoc.info
Gem Dependencies: jsonpath gem

Usage:

#! Partially require just JSON Importer
require 'daru/io/importers/json'

#! Usage from Daru::IO
df1 = Daru::IO::Importers::JSON.read('https://path/to/json/response').call(index: '$..time', col1: '$..name', col2: '$..age')
df2 = Daru::IO::Importers::JSON.read('path/to/file.json').call(index: '$..time', col1: '$..name', col2: '$..age')

#! Usage from Daru::DataFrame
df1 = Daru::DataFrame.read_json('https://path/to/json/response', index: '$..time', col1: '$..name', col2: '$..age')
df2 = Daru::DataFrame.read_json('path/to/file.json', index: '$..time', col1: '$..name', col2: '$..age')

Mongo Importer

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Note: The Mongo gem faces Argument Error : expected Proc Argument issue due to the bug in MRI Ruby 2.4.0 mentioned here. This seems to have been fixed in Ruby 2.4.1 onwards. Hence, please avoid using this Mongo Importer in Ruby version 2.4.0.

Imports a Daru::DataFrame from a Mongo collection.

Docs: rubydoc.info
Gem Dependencies: jsonpath and mongo gems
Other Dependencies: Install MongoDB

Usage:

#! Partially require just Mongo Importer
require 'daru/io/importers/mongo'

#! Usage from Daru::IO
df = Daru::IO::Importers::Mongo.from('mongodb://127.0.0.1:27017/test').call('cars')

#! Usage from Daru::DataFrame
df = Daru::DataFrame.from_mongo('mongodb://127.0.0.1:27017/test', 'cars')

Plaintext Importer

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Imports a Daru::DataFrame from a .dat plaintext file (space separated table of simple strings and numbers). For a sample format of the plaintext file, have a look at the example bank2.dat file.

Docs: rubydoc.info

Usage:

#! Partially require just Plaintext Importer
require 'daru/io/importers/plaintext'

#! Usage from Daru::IO
df = Daru::IO::Importers::Plaintext.read('path/to/file.dat').call([:col1, :col2, :col3])

#! Usage from Daru::DataFrame
df = Daru::DataFrame.read_plaintext('path/to/file.dat', [:col1, :col2, :col3])

RData Importer

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Imports a Daru::DataFrame from a variable in .rdata file.

Docs: rubydoc.info
Gem Dependencies: rsruby gem
Other Dependencies: Install R and set R_HOME variable as given in the Contribution Guidelines

Usage:

#! Partially require just RData Importer
require 'daru/io/importers/r_data'

#! Usage from Daru::IO
df = Daru::IO::Importers::RData.read('path/to/file.RData').call('ACS3')

#! Usage from Daru::DataFrame
df = Daru::DataFrame.read_rdata('path/to/file.RData', 'ACS3')

RDS Importer

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Imports a Daru::DataFrame from a .rds file.

Docs: rubydoc.info
Gem Dependencies: rsruby gem
Other Dependencies: Install R and set R_HOME variable as given in the Contribution Guidelines

Usage:

#! Partially require just RDS Importer
require 'daru/io/importers/rds'

#! Usage from Daru::IO
df = Daru::IO::Importers::RDS.read('path/to/file.rds').call

#! Usage from Daru::DataFrame
df = Daru::DataFrame.read_rds('path/to/file.rds')

Redis Importer

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Imports a Daru::DataFrame from Redis key(s).

Docs: rubydoc.info
Gem Dependencies: redis gem
Other Dependencies: Install Redis, and run an instance of redis-server

Usage:

#! Partially require just Redis Importer
require 'daru/io/importers/redis'

#! Usage from Daru::IO
df = Daru::IO::Importers::Redis.from({url: 'redis://:password@host:port/db'}).call(match: 'time:1*', count: 1000)

#! Usage from Daru::DataFrame
df = Daru::DataFrame.from_redis({url: 'redis://:password@host:port/db'}, match: 'time:1*', count: 1000)

SQL Importer

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Imports a Daru::DataFrame from a sqlite.db file / DBI connection.

Docs: rubydoc.info
Gem Dependencies: dbd-sqlite3, activerecord, dbi and sqlite3 gems

Usage:

#! Partially require just SQL Importer
require 'daru/io/importers/sql'

#! Usage from Daru::IO
df1 = Daru::IO::Importers::SQL.read('path/to/file.sqlite').call('SELECT * FROM test')
df2 = Daru::IO::Importers::SQL.from(dbi_connection).call('SELECT * FROM test')

#! Usage from Daru::DataFrame
df1 = Daru::DataFrame.read_sql('path/to/file.sqlite', 'SELECT * FROM test')
df2 = Daru::DataFrame.from_sql(dbi_connection, 'SELECT * FROM test')

Exporters

The Daru::IO Exporters are intended to 'migrate' a Daru::DataFrame into a file, or database. All Exporters can be called in two ways - from Daru::IO or Daru::DataFrame.

#! Partially requires Format Exporter
require 'daru/io/exporters/format'

#! Usage from Daru::IO
instance = Daru::IO::Exporters::Format.new(df, opts)
instance.to_s #=> Provides a file-writable string, which can be used in web applications for file download purposes
instance.to #=> Provides a Format instance
instance.write(path) #=> Writes to the given path

#! Usage from Daru::DataFrame
string = df.to_format_string(opts) #=> Provides a file-writable string, which can be to write into a file later
instance = df.to_format(opts) #=> Provides a Format instance
df.write_format(path, opts) #=> Writes to the given path

Note: Please have a look at the respective Exporter Doc links below, for having a look at arguments and examples.

Avro Exporter

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Exports a Daru::DataFrame into a .avro file.

Docs: rubydoc.info
Gem Dependencies: avro gem

Usage:

#! Partially require just Avro Exporter
require 'daru/io/exporters/avro'

avro_schema = {
  'type' => 'record',
  'name' => 'Example',
  'fields' => [
    {'name' => 'col_1', 'type' => 'string'},
    {'name' => 'col_2', 'type' => 'int'},
    {'name' => 'col_3', 'type'=> 'boolean'}
  ]
}

#! Usage from Daru::IO
string = Daru::IO::Exporters::Avro.new(df, avro_schema).to_s
Daru::IO::Exporters::Avro.new(df, avro_schema).write('path/to/file.avro')

#! Usage from Daru::DataFrame
string = df.to_avro_string(avro_schema)
df.write_avro('path/to/file.avro', avro_schema)

CSV Exporter

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Exports a Daru::DataFrame into a .csv or .csv.gz file.

Docs: rubydoc.info

Usage:

#! Partially require just CSV Exporter
require 'daru/io/exporters/csv'

#! Usage from Daru::IO
csv_string = Daru::IO::Exporters::CSV.new(df, converters: :numeric, convert_comma: true).to_s
Daru::IO::Exporters::CSV.new(df, converters: :numeric, convert_comma: true).write('path/to/file.csv')
csv_gz_string = Daru::IO::Exporters::CSV.new(df, converters: :numeric, compression: :gzip, convert_comma: true).to_s
Daru::IO::Exporters::CSV.new(df, converters: :numeric, compression: :gzip, convert_comma: true).write('path/to/file.csv.gz')

#! Usage from Daru::DataFrame
csv_string = df.to_csv_string(converters: :numeric, convert_comma: true)
df.write_csv('path/to/file.csv', converters: :numeric, convert_comma: true)
csv_gz_string = df.to_csv_string(converters: :numeric, compression: :gzip, convert_comma: true)
df.write_csv('path/to/file.csv.gz', converters: :numeric, compression: :gzip, convert_comma: true)

Excel Exporter

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Exports a Daru::DataFrame into a .xls file.

Docs: rubydoc.info
Gem Dependencies: spreadsheet gem

Usage:

#! Partially require just Excel Exporter
require 'daru/io/exporters/excel'

#! Usage from Daru::IO
string = Daru::IO::Exporters::Excel.new(df, header: {color: :red, weight: :bold}, data: {color: :blue }, index: false).to_s
Daru::IO::Exporters::Excel.new(df, header: {color: :red, weight: :bold}, data: {color: :blue }, index: false).write('path/to/file.xls')

#! Usage from Daru::DataFrame
string = df.to_excel_string(header: {color: :red, weight: :bold}, data: {color: :blue }, index: false)
df.write_excel('path/to/file.xls', header: {color: :red, weight: :bold}, data: {color: :blue }, index: false)

JSON Exporter

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Exports a Daru::DataFrame into a .json file.

Docs: rubydoc.info
Gem Dependencies: jsonpath gem

Usage:

#! Partially require just JSON Exporter
require 'daru/io/exporters/json'

#! Usage from Daru::IO
hashes = Daru::IO::Exporters::JSON.new(df, orient: :records, pretty: true, name: '$.person.name', age: '$.person.age').to
string = Daru::IO::Exporters::JSON.new(df, 'path/to/file.json', orient: :records, pretty: true, name: '$.person.name', age: '$.person.age').to_s
Daru::IO::Exporters::JSON.new(df, orient: :records, pretty: true, name: '$.person.name', age: '$.person.age').write('path/to/file.json')

#! Usage from Daru::DataFrame
hashes = df.to_json('orient: :records, pretty: true, name: '$.person.name', age: '$.person.age')
string = df.to_json_string(orient: :records, pretty: true, name: '$.person.name', age: '$.person.age')
df.write_json('path/to/file.json', orient: :records, pretty: true, name: '$.person.name', age: '$.person.age')

RData Exporter

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Exports multiple Daru::DataFrames into a .rdata file.

Docs: rubydoc.info
Gem Dependencies: rsruby gem
Other Dependencies: Install R and set R_HOME variable as given in the Contribution Guidelines

Usage:

#! Partially require just RData Exporter
require 'daru/io/exporters/r_data'

#! Usage from Daru::IO
string = Daru::IO::Exporters::RData.new('first.df': df1, 'second.df': df2).to_s
Daru::IO::Exporters::RData.new('first.df': df1, 'second.df': df2).write('path/to/file.RData')

RDS Exporter

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Exports a Daru::DataFrame into a .rds file.

Docs: rubydoc.info
Gem Dependencies: rsruby gem
Other Dependencies: Install R and set R_HOME variable as given in the Contribution Guidelines

Usage:

#! Partially require just RDS Exporter
require 'daru/io/exporters/rds'

#! Usage from Daru::IO
string = Daru::IO::Exporters::RDS.new(df, 'sample.dataframe').to_s
Daru::IO::Exporters::RDS.new(df, 'sample.dataframe').write('path/to/file.rds')

#! Usage from Daru::DataFrame
string = df.to_rds_string('sample.dataframe')
df.write_rds('path/to/file.rds', 'sample.dataframe')

SQL Exporter

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Exports a Daru::DataFrame into a database (SQL) table through DBI connection.

Docs: rubydoc.info
Gem Dependencies: dbd-sqlite3, dbi and sqlite3 gems
Other Dependencies: Install SQL database server

Usage:

#! Partially require just SQL Exporter
require 'daru/io/exporters/sql'

#! Usage from Daru::IO
Daru::IO::Exporters::SQL.new(df, DBI.connect('DBI:Mysql:database:localhost', 'user', 'password'), 'cars_table').to

#! Usage from Daru::DataFrame
df.to_sql(DBI.connect('DBI:Mysql:database:localhost', 'user', 'password'), 'cars_table')

Creating your own IO modules

Daru-IO currently supports various Import / Export methods, as it can be seen from the above list. But the list is NEVER complete - there may always be specific use-case format(s) that you need very badly, but might not fit the needs of majority of the community. In such a case, don't worry - you can always tweak (aka monkey-patch) daru-io in your application. The architecture of daru-io provides a neater way of monkey-patching into Daru::DataFrame to support your unique use-case.

Adding new IO modules to Daru-IO

Say, your unique use-case is of YAML IO Modules. Here's how you can proceed with tweaking -

#! YAML Importer

require 'daru/io'

class Daru::IO::Importers::YAML < Daru::IO::Importers::Base
  Daru::DataFrame.register_io_module :from_yaml, self
  Daru::DataFrame.register_io_module :read_yaml, self

  def initialize
    optional_gem 'yaml'
    #! Add all required gem(s) here.
  end

  def from(instance)
    #! Your code to create initialize instance
    self
  end

  def read(path)
    #! Your code to read the YAML file
    #! and create Daru::DataFrame
    self
  end

  def call(opts)
    #! Unified code to create Daru::DataFrame
    #! irrespective of which method
    #! (from / read) is used by user
  end
end

df = Daru::DataFrame.read_yaml('path/to/file.yaml', skip: 10)
# or,
df = Daru::IO::Importers::YAML.read('path/to/file.yaml').call(skip: 10)

#! YAML Exporter

require 'daru/io'

class Daru::IO::Exporters::YAML < Daru::IO::Exporters::Base
  Daru::DataFrame.register_io_module :to_yaml, self
  Daru::DataFrame.register_io_module :to_yaml_string, self
  Daru::DataFrame.register_io_module :write_yaml, self

  def initialize(dataframe, opts)
    super(dataframe) #! Have a look at documentation of Daru::IO::Exporters::Base#initialize
    @opts = opts
  end

  def to
    #! Your code to return a YAML instance
  end

  def to_s
    super
    #! By default, Exporters::Base adds this to_s method to all Exporters,
    #! by making the write mthod to write to a tempfile, and then reading it.
  end

  def write(path)
    #! Your code to write the YAML file
    #! with the data in the @dataframe
  end
end

df = Daru::DataFrame.new(x: [1,2], y: [3,4])

df.to_yaml(rows: 10..19) #! or, Daru::IO::Exporters::YAML.new(df, rows: 10..19).to
df.to_yaml_string(rows: 10..19) #! or, Daru::IO::Exporters::YAML.new(df, rows: 10..19).to_s
df.write_yaml('dataframe.yml', rows: 10..19) #! or, Daru::IO::Exporters::YAML.new(df, rows: 10..19).write('dataframe.yml')

Adding new IO modules to custom modules

Behaviour of existing IO modules can also be reused according to your needs, similar to the above example. For example, if the CSV Importer has to be tweaked with a faster processing gem, simply follow an approach similar to this -
```
class CustomNamespace::Importers::CSV < Daru::IO::Importers::CSV
  Daru::DataFrame.register_io_module :custom_csv, self

  #! Your CSV Importer code here
end
```

Note: The new module can be made to inherit from another module (like Importers::JSON) rather than Importers::Base, depending on use-case (say, parse a complexly nested API response with JsonPaths).

Contributing

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Contributions are always welcome. But, please have a look at the contribution guidelines first before contributing. 🎉

License

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The MIT License (MIT) 2017 - Athitya Kumar and Ruby Science Foundation. Please have a look at the LICENSE.md for more details.