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.
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.
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.
Imports a Daru::DataFrame from an ActiveRecord connection.
activerecord
gemUsage:
#! 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)
Imports a Daru::DataFrame from an .avro file.
avro
and snappy
gemsUsage:
#! 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')
Imports a Daru::DataFrame from a .csv or .csv.gz file.
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)
Imports a Daru::DataFrame from a .xls file.
spreadsheet
gemUsage:
#! 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)
Imports a Daru::DataFrame from a .xlsx file.
roo
gemUsage:
#! 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)
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.
nokogiri
gemUsage:
#! 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')
Imports a Daru::DataFrame from a .json file / response.
jsonpath
gemUsage:
#! 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')
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.
jsonpath
and mongo
gemsUsage:
#! 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')
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.
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])
Imports a Daru::DataFrame from a variable in .rdata file.
rsruby
gemR_HOME
variable as given in the Contribution GuidelinesUsage:
#! 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')
Imports a Daru::DataFrame from a .rds file.
rsruby
gemR_HOME
variable as given in the Contribution GuidelinesUsage:
#! 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')
Imports a Daru::DataFrame from Redis key(s).
redis
gemredis-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)
Imports a Daru::DataFrame from a sqlite.db file / DBI connection.
dbd-sqlite3
, activerecord
, dbi
and sqlite3
gemsUsage:
#! 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')
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.
Exports a Daru::DataFrame into a .avro file.
avro
gemUsage:
#! 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)
Exports a Daru::DataFrame into a .csv or .csv.gz file.
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)
Exports a Daru::DataFrame into a .xls file.
spreadsheet
gemUsage:
#! 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)
Exports a Daru::DataFrame into a .json file.
jsonpath
gemUsage:
#! 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')
Exports multiple Daru::DataFrames into a .rdata file.
rsruby
gemR_HOME
variable as given in the Contribution GuidelinesUsage:
#! 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')
Exports a Daru::DataFrame into a .rds file.
rsruby
gemR_HOME
variable as given in the Contribution GuidelinesUsage:
#! 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')
Exports a Daru::DataFrame into a database (SQL) table through DBI connection.
dbd-sqlite3
, dbi
and sqlite3
gemsUsage:
#! 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')
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).
Contributions are always welcome. But, please have a look at the contribution guidelines first before contributing. :tada:
The MIT License (MIT) 2017 - Athitya Kumar and Ruby Science Foundation. Please have a look at the LICENSE.md for more details.