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,
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Add this line to your application's Gemfile:
gem 'daru-io'
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And then execute on your terminal:
$ bundle
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If you're NOT working with a Gemfile, simply install it yourself by executing on your terminal:
$ gem install daru-io
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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
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Gem Dependencies:
activerecord
gem - Other Dependencies: Install database server(s) such as SQL / Postgresql / etc.
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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
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Gem Dependencies:
avro
andsnappy
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
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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
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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
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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
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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
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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
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Gem Dependencies:
jsonpath
andmongo
gems - Other Dependencies: Install MongoDB
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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
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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
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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
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Gem Dependencies:
redis
gem -
Other Dependencies: Install Redis, and run an instance of
redis-server
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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
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Gem Dependencies:
dbd-sqlite3
,activerecord
,dbi
andsqlite3
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
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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
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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
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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
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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
andsqlite3
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')
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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.