What is DISCIPLINA (DSCPL) | What is DISCIPLINA token | What is DSCPL token

In this article, we’ll discuss information about the DISCIPLINA project and DSCPL token

DISCIPLINA is a multifunctional blockchain for projects in the educational and recruiting spheres. It provides the transparency of work and creates conditions of maintaining confidentiality and reliability of information added by system participants. DISCIPLINA doesn’t use any other blockchains in its work, and is being developed for the demands of the educational and recruiting fields, taking into account the specificity of their work.

Project mission

To create a multifunctional blockchain for keeping a unified register of academic achievement and qualifications to generate a scoring system for every user of our platform

Our Goals

  • To create a universal blockchain that will store personal achievements in a digital form and guarantee their permanence and credibility
  • To offer an effective algorithm for candidate search by their fields of expertise
  • To develop a mechanism of monetization of the data stored by the educational institutions

Advantages of the platform

The opportunity to store the data on personal achievements in digital form and provide the access to the data through the unified platform which guarantees its permanence and credibility

An effective search tool by candidates’ achievements and their fields of expertise

DISCIPLINA is an open-source platform. Every educational or recruiting service will be able to use blockchain in their projects

Monetization of the stored data on student academic achievement through its trade to the recruiters. Fulfillment of obligations by all parties are guaranteed, and the option for cross-border payment provided

Reliable information on ratings, feedbacks and student grades

The opportunity of targeted education, when students have a certain milestones by completion of which they will be guaranteed the job in a given organization

Ecosystem participants

Academic institutions

State and private offline and online organisations, children’s educational institutions, universities, academies, etc

Tutors

Offline and online tutors, coaches, instructors, teachers, psychologists, mentors etc

Students

Any person that is studying, or would like to find an educational programme for themselves or for their friends and family

Recruiters

HR-agencies, private HR-specialists, platforms for personnel search and recruitment, employers and entrepreneurs

Ecosystem

DISCIPLINA unites students, educational institutions (including private tutors), employers and recruiters. The users will interact with each other and the DISCIPLINA platform through applications with a convenient interface, providing a wide range of platform functions.

DISCIPLINA is an open-source blockchain, which can be used as a basis for application development by anyone. TeachMePlease will be the first project in the field of education based on the DISCIPLINA blockchain platform.

Technologies

Why are we developing our own blockchain architecture?

DISCIPLINA will store confidential information, such as the courses, students’ tasks, grades, and test results. Therefore, public blockchain solutions, which store all of their transactions in open access — Ethereum or EOS, for example — are unacceptable. At the same time, private blockchain solutions, such as Hyperledger, do not provide enough verifiability of the data stored on them.

DISCIPLINA Technology

Proof-of-Stake

Disciplina is a proof-of-stake blockchain, which means faster transactions and no need for energy-consuming mining farms. We do not require stake delegation — any node is free to join the network and validate transactions. In order to increase participation in the protocol, we offer rewards for nodes that stay online and produce blocks. The probability of such a reward is proportional to the stake of the participant.

Two-layer architecture

DISCIPLINA respects privacy — it has private and public layers in its architecture. These layers work closely in order to guarantee both privacy and validity of the data. Private layer contains the actual data, whereas the public one stores cryptographic proofs that the data is untampered.

Web of Trust

We do not use any central organisation to tackle fake educational institutions. Instead, we integrate an intrinsic reputation mechanism called Web of Trust into the core of our architecture. Every entity is able to express opinions on the others’ ability to assess skills. The system builds the ratings of the participants based on these opinions. Respected educational institutions would have more weight and influence in our ecosystem.

Fair data disclosure

DISCIPLINA implements a novel data disclosure algorithm that preserves privacy and ensures that educational institutions can’t cheat while disclosing the data. We use blockchain as a final judge that decides whether the data being disclosed to the interested party is valid. Most importantly, it does not require opening the sensitive data to the public!

High-assurance code

With blockchains and cryptocurrencies one small error can cause big damage. This is why we prefer high-assurance software development techniques. Our core blockchain code is written in Haskell — a type-safe functional programming language that catches most of the errors at compile-time. We also value formal specification — it helps us create a clear understanding about how our system should work, and allows us to clarify all the subtleties of implementation before we even start implementing a feature.

Minting in DISCIPLINA

Unlike traditional PoW mining, the DISCIPLINA platform provides energy-efficient PoS minting. The users will get rewards for any productive activity devoted to transaction processing and supporting the network. The network rewards the users proportionally to the volume of DSCPL tokens on the balance of each user.

The reward to minters will come both from a part of the commission earned on transactions, and in tokens from the technical pool. The size of the reward distributed from the technical pool will continuously be reduced in such a way that the pool itself will never run out.

DSCPL TOKEN

Total Supply: 60,000,100 DSCPL

Join To Get BNB (Binance Coin)! ☞ CLICK HERE

How and Where to Buy DSCPL ?

DSCPL token is now live on the Ethereum mainnet. The token address for DSCPL is 0xdECE0F6864c1511369ae2c30B90Db9f5fe92832c. Be cautious not to purchase any other token with a smart contract different from this one (as this can be easily faked). We strongly advise to be vigilant and stay safe throughout the launch. Don’t let the excitement get the best of you.

Just be sure you have enough ETH in your wallet to cover the transaction fees.

You will have to first buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…

We will use Binance Exchange here as it is one of the largest crypto exchanges that accept fiat deposits.

Once you finished the KYC process. You will be asked to add a payment method. Here you can either choose to provide a credit/debit card or use a bank transfer, and buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…

SIGN UP ON BINANCE

Step by Step Guide : What is Binance | How to Create an account on Binance (Updated 2021)

Next step

You need a wallet address to Connect to Uniswap Decentralized Exchange, we use Metamask wallet

If you don’t have a Metamask wallet, read this article and follow the steps

What is Metamask wallet | How to Create a wallet and Use

Transfer $ETH to your new Metamask wallet from your existing wallet

Next step

Connect Metamask wallet to Uniswap Decentralized Exchange and Buy, Swap DSCPL token

Contract: 0xdECE0F6864c1511369ae2c30B90Db9f5fe92832c

Read more: What is Uniswap | Beginner’s Guide on How to Use Uniswap

The top exchange for trading in DSCPL token is currently Uniswap (V2) and Sushiswap

There are a few popular crypto exchanges where they have decent daily trading volumes and a huge user base. This will ensure you will be able to sell your coins at any time and the fees will usually be lower. It is suggested that you also register on these exchanges since once DSCPL gets listed there it will attract a large amount of trading volumes from the users there, that means you will be having some great trading opportunities!

Top exchanges for token-coin trading. Follow instructions and make unlimited money

https://www.binance.com
  ☞ https://www.bittrex.com
  ☞ https://www.poloniex.com
  ☞ https://www.bitfinex.com
  ☞ https://www.huobi.com

Find more information DSCPL

WebsiteExplorerExplorer 2Source CodeSocial ChannelSocial Channel 2Coinmarketcap

🔺DISCLAIMER: The Information in the post isn’t financial advice, is intended FOR GENERAL INFORMATION PURPOSES ONLY. Trading Cryptocurrency is VERY risky. Make sure you understand these risks and that you are responsible for what you do with your money.

🔥 If you’re a beginner. I believe the article below will be useful to you

⭐ ⭐ ⭐ What You Should Know Before Investing in Cryptocurrency - For Beginner ⭐ ⭐ ⭐

I hope this post will help you. Don’t forget to leave a like, comment and sharing it with others. Thank you!

#blockchain #bitcoin #dscpl #disciplina

What is GEEK

Buddha Community

What is DISCIPLINA (DSCPL) | What is DISCIPLINA token | What is DSCPL token

What is DISCIPLINA (DSCPL) | What is DISCIPLINA token | What is DSCPL token

In this article, we’ll discuss information about the DISCIPLINA project and DSCPL token

DISCIPLINA is a multifunctional blockchain for projects in the educational and recruiting spheres. It provides the transparency of work and creates conditions of maintaining confidentiality and reliability of information added by system participants. DISCIPLINA doesn’t use any other blockchains in its work, and is being developed for the demands of the educational and recruiting fields, taking into account the specificity of their work.

Project mission

To create a multifunctional blockchain for keeping a unified register of academic achievement and qualifications to generate a scoring system for every user of our platform

Our Goals

  • To create a universal blockchain that will store personal achievements in a digital form and guarantee their permanence and credibility
  • To offer an effective algorithm for candidate search by their fields of expertise
  • To develop a mechanism of monetization of the data stored by the educational institutions

Advantages of the platform

The opportunity to store the data on personal achievements in digital form and provide the access to the data through the unified platform which guarantees its permanence and credibility

An effective search tool by candidates’ achievements and their fields of expertise

DISCIPLINA is an open-source platform. Every educational or recruiting service will be able to use blockchain in their projects

Monetization of the stored data on student academic achievement through its trade to the recruiters. Fulfillment of obligations by all parties are guaranteed, and the option for cross-border payment provided

Reliable information on ratings, feedbacks and student grades

The opportunity of targeted education, when students have a certain milestones by completion of which they will be guaranteed the job in a given organization

Ecosystem participants

Academic institutions

State and private offline and online organisations, children’s educational institutions, universities, academies, etc

Tutors

Offline and online tutors, coaches, instructors, teachers, psychologists, mentors etc

Students

Any person that is studying, or would like to find an educational programme for themselves or for their friends and family

Recruiters

HR-agencies, private HR-specialists, platforms for personnel search and recruitment, employers and entrepreneurs

Ecosystem

DISCIPLINA unites students, educational institutions (including private tutors), employers and recruiters. The users will interact with each other and the DISCIPLINA platform through applications with a convenient interface, providing a wide range of platform functions.

DISCIPLINA is an open-source blockchain, which can be used as a basis for application development by anyone. TeachMePlease will be the first project in the field of education based on the DISCIPLINA blockchain platform.

Technologies

Why are we developing our own blockchain architecture?

DISCIPLINA will store confidential information, such as the courses, students’ tasks, grades, and test results. Therefore, public blockchain solutions, which store all of their transactions in open access — Ethereum or EOS, for example — are unacceptable. At the same time, private blockchain solutions, such as Hyperledger, do not provide enough verifiability of the data stored on them.

DISCIPLINA Technology

Proof-of-Stake

Disciplina is a proof-of-stake blockchain, which means faster transactions and no need for energy-consuming mining farms. We do not require stake delegation — any node is free to join the network and validate transactions. In order to increase participation in the protocol, we offer rewards for nodes that stay online and produce blocks. The probability of such a reward is proportional to the stake of the participant.

Two-layer architecture

DISCIPLINA respects privacy — it has private and public layers in its architecture. These layers work closely in order to guarantee both privacy and validity of the data. Private layer contains the actual data, whereas the public one stores cryptographic proofs that the data is untampered.

Web of Trust

We do not use any central organisation to tackle fake educational institutions. Instead, we integrate an intrinsic reputation mechanism called Web of Trust into the core of our architecture. Every entity is able to express opinions on the others’ ability to assess skills. The system builds the ratings of the participants based on these opinions. Respected educational institutions would have more weight and influence in our ecosystem.

Fair data disclosure

DISCIPLINA implements a novel data disclosure algorithm that preserves privacy and ensures that educational institutions can’t cheat while disclosing the data. We use blockchain as a final judge that decides whether the data being disclosed to the interested party is valid. Most importantly, it does not require opening the sensitive data to the public!

High-assurance code

With blockchains and cryptocurrencies one small error can cause big damage. This is why we prefer high-assurance software development techniques. Our core blockchain code is written in Haskell — a type-safe functional programming language that catches most of the errors at compile-time. We also value formal specification — it helps us create a clear understanding about how our system should work, and allows us to clarify all the subtleties of implementation before we even start implementing a feature.

Minting in DISCIPLINA

Unlike traditional PoW mining, the DISCIPLINA platform provides energy-efficient PoS minting. The users will get rewards for any productive activity devoted to transaction processing and supporting the network. The network rewards the users proportionally to the volume of DSCPL tokens on the balance of each user.

The reward to minters will come both from a part of the commission earned on transactions, and in tokens from the technical pool. The size of the reward distributed from the technical pool will continuously be reduced in such a way that the pool itself will never run out.

DSCPL TOKEN

Total Supply: 60,000,100 DSCPL

Join To Get BNB (Binance Coin)! ☞ CLICK HERE

How and Where to Buy DSCPL ?

DSCPL token is now live on the Ethereum mainnet. The token address for DSCPL is 0xdECE0F6864c1511369ae2c30B90Db9f5fe92832c. Be cautious not to purchase any other token with a smart contract different from this one (as this can be easily faked). We strongly advise to be vigilant and stay safe throughout the launch. Don’t let the excitement get the best of you.

Just be sure you have enough ETH in your wallet to cover the transaction fees.

You will have to first buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…

We will use Binance Exchange here as it is one of the largest crypto exchanges that accept fiat deposits.

Once you finished the KYC process. You will be asked to add a payment method. Here you can either choose to provide a credit/debit card or use a bank transfer, and buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…

SIGN UP ON BINANCE

Step by Step Guide : What is Binance | How to Create an account on Binance (Updated 2021)

Next step

You need a wallet address to Connect to Uniswap Decentralized Exchange, we use Metamask wallet

If you don’t have a Metamask wallet, read this article and follow the steps

What is Metamask wallet | How to Create a wallet and Use

Transfer $ETH to your new Metamask wallet from your existing wallet

Next step

Connect Metamask wallet to Uniswap Decentralized Exchange and Buy, Swap DSCPL token

Contract: 0xdECE0F6864c1511369ae2c30B90Db9f5fe92832c

Read more: What is Uniswap | Beginner’s Guide on How to Use Uniswap

The top exchange for trading in DSCPL token is currently Uniswap (V2) and Sushiswap

There are a few popular crypto exchanges where they have decent daily trading volumes and a huge user base. This will ensure you will be able to sell your coins at any time and the fees will usually be lower. It is suggested that you also register on these exchanges since once DSCPL gets listed there it will attract a large amount of trading volumes from the users there, that means you will be having some great trading opportunities!

Top exchanges for token-coin trading. Follow instructions and make unlimited money

https://www.binance.com
  ☞ https://www.bittrex.com
  ☞ https://www.poloniex.com
  ☞ https://www.bitfinex.com
  ☞ https://www.huobi.com

Find more information DSCPL

WebsiteExplorerExplorer 2Source CodeSocial ChannelSocial Channel 2Coinmarketcap

🔺DISCLAIMER: The Information in the post isn’t financial advice, is intended FOR GENERAL INFORMATION PURPOSES ONLY. Trading Cryptocurrency is VERY risky. Make sure you understand these risks and that you are responsible for what you do with your money.

🔥 If you’re a beginner. I believe the article below will be useful to you

⭐ ⭐ ⭐ What You Should Know Before Investing in Cryptocurrency - For Beginner ⭐ ⭐ ⭐

I hope this post will help you. Don’t forget to leave a like, comment and sharing it with others. Thank you!

#blockchain #bitcoin #dscpl #disciplina

Royce  Reinger

Royce Reinger

1658068560

WordsCounted: A Ruby Natural Language Processor

WordsCounted

We are all in the gutter, but some of us are looking at the stars.

-- Oscar Wilde

WordsCounted is a Ruby NLP (natural language processor). WordsCounted lets you implement powerful tokensation strategies with a very flexible tokeniser class.

Features

  • Out of the box, get the following data from any string or readable file, or URL:
    • Token count and unique token count
    • Token densities, frequencies, and lengths
    • Char count and average chars per token
    • The longest tokens and their lengths
    • The most frequent tokens and their frequencies.
  • A flexible way to exclude tokens from the tokeniser. You can pass a string, regexp, symbol, lambda, or an array of any combination of those types for powerful tokenisation strategies.
  • Pass your own regexp rules to the tokeniser if you prefer. The default regexp filters special characters but keeps hyphens and apostrophes. It also plays nicely with diacritics (UTF and unicode characters): Bayrūt is treated as ["Bayrūt"] and not ["Bayr", "ū", "t"], for example.
  • Opens and reads files. Pass in a file path or a url instead of a string.

Installation

Add this line to your application's Gemfile:

gem 'words_counted'

And then execute:

$ bundle

Or install it yourself as:

$ gem install words_counted

Usage

Pass in a string or a file path, and an optional filter and/or regexp.

counter = WordsCounted.count(
  "We are all in the gutter, but some of us are looking at the stars."
)

# Using a file
counter = WordsCounted.from_file("path/or/url/to/my/file.txt")

.count and .from_file are convenience methods that take an input, tokenise it, and return an instance of WordsCounted::Counter initialized with the tokens. The WordsCounted::Tokeniser and WordsCounted::Counter classes can be used alone, however.

API

WordsCounted

WordsCounted.count(input, options = {})

Tokenises input and initializes a WordsCounted::Counter object with the resulting tokens.

counter = WordsCounted.count("Hello Beirut!")

Accepts two options: exclude and regexp. See Excluding tokens from the analyser and Passing in a custom regexp respectively.

WordsCounted.from_file(path, options = {})

Reads and tokenises a file, and initializes a WordsCounted::Counter object with the resulting tokens.

counter = WordsCounted.from_file("hello_beirut.txt")

Accepts the same options as .count.

Tokeniser

The tokeniser allows you to tokenise text in a variety of ways. You can pass in your own rules for tokenisation, and apply a powerful filter with any combination of rules as long as they can boil down into a lambda.

Out of the box the tokeniser includes only alpha chars. Hyphenated tokens and tokens with apostrophes are considered a single token.

#tokenise([pattern: TOKEN_REGEXP, exclude: nil])

tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise

# With `exclude`
tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise(exclude: "hello")

# With `pattern`
tokeniser = WordsCounted::Tokeniser.new("I <3 Beirut!").tokenise(pattern: /[a-z]/i)

See Excluding tokens from the analyser and Passing in a custom regexp for more information.

Counter

The WordsCounted::Counter class allows you to collect various statistics from an array of tokens.

#token_count

Returns the token count of a given string.

counter.token_count #=> 15

#token_frequency

Returns a sorted (unstable) two-dimensional array where each element is a token and its frequency. The array is sorted by frequency in descending order.

counter.token_frequency

[
  ["the", 2],
  ["are", 2],
  ["we",  1],
  # ...
  ["all", 1]
]

#most_frequent_tokens

Returns a hash where each key-value pair is a token and its frequency.

counter.most_frequent_tokens

{ "are" => 2, "the" => 2 }

#token_lengths

Returns a sorted (unstable) two-dimentional array where each element contains a token and its length. The array is sorted by length in descending order.

counter.token_lengths

[
  ["looking", 7],
  ["gutter",  6],
  ["stars",   5],
  # ...
  ["in",      2]
]

#longest_tokens

Returns a hash where each key-value pair is a token and its length.

counter.longest_tokens

{ "looking" => 7 }

#token_density([ precision: 2 ])

Returns a sorted (unstable) two-dimentional array where each element contains a token and its density as a float, rounded to a precision of two. The array is sorted by density in descending order. It accepts a precision argument, which must be a float.

counter.token_density

[
  ["are",     0.13],
  ["the",     0.13],
  ["but",     0.07 ],
  # ...
  ["we",      0.07 ]
]

#char_count

Returns the char count of tokens.

counter.char_count #=> 76

#average_chars_per_token([ precision: 2 ])

Returns the average char count per token rounded to two decimal places. Accepts a precision argument which defaults to two. Precision must be a float.

counter.average_chars_per_token #=> 4

#uniq_token_count

Returns the number of unique tokens.

counter.uniq_token_count #=> 13

Excluding tokens from the tokeniser

You can exclude anything you want from the input by passing the exclude option. The exclude option accepts a variety of filters and is extremely flexible.

  1. A space-delimited string. The filter will normalise the string.
  2. A regular expression.
  3. A lambda.
  4. A symbol that names a predicate method. For example :odd?.
  5. An array of any combination of the above.
tokeniser =
  WordsCounted::Tokeniser.new(
    "Magnificent! That was magnificent, Trevor."
  )

# Using a string
tokeniser.tokenise(exclude: "was magnificent")
# => ["that", "trevor"]

# Using a regular expression
tokeniser.tokenise(exclude: /trevor/)
# => ["magnificent", "that", "was", "magnificent"]

# Using a lambda
tokeniser.tokenise(exclude: ->(t) { t.length < 4 })
# => ["magnificent", "that", "magnificent", "trevor"]

# Using symbol
tokeniser = WordsCounted::Tokeniser.new("Hello! محمد")
tokeniser.tokenise(exclude: :ascii_only?)
# => ["محمد"]

# Using an array
tokeniser = WordsCounted::Tokeniser.new(
  "Hello! اسماءنا هي محمد، كارولينا، سامي، وداني"
)
tokeniser.tokenise(
  exclude: [:ascii_only?, /محمد/, ->(t) { t.length > 6}, "و"]
)
# => ["هي", "سامي", "وداني"]

Passing in a custom regexp

The default regexp accounts for letters, hyphenated tokens, and apostrophes. This means twenty-one is treated as one token. So is Mohamad's.

/[\p{Alpha}\-']+/

You can pass your own criteria as a Ruby regular expression to split your string as desired.

For example, if you wanted to include numbers, you can override the regular expression:

counter = WordsCounted.count("Numbers 1, 2, and 3", pattern: /[\p{Alnum}\-']+/)
counter.tokens
#=> ["numbers", "1", "2", "and", "3"]

Opening and reading files

Use the from_file method to open files. from_file accepts the same options as .count. The file path can be a URL.

counter = WordsCounted.from_file("url/or/path/to/file.text")

Gotchas

A hyphen used in leu of an em or en dash will form part of the token. This affects the tokeniser algorithm.

counter = WordsCounted.count("How do you do?-you are well, I see.")
counter.token_frequency

[
  ["do",   2],
  ["how",  1],
  ["you",  1],
  ["-you", 1], # WTF, mate!
  ["are",  1],
  # ...
]

In this example -you and you are separate tokens. Also, the tokeniser does not include numbers by default. Remember that you can pass your own regular expression if the default behaviour does not fit your needs.

A note on case sensitivity

The program will normalise (downcase) all incoming strings for consistency and filters.

Roadmap

Ability to open URLs

def self.from_url
  # open url and send string here after removing html
end

Are you using WordsCounted to do something interesting? Please tell me about it.

Gem Version 

RubyDoc documentation.

Demo

Visit this website for one example of what you can do with WordsCounted.


Contributors

See contributors.

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request

Author: Abitdodgy
Source Code: https://github.com/abitdodgy/words_counted 
License: MIT license

#ruby #nlp 

Words Counted: A Ruby Natural Language Processor.

WordsCounted

We are all in the gutter, but some of us are looking at the stars.

-- Oscar Wilde

WordsCounted is a Ruby NLP (natural language processor). WordsCounted lets you implement powerful tokensation strategies with a very flexible tokeniser class.

Are you using WordsCounted to do something interesting? Please tell me about it.

 

Demo

Visit this website for one example of what you can do with WordsCounted.

Features

  • Out of the box, get the following data from any string or readable file, or URL:
    • Token count and unique token count
    • Token densities, frequencies, and lengths
    • Char count and average chars per token
    • The longest tokens and their lengths
    • The most frequent tokens and their frequencies.
  • A flexible way to exclude tokens from the tokeniser. You can pass a string, regexp, symbol, lambda, or an array of any combination of those types for powerful tokenisation strategies.
  • Pass your own regexp rules to the tokeniser if you prefer. The default regexp filters special characters but keeps hyphens and apostrophes. It also plays nicely with diacritics (UTF and unicode characters): Bayrūt is treated as ["Bayrūt"] and not ["Bayr", "ū", "t"], for example.
  • Opens and reads files. Pass in a file path or a url instead of a string.

Installation

Add this line to your application's Gemfile:

gem 'words_counted'

And then execute:

$ bundle

Or install it yourself as:

$ gem install words_counted

Usage

Pass in a string or a file path, and an optional filter and/or regexp.

counter = WordsCounted.count(
  "We are all in the gutter, but some of us are looking at the stars."
)

# Using a file
counter = WordsCounted.from_file("path/or/url/to/my/file.txt")

.count and .from_file are convenience methods that take an input, tokenise it, and return an instance of WordsCounted::Counter initialized with the tokens. The WordsCounted::Tokeniser and WordsCounted::Counter classes can be used alone, however.

API

WordsCounted

WordsCounted.count(input, options = {})

Tokenises input and initializes a WordsCounted::Counter object with the resulting tokens.

counter = WordsCounted.count("Hello Beirut!")

Accepts two options: exclude and regexp. See Excluding tokens from the analyser and Passing in a custom regexp respectively.

WordsCounted.from_file(path, options = {})

Reads and tokenises a file, and initializes a WordsCounted::Counter object with the resulting tokens.

counter = WordsCounted.from_file("hello_beirut.txt")

Accepts the same options as .count.

Tokeniser

The tokeniser allows you to tokenise text in a variety of ways. You can pass in your own rules for tokenisation, and apply a powerful filter with any combination of rules as long as they can boil down into a lambda.

Out of the box the tokeniser includes only alpha chars. Hyphenated tokens and tokens with apostrophes are considered a single token.

#tokenise([pattern: TOKEN_REGEXP, exclude: nil])

tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise

# With `exclude`
tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise(exclude: "hello")

# With `pattern`
tokeniser = WordsCounted::Tokeniser.new("I <3 Beirut!").tokenise(pattern: /[a-z]/i)

See Excluding tokens from the analyser and Passing in a custom regexp for more information.

Counter

The WordsCounted::Counter class allows you to collect various statistics from an array of tokens.

#token_count

Returns the token count of a given string.

counter.token_count #=> 15

#token_frequency

Returns a sorted (unstable) two-dimensional array where each element is a token and its frequency. The array is sorted by frequency in descending order.

counter.token_frequency

[
  ["the", 2],
  ["are", 2],
  ["we",  1],
  # ...
  ["all", 1]
]

#most_frequent_tokens

Returns a hash where each key-value pair is a token and its frequency.

counter.most_frequent_tokens

{ "are" => 2, "the" => 2 }

#token_lengths

Returns a sorted (unstable) two-dimentional array where each element contains a token and its length. The array is sorted by length in descending order.

counter.token_lengths

[
  ["looking", 7],
  ["gutter",  6],
  ["stars",   5],
  # ...
  ["in",      2]
]

#longest_tokens

Returns a hash where each key-value pair is a token and its length.

counter.longest_tokens

{ "looking" => 7 }

#token_density([ precision: 2 ])

Returns a sorted (unstable) two-dimentional array where each element contains a token and its density as a float, rounded to a precision of two. The array is sorted by density in descending order. It accepts a precision argument, which must be a float.

counter.token_density

[
  ["are",     0.13],
  ["the",     0.13],
  ["but",     0.07 ],
  # ...
  ["we",      0.07 ]
]

#char_count

Returns the char count of tokens.

counter.char_count #=> 76

#average_chars_per_token([ precision: 2 ])

Returns the average char count per token rounded to two decimal places. Accepts a precision argument which defaults to two. Precision must be a float.

counter.average_chars_per_token #=> 4

#uniq_token_count

Returns the number of unique tokens.

counter.uniq_token_count #=> 13

Excluding tokens from the tokeniser

You can exclude anything you want from the input by passing the exclude option. The exclude option accepts a variety of filters and is extremely flexible.

  1. A space-delimited string. The filter will normalise the string.
  2. A regular expression.
  3. A lambda.
  4. A symbol that names a predicate method. For example :odd?.
  5. An array of any combination of the above.
tokeniser =
  WordsCounted::Tokeniser.new(
    "Magnificent! That was magnificent, Trevor."
  )

# Using a string
tokeniser.tokenise(exclude: "was magnificent")
# => ["that", "trevor"]

# Using a regular expression
tokeniser.tokenise(exclude: /trevor/)
# => ["magnificent", "that", "was", "magnificent"]

# Using a lambda
tokeniser.tokenise(exclude: ->(t) { t.length < 4 })
# => ["magnificent", "that", "magnificent", "trevor"]

# Using symbol
tokeniser = WordsCounted::Tokeniser.new("Hello! محمد")
tokeniser.tokenise(exclude: :ascii_only?)
# => ["محمد"]

# Using an array
tokeniser = WordsCounted::Tokeniser.new(
  "Hello! اسماءنا هي محمد، كارولينا، سامي، وداني"
)
tokeniser.tokenise(
  exclude: [:ascii_only?, /محمد/, ->(t) { t.length > 6}, "و"]
)
# => ["هي", "سامي", "وداني"]

Passing in a custom regexp

The default regexp accounts for letters, hyphenated tokens, and apostrophes. This means twenty-one is treated as one token. So is Mohamad's.

/[\p{Alpha}\-']+/

You can pass your own criteria as a Ruby regular expression to split your string as desired.

For example, if you wanted to include numbers, you can override the regular expression:

counter = WordsCounted.count("Numbers 1, 2, and 3", pattern: /[\p{Alnum}\-']+/)
counter.tokens
#=> ["numbers", "1", "2", "and", "3"]

Opening and reading files

Use the from_file method to open files. from_file accepts the same options as .count. The file path can be a URL.

counter = WordsCounted.from_file("url/or/path/to/file.text")

Gotchas

A hyphen used in leu of an em or en dash will form part of the token. This affects the tokeniser algorithm.

counter = WordsCounted.count("How do you do?-you are well, I see.")
counter.token_frequency

[
  ["do",   2],
  ["how",  1],
  ["you",  1],
  ["-you", 1], # WTF, mate!
  ["are",  1],
  # ...
]

In this example -you and you are separate tokens. Also, the tokeniser does not include numbers by default. Remember that you can pass your own regular expression if the default behaviour does not fit your needs.

A note on case sensitivity

The program will normalise (downcase) all incoming strings for consistency and filters.

Roadmap

Ability to open URLs

def self.from_url
  # open url and send string here after removing html
end

Contributors

See contributors.

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request

Author: abitdodgy
Source code: https://github.com/abitdodgy/words_counted
License: MIT license

#ruby  #ruby-on-rails 

aaron silva

aaron silva

1622197808

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