What is MATCH (MATCH) | What is MATCH token | MATCH (MATCH) ICO

What is MATCH Token?

MATCH token is a utility token for the De-Fi and Decentralized Bet (De-Bet) platforms. MATCH token is developed by a group of people who want to share the equal great opportunity to the holders through a decentralized network. MATCH token leverages the decentralized (blockchain) network because it offers more greatness compared to a centralized network. They believe as a token, it can be nurtured to become a priceless token to the holders while at the same time to be used on an application that provides secure and transparent transactions on top of a smart contract designed to get all involved persons to have the same opportunities to grow their accounts actively and passively on an ecosystem

Where MATCH token is deployed and why?

MATCH token is running on top of the TRON network which is one of the largest blockchain-based operating systems in the world. The token leverages the TRON network because it offers high-throughout, high-availability, and high-scalability. Supported by 1,332 nodes across the globe, TRON can support MATCH tokens in rendering a swift transaction time with the lowest fees compared to other smart contract networks, whereas pace is one of the nowadays application requirements. TRON TPS has exceeded the TPS of Bitcoin and Ethereum, which is one of our main reasons for selecting TRON as our main blockchain network.

Can MATCH token’s value steady and tend to be increased?

MATCH token team’s vision is to grow the token’s value by using it actively and passively in an ecosystem. Thus, the value of the token can be maintained and tend to be increased over time. This vision can be gained through De-Fi and Decentralized Bet (De-Bet) platforms.

How does the MATCH token apply De-Fi in the ecosystem?

The other proven way that can be used to grow the holders’ account passively is through a liquidity stake as part of Decentralized Finance running on top of blockchain systems to apply the Automatic Market Makers (AMM) principle. The token holders can become Liquidity Providers that could earn Swap Fee and MATCH tokens through mining based on existing APY (Annual Percentage Yield). As a Liquidity Provider, you are eligible to earn a portion of fees from the Liquidity Pool as much as 0.3% from each swap activity performed in the justswap.io platform with respect to pool shares. By staking your token in the Liquidity Pool, you can be eligible to yield a MATCH token based on the current APY. The transparent calculation is performed in the background systematically without any human interference and purely mathematical logarithm and financial investment fusion.

What is Decentralized Bet (De-Bet)?

MATCH token is a token that can only be used actively on a decentralized application (DApp) named De-Bet which is a transparent and trusted sports betting. Moreover, De-Bet is the first decentralized betting for sports in the TRON network. De-Bet focuses on User Experience and the Smart Contract technology that can help Makers and Takers to play their own roles without any human’s interference, in order to get another uplifted level of amusement in the betting arena with the benefit of Blockchain technology. De-Bet will be delivered in two phases: (1) Decentralized Betting Smart Contract and (2) Decentralized Betting for other Providers in Smart Contract. For detailed information on improvement and process flow can be found in our whitepaper (link).

How can I participate in MATCH token development?

MATCH token team will initiate ICO (Initial Currency Offering) through Private Sale and Pre-Sale events.

When is the MATCH Token Private Sale started?

The Private Sale will be opened on 6-13 Dec 2020 for limited investors. Throughout this Private Sales, we expect to gain 1,250,000 MATCH tokens with 5 TRX for each MATCH token. Be the first holder of MATCH Token! By joining this private sale you will have the opportunity to get MATCH tokens at 50% of the market price.

  • Private Sale price: 5 TRX
  • Minimum contribution: 500 TRX
  • Normal price: 10 TRXQ

Roadmap

phone

When is the MATCH Token Pre-Sale started?

There will be a Pre-Sale on 20 - 27 December 2020 which will be opened to the public for enthusiastic investors. From this Pre-Sale, we expect to acquire 5,000,000 MATCH tokens with 6 TRX for each MATCH token. By joining this pre-sale you will have the opportunity to get MATCH tokens at 60% of the market price.

  • Private Sale price: 6 TRX
  • Minimum contribution: 500 TRX
  • Normal price: 10 TRX

How do I get MATCH tokens during the Sale event?

It is very simple. What you need to do is have TRX in your wallet and you can just click the “Buy MATCH token" link on our site.

Can you recommend a digital wallet?

Most people are using the TRON Link wallet. Disclaimer: The MATCH team does not endorse, recommend, or make any representations with respect to digital wallets. It’s advisable to always conduct your own due diligence before trusting any third party or third-party technology.

How can I get a MATCH token after the Sale event?

You will be able to trade MATCH once MATCH listed in Justswap.io which we aim to be listed in January 2021. Disclaimer: Please note that the MATCH team does not endorse, recommend, or make any representations with respect to Internet lists or exchanges more generally. Every exchange has a different process for trading MATCH tokens and their customer support and policies and practices may vary widely. It’s advisable to conduct your own due diligence before trusting any third party or third-party technology.

Can I get an airdrop from MATCH Token?

MATCH will announce the airdrop the very first time we launch our product, and the airdrop itself will be dropped in Q1 2021. Make sure you will not miss this opportunity, follow our community channel to keep yourself updated

Instagram : https://www.instagram.com/matchtoken/

ICO DATE: Dec 6, 2020 - Dec 27, 2020

Private Sale: Dec 6 — Dec 13, 2020

Private Sale price: 5 TRX (50% Discount from the public sale price)

Pre-Sale: Dec 20 — Dec 27, 2020

Private Sale price: 6 TRX (40% Discount from the public sale price)

Would you like to earn many tokens and cryptocurrencies right now! ☞ CLICK HERE

Looking for more information…

☞ Website
☞ Explorer
☞ Whitepaper

Create an Account and Trade Cryptocurrency NOW

Binance
Bittrex
Poloniex

Thank for visiting and reading this article! I’m highly appreciate your actions! Please share if you liked it!

#blockchain #crypto #match #match token

What is GEEK

Buddha Community

What is MATCH (MATCH) | What is MATCH token | MATCH (MATCH) ICO

What is MATCH (MATCH) | What is MATCH token | MATCH (MATCH) ICO

What is MATCH Token?

MATCH token is a utility token for the De-Fi and Decentralized Bet (De-Bet) platforms. MATCH token is developed by a group of people who want to share the equal great opportunity to the holders through a decentralized network. MATCH token leverages the decentralized (blockchain) network because it offers more greatness compared to a centralized network. They believe as a token, it can be nurtured to become a priceless token to the holders while at the same time to be used on an application that provides secure and transparent transactions on top of a smart contract designed to get all involved persons to have the same opportunities to grow their accounts actively and passively on an ecosystem

Where MATCH token is deployed and why?

MATCH token is running on top of the TRON network which is one of the largest blockchain-based operating systems in the world. The token leverages the TRON network because it offers high-throughout, high-availability, and high-scalability. Supported by 1,332 nodes across the globe, TRON can support MATCH tokens in rendering a swift transaction time with the lowest fees compared to other smart contract networks, whereas pace is one of the nowadays application requirements. TRON TPS has exceeded the TPS of Bitcoin and Ethereum, which is one of our main reasons for selecting TRON as our main blockchain network.

Can MATCH token’s value steady and tend to be increased?

MATCH token team’s vision is to grow the token’s value by using it actively and passively in an ecosystem. Thus, the value of the token can be maintained and tend to be increased over time. This vision can be gained through De-Fi and Decentralized Bet (De-Bet) platforms.

How does the MATCH token apply De-Fi in the ecosystem?

The other proven way that can be used to grow the holders’ account passively is through a liquidity stake as part of Decentralized Finance running on top of blockchain systems to apply the Automatic Market Makers (AMM) principle. The token holders can become Liquidity Providers that could earn Swap Fee and MATCH tokens through mining based on existing APY (Annual Percentage Yield). As a Liquidity Provider, you are eligible to earn a portion of fees from the Liquidity Pool as much as 0.3% from each swap activity performed in the justswap.io platform with respect to pool shares. By staking your token in the Liquidity Pool, you can be eligible to yield a MATCH token based on the current APY. The transparent calculation is performed in the background systematically without any human interference and purely mathematical logarithm and financial investment fusion.

What is Decentralized Bet (De-Bet)?

MATCH token is a token that can only be used actively on a decentralized application (DApp) named De-Bet which is a transparent and trusted sports betting. Moreover, De-Bet is the first decentralized betting for sports in the TRON network. De-Bet focuses on User Experience and the Smart Contract technology that can help Makers and Takers to play their own roles without any human’s interference, in order to get another uplifted level of amusement in the betting arena with the benefit of Blockchain technology. De-Bet will be delivered in two phases: (1) Decentralized Betting Smart Contract and (2) Decentralized Betting for other Providers in Smart Contract. For detailed information on improvement and process flow can be found in our whitepaper (link).

How can I participate in MATCH token development?

MATCH token team will initiate ICO (Initial Currency Offering) through Private Sale and Pre-Sale events.

When is the MATCH Token Private Sale started?

The Private Sale will be opened on 6-13 Dec 2020 for limited investors. Throughout this Private Sales, we expect to gain 1,250,000 MATCH tokens with 5 TRX for each MATCH token. Be the first holder of MATCH Token! By joining this private sale you will have the opportunity to get MATCH tokens at 50% of the market price.

  • Private Sale price: 5 TRX
  • Minimum contribution: 500 TRX
  • Normal price: 10 TRXQ

Roadmap

phone

When is the MATCH Token Pre-Sale started?

There will be a Pre-Sale on 20 - 27 December 2020 which will be opened to the public for enthusiastic investors. From this Pre-Sale, we expect to acquire 5,000,000 MATCH tokens with 6 TRX for each MATCH token. By joining this pre-sale you will have the opportunity to get MATCH tokens at 60% of the market price.

  • Private Sale price: 6 TRX
  • Minimum contribution: 500 TRX
  • Normal price: 10 TRX

How do I get MATCH tokens during the Sale event?

It is very simple. What you need to do is have TRX in your wallet and you can just click the “Buy MATCH token" link on our site.

Can you recommend a digital wallet?

Most people are using the TRON Link wallet. Disclaimer: The MATCH team does not endorse, recommend, or make any representations with respect to digital wallets. It’s advisable to always conduct your own due diligence before trusting any third party or third-party technology.

How can I get a MATCH token after the Sale event?

You will be able to trade MATCH once MATCH listed in Justswap.io which we aim to be listed in January 2021. Disclaimer: Please note that the MATCH team does not endorse, recommend, or make any representations with respect to Internet lists or exchanges more generally. Every exchange has a different process for trading MATCH tokens and their customer support and policies and practices may vary widely. It’s advisable to conduct your own due diligence before trusting any third party or third-party technology.

Can I get an airdrop from MATCH Token?

MATCH will announce the airdrop the very first time we launch our product, and the airdrop itself will be dropped in Q1 2021. Make sure you will not miss this opportunity, follow our community channel to keep yourself updated

Instagram : https://www.instagram.com/matchtoken/

ICO DATE: Dec 6, 2020 - Dec 27, 2020

Private Sale: Dec 6 — Dec 13, 2020

Private Sale price: 5 TRX (50% Discount from the public sale price)

Pre-Sale: Dec 20 — Dec 27, 2020

Private Sale price: 6 TRX (40% Discount from the public sale price)

Would you like to earn many tokens and cryptocurrencies right now! ☞ CLICK HERE

Looking for more information…

☞ Website
☞ Explorer
☞ Whitepaper

Create an Account and Trade Cryptocurrency NOW

Binance
Bittrex
Poloniex

Thank for visiting and reading this article! I’m highly appreciate your actions! Please share if you liked it!

#blockchain #crypto #match #match token

Deep Shah

Deep Shah

1603255867

ICO Development Company | Hire ICO Developer in India | ICO Consulting

We at ICO Development cover all the major steps or activities i.e. light paper & white paper drafting, coin or token creation, ICO fundraising dashboard, coin drop, marketing plan, bounty management etc. that will help you to raise a successful ICO.

#ico development #ico development services #ico solutions #ico services #ico development company

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 

Deep Shah

Deep Shah

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