What is Daiquilibrium (DAIQ) | What is DAIQ token

Daiquilibrium (DAIQ) is an algorithmic stablecoin forked from code written by the Empty Set Dollar (ESD) and Dynamic Det Dollar (DSD) devs.We’ve implemented a few custom features with original code, as well as a redesigned bootstrapping method which gives everyone the opportunity to buy at the same price, maximally reflexive to demand.

For a bulleted summary, please visit the TL;DR at the end.

What’s the issue?

ESD introduced the concept of a non-collateralized stablecoin but carries design elements that seem intended to benefit earlier adopters at the expense of maintaining its peg. DSD refined some issues by improving reflexivity, but maintains a slow response to demand due to overly long lockups. Both rely on centralized, freezable USDC in their design, with ESD going so far as to maintain a USDC treasury, arguably eroding its status as a pure non-collateralized stablecoin.

The advance bootstrapping method of launch, ineffective at distributing tokens fairly based on demand, leads to unnecessary price fluctuations and bloated rewards for early DAO holders. It is unnecessary and counterproductive to limit supply so tightly at launch, which results in early holders massively in profit and capable of singlehandedly impacting the price beyond the bounds of acceptability for a useful stablecoin. This problem is magnified by the extraordinarily over-incentivized early advance calls, and the hoarding of the rewards from those calls out of general circulation, and into the DAO. The competition and massive gas wars around early advances benefit no one but ETH miners and bot makers. It doesn’t have to be this way.

Why DAIQ?

We built Daiquilibrium hoping to solve the issues we see in ESD and its derivatives. We introduce a new launch method, the initial swap offering, allowing anyone to purchase DAIQ in exchange for 1 DAI prior to the start of bootstrapping. Proceeds from the initial swap will fund advance callers to the tune of 150 DAI per epoch. This approach to launch has two key advantages: it tempers the typical price spike at launch, and curbs the fluctuations afterwards by providing a launch method that is reflexive to initial demand.

We’ve introduced a dynamic bootstrapping length which targets a supply of 25m tokens at a fixed rate of 4.5% inflation per epoch, corresponding to a fixed time weighted average price (TWAP) of 1.54 DAI:DAIQ. Please see our bootstrapping length visualizations:

A dynamic bootstrapping length lets our protocol be reflexive to initial demand, without minting an oversupply of tokens, all while staying closer to peg.

Our second change to launch is to pay advance callers in DAI, saving liquidity providers from impermanent loss. Each successful advance call will be paid 150 DAI from the reserves built up during the initial swap. Once the DAI from the swap is exhausted, the protocol will switch to rewarding 100 DAIQ per advance. We believe this is sufficient to incentivize development of automated protocol management, without being overcompensated at the expense of regular users. After all, the protocol is hiring for a job, and holders pay the salary, so best be frugal.

The Daiquilibrium protocol is designed to be more reflexive to demand by varying the length of each epoch depending on the TWAP, between a minimum of 30 minutes and a maximum of 2 hours. A projection of epoch length vs. TWAP is provided below:

Epoch length is calculated using this formula:

let normalizedPrice;

if price > peg

normalizedPrice = peg / price;

else

normalizedPrice = price;

Epoch duration =Min Period + normalized price*(Max Period — Min Period)

with an initial maximum period of 7200 seconds (2 hours) and a minimum period of 1800 seconds (30 minutes).

Active contracts are located at:

• 0x0aF9087FE3e8e834F3339FE4bEE87705e84Fd488 DAO (DAIQS)
• 0x73D9E335669462Cbdd6aa3AdaFe9efeE86a37Fe9 DAIQ
• 0x362f5F2C5855Ff09e542e89b8Ab7f7d0928C62da Oracle
• 0x26B4B107dCe673C00D59D71152136327cF6dFEBf UniswapV2 DAI:DAIQ Pair
• 0x7D9A429e8EBecD2726BD2bc0B843864ba075F0b4 LP Incentivation Pool

TL;DR

• Initial swap offering lets anyone buy DAIQ at $1
• After conclusion of the swap, bootstrapping begins at a fixed 4.5% inflation targeting 25m supply
• Epoch duration is dynamic, and varies between 30 minutes and 2 hours, getting shorter the further it is away from the time weighted average price (TWAP)
• Supply is distributed 40% DAO / 60% LP (favoring liquidity providers)
• Advance callers are paid 150 DAI, transitioning to 100 DAIQ after bootstrap
• DAO exit lockup 24 epochs, LP exit lockup 12 epochs
• After bootstrapping, a maximum supply change of 10% takes effect
• DAIQ keeps the DIP-2 coupon redemption penalties introduced by DSD
• 360 epoch coupon expiry
• Full governance integration
• Custom unit tests to accommodate the changes, including the DAI oracle (i.e. no ZAI bug)
• No team tokens, no premine, everyone acquires tokens the same way during the initial swap

Would you like to earn DAIQ right now! ☞ CLICK HERE

Please add our communication channel to keep you up to date! Looking for more information…

☞ Website ☞ Explorer ☞ Explorer 2 ☞ Source Code ☞ Social Channel, ☞ Social Channel 2 ☞ Message Board☞ Coinmarketcap

Create an Account and Trade Cryptocurrency NOW

☞ Binance ☞ Bittrex ☞ Poloniex ☞ Bitfinex

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

#blockchain #bitcoin #daiquilibrium #daiq

What is GEEK

Buddha Community

What is Daiquilibrium (DAIQ) | What is DAIQ token

Daiquilibrium (DAIQ) is an algorithmic stablecoin forked from code written by the Empty Set Dollar (ESD) and Dynamic Det Dollar (DSD) devs.We’ve implemented a few custom features with original code, as well as a redesigned bootstrapping method which gives everyone the opportunity to buy at the same price, maximally reflexive to demand.

For a bulleted summary, please visit the TL;DR at the end.

What’s the issue?

ESD introduced the concept of a non-collateralized stablecoin but carries design elements that seem intended to benefit earlier adopters at the expense of maintaining its peg. DSD refined some issues by improving reflexivity, but maintains a slow response to demand due to overly long lockups. Both rely on centralized, freezable USDC in their design, with ESD going so far as to maintain a USDC treasury, arguably eroding its status as a pure non-collateralized stablecoin.

The advance bootstrapping method of launch, ineffective at distributing tokens fairly based on demand, leads to unnecessary price fluctuations and bloated rewards for early DAO holders. It is unnecessary and counterproductive to limit supply so tightly at launch, which results in early holders massively in profit and capable of singlehandedly impacting the price beyond the bounds of acceptability for a useful stablecoin. This problem is magnified by the extraordinarily over-incentivized early advance calls, and the hoarding of the rewards from those calls out of general circulation, and into the DAO. The competition and massive gas wars around early advances benefit no one but ETH miners and bot makers. It doesn’t have to be this way.

Why DAIQ?

We built Daiquilibrium hoping to solve the issues we see in ESD and its derivatives. We introduce a new launch method, the initial swap offering, allowing anyone to purchase DAIQ in exchange for 1 DAI prior to the start of bootstrapping. Proceeds from the initial swap will fund advance callers to the tune of 150 DAI per epoch. This approach to launch has two key advantages: it tempers the typical price spike at launch, and curbs the fluctuations afterwards by providing a launch method that is reflexive to initial demand.

We’ve introduced a dynamic bootstrapping length which targets a supply of 25m tokens at a fixed rate of 4.5% inflation per epoch, corresponding to a fixed time weighted average price (TWAP) of 1.54 DAI:DAIQ. Please see our bootstrapping length visualizations:

A dynamic bootstrapping length lets our protocol be reflexive to initial demand, without minting an oversupply of tokens, all while staying closer to peg.

Our second change to launch is to pay advance callers in DAI, saving liquidity providers from impermanent loss. Each successful advance call will be paid 150 DAI from the reserves built up during the initial swap. Once the DAI from the swap is exhausted, the protocol will switch to rewarding 100 DAIQ per advance. We believe this is sufficient to incentivize development of automated protocol management, without being overcompensated at the expense of regular users. After all, the protocol is hiring for a job, and holders pay the salary, so best be frugal.

The Daiquilibrium protocol is designed to be more reflexive to demand by varying the length of each epoch depending on the TWAP, between a minimum of 30 minutes and a maximum of 2 hours. A projection of epoch length vs. TWAP is provided below:

Epoch length is calculated using this formula:

let normalizedPrice;

if price > peg

normalizedPrice = peg / price;

else

normalizedPrice = price;

Epoch duration =Min Period + normalized price*(Max Period — Min Period)

with an initial maximum period of 7200 seconds (2 hours) and a minimum period of 1800 seconds (30 minutes).

Active contracts are located at:

• 0x0aF9087FE3e8e834F3339FE4bEE87705e84Fd488 DAO (DAIQS)
• 0x73D9E335669462Cbdd6aa3AdaFe9efeE86a37Fe9 DAIQ
• 0x362f5F2C5855Ff09e542e89b8Ab7f7d0928C62da Oracle
• 0x26B4B107dCe673C00D59D71152136327cF6dFEBf UniswapV2 DAI:DAIQ Pair
• 0x7D9A429e8EBecD2726BD2bc0B843864ba075F0b4 LP Incentivation Pool

TL;DR

• Initial swap offering lets anyone buy DAIQ at $1
• After conclusion of the swap, bootstrapping begins at a fixed 4.5% inflation targeting 25m supply
• Epoch duration is dynamic, and varies between 30 minutes and 2 hours, getting shorter the further it is away from the time weighted average price (TWAP)
• Supply is distributed 40% DAO / 60% LP (favoring liquidity providers)
• Advance callers are paid 150 DAI, transitioning to 100 DAIQ after bootstrap
• DAO exit lockup 24 epochs, LP exit lockup 12 epochs
• After bootstrapping, a maximum supply change of 10% takes effect
• DAIQ keeps the DIP-2 coupon redemption penalties introduced by DSD
• 360 epoch coupon expiry
• Full governance integration
• Custom unit tests to accommodate the changes, including the DAI oracle (i.e. no ZAI bug)
• No team tokens, no premine, everyone acquires tokens the same way during the initial swap

Would you like to earn DAIQ right now! ☞ CLICK HERE

Please add our communication channel to keep you up to date! Looking for more information…

☞ Website ☞ Explorer ☞ Explorer 2 ☞ Source Code ☞ Social Channel, ☞ Social Channel 2 ☞ Message Board☞ Coinmarketcap

Create an Account and Trade Cryptocurrency NOW

☞ Binance ☞ Bittrex ☞ Poloniex ☞ Bitfinex

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

#blockchain #bitcoin #daiquilibrium #daiq

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.

 

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 

SafeMoon Clone | Create A DeFi Token Like SafeMoon | DeFi token like SafeMoon

SafeMoon is a decentralized finance (DeFi) token. This token consists of RFI tokenomics and auto-liquidity generating protocol. A DeFi token like SafeMoon has reached the mainstream standards under the Binance Smart Chain. Its success and popularity have been immense, thus, making the majority of the business firms adopt this style of cryptocurrency as an alternative.

A DeFi token like SafeMoon is almost similar to the other crypto-token, but the only difference being that it charges a 10% transaction fee from the users who sell their tokens, in which 5% of the fee is distributed to the remaining SafeMoon owners. This feature rewards the owners for holding onto their tokens.

Read More @ https://bit.ly/3oFbJoJ

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SafeMoon Clone | SafeMoon Token Clone | SafeMoon Token Clone Development

The SafeMoon Token Clone Development is the new trendsetter in the digital world that brought significant changes to benefit the growth of investors’ business in a short period. The SafeMoon token clone is the most widely discussed topic among global users for its value soaring high in the marketplace. The SafeMoon token development is a combination of RFI tokenomics and the auto-liquidity generating process. The SafeMoon token is a replica of decentralized finance (DeFi) tokens that are highly scalable and implemented with tamper-proof security.

The SafeMoon tokens execute efficient functionalities like RFI Static Rewards, Automated Liquidity Provisions, and Automatic Token Burns. The SafeMoon token is considered the most advanced stable coin in the crypto market. It gained global audience attention for managing the stability of asset value without any fluctuations in the marketplace. The SafeMoon token clone is completely decentralized that eliminates the need for intermediaries and benefits the users with less transaction fee and wait time to overtake the traditional banking process.

Reasons to invest in SafeMoon Token Clone :

• The SafeMoon token clone benefits the investors with Automated Liquidity Pool as a unique feature since it adds more revenue for their business growth in less time. The traders can experience instant trade round the clock for reaping profits with less investment towards the SafeMoon token.
• It is integrated with high-end security protocols like two-factor authentication and signature process to prevent various hacks and vulnerable activities. The Smart Contract system in SafeMoon token development manages the overall operation of transactions without any delay,
• The users can obtain a reward amount based on the volume of SafeMoon tokens traded in the marketplace. The efficient trading mechanism allows the users to trade the SafeMoon tokens at the best price for farming. The user can earn higher rewards based on the staking volume of tokens by users in the trade market.
• It allows the token holders to gain complete ownership over their SafeMoon tokens after purchasing from DeFi exchanges. The SafeMoon community governs the token distribution, price fluctuations, staking, and every other token activity. The community boosts the value of SafeMoon tokens.
• The Automated Burning tokens result in the community no longer having control over the SafeMoon tokens. Instead, the community can control the burn of the tokens efficiently for promoting its value in the marketplace. The transaction of SafeMoon tokens on the blockchain platform is fast, safe, and secure.

The SafeMoon Token Clone Development is a promising future for upcoming investors and startups to increase their business revenue in less time. The SafeMoon token clone has great demand in the real world among millions of users for its value in the market. Investors can contact leading Infinite Block Tech to gain proper assistance in developing a world-class SafeMoon token clone that increases the business growth in less time.

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