Crypto Like

Crypto Like

1606199826

What is Lock3r Network (LK3R) | What is LK3R token

Lock3r Network is a decentralized keeper network for projects that need external devops and for external teams to find locker jobs - a fundamental example of a MaaS (Maintenance as a Service) protocol.

Lock3rs

A Locker in our project is the term used to refer to an external person and/or team that executes a job, ordinarily these we’re called Keepers. This can be as simplistic as calling a transaction, or as complex as requiring extensive off-chain logic. The scope of Lock3r network is not to manage these jobs themselves, but to allow contracts to register as jobs for lockers, and lockers to register themselves as available to perform jobs. It is up to the individual locker to set up their devops and infrastructure and create their own rules based on what transactions they deem profitable.

Jobs

A Job is the term used to refer to a smart contract that wishes an external entity to perform an action. They would like the action to be performed in “good will” and not have a malicious result. For this reason they register as a job, and lockers can then execute on their contract.

Becoming a Locker

To join as a Locker you call bond(uint) on the Lock3r contract. You do not need to have LK3R tokens to join as a Locker, so you can join with bond(0). There is a 2 day bonding delay before you can activate as a Locker. Once the 2 days have passed, you can call activate(). Once activated your lastJob timestamp will be set to the current block timestamp.

Registering a Job

A job can be any system that requires external execution, the scope of Lock3r is not to define or restrict the action taken, but to create an incentive mechanism for all parties involved. There are two cores ways to create a Job;

Registering a Job via Governance

If you prefer, you can register as a job by simply submitting a proposal via Governance, to include the contract as a job. If governance approves, no further steps are required.

Registering a Job via Contract Interface

You can register as a job by calling addLiquidityToJob(address,uint) on the Lock3r contract. You must not have any current active jobs associated with this account. Calling addLiquidityToJob(address,uint) will create a pending Governance vote for the job specified by address in the function arguments. You are limited to submit a new job request via this address every 14 days.

Job Interface

Some contracts require external event execution, an example for this is the harvest() function in the yearn ecosystem, or the update(address,address) function in the uniquote ecosystem. These normally require a restricted access control list, however these can be difficult for fully decentralized projects to manage, as they lack devops infrastructure.

These interfaces can be broken down into two types, no risk delta (something like update(address,address) in uniquote, which needs to be executed, but not risk to execution), and harvest() in yearn, which can be exploited by malicious actors by front-running deposits.

For no, or low risk executions, you can simply call Lock3r.isLocker(msg.sender) which will let you know if the given actor is a locker in the network.

For high, sensitive, or critical risk executions, you can specify a minimum bond, minimum jobs completed, and minimum Locker age required to execute this function. Based on these 3 limits you can define your own trust ratio on these lockers.

So a function definition would look as follows;

function execute() external {  require(Lock3r.isLocker(msg.sender), "Lock3r not allowed");}

At the end of the call, you simply need to call workReceipt(address,uint) to finalize the execution for the locker network. In the call you specify the locker being rewarded, and the amount of LK3R you would like to award them with. This is variable based on what you deem is a fair reward for the work executed.

Example Lock3rJob

interface UniOracleFactory {    function update(address tokenA, address tokenB) external;}​interface Lock3r {    function isLocker(address) external view returns (bool);    function workReceipt(address locker, uint amount) external;}​contract Lock3rJob {    UniOracleFactory constant JOB = UniOracleFactory(0x61da8b0808CEA5281A912Cd85421A6D12261D136);    Lock3r constant LK3R = Lock3r(0x1cEB5cB57C4D4E2b2433641b95Dd330A33185A44);​    function update(address tokenA, address tokenB) external {        require(LK3R.isLocker(msg.sender), "Lock3rJob::update: not a valid locker");        JOB.update(tokenA, tokenB);        LK3R.workReceipt(msg.sender, 1e18);    }}

Job Credits

As mentioned in Job Interface, a job has a set amount of credits that they can award lockers with. To receive credits you do not need to purchase LK3R tokens, instead you need to provide LK3R-WETH liquidity in Uniswap. This will give you an amount of credits equal to the amount of LK3R tokens in the liquidity you provide.

You can remove your liquidity at any time, so you do not have to keep buying new credits. Your liquidity provided is never reduced and as such you can remove it whenever you no longer would like a job to be executed.

To add credits, you simply need to have LK3R-WETH LP tokens, you then call addLiquidityToJob(address,uint) specifying the job in the address and the amount in the uint. This will then transfer your LP tokens to the contract and keep them in escrow. You can remove your liquidity at any time by calling unbondLiquidityFromJob(), this will allow you to remove the liquidity after 14 days by calling removeLiquidityFromJob()

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☞ Website
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What is GEEK

Buddha Community

What is Lock3r Network (LK3R) | What is LK3R token
Crypto Like

Crypto Like

1606199826

What is Lock3r Network (LK3R) | What is LK3R token

Lock3r Network is a decentralized keeper network for projects that need external devops and for external teams to find locker jobs - a fundamental example of a MaaS (Maintenance as a Service) protocol.

Lock3rs

A Locker in our project is the term used to refer to an external person and/or team that executes a job, ordinarily these we’re called Keepers. This can be as simplistic as calling a transaction, or as complex as requiring extensive off-chain logic. The scope of Lock3r network is not to manage these jobs themselves, but to allow contracts to register as jobs for lockers, and lockers to register themselves as available to perform jobs. It is up to the individual locker to set up their devops and infrastructure and create their own rules based on what transactions they deem profitable.

Jobs

A Job is the term used to refer to a smart contract that wishes an external entity to perform an action. They would like the action to be performed in “good will” and not have a malicious result. For this reason they register as a job, and lockers can then execute on their contract.

Becoming a Locker

To join as a Locker you call bond(uint) on the Lock3r contract. You do not need to have LK3R tokens to join as a Locker, so you can join with bond(0). There is a 2 day bonding delay before you can activate as a Locker. Once the 2 days have passed, you can call activate(). Once activated your lastJob timestamp will be set to the current block timestamp.

Registering a Job

A job can be any system that requires external execution, the scope of Lock3r is not to define or restrict the action taken, but to create an incentive mechanism for all parties involved. There are two cores ways to create a Job;

Registering a Job via Governance

If you prefer, you can register as a job by simply submitting a proposal via Governance, to include the contract as a job. If governance approves, no further steps are required.

Registering a Job via Contract Interface

You can register as a job by calling addLiquidityToJob(address,uint) on the Lock3r contract. You must not have any current active jobs associated with this account. Calling addLiquidityToJob(address,uint) will create a pending Governance vote for the job specified by address in the function arguments. You are limited to submit a new job request via this address every 14 days.

Job Interface

Some contracts require external event execution, an example for this is the harvest() function in the yearn ecosystem, or the update(address,address) function in the uniquote ecosystem. These normally require a restricted access control list, however these can be difficult for fully decentralized projects to manage, as they lack devops infrastructure.

These interfaces can be broken down into two types, no risk delta (something like update(address,address) in uniquote, which needs to be executed, but not risk to execution), and harvest() in yearn, which can be exploited by malicious actors by front-running deposits.

For no, or low risk executions, you can simply call Lock3r.isLocker(msg.sender) which will let you know if the given actor is a locker in the network.

For high, sensitive, or critical risk executions, you can specify a minimum bond, minimum jobs completed, and minimum Locker age required to execute this function. Based on these 3 limits you can define your own trust ratio on these lockers.

So a function definition would look as follows;

function execute() external {  require(Lock3r.isLocker(msg.sender), "Lock3r not allowed");}

At the end of the call, you simply need to call workReceipt(address,uint) to finalize the execution for the locker network. In the call you specify the locker being rewarded, and the amount of LK3R you would like to award them with. This is variable based on what you deem is a fair reward for the work executed.

Example Lock3rJob

interface UniOracleFactory {    function update(address tokenA, address tokenB) external;}​interface Lock3r {    function isLocker(address) external view returns (bool);    function workReceipt(address locker, uint amount) external;}​contract Lock3rJob {    UniOracleFactory constant JOB = UniOracleFactory(0x61da8b0808CEA5281A912Cd85421A6D12261D136);    Lock3r constant LK3R = Lock3r(0x1cEB5cB57C4D4E2b2433641b95Dd330A33185A44);​    function update(address tokenA, address tokenB) external {        require(LK3R.isLocker(msg.sender), "Lock3rJob::update: not a valid locker");        JOB.update(tokenA, tokenB);        LK3R.workReceipt(msg.sender, 1e18);    }}

Job Credits

As mentioned in Job Interface, a job has a set amount of credits that they can award lockers with. To receive credits you do not need to purchase LK3R tokens, instead you need to provide LK3R-WETH liquidity in Uniswap. This will give you an amount of credits equal to the amount of LK3R tokens in the liquidity you provide.

You can remove your liquidity at any time, so you do not have to keep buying new credits. Your liquidity provided is never reduced and as such you can remove it whenever you no longer would like a job to be executed.

To add credits, you simply need to have LK3R-WETH LP tokens, you then call addLiquidityToJob(address,uint) specifying the job in the address and the amount in the uint. This will then transfer your LP tokens to the contract and keep them in escrow. You can remove your liquidity at any time by calling unbondLiquidityFromJob(), this will allow you to remove the liquidity after 14 days by calling removeLiquidityFromJob()

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

Looking for more information…

☞ Website
☞ Explorer
☞ Source Code
☞ Social Channel
☞ Coinmarketcap

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

Create an Account and Trade NOW

☞ Binance
☞ Bittrex
☞ Poloniex

#blockchain #bitcoin #cryptocurrency #lock3r network #lk3r

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 

Mohammed Richards

Mohammed Richards

1659601560

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 

Lisa joly

Lisa joly

1624658400

PAID NETWORK Review, Is it worth Investing in? Token Sale Coming Soon !!

Hey guys, in this video I review PAID NETWORK. This is a DeFi project that aims to solve complex legal process using decentralised protocols and DeFi products for 2021.

PAID Network is an ecosystem DAPP that leverages blockchain technology to deliver DeFi powered SMART Agreements to make business exponentially more efficient. We allow users to create their own policy, to ensure they Get PAID.

📺 The video in this post was made by Crypto expat
The origin of the article: https://www.youtube.com/watch?v=ZIU5javfL90
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
Cryptocurrency trading 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
⭐ ⭐ ⭐The project is of interest to the community. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!
☞ **-----CLICK HERE-----**⭐ ⭐ ⭐
Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#bitcoin #blockchain #paid network #paid network review #token sale #paid network review, is it worth investing in? token sale coming soon !!

aaron silva

aaron silva

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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

#create a defi token like safemoon #defi token like safemoon #safemoon token #safemoon token clone #defi token