1613633924
What is Modefi (MOD) | What is Modefi token | What is MOD token
Modefi’s main objective is developing Oracle blockchain solutions that empower true decentralization of data on-chain for integration via Smart Contracts. Modefi’s suite of Oracle solutions will provide higher level transparency, precise data, and a fully trustless ecosystem.
Oracle manipulation has been one of the biggest culprits when it comes to contracts and DeFi hacks. Protocols are exposing their users to potentially massive risks when relying on centralized or single data point oracles within their eco-systems.
Modefi’s Oracle Solution Suite will allow DeFi protocols to reduce the potential of putting their users’ hard earned capital at risk due to unforeseen circumstances.
On-Demand Oracle Solution
Leveraging Modefi’s by design decentralized model, the platform introduces the ability for developers and end users to obtain one-time and uncommon data requests to meet the demands of their custom smart contracts that are reliant on outside data sources that may not have API’s.
What is an Oracle?
A data oracle provides the transfer of real world data to smart contracts on the blockchain.
Why are Oracles needed?
Blockchains and smart contracts don’t have direct access to off-chain (real world) data. However, for many smart contracts, it is important to have relevant information from the outside world to function as intended.
This is where oracles are necessary, as they provide a connection between off-chain and on-chain executions. Oracles are extremely important to the blockchain ecosystem since they open a gateway of possibilities to smart contract uses.
The Problem
Finding a Oracle data provider is proven to be difficult for small one-off or uncommon data requirements. Typically most trusted Oracles stick with the common data outputs. E.g. The price of a popular cryptocurrency. This currently works for a large portion of data requirements on-chain at the moment, but with adoption of smart contracts in other sectors like insurance, gambling, or voting, the need for all types of data on-chain will grow exponentially.
The Modefi Solution
At Modefi we understand the importance of off-chain data requests regardless if the requirements are ongoing or one-off tasks.
The On-Demand data oracle comprises a P2P network built around smart contracts and EOA’s. It’s designed to be easy to use and integrate by end users, developers and data validators.
Data reporters (validators) may be subject to Governance, and other means of social verification. Prior to being eligible to report data, the validator bonds collateral (if required by client) and will be rewarded upon successful consensus of the data they provide. Providing incorrect or manipulated data will result in the validator being disqualified from future requests and at risk of losing their stake.
With the use of Modefi’s P2P On-Demand data oracle it opens up the possibility for small data requests ranging from a friendly wager on who will win the next presidential campaign, or a multi-million dollar decentralized sports betting platform needing the score for tonight’s big game.
What can this data be used for?
- E-Sports
- Sporting Events
- Elections
- Voting
- Weather conditions in a location at a specific time
- Prediction Markets
- P2P wagers
- Insurance Payouts
How it works
Bob and Alice decide to create a friendly wager smart contract to bet on who will win the next Presidential Election. The smart contract allows both parties to submit their pick and deposit the wager amount. The wager smart contract is programmed to only accept the winning result from a custom oracle contract deployed on the Modefi network.
The oracle contract is deployed automatically after Bob and Alice fill out all the relative information on the Modefi oracle dApp.
This information includes but is not limited to
- Brief description of the data requested
- Where the result data should be sourced from
- List of potential outcomes
- Event timer
- Required number of validators for consensus
- Required value of tokens staked by validator
- Minimum reputation
- Validator Incentive
Once the oracle contract is deployed and the required timer has expired, eligible validators can start submitting their results. After the minimum number of validators have submitted data, the contract will reach consensus and the results will be available on-chain for the wager contract to react accordingly. The wager contract will then allow the winner to withdraw their funds.
Decentralized Aggregated Oracle Solution
There is a big problem with today’s oracle providers, which is currently inhibiting them from reaching their potential value and use cases. Oracles at present are not fully trustless, transparent or decentralized. When oracles can overcome this problem, adoption will scale to an entirely new level and into the mainstream with it bringing an influx of money into the Decentralized Finance markets.
What is an Oracle?
A data oracle (such as Chainlink, Tellor, Band etc.) provides the transfer of real world data to smart contracts on the blockchain.
Why are Oracles needed?
Blockchains and smart contracts don’t have direct access to off-chain (real world) data. However, for many smart contracts, it is important to have relevant information from the outside world to function as intended.
This is where oracles are necessary, as they provide a connection between off-chain and on-chain data. Oracles are extremely important to the blockchain ecosystem because they open a gateway of possibilities to smart contract uses.
The Oracle Problem
Since smart contracts execute decisions based on data provided by oracles, they are key to a healthy blockchain ecosystem. The main challenge with designing oracles is that if the oracle is compromised, the smart contract relying on it is also affected. This is often referred to as The Oracle Problem.
Since oracles are not part of the main blockchain consensus, they are unfortunately not part of the security mechanisms that public blockchains can provide. The trust conflict between third-party oracles and the trustless execution of smart contracts remains a mostly unsolved issue.
Man-in-the-middle attacks can also be a threat, where a malicious actor gains access to the data flow between the oracles and the contract and modifies or falsifies the data.
The Modefi DAOS Solution
Modefi integrates major oracle and data providers to use them as complementary entities instead of treating them as competition. Integrating multiple oracles into the platform gives clients using Modefi’s DAOS the ability to obtain trustless, transparent, secure, and decentralized data.
Aggregation of on-chain data
To maximize the security and precision behind the data provided by an Oracle, multiple Oracles across multiple networks must be used simultaneously. Outliers, malicious actors, and
corrupt data are removed autonomously with no outside interaction through the use of Smart Contracts and multiple transparent data sources.
Modefi’s DAOS is a game-changing solution for DeFi, and clients that require the utmost reliable and trustless oracle data. It’s time to put an end to one of the most extensive problems known to blockchain once and for all.
Modefi Sale Details / Tokenomics
Token Name: Modefi
Token Ticker: MOD
Token Type: ERC20
Max Total Supply: 22 Million
Circ. Supply on Listing: 2,860,000.00 MOD
Uniswap Listing Price: $0.24
Marketcap on Listing: $686,400.00
Venture — 3 M MOD tokens — $0.12 each
20% unlock on listing Vested for 90 Days
Strategic — 1.4 M MOD tokens — $0.18 each
15% unlock on listing Vested for 90 Days
Public — 7 M MOD tokens — $0.20 each
20% unlock on listing Vested for 60 Days
Token Distribution
Sale (Vesting 60–90 Days) — 11.4 Million MOD
Fully released after 90 Days
Team (Locked for 6 months, then 3 years vesting) — 1.5 Million MOD
Fully released after 3 years and 6 months
Foundation (Unlocked — Non circulating) — 4.5 Million MOD Marketing, Strategic Partners, Advisors, Infrastructure, Development and Exchanges
Core Partners (Locked for 6 months, then 3 years vesting) — 2 Million MOD Fully released after 3 years and 6 months
Validation / Staking Rewards / AD (No lock, 1 year vesting) — 1.95 Million MOD
Fully released after 1 year
Uniswap Tokens for Liquidity ~650,000 MOD
Looking for more information…
☞ Website ☞ Explorer ☞ Explorer 2 ☞ Whitepaper ☞ Source Code ☞ Social Channel ☞ Social Channel 2 ☞ Message Board ☞ Coinmarketcap
Would you like to earn MOD right now! ☞ CLICK HERE
Top exchanges for token-coin trading. Follow instructions and make unlimited money
☞ Binance ☞ Bittrex ☞ Poloniex ☞ Bitfinex ☞ Huobi
Thank for visiting and reading this article! I’m highly appreciate your actions! Please share if you liked it!
#cryptocurrency #bitcoin #modefi #mod
What is GEEK
Buddha Community
1613633924
What is Modefi (MOD) | What is Modefi token | What is MOD token
Modefi’s main objective is developing Oracle blockchain solutions that empower true decentralization of data on-chain for integration via Smart Contracts. Modefi’s suite of Oracle solutions will provide higher level transparency, precise data, and a fully trustless ecosystem.
Oracle manipulation has been one of the biggest culprits when it comes to contracts and DeFi hacks. Protocols are exposing their users to potentially massive risks when relying on centralized or single data point oracles within their eco-systems.
Modefi’s Oracle Solution Suite will allow DeFi protocols to reduce the potential of putting their users’ hard earned capital at risk due to unforeseen circumstances.
On-Demand Oracle Solution
Leveraging Modefi’s by design decentralized model, the platform introduces the ability for developers and end users to obtain one-time and uncommon data requests to meet the demands of their custom smart contracts that are reliant on outside data sources that may not have API’s.
What is an Oracle?
A data oracle provides the transfer of real world data to smart contracts on the blockchain.
Why are Oracles needed?
Blockchains and smart contracts don’t have direct access to off-chain (real world) data. However, for many smart contracts, it is important to have relevant information from the outside world to function as intended.
This is where oracles are necessary, as they provide a connection between off-chain and on-chain executions. Oracles are extremely important to the blockchain ecosystem since they open a gateway of possibilities to smart contract uses.
The Problem
Finding a Oracle data provider is proven to be difficult for small one-off or uncommon data requirements. Typically most trusted Oracles stick with the common data outputs. E.g. The price of a popular cryptocurrency. This currently works for a large portion of data requirements on-chain at the moment, but with adoption of smart contracts in other sectors like insurance, gambling, or voting, the need for all types of data on-chain will grow exponentially.
The Modefi Solution
At Modefi we understand the importance of off-chain data requests regardless if the requirements are ongoing or one-off tasks.
The On-Demand data oracle comprises a P2P network built around smart contracts and EOA’s. It’s designed to be easy to use and integrate by end users, developers and data validators.
Data reporters (validators) may be subject to Governance, and other means of social verification. Prior to being eligible to report data, the validator bonds collateral (if required by client) and will be rewarded upon successful consensus of the data they provide. Providing incorrect or manipulated data will result in the validator being disqualified from future requests and at risk of losing their stake.
With the use of Modefi’s P2P On-Demand data oracle it opens up the possibility for small data requests ranging from a friendly wager on who will win the next presidential campaign, or a multi-million dollar decentralized sports betting platform needing the score for tonight’s big game.
What can this data be used for?
- E-Sports
- Sporting Events
- Elections
- Voting
- Weather conditions in a location at a specific time
- Prediction Markets
- P2P wagers
- Insurance Payouts
How it works
Bob and Alice decide to create a friendly wager smart contract to bet on who will win the next Presidential Election. The smart contract allows both parties to submit their pick and deposit the wager amount. The wager smart contract is programmed to only accept the winning result from a custom oracle contract deployed on the Modefi network.
The oracle contract is deployed automatically after Bob and Alice fill out all the relative information on the Modefi oracle dApp.
This information includes but is not limited to
- Brief description of the data requested
- Where the result data should be sourced from
- List of potential outcomes
- Event timer
- Required number of validators for consensus
- Required value of tokens staked by validator
- Minimum reputation
- Validator Incentive
Once the oracle contract is deployed and the required timer has expired, eligible validators can start submitting their results. After the minimum number of validators have submitted data, the contract will reach consensus and the results will be available on-chain for the wager contract to react accordingly. The wager contract will then allow the winner to withdraw their funds.
Decentralized Aggregated Oracle Solution
There is a big problem with today’s oracle providers, which is currently inhibiting them from reaching their potential value and use cases. Oracles at present are not fully trustless, transparent or decentralized. When oracles can overcome this problem, adoption will scale to an entirely new level and into the mainstream with it bringing an influx of money into the Decentralized Finance markets.
What is an Oracle?
A data oracle (such as Chainlink, Tellor, Band etc.) provides the transfer of real world data to smart contracts on the blockchain.
Why are Oracles needed?
Blockchains and smart contracts don’t have direct access to off-chain (real world) data. However, for many smart contracts, it is important to have relevant information from the outside world to function as intended.
This is where oracles are necessary, as they provide a connection between off-chain and on-chain data. Oracles are extremely important to the blockchain ecosystem because they open a gateway of possibilities to smart contract uses.
The Oracle Problem
Since smart contracts execute decisions based on data provided by oracles, they are key to a healthy blockchain ecosystem. The main challenge with designing oracles is that if the oracle is compromised, the smart contract relying on it is also affected. This is often referred to as The Oracle Problem.
Since oracles are not part of the main blockchain consensus, they are unfortunately not part of the security mechanisms that public blockchains can provide. The trust conflict between third-party oracles and the trustless execution of smart contracts remains a mostly unsolved issue.
Man-in-the-middle attacks can also be a threat, where a malicious actor gains access to the data flow between the oracles and the contract and modifies or falsifies the data.
The Modefi DAOS Solution
Modefi integrates major oracle and data providers to use them as complementary entities instead of treating them as competition. Integrating multiple oracles into the platform gives clients using Modefi’s DAOS the ability to obtain trustless, transparent, secure, and decentralized data.
Aggregation of on-chain data
To maximize the security and precision behind the data provided by an Oracle, multiple Oracles across multiple networks must be used simultaneously. Outliers, malicious actors, and
corrupt data are removed autonomously with no outside interaction through the use of Smart Contracts and multiple transparent data sources.
Modefi’s DAOS is a game-changing solution for DeFi, and clients that require the utmost reliable and trustless oracle data. It’s time to put an end to one of the most extensive problems known to blockchain once and for all.
Modefi Sale Details / Tokenomics
Token Name: Modefi
Token Ticker: MOD
Token Type: ERC20
Max Total Supply: 22 Million
Circ. Supply on Listing: 2,860,000.00 MOD
Uniswap Listing Price: $0.24
Marketcap on Listing: $686,400.00
Venture — 3 M MOD tokens — $0.12 each
20% unlock on listing Vested for 90 Days
Strategic — 1.4 M MOD tokens — $0.18 each
15% unlock on listing Vested for 90 Days
Public — 7 M MOD tokens — $0.20 each
20% unlock on listing Vested for 60 Days
Token Distribution
Sale (Vesting 60–90 Days) — 11.4 Million MOD
Fully released after 90 Days
Team (Locked for 6 months, then 3 years vesting) — 1.5 Million MOD
Fully released after 3 years and 6 months
Foundation (Unlocked — Non circulating) — 4.5 Million MOD Marketing, Strategic Partners, Advisors, Infrastructure, Development and Exchanges
Core Partners (Locked for 6 months, then 3 years vesting) — 2 Million MOD Fully released after 3 years and 6 months
Validation / Staking Rewards / AD (No lock, 1 year vesting) — 1.95 Million MOD
Fully released after 1 year
Uniswap Tokens for Liquidity ~650,000 MOD
Looking for more information…
☞ Website ☞ Explorer ☞ Explorer 2 ☞ Whitepaper ☞ Source Code ☞ Social Channel ☞ Social Channel 2 ☞ Message Board ☞ Coinmarketcap
Would you like to earn MOD right now! ☞ CLICK HERE
Top exchanges for token-coin trading. Follow instructions and make unlimited money
☞ Binance ☞ Bittrex ☞ Poloniex ☞ Bitfinex ☞ Huobi
Thank for visiting and reading this article! I’m highly appreciate your actions! Please share if you liked it!
#cryptocurrency #bitcoin #modefi #mod
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.
- A space-delimited string. The filter will normalise the string.
- A regular expression.
- A lambda.
- A symbol that names a predicate method. For example
:odd?. - 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
- Fork it
- Create your feature branch (
git checkout -b my-new-feature) - Commit your changes (
git commit -am 'Add some feature') - Push to the branch (
git push origin my-new-feature) - Create new Pull Request
Author: abitdodgy
Source code: https://github.com/abitdodgy/words_counted
License: MIT license
#ruby #ruby-on-rails
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.
- A space-delimited string. The filter will normalise the string.
- A regular expression.
- A lambda.
- A symbol that names a predicate method. For example
:odd?. - 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.
Demo
Visit this website for one example of what you can do with WordsCounted.
Contributors
See contributors.
Contributing
- Fork it
- Create your feature branch (
git checkout -b my-new-feature) - Commit your changes (
git commit -am 'Add some feature') - Push to the branch (
git push origin my-new-feature) - Create new Pull Request
Author: Abitdodgy
Source Code: https://github.com/abitdodgy/words_counted
License: MIT license
1622197808
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