1606180201
What is BIOKKOIN (BKKG) | What is BKKG token
BIOONLINE PTE LTD., a company incorporated in Singapore with roots in India, is a real estate establishment equitized by Crypto-currency. BIOKKOIN is a unique digital asset, with its intrinsic value backed by land bank worth over $70m. BKK Global is equitizing the global real estate space with BIOKKOIN as its cryptoasset of an evolved blockchain that encourages to lend, borrow, stake Real Estate DeFi through the development of a new communiqué and governance protocol. To grow its foot internationally and to give wings to global presence; the global conglomerate has triggered projects in India, Nepal, Sri Lanka, Thailand, Malaysia, Cambodia and Mauritius confined to and adhering universal business guidelines.
It is the company’s mission to deliver value creating spaces, and its endeavors epitomize this philosophy. It does not have a single pending grievance with over 1 million gratified clients. The company has a vast land bank with multiple ongoing projects spread over 2200 acres across Maharashtra and Goa.
It has been remarkable accomplishment by the organization in delivering assurances in record time and
Crypto
BIOKKOIN is a distinctive crypto currency, the first ever ALT coin formed on a Blockchain generated by the Ethereum platform with an INTRINSIC value of asset backing. There are 1000s of crypto currencies, coins and tokens where the founders, projects or valuations are completely absent. They are still doing quite well and there existence is speculative in the future as no backing. BKKG is a medium of exchange that uses cryptography to manage the creation of new coins as well as fully secure the transactions weeding out the need for third party like bank, broker or agencies.
The total number of BIOKKOINs that shall be in circulation is capped at 18 million, mined over a period of 13 years.
BIOKKOIN is a digital asset that was launched on 10/10/2017 at $1(one) and had reached $4(four) during Private Sale. After the launch of White Paper (Legal Manuscript & Prospectus) in March 2018, it kept steadily rising till the end of Pre-Sale on 10/01/2018. The company went public and launched its Initial Coin Offering (ICO) on the 10th January, 2019 till 31st December, 2019 @ $15/-(fifteen) per coin. BKKG is successfully trading on international exchanges since March 2020.
Looking for more information…
☞ Website
☞ Explorer
☞ Source Code
☞ Social Channel
☞ Documentation
☞ 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 #biokkoin #bkkg
What is GEEK
Buddha Community
1606180201
What is BIOKKOIN (BKKG) | What is BKKG token
BIOONLINE PTE LTD., a company incorporated in Singapore with roots in India, is a real estate establishment equitized by Crypto-currency. BIOKKOIN is a unique digital asset, with its intrinsic value backed by land bank worth over $70m. BKK Global is equitizing the global real estate space with BIOKKOIN as its cryptoasset of an evolved blockchain that encourages to lend, borrow, stake Real Estate DeFi through the development of a new communiqué and governance protocol. To grow its foot internationally and to give wings to global presence; the global conglomerate has triggered projects in India, Nepal, Sri Lanka, Thailand, Malaysia, Cambodia and Mauritius confined to and adhering universal business guidelines.
It is the company’s mission to deliver value creating spaces, and its endeavors epitomize this philosophy. It does not have a single pending grievance with over 1 million gratified clients. The company has a vast land bank with multiple ongoing projects spread over 2200 acres across Maharashtra and Goa.
It has been remarkable accomplishment by the organization in delivering assurances in record time and
Crypto
BIOKKOIN is a distinctive crypto currency, the first ever ALT coin formed on a Blockchain generated by the Ethereum platform with an INTRINSIC value of asset backing. There are 1000s of crypto currencies, coins and tokens where the founders, projects or valuations are completely absent. They are still doing quite well and there existence is speculative in the future as no backing. BKKG is a medium of exchange that uses cryptography to manage the creation of new coins as well as fully secure the transactions weeding out the need for third party like bank, broker or agencies.
The total number of BIOKKOINs that shall be in circulation is capped at 18 million, mined over a period of 13 years.
BIOKKOIN is a digital asset that was launched on 10/10/2017 at $1(one) and had reached $4(four) during Private Sale. After the launch of White Paper (Legal Manuscript & Prospectus) in March 2018, it kept steadily rising till the end of Pre-Sale on 10/01/2018. The company went public and launched its Initial Coin Offering (ICO) on the 10th January, 2019 till 31st December, 2019 @ $15/-(fifteen) per coin. BKKG is successfully trading on international exchanges since March 2020.
Looking for more information…
☞ Website
☞ Explorer
☞ Source Code
☞ Social Channel
☞ Documentation
☞ 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 #biokkoin #bkkg
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
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
1621844791
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.
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- 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.
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