1637546438
ZatCoin Tools
Zatcointools platform will ensure you are upto date with the ever-changing Crypto world. Here we will provide protection against scams and launch verified projects on our Launchpad. A learning platform (ZAT academy) this will regularly be updated. You will find detailed information to get you started on your crypto journey. Zatcoin holders will recieve exclusive benefits including access to presales on our Launchpad. Dependent on how much Zatcoin you hold you will have access to more user benefits. We will list existing projects that we have verified. Verification of team and the business model and viability of the project will be required to list the project. There will be no paid listings so our level of investor protection will never be compromised by bad practices!
ZAT Marketplace
This is a unique concept and huge for developers enabling them to find the best crypto related services quickly and easily. All in one place just to name a few on ZAT market we wil have verified influencers, marketing managers, moderators, developers, graphic designers and more. Applications have already begun please contact us if you would like to be part of ZAT marketplace. Why choose ZAT Market?
Currently as you may be aware there are thousands of people who are offering services on all social platforms however we are unaware of who they are and what their intentions are. ZAT market will no only save you time with ZAT marketplace you will be sure to recieve the services you pay for or your money back!
ZAT Exchange
Our aim is to make ZAT exchange the safest place to find and trade Crypto on. Only KYC listed projects and manually verified contracts will be marked as verified. All verified projects will be on our verified projects section and highlighted on our platform. You will be able to swap any token even if it has not been verified by us. We will accept upvotes from ZAT community to fast track verification for the most popular projects to ensure we keep up with verifying the hottest projects. Our aim is to create an exchange with ease of use. This further helps our goal of humanising Crypto, currently the complexity of Crypto is far higher than it should be we will make sure ZAT platform changes that. Our long term goal with ZAT exchange is to become the most trusted crypto exchange in the world!
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1658068560
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.
["Bayrūt"]
and not ["Bayr", "ū", "t"]
, for example.Add this line to your application's Gemfile:
gem 'words_counted'
And then execute:
$ bundle
Or install it yourself as:
$ gem install words_counted
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.
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
.
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.
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
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.
:odd?
.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"]
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"]
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")
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.
The program will normalise (downcase) all incoming strings for consistency and filters.
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.
Visit this website for one example of what you can do with WordsCounted.
Contributors
See contributors.
git checkout -b my-new-feature
)git commit -am 'Add some feature'
)git push origin my-new-feature
)Author: Abitdodgy
Source Code: https://github.com/abitdodgy/words_counted
License: MIT license
1659601560
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.
Visit this website for one example of what you can do with WordsCounted.
["Bayrūt"]
and not ["Bayr", "ū", "t"]
, for example.Add this line to your application's Gemfile:
gem 'words_counted'
And then execute:
$ bundle
Or install it yourself as:
$ gem install words_counted
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.
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
.
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.
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
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.
:odd?
.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"]
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"]
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")
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.
The program will normalise (downcase) all incoming strings for consistency and filters.
def self.from_url
# open url and send string here after removing html
end
See contributors.
git checkout -b my-new-feature
)git commit -am 'Add some feature'
)git push origin my-new-feature
)Author: abitdodgy
Source code: https://github.com/abitdodgy/words_counted
License: MIT license
#ruby #ruby-on-rails
1622197808
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
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.
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.
#safemoon token #safemoon token clone #safemoon token clone development #defi token
1624230000
How to Buy FEG Token - The EASIEST Method 2021
In today’s video, I will be showing you guys how to buy the FEG token/coin using Trust Wallet and Pancakeswap. This will work for both iOS and Android devices!
📺 The video in this post was made by More LimSanity
The origin of the article: https://www.youtube.com/watch?v=LAVwpiEN6bg
🔺 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.
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