1630995638
In this article, we'll discuss information about the DogeZoo project and DZOO token.
DogeZoo is a crypto project that where game-fi, NFT and meme met. Have you ever thought of buying all those cute memecoins out there, or owning all those cute NFT? Are you the type of people that are not very great with playing games, but love the idea of game-fi as well? DogeZoo, is basically a “zoo” that all cute animals are gonna live in, and one can acquire them based on luck!
It is easy to understand, fun to play, and most importantly you can play-to-earn and collect rare meme NFT. It is never too late to join Dogezoo!!
Meme Based
Every dog that coming will be cute and meme related animals, like doge, shiba, Samoyed. And they will have different behaviours with different toys, just like some rare dogs will only be attracted by certain food. Cute to attract them to get some worthy NFT!
Ready to collect them all?
NFT
When a new dog comes to your Dogezoo, you will earn a new NFT card for that new dog. We will be having 4 levels of dogs, and the most rare ones would be the most expensive. This is how meme, NFT, game-fi combined to be a play-to-earn NFT meme project!
Gameplay
You're gonna be the owner of this Dogezoo! However, this Dogezoo is empty and under-developed; therefore no dogs are willing to live here. Therefore, you have to purchase food and toys to attract more
GameFi
Neko Atsume is a famous mobile cat collecting game, but then why can’t we have a dog collecting game in blockchain when Gamefi is so popular nowadays? We all know how people in crypto space love dogs, then why can’t gamefi incorporate that? You can collect cute dogs, and in the future other animals as well in our Dogezoo simply by placing different foods and toys to attract them. Then dogs will appear over time, and you can collect them as NFT cards and also watch how they play with the toys that you placed!
Buying, waiting, collecting doges - Easy to play!
Most of the animals appearing in our Dogezoo are going to be famous meme related animals, doge, shiba, Samoyed etc. It will be exciting to see how these cute animals interact with the toys you just bought, and how they are attracted by different types of food as well. They will be super cute and you would love every minute you spent on this zoo, as you are your Dogezoo owner!
NFT
When a new dog comes to your Dogezoo, you will earn a new NFT card for that new dog. Some dogs will appear over and over again, while some are rare and you might not be seeing them even with numerous tries. We will be having 4 levels of dogs: 1) Common (60%) 2) Regular (30%) 3) Rare (9%) 4) Legend (1%) And of course based on the level and the difficulty, different NFT cards will be priced differently. There will be a NFT marketplace built in our game. Players can trade their NFT cards using our native tokens $DZOO. On the other hand, one also has to purchase food and toys with our native tokens $DZOO as well. Therefore $DZOO has an actual use case, and it will build a system that avoids inflation due to this closed and well-planned economy.
Metaverse
For now we are still focusing on building and upgrading our Dogezoo game, but eventually we will expand our project. Not only Dogezoo will have more cute animals other than dogs, we will also have more games being built. It will turn Dogezoo into an Amusement Park, with different games booths and a large zoo with different animals. NFT that one acquired from the early stage would have more features in the future. The metaverse will be filled with different games, and an Amusement park that is fun and play-to-earn based will be constructed in the long run!
Unique Features
We hope to make an easy to play but fun game, as we are seeing the potential of gameFi. However, blockchain game is still a small circle thing and is yet to realize its full potential. The vast majority of people still don’t know what is gameFi, but the cat collection game was popular in the mainstream. This is the reason we are combining gameFi, NFT and meme together, because we want to make Dogezoo famous and accessible to the mainstream as well.
Gamefi, NFT, meme combined project
Reflection tax to reward long term holders
Built in NFT marketplace
Clearly designed tokenomics with real use case
Tokenomics
Total Supply: 420,000,000,000,000,000 $DZOO
30% Burned
So whenever transaction happen some $DZOO would be sent to the dead address and make $DZOO a deflationary token!
12% Play-To-Earn Token
Play-To-Earn Token will be reserved and locked in contract for future development
53% Liquidity
5% Airdrops
Will be distributed in different phases or reached our next milestone!
On every transaction:
5% will redistribute to all holders
5% will be automatically added to the Liquidity Pool
2% will be reflected to the marketing wallet for occassionally buy back and burn, and for marketing activities.
Please Set Slippage to 15%, and if still can’t swap; try higher slippage to 20% or round up your numbers in Pancakeswap.
If problem persists, please do not hestitate to contact us via Telegram as our admin are always here.
How and Where to Buy DZOO token?
DZOO token is now live on the Binance mainnet. The token address for DZOO is 0x5419291d81c68c103363e06046f40a9056ab2b7f. Be cautious not to purchase any other token with a smart contract different from this one (as this can be easily faked). We strongly advise to be vigilant and stay safe throughout the launch. Don’t let the excitement get the best of you.
Just be sure you have enough BNB in your wallet to cover the transaction fees.
Join To Get BNB (Binance Coin)! ☞ CLICK HERE
You will have to first buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…
We will use Binance Exchange here as it is one of the largest crypto exchanges that accept fiat deposits.
Once you finished the KYC process. You will be asked to add a payment method. Here you can either choose to provide a credit/debit card or use a bank transfer, and buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…
Step by Step Guide : What is Binance | How to Create an account on Binance (Updated 2021)
Next step
You need a wallet address to Connect to Pancakeswap Decentralized Exchange, we use Metamask wallet
If you don’t have a Metamask wallet, read this article and follow the steps
☞What is Metamask wallet | How to Create a wallet and Use
Transfer $BNB to your new Metamask wallet from your existing wallet
Next step
Connect Metamask Wallet to Pancakeswap Decentralized Exchange and Buy, Swap DZOO token
Contract: 0x5419291d81c68c103363e06046f40a9056ab2b7f
Read more: What is Pancakeswap | Beginner’s Guide on How to Use Pancakeswap
The top exchange for trading in DZOO token is currently: PancakeSwap (V2)
Find more information DZOO token
☞ Website ☞ Explorer ☞ Social Channel ☞ Social Channel 2 ☞ Social Channel 3 ☞ Coinmarketcap
🔺DISCLAIMER: The Information in the post isn’t financial advice, is intended FOR GENERAL INFORMATION PURPOSES ONLY. Trading Cryptocurrency 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)!
☞ **-----https://geekcash.org-----**⭐ ⭐ ⭐
Thank for visiting and reading this article! Please don’t forget to leave a like, comment and share!
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.
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 #feg token #token #how to buy feg token #how to buy feg token - the easiest method 2021