1635857835
Why are TRON tokens a better choice for ICO?
ICO has been a reliable source to raise funds for business. It has played a major role in helping to develop businesses. In 2017 almost $252 million funds were collected through ICO. Telegram - the popular messaging app, has raised $17 million through ICO. This is how much investors have trust in ICO.
But there are a few regulations that will make your ICO more efficient. For instance, crypto tokens have a great impact on ICO like their blockchain platform and standards. So it is mandatory to select the blockchain platform and the token standard heedfully. Experts will recommend the ERC20 standard of Ethereum. Yes, it is pretty much good. But the problem is that the Ethereum blockchain requires high costs for transactions at a low transaction speed. So, still, wondering which one to choose? You can go with the TRON blockchain. TRON has been more supportive of ICO over the years. Let me provide you with some facts on TRON.
- TRON has more popularity compared to many of the blockchain networks. This popularity will work against your crypto enthusiasts who are potential investors. You can attract more investors with a popular token.
- The transaction cost of TRON is comparatively low and also has high transaction speed. This is another feature that will help you in attracting more investors.
- After all, TRON provides a high-security level.
Apart from these, TRON has two standards that could help you in ICO. TRC10 & TRC20. TRC10 is the basic token standard that is easy to create. Yet, it has a few issues. TRC20 token has more reasons to be used in ICO. It is an updated version of TRC10. As a matter of fact, TRC20 implies smart contracts. Creating a TRC20 token can be done by any tech-savvy individual. But, to imply a smart contract requires more attention. Smart contracts are immutable, and thus once implied, you cannot make changes in them. So you will require the guidance of an expert to finish the job. Or you can just hire a TRON token development company to do your work. But, there are many token creation companies out there. Worry not. I have done some groundwork to find out that Zab Technologies - a renowned blockchain development company, are quite good with TRON token development services. All you need to do is contact them and provide a list of functionalities required for your token. You can contact them via
Mail-id: contact@zabtechnologies.net
Whatsapp: +91 77085 29089
Telegram: https://t.me/Zabtechnologies
skype: live:contact_86571
What is GEEK
Buddha Community
1622544031
Tron - What is TRX? Is it Worth Buying Tron in 2021?
Tron is one of the most popular cryptocurrencies in this market, practically since its birth in 2017,
Opinions are strongly divided between those who, on the one hand, believe in the value of the project and, on the other, believe that the currency is no more than a fad.
In part, this is also due to the personality of its CEO, Justin Sun, who does everything to be media, since he knows that this is a way to boost the growth of the project.
Tron has competed to be among the top cryptocurrencies, conquering a place in the Top 10 of the market repeatedly. But why? Could it be that this project has value? In this article, we will make it clear what the objective of this cryptocurrency is and how you can invest in Tron safely.
What is Tron?
The project of this cryptocurrency was born in 2017, created by Justin Sun, current CEO of Tron Foundation - a non-profit company based in Singapore.
Its token is known as Tronix (TRX). It initially started as an ERC20 token (that is, it existed on the Ethereum blockchain ).
However, in 2018 Tron successfully concluded the launch of its blockchain.
Tron aims to build a decentralized ecosystem of entertainment content, which facilitates the creation and dissemination of the same.
One Step Back …
To better contextualize, it is necessary to take a step back and understand the business model of the entertainment platforms that lead the current market …
Platforms such as YouTube host the content produced by our favorite creators ( streamers, YouTubers, series, songs, etc.) which we can later access and consume for hours and hours of entertainment.
What do those platforms gain from that?
Access to this content may be free or require a monthly subscription or purchase of the service.
Not forgetting that being free, we are always subject to advertisements that can often be considered invasive.
Part of the profit generated is shared with the creators of the content, under the terms determined by the platforms that host the content.
However, these platforms have great power of control over the content and its respective creators.
They control all the variables that determine the possible views and profits generated by these contents using a centralized business model.
And that can be a problem.
The review of content creators has been increasingly frequent, demonstrating their dissatisfaction with the policies of censorship that demonetizes the content that is placed on these platforms.
The same applies to app stores, a market currently dominated by Apple and Google, which make mobile operating systems on virtually all cell phones and tablets.
Two Steps Ahead?
Drawing on the innovative features of blockchain, [TRON token development] aims to approximate the relationship between consumers and content creators.
This proximity is created by eliminating intermediate elements of this process.
The intermediaries in question are the entertainment platforms that control and receive a “fat” share of the profits that belong to the content creators.
In summary:
The current business model flaw that TRON intends to explore is the centralization of the entertainment traffic that exists on the Internet.
These contents are mostly controlled by a small number of large companies such as Google, Facebook, Amazon, and the like, which in turn control platforms such as YouTube, Twitch, Google Play, etc
How does Tron work?
Tron architecture.
This illustration represents the current architecture of this project, which is divided into 3 stages:
Applications - where developers can create and install decentralized applications, as well as create and customize their tokens on the Tron blockchain;
Core - where the main components of the protocol are, such as smart contracts, software development kits (SDK), and other modules that are used in the creation of decentralized applications;
Storage - Tron applies a distributed data storage model on its blockchain, which allows for rapid processing and updating.
To achieve these goals, the TRON protocol aims to take advantage of peer-to-peer (P2P) technology and the blockchain.
The TRON blockchain uses the consensus algorithm known as Delegated Proof-of-Stake - an algorithm derived from Proof of Stake that allows TRX holders to generate passive income.
This means that when buying TRX you can store them in a wallet that allows you to stake your coins.
In this way, you are often rewarded with more TRX for your contribution to the Tron network.
The Tron blockchain supposedly can process 2,000 transactions per second (TPS). A number was much higher than the 7 TPS of the Bitcoin network. However, this information has not yet been verified by third parties.
Some Associations
TRX can have other uses thanks to some associations that have emerged, some of which are:
Game.com - Tron created a partnership with this online gaming platform to extend its presence in the gaming industry.
Gift - A decentralized platform where it is possible to offer virtual gifts.
Peiwo - A social media network, also founded by Justin Sun, often referred to as China’s Snapchat.
Alliance announcements and rumors have always contributed to the controversy surrounding this project, leading many crypto enthusiasts to label TRON a " shitcoin " due to these aggressive marketing tactics.
However, it is safe to say that [Tron token development]is a well-positioned cryptocurrency for exploring the Asian social media and entertainment market. The volume of traffic is huge!
Wink
It is on the Tron blockchain that one of the most popular dapps resides: Wink (previously TronBet).
Wink is a decentralized gambling and casino gaming platform that allows you to use TRX for gambling.
Developers can create games and then be rewarded depending on the success of the game.
This dApp is one of the largest, not only on the TRON blockchain but in the entire market.
It has an average of 10,000 users per week, handling 1,351 trillion TRX
The Personification Of The Project
TRON CEO Justin Sun is a well-known “crypto-celebrity.” At the age of 30, he has in his CV positions such as Chief Representative of Ripple, CEO of BitTorrent, and now CEO of Tron.
Justin is one of the great reasons why this cryptocurrency has a profile surrounded by so much controversy.
His personality and behavior on social media are notorious, particularly for his marketing tactics.
Some see him as a role model, while others call him an “imposter.”
Despite what people may think, the truth is that TRON is one of the most popular cryptocurrencies in the media, something that always influences the price of a coin.
Acquisition of BitTorrent
In 2019, Tron bought BitTorrent (BTT), a cryptocurrency created on the Tron blockchain, and with a vision aligned to decentralize the Internet.
How to Buy Tron (TRX)?
Platforms like IQ Option greatly facilitate investing in cryptocurrencies.
When investing through a broker, the need to configure virtual wallets (discarded wallets ) to keep your safe criptomonedas , which is a Recommended Practice for the time to buy in a bag.
For this reason, the buying and selling process becomes very simple.
In addition to other advantages, this broker offers tools called CFDs.
With CFDs, you can make a profit with the rise and fall of the price of cryptocurrencies, unlike other options. This is one of the few types of investment in which that happens.
TRX price
On the date of its ICO, in September 2017, a TRX cost approximately 0.002 USD. That is, less than 1 cent per TRX!
The price of Tron reached an all-time high of $ 0.254 in January 2018, which represented, at height, a growth of 125 times its initial value.
Since then, it had a great correction in its price that, to tell the truth, affected the entire cryptocurrency market at the beginning of 2018.
2020 was a good year for Tron. This cryptocurrency grew close to 80%, once again encouraging its investors. However, this value is well below what it achieved in other years.
Conclusion
TRON’s goals are undoubtedly ambitious!
Decentralizing the business model of big tech companies and bringing power back to content creators would undoubtedly be a game-changing feat.
With everything you’ve shown so far, it can be said with some confidence that this is not just a shitcoin (dubious project).
It would be good to see the final result of some of their collaborations already obtained to understand more clearly all that Tron can achieve.
We recognize that, like many others in this market, this project is in an early stage, despite the large network of business contacts that it has already achieved.
#tron-token-development-services #tron-token-development-company #tron-token-development
1603255867
ICO Development Company | Hire ICO Developer in India | ICO Consulting
We at ICO Development cover all the major steps or activities i.e. light paper & white paper drafting, coin or token creation, ICO fundraising dashboard, coin drop, marketing plan, bounty management etc. that will help you to raise a successful ICO.
#ico development #ico development services #ico solutions #ico services #ico development company
1606449233
TRON Dapp Development Services Company | TRON Wallet Development
Shamlatech Provide TRON DApps best for your business needs.
TRON DApps with improvised and superfast transactions, high scalability, availability, and adaptability to be best suitable for your business.
#tron dapp development services company #tron dapp development services #custom smart contracts on tron blockchain #tron dapp development company #tron dapp development #tron dapp developers
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