Take you to observe Bitcoin and its competing coins from a new perspective of the coin code itself

Everyone has different opinions on how to evaluate the quality of various electronic currencies. We can only say that the perspectives are different, but we cannot simply say who is right or wrong. The common perspectives are to look at the trading volume and trading popularity, the popularity of the daily Weibo and Twitter volume, the number and quality of merchants and applications that have announced support for this currency, and the total circulation market value ranking of existing circulating currencies.

I personally agree that the value of an electronic currency comes from the number of fans and the amount of applications, which is the product of the two. It has nothing to do with speculation, or good or bad news, unless the news can affect the number of fans or the amount of applications. The circulating market value is the result of everyone's vote with their wealth on whether the electronic currency is valuable. People will naturally hold more of the currency they think is valuable, and thus have a higher circulating market value.

This article will provide you with a new perspective, hoping to help you understand a certain electronic currency more comprehensively.

1. Raw Data

You will understand it when you see the picture below. It is to search for the names of various coins on the famous open source code website GitHub to get the data. The implicit meaning behind these data will be analyzed below. First, I will give you some screenshots of common currency data.

First, Bitcoin

2. Ripple

3. Litecoin

4. Ethereum

6. Dogecoin

8. BitShares

Note: The above number refers to the current ranking of the circulating market value, which is obtained based on the current screenshot below.

2. Data Summary

The data in the above figures are summarized into the following table, and two important parameters are added, namely the Star rating of the core wallet and the Forks data, which are organized as follows:

It can be seen that Bitcoin is far ahead in all data. Ripple, which ranks second in circulation market value, ranks second in all other aspects except for the Forks data, which is only slightly inferior to Dogecoin. From the perspective of Ripple technology, it is well deserved to be second. Ethereum has many issues. BitShares seems to be inferior to the top few.

3. Data Mining

Deeply digging and analyzing these data will yield more results, such as the speed of each data increase and change. And why the number of repositories of Litecoin, Ethereum and Dogecoin is close to 400 projects, while the code search results of Litecoin are much larger than those of the other two? Here, let's study a data that is not counted in the above table, Languages.

Just like each coin has its own application field, and they coexist. Bitcoin is used for large-scale storage transactions, Ripple is used to process global assets, and Dogecoin is used for rewards and tips. Fiat currency is used for traditional business life, and electronic currency is used for Internet finance.

Each language also has its own expertise or specialized fields, so it is unlikely that a super language will emerge to replace all programming languages.

Desktop programs : C++, Java, C#, C
Website frontend : HTML, JavaScript, CSS
Website backend : PHP, Python, JSP, ASP
Public interfaces : XML, JSON, SQL

Based on the different distribution of languages, we can roughly outline the macro development areas and directions of this currency. For example, the language characteristics of Bitcoin and Ripple are shown in the figure below.

Bitcoin has the largest number of repositories in JavaScript , Python , and PHP , and these three categories are mostly related to building specific website applications. That is, Bitcoin has entered the application stage. The core underlying C++ , C , etc. are ranked behind because they are more mature.

As for Ripple, since it is mainly built with JavaScript, its JavaScript and Java repositories libraries account for the majority, but Python and PHP, which are specific applications, are relatively backward, that is, they are still mainly in the research and development stage, and have some applications but not very many.

The above analysis is just a starting point. If there is anything wrong with the analysis, please communicate with me. You can make a guess and judgment on the technical status of each currency from the code level based on the previous language classification and your own understanding of each language.

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