Brad Lucas

Programming, Clojure and other interests


July 5, 2017

Whenever I need to look at a Git repository in a visual way I pull out GitX. Today, I thought to mention it in case anyone is looking for a Git gui for the Mac.

I've used GitX for a number of years and have yet to find a reason to try anything else.

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Tokenwatch (Part 2)

July 4, 2017

Once part 1 of TokenWatch was done the next step appeared when you saw all the details on each entries interior page. There I was most interested in the links to the Whitepapers so I could collect them and read through them more easily as a group.

For this part of the project I created another script which extends the previous script.


To start I'll be getting the dataframe from the script sorted by NAME.

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Tokenwatch (Part 1)

July 3, 2017

Continuing with my research into tokens and blockchain assets I found another site called This site includes ICOs which are running as well as upcoming campaigns.

In a similar fashion as previous post ( I decided to scrape the site so I could group the entries by status more easily. The result of this is a Python script called

The following are some highlights to get the script working.

Table Data

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Gist mode issue

July 2, 2017


Recently, I recommended using gist.el to work with your Gists on GitHub. I found an issue with gist.el in the version installed here.

I was having trouble editing the description of the gists with the e command.

e               gist-edit-current-description

The error that was returned was:

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Coin Market Cap

July 1, 2017

There is a useful page called CryptoCurrency Market Capitalizations for viewing the current state of the crytocurency markets.

The site shows all currencies runing today on a number of platforms. I'm interested in the ones running on Ethereum which have a Market Cap. Since, the site doesn't have this specific filtering capability I thought it would make a good project to grab the data from the page and filter it the way I'd like.

To do this I decided to investigate Pandas and it's read_html function for pulling data in from html tables.

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