SimpleCov VS Sequel

gem "simplecov" - https://github.com/simplecov-ruby/simplecov | Gather spec coverage stats locally and on CI, aim for those 90+%.

Have you wondered how much of the logic in your views is exercised in your test suite? Thanks to this change, now you can see that in tools like SimpleCov.

My talk is about different best practices - specifically when adhering to them breaks down. One of those best practices is high test coverage. I start to work on the content for my presentation by building the code samples that I want to use in the slides. For the code coverage section, I'm writing some code with some tests. I'm using SimpleCov to generate code coverage results.

SimpleCov - a tool to check Ruby application code coverage. You can configure it to run alongside your tests. It provides metrics on code coverage so that you can identify what you need to pay attention to and where to invest your time to create better test cases.

Ensure that you have sufficient test coverage. You can use code coverage analysis tools like SimpleCov to gain insight into gaps in your coverage.

simplecov might the answer you need, it generates a report of the lines of code your test suite hits.

Use SimpleCov to generate a report of how many statements are covered by your test suite. It won't assess the test suite quality, though.

There are many tools for measuring test coverage, but one is SimpleCov. It also supports branches coverage. To measure coverage of production code, check out Coverband, which you can set up to use oneshot lines mode.

Some of the most enlightening books I’ve read when I was first learning Ruby were Text Processing in Ruby, and Building Awesome Command Line Apps in Ruby 2. They each reveal certain features and perspectives that work towards this end, such as text parsing moves, Ruby flags to help you build shell 1-liners you can pipe against, and features with stdio beyond just printing to stdout.

Then add in something like Pry or Irb, where you are able to build castles in your sandbox.

Most of my data exploration happens in Pry.

A final book I’ll toss out is Data Science at the Command Line, in particular the first 40 or so pages. They highlight the amount of tooling that exists that’s just python shell scripts posing as bins. (Ruby of course has every bit of the same potential.) I had always been aware of this, but I found the way it was presented to be very inspirational, and largely transformed how I work with data.

A good practical example I use regularly is: I have a project set up that keeps connection strings for ten or so SQL Server DBs that I regularly interact with. I have constants defined to expedite connections. The [Sequel library](https://sequel.jeremyevans.net/) is absolutely delightful to use. I have a `bin/console` file that sets up a pry session hooking up the default environment and tools I like to work with. Now it’s very easy to find tables with certain names, schemas, containing certain data, certain sprocs, mass update definitions across our entire system.

```

Thea answer to your prayers already exists: http://sequel.jeremyevans.net/.

By far the best database toolkit (ORM, query builder, migration engine) I have seen for any programming language.

Ruby sequel (http://sequel.jeremyevans.net/) is the only library where you can combine classic ORM Model bases usage, with a more raw query builder "just get me all the data into plain objects". You'll never need anything again in your career life.

If you want a db tool which can be an ORM for your app, and drop down to a lower level dsl, while targeting specific features of the databases it supports, + having a "composable superset for building queries", there's [ruby sequel](http://sequel.jeremyevans.net/), which is the best tool of the kind you'll get for any proglang. Everything the author wants, minus the typrchecking perhaps, which is IMO shooting at the stars.

I love the Sequel library from Jeremy Evans (so much better than Rails' AREL). I've used it as my ORM-of-choice since 2008. When leveraging Sequel I almost always use the DSL, but there are times that I want to use bare SQL. When that happens, I almost always use HEREDOCs and my own version of String#squish.

sequel is a pretty good option! To use the above snowflake adapter for sequel, you'll have to learn to use sequel (which is pretty easy). https://sequel.jeremyevans.net/