Pipeline

[klapaukh]

This basically allows you to create ccd objects not from the XML or the RData, but rather than the database using the following: con <- connect(username="something", database="something") ccd <- table.to.ccdata(exportData(con) %>% collect, metadata(connection = con))

The only real changes are in R/dbConnection.R [and the README but those are trivial]

[codecov-io]

Codecov Report

Merging #148 into master will decrease coverage by 3.08%. The diff coverage is 0%.

@@            Coverage Diff             @@
##           master     #148      +/-   ##
==========================================
- Coverage   75.65%   72.56%   -3.09%     
==========================================
  Files          14       15       +1     
  Lines        1269     1323      +54     
==========================================
  Hits          960      960              
- Misses        309      363      +54

Impacted Files	Coverage Δ
R/dbConnection.R	0% <0%> (ø)

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[jonc125]

Is the AppVeyor failure specific to this PR, or a long-standing problem?

[jonc125]

Seems to have been failing for a while, including all of #145. From #135 it may be caused by importing dplyr?

[sinanshi]

It is really great to see you guys starting to implement the database approach. Although I don't know exactly what you are planning to do, cleanEHR now has been branded as a more generic data cleaning package, at least this is what we said in the JOSS paper, which is still under review. Moving from ccdata to database fits the purpose well. As you named the branch as "pipeline", I wonder if this is the data processing pipeline only for CCHIC, e.g. import XML files from hospitals to the database, you might want to consider to move it to a separate package, at least until the JOSS paper is published.

[dpshelio]

@sinanshi - the database importer is done in a different package, this is only to read from a database and generate a ccdata object.

[sinanshi]

@dpshelio that's great.