Updated on June 10, 2016 by FvD
The couchDB package has been designed for communication with couchDB, a popular noSQL database. For details consult the help pages for
To interact with a couchDB instance you will need to create a connection object. Communication with couchDB happens over a http protocol. A minimal connection (running on the default port and no password protection) would be:
library(couchDB) myConn <- couch_http_connection("localhost")
The variable "myConn" can now be used as parameters to other functions.
For convenience a default connection can also be created with
couch_set_default_connection
using the same parameters.
Once a connection object exists, you may want to make sure it is connecting
correctly with the couch_ping
function. If you are properly connected the
reponse should look like:
Response [http://localhost:5984] Status: 200 Content-type: text/plain; charset=utf-8 Size: 151 B {"couchdb":"Welcome","uuid":"c1a367c91517195b57ddafe788a72b75","version":"1.4.0","vendor" {"name":"...
To connect to cloudant specify the service (otherwise it defaults to couchdb) as follows:
myConn <- couch_http_connection(host = "demo.cloudant.com", https = TRUE, service = "cloudant")
Response [https://demo.cloudant.com/] Date: 2016-05-13 16:50 Status: 200 Content-Type: application/json Size: 64 B {"couchdb":"Welcome","version":"1.0.2","cloudant_build":"2580"}
On a couchDB install there can be several databases (i.e. namespaces). The function
will provide a list of available databases on the connection provided.
The function couch_create_database
will, similarly, allow you to create a
new database or namespace on the couchDB instance.
CouchDB allows for setting a default connection and a default database to work with. This is useful, and provides for cleaner code, if you are mainly working with one specific database at a specific connection.
Once you have a connection and a database to work with you can fetch, store and delete documents by using the corresponding functions:
The document to be stored can be provided either as a list (which will be converted to json for insertion), or for tighter control over the document structure a character vector in json format can be provided.
R Development Core Team. Writing R Extensions. R Foundation for Statistical Computing, Vienna, Austria, 2008.
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