couch-named-python 0.2.2

couch-named-python is a CouchDB view server that executes functions on the python path by name.

Installation

You will need couch-named-python and your functions installed in the same python path, be it globally, in a virtualenv, or a distribute-less folder with a wrapper script that sets the pythonpath and then invokes couch_named_python.pyviews:main. In this example I'm using virtualenv:

virtualenv /opt/couch_vs
source /opt/couch_vs/bin/activate
pip install couch-named-python myfunctions
# or check out each package, and use ./setup.py install while virtualenv'd.

Next, edit /etc/couchdb/local.ini and add to the query_servers section:

[query_servers]
python = /opt/couch_vs/bin/couch-named-python

And restart couchdb

Usage

Functions in the design doc are just module.module.module.function paths, for example if myviews.py (which is installed in the /opt/couch_vs python path by pip) contained

from couch_named_python import Unauthorized, Forbidden, version

@version(123)
def townmap(doc):
 yield doc["town"]

@version(21)
def validate(new, old, userctx, secobj):
 if userctx["name"] != "daniel":
 raise Unauthorized("No")
 elif "town" not in new:
 raise Forbidden("No town in doc")

Then the design doc might be

{"id": "_design/location",
 "views": {"towns": {"map": "myviews.townmap|123"}},
 "validate_doc_update": "myviews.validate|21",
 "language": "python"}

i.e., the format is module.module.function|version.

You may prefer to describe your design doc in a yaml file, like this:

location:
 views:
 towns:
 map: myviews.townmap
 validate_doc_update: myviews.validate

Then running

cnp-upload http://admin:password@localhost:5984 mydatabase design.yml

Will upload the same design doc as above. You may have multiple design docs in a yaml file, and if a view has no reduce function you may omit the map:, like so:

design_a:
 views:
 one: module.path
 two: module.other
design_b:
 views:
 stats:
 map: module.map
 reduce: module.reduce

Furthermore, cnp-upload imports, detects and appends the |version suffixes for you (note how they are ommitted in the yaml above, yet it would produce exactly the same design doc as the example). Your module therefore needs to be on the path, so make sure you have your virtualenv where the view server is installed activated.

Rational for @version decorator

When the code is stored in the design document, like with the default javascript view server, CouchDB can track and deal with changes.

However, we have a couple of problems:

- couch-named-python doesn't reload modules. The viewserver will have to die by SIGTERM or error in order to force it to reload code.
- couch-named-python can't tell CouchDB that the view function has been changed. CouchDB will not even think that the view function has changed unless you modify the string for the function in the design document (saving the doc without changes or modifying other attributes doesn't work).
- It's actually quite difficult for couch-named-python to even work out if the view function's behaviour has changed, since it could be spread across more than one file.

Annotating functions with a manually changed 'version' is the easiest solution.

When doing an upgrade, you need to:

- update your python files, changing the @version on functions whose behaviour has changed
- re-upload the design docs for these functions
- load a view to make sure everything's back up.

If the versions on a loaded function and the design doc don't match then the view server raises an error and dies. This will probably cause the request that initiated the view update to fail and instead produce an {"error": blah} response from couch. Refreshing the page will restart the view server, load the updated file, and run the view properly. (Alternatively, you may kill the view server process yourself. If it's idle at the time, couch won't mind, and won't complain on first view load.)

Use of the version decorator and checking for it is optional but strongly recommended. You may simply use functions without the decorator and put module.module.function in the design document if you wish.


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Requirements:

· Python