It doesn't look like the elasticsearch-py API covers the river use case.
When I've run into things like this I've always just run a manual CURL
request, or if I need to do it from within a script I just do a basic
command with requests, ala
requests.put("http://localhost:9200/_river/mydocs/_meta"; data='{"type":
"fs", "fs": { "url": "/tmp", "update_rate": 900000, "includes":
"*.doc,*.pdf", "excludes": "resume" }}')
Not the most elegant approach, but it works!
On Thursday, March 13, 2014 1:57:55 PM UTC-7, Kent Tenney wrote:
>
> From the fsriver doc:
>
> curl -XPUT 'localhost:9200/_river/mydocs/_meta' -d '{
> "type": "fs",
> "fs": {
> "url": "/tmp",
> "update_rate": 900000,
> "includes": "*.doc,*.pdf",
> "excludes": "resume"
> }
> }'
>
> How does this translate to the Python API?
>
> Thanks,
> Kent
>
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