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Fix minor
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README.md

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@@ -37,12 +37,12 @@ pip install rekcurd_client
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Example code is available [here](./example/sample.py).
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```python
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from drucker_client import DruckerWorkerClient
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from drucker_client.logger import logger
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from rekcurd_client import RekcurdWorkerClient
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from rekcurd_client.logger import logger
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host = 'localhost:5000'
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client = DruckerWorkerClient(logger=logger, host=host)
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client = RekcurdWorkerClient(logger=logger, host=host)
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input = [0,0,0,1,11,0,0,0,0,0,
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0,7,8,0,0,0,0,0,1,13,
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When you use Kubernetes and deploy Rekcurd service via Rekcurd dashboard, you can access your Rekcurd service like the below.
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```python
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from drucker_client import DruckerWorkerClient
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from drucker_client.logger import logger
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from rekcurd_client import RekcurdWorkerClient
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from rekcurd_client.logger import logger
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domain = 'example.com'
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app = 'drucker-sample'
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app = 'rekcurd-sample'
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env = 'development'
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client = DruckerWorkerClient(logger=logger, domain=domain, app=app, env=env)
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client = RekcurdWorkerClient(logger=logger, domain=domain, app=app, env=env)
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input = [0,0,0,1,11,0,0,0,0,0,
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response = client.run_predict_arrint_arrint(input)
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```
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### DruckerWorkerClient
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### RekcurdWorkerClient
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You need to use an appropriate method for your Rekcurd service. The methods are generated according to the input and output formats. *V* is the length of feature vector. *M* is the number of classes. If your algorithm is a binary classifier, you set *M* to 1. If your algorithm is a multi-class classifier, you set *M* to the number of classes.
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|method |input: data<BR>(required) |input: option |output: label<BR>(required) |output: score<BR>(required) |output: option |

tox.ini

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[testenv:coverage]
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commands =
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python -V
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nosetests --with-coverage --cover-package=drucker_client --cover-tests
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nosetests --with-coverage --cover-package=rekcurd_client --cover-tests
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[testenv:codecov]
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commands =

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