Merge pull request #306 from jklaise/python-package

Create initial Python package
SeldonIO · Dec 12, 2018 · 554e322 · 554e322
2 parents 340b6aa + f1cf8d8
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diff --git a/.gitignore b/.gitignore
@@ -143,3 +143,9 @@ openapi/tensorflow/
 proto/tensorflow/tensorflow/
 
 util/loadtester/MNIST_data/
+
+# python build
+eggs/
+.eggs/
+*.egg-info/
+./pytest_cache
diff --git a/docs/examples/h2oexample.md b/docs/examples/h2oexample.md
diff --git a/docs/wrappers/h2o.md b/docs/wrappers/h2o.md
diff --git a/docs/wrappers/nodejs.md b/docs/wrappers/nodejs.md
@@ -15,7 +15,7 @@ If you are not familiar with s2i you can read [general instructions on using s2i
 To check everything is working you can run
 
 ```bash
-s2i usage seldonio/seldon-core-s2i-r:0.1
+s2i usage seldonio/seldon-core-s2i-nodejs:0.1
 ```
 
 # Step 2 - Create your source code

diff --git a/docs/wrappers/python-docker.md b/docs/wrappers/python-docker.md
diff --git a/docs/wrappers/readme.md b/docs/wrappers/readme.md
@@ -13,28 +13,18 @@ To test a wrapped components you can use one of our [testing scripts](../api-tes
 
 Python based models, including [TensorFlow](https://www.tensorflow.org/), [Keras](https://keras.io/), [pyTorch](http://pytorch.org/), [StatsModels](http://www.statsmodels.org/stable/index.html), [XGBoost](https://github.com/dmlc/xgboost) and [Scikit-learn](http://scikit-learn.org/stable/) based models.
 
-You can use either:
-
-- [Source-to-image (s2i) tool](./python.md)
-- [Seldon Docker wrapper application](./python-docker.md)
+- [Python models wrapped using source-to-image](./python.md)
 
 ## R
 
-- [R models can be wrapped using source-to-image](r.md)
+- [R models wrapped using source-to-image](r.md)
 
 ## Java
 
 Java based models including, [H2O](https://www.h2o.ai/), [Deep Learning 4J](https://deeplearning4j.org/), Spark (standalone exported models).
 
 - [Java models wrapped using source-to-image](java.md)
 
-## H2O
-
-H2O models can be wrapped either from Java or Python.
-
-- [Java models wrapped using source-to-image](java.md)
-- [H2O models saved and called from python](./h2o.md)
-
 ## NodeJS
 
-- [Javascript models can be wrapped using source-to-image](nodejs.md)
+- [Javascript models wrapped using source-to-image](nodejs.md)
diff --git a/docs/wrappers/s2i.md b/docs/wrappers/s2i.md
@@ -16,7 +16,8 @@ The general work flow is:
 
 At present we have s2i builder images for
 
- * [python (python2 or python3)](./python.md) : use this for Tensorflow, Keras, pyTorch or sklearn models.
+ * [Python (Python2 or Python3)](./python.md) : use this for Tensorflow, Keras, PyTorch or sklearn models.
  * [R](r.md)
  * [Java](java.md)
+ * [NodeJS](nodejs.md)