refactoring examples to use riverapi (#2)

Signed-off-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>

.all-contributorsrc

@@ -0,0 +1,26 @@
+{
+    "projectName": "django-river-ml",
+    "projectOwner": "vsoch",
+    "repoType": "github",
+    "repoHost": "https://github.com",
+    "files": [
+        "README.md"
+    ],
+    "imageSize": 100,
+    "commit": true,
+    "commitConvention": "none",
+    "contributors": [
+        {
+            "login": "vsoch",
+            "name": "Vanessasaurus",
+            "contributions": [
+                "code"
+            ],
+            "profile": "https://vsoch.github.io",
+            "avatar_url": [
+                "https://avatars.githubusercontent.com/u/814322?v=4"
+            ]
+        }
+    ],
+    "contributorsPerLine": 7
+}

.github/CONTRIBUTING.md

@@ -0,0 +1,54 @@
+# Contributing
+
+Contributions are welcome, and they are greatly appreciated! Every
+little bit helps, and credit will always be given. 
+
+You can contribute in many ways:
+
+## Types of Contributions
+
+### Report Bugs
+
+Report bugs at https://github.com/vsoch/django-river-ml/issues.
+
+If you are reporting a bug, please include:
+
+* Your operating system name and version.
+* Any details about your local setup that might be helpful in troubleshooting.
+* Detailed steps to reproduce the bug.
+
+### Fix Bugs
+Look through the GitHub issues for bugs. Anything tagged with "bug"
+is open to whoever wants to implement it.
+
+### Implement Features
+
+Look through the GitHub issues for features. Anything tagged with "feature"
+is open to whoever wants to implement it.
+
+### Write Documentation
+
+django-river-ml could always use more documentation, whether as part of the 
+official django-river-ml docs, in docstrings, or even on the web in blog posts,
+articles, and such.
+
+### Submit Feedback
+
+The best way to send feedback is to file an issue at https://github.com/vsoch/django-river-ml/issues.
+
+If you are proposing a feature:
+
+* Explain in detail how it would work.
+* Keep the scope as narrow as possible, to make it easier to implement.
+* Remember that this is a volunteer-driven project, and that contributions
+  are welcome :)
+
+## Pull Request Guidelines
+
+Before you submit a pull request, check that it meets these guidelines:
+
+1. The pull request should include tests.
+2. If the pull request adds functionality, the docs should be updated. Put
+   your new functionality into a function with a docstring, and add the
+   feature to the list in README.rst.
+3. The pull request should work for minimally Python 3.5 and for PyPy.

.github/workflows/release.yaml

@@ -0,0 +1,31 @@
+name: Release Python Package
+
+on:
+  release:
+    types: [created]
+
+jobs:
+  deploy:
+    runs-on: ubuntu-20.04
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Install
+      run: conda create --quiet --name djriver twine
+
+    - name: Install dependencies
+      run: |
+        export PATH="/usr/share/miniconda/bin:$PATH"
+        source activate djriver
+        pip install -e .
+        pip install setuptools wheel twine
+    - name: Build and publish
+      env:
+        TWINE_USERNAME: ${{ secrets.PYPI_USER }} 
+        TWINE_PASSWORD: ${{ secrets.PYPI_PASS }}
+      run: |
+        export PATH="/usr/share/miniconda/bin:$PATH"
+        source activate djriver
+        python setup.py sdist bdist_wheel
+        twine upload dist/*

.github/workflows/update-contributors.yaml

@@ -0,0 +1,82 @@
+name: allcontributors-auto-detect
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  Update:
+    name: Generate
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Repository
+        uses: actions/checkout@v2
+      - name: Tributors Update
+
+        # Important! Update to release https://github.com/con/tributors
+        uses: con/tributors@0.0.20
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:        
+
+          # Single text list (space separated) of parsers, leave unset to auto-detect
+          parsers: unset
+
+          # Update lookup with GitHub metadata
+          update_lookup: github
+
+          # INFO, DEBUG, ERROR, WARNING, etc.
+          log_level: DEBUG
+
+          # If files already exist and an init is done, force overwrite
+          force: true
+
+          # the minimum number of contributions required to add a user
+          threshold: 1
+
+      - name: Checkout New Branch
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          BRANCH_AGAINST: "main"
+        run: |
+          printf "GitHub Actor: ${GITHUB_ACTOR}\n"
+          export BRANCH_FROM="contributors/update-$(date '+%Y-%m-%d')"
+          git remote set-url origin "https://x-access-token:${GITHUB_TOKEN}@github.com/${GITHUB_REPOSITORY}.git"
+
+          BRANCH_EXISTS=$(git ls-remote --heads origin ${BRANCH_FROM})
+          if [[ -z ${BRANCH_EXISTS} ]]; then
+              printf "Branch does not exist in remote.\n"
+          else
+              printf "Branch already exists in remote.\n"
+              exit 1
+          fi
+          git branch
+          git checkout -b "${BRANCH_FROM}" || git checkout "${BRANCH_FROM}"
+          git branch
+
+          git config --global user.name "github-actions"
+          git config --global user.email "github-actions@users.noreply.github.com"
+          git status
+
+          if git diff-index --quiet HEAD --; then
+             export OPEN_PULL_REQUEST=0
+             printf "No changes\n"
+          else
+             export OPEN_PULL_REQUEST=1
+             printf "Changes\n"
+             git commit -a -m "Automated deployment to update contributors $(date '+%Y-%m-%d')"
+             git push origin "${BRANCH_FROM}"
+          fi
+
+          echo "OPEN_PULL_REQUEST=${OPEN_PULL_REQUEST}" >> $GITHUB_ENV
+          echo "PULL_REQUEST_FROM_BRANCH=${BRANCH_FROM}" >> $GITHUB_ENV
+          echo "PULL_REQUEST_TITLE=[tributors] ${BRANCH_FROM}" >> $GITHUB_ENV
+          echo "PULL_REQUEST_BODY=Tributors update automated pull request." >> $GITHUB_ENV
+
+      - name: Open Pull Request
+        uses: vsoch/pull-request-action@1.0.12
+        if: ${{ env.OPEN_PULL_REQUEST == '1' }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          PULL_REQUEST_BRANCH: "main"

README.md

@@ -6,16 +6,35 @@
 Django models to deploy [river](https://riverml.xyz) online machine learning. 
 This is a Django version of [chantilly](https://github.com/online-ml/chantilly) that aims to use the
 same overall design. We also include [example clients](examples/) and a test application in [tests](tests).
+We also are developing an [API client](https://github.com/vsoch/riverapi) and early work on a specification that can be extended to other
+Python based servers intended for river.
 
 See the ⭐️ [Documentation](https://vsoch.github.io/django-river-ml/) ⭐️ to get started!
 
+## Contributors
+
+We use the [all-contributors](https://github.com/all-contributors/all-contributors) 
+tool to generate a contributors graphic below.
+
+<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
+<!-- prettier-ignore-start -->
+<!-- markdownlint-disable -->
+
+<!-- markdownlint-restore -->
+<!-- prettier-ignore-end -->
+
+<!-- ALL-CONTRIBUTORS-LIST:END -->
+
+
 ## TODO
 
 - tests
 - should we have a server generic client to plug in here instead?
+- create client that can easily interact with API
+- add some basic set of frontend views?
 - do we want a spec? [issue](https://github.com/online-ml/river/issues/845)
 - clean up docstrings -> docs and python docs -> envars list and how to define -> pretty docs
 - implement more examples?
 - add and test authenticated views
 - do we want a default interface for something?
-- upload to pypi and automated release after that
+

django_river_ml/client.py

@@ -271,9 +271,10 @@ def update_metrics(self, prediction, ground_truth, model_name):
                 pred = max(prediction, key=prediction.get)
                 metric.update(y_true=ground_truth, y_pred=pred)
 
-            # In some cases the prediction dict either has or doesn't have the ground truth
-            # is this correct?
+            # In some cases we have a dict that isn't a Classification Metric
             elif isinstance(prediction, dict):
+
+                # The ground truth may not be present
                 y_pred = prediction.get(ground_truth)
                 if y_pred:
                     metric.update(y_true=ground_truth, y_pred=y_pred)

django_river_ml/settings.py

@@ -12,10 +12,13 @@
 # Default views to Authenticate
 # TODO update here
 authenticated_views = [
-    #    "django_river_ml.views.learn.",
-    #    "django_river_ml.views.blobs.BlobDownload",
-    #    "django_river_ml.views.image.ImageTags",
-    #   "django_river_ml.views.image.ImageManifest",
+    #    "django_river_ml.views.learn.view",
+    #    "django_river_ml.views.metrics.view",
+    #   "django_river_ml.views.model.view",
+    #   "django_river_ml.views.predict.view",
+    #    "django_river_ml.views.metrics.view",
+    #    "django_river_ml.views.metrics.stream_events",
+    #    "django_river_ml.views.metrics.stream_metrics",
 ]
 
 # Defaults for models and storage

examples/README.md

@@ -1,7 +1,14 @@
 # Examples
 
 The following examples will show you how to interact with the test application
-provided. The subdirectories are named based on the model type. E.g., for
+provided. All examples use the [riverapi](https://github.com/vsoch/riverapi)
+library that you can install from pip.
+
+```bash
+$ pip install riverapi
+```
+
+The subdirectories are named based on the model type. E.g., for
 "regression" make sure you set the settings.py `MODEL_FLAVOR` to regression first.
 And then start the server:
 
@@ -10,3 +17,4 @@ $ python manage.py runserver
 ```
 
  - [regression](regression)
+

examples/binary/requirements.txt

@@ -1 +1 @@
-requests
+riverapi

examples/binary/run.py

@@ -1,65 +1,46 @@
-from river import datasets
 from river import naive_bayes
 from river import preprocessing
 from river import stream
 
-import json
-import dill
-import requests
-
-
-def print_response(r):
-    assert r.status_code in [200, 201]
-    response = r.json()
-    print("%s: %s" % (r.url, json.dumps(response, indent=4)))
+from riverapi.main import Client
 
 
 def main():
-    host = "http://localhost:8000"
+
+    # This is the default, just to show how to customize
+    cli = Client("http://localhost:8000")
 
     # Upload a model
     model = preprocessing.StandardScaler() | naive_bayes.GaussianNB()
-    r = requests.post(host + "/api/model/binary/", data=dill.dumps(model))
-    model_name = r.json()["name"]
-    print_response(r)
+
+    # Save the model name for other endpoint interaction
+    model_name = cli.upload_model(model, "binary")
     print("Created model %s" % model_name)
 
     # Train on some data
     X = [[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]]
     Y = [1, 1, 1, 2, 2, 2]
 
     for x, y in stream.iter_array(X, Y):
-        r = requests.post(
-            host + "/api/learn/",
-            json={"model": model_name, "features": x, "ground_truth": y},
-        )
-        print_response(r)
+        cli.learn(model_name, x=x, y=y)
 
     # Get the model (this is a json representation)
-    r = requests.get(host + "/api/model/%s/" % model_name)
-    assert r.status_code == 200
-    print(json.dumps(r.json(), indent=4))
-
-    # Get the model (this is a download of the pickled model with dill)
-    r = requests.get(host + "/api/model/download/%s/" % model_name)
-    assert r.status_code == 200
+    model_json = cli.get_model_json(model_name)
+    model_json
 
-    # Here is how to save and load
-    # with open("%s.pkl" % model_name, 'wb') as f:
-    #     for chunk in r:
-    #         f.write(chunk)
-
-    # with open("muffled-pancake-9439.pkl", "rb") as fd:
-    #    content=pickle.load(fd)
+    # Saves to model-name>.pkl in pwd unless you provide a second arg, dest
+    cli.download_model(model_name)
 
     # Make predictions
     for x, y in stream.iter_array(X, Y):
-        r = requests.post(
-            host + "/api/predict/",
-            json={"model": model_name, "features": x},
-        )
-        print_response(r)
+        print(cli.predict(model_name, x=x))
+
+    # Get all models
+    print(cli.models())
+
 
+if __name__ == "__main__":
+    main()
 
 if __name__ == "__main__":
     main()

examples/regression/requirements.txt

@@ -1 +1 @@
-requests
+riverapi