IRIS App

.gitignore

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+# Virtual Env
+env/venv
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# OSX Filesystem thing
+.DS_Store
+
+# Ignore temp files from other editors
+*~
+.#*
+.*.sw?
+.idea/
+*.dpkg-*
+*.exe
+*.ZILESAVE
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# C extensions
+*.so
+
+# Installer logs
+*.log
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*,cover
+.hypothesis/
+
+# Translations
+*.mo
+*.pot
+
+# Log Files
+*.log
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# DotEnv configuration
+.env
+
+# Database
+*.db
+*.sqlite
+*.rdb
+
+# Pycharm
+.idea
+
+# Working Files - not ready to be shared
+local/
+
+# IPython NB Checkpoints
+.ipynb_checkpoints/
+
+# Exclude data from source control by default
+/data/*
+
+# Exclude Model Pickle Files
+*.pickle
+*.pkl
+*.npy

LICENSE

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+
+The MIT License (MIT)
+Copyright (c) 2016, Your name (or your organization/company/team)
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+

README.md

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+# Sample IRIS API Application
+
+Build IRIS Machine Learning Model using Scikit-Learn and deploy using Tornado Web Framework.
+
+## Setup Environment on Local Machine
+
+### Installation
+
+```
+cookiecutter https://github.com/sampathweb/cc-iris-api
+
+cd <repo>  # cd iris-api
+
+# Install Packages
+python env/create_env.py
+source activate env/venv  # Windows users: activate env/venv
+python env/install_packages.py
+
+# Build the Model
+python ml_src/build_model.py
+
+# Run the App
+python run.py
+````
+
+### Test App
+
+
+1. Open Browser:  [http://localhost:9000](http://localhost:9000)
+
+2. Command Line:
+
+```
+curl -i http://localhost:9000/api/iris/predict -X POST -d '{ "sepal_length": 2, "sepal_width": 5, "petal_length": 3, "petal_width": 4}'
+```
+
+3. Jupyter Notebook:
+
+Open new terminal navigate to the new folder `iris-api`.  Start `jupyter notebook`. Open ml_src -> `api_client.ipynb`.  Test the API.
+
+Api works!
+
+
+
+## Credits:
+
+Template from https://github.com/sampathweb/cc-iris-api
+
+
+### The End.

app/base_handler.py

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+"""
+Base Handler
+"""
+
+import json
+import traceback
+import logging
+import tornado.web
+import tornado.escape
+
+from app.exceptions import ApplicationError, RouteNotFound, ServerError
+
+logger = logging.getLogger("app")
+
+class BaseApiHandler(tornado.web.RequestHandler):
+
+    @tornado.web.asynchronous
+    def post(self, action):
+        try:
+            # Fetch appropriate handler
+            if not hasattr(self, str(action)):
+                raise RouteNotFound(action)
+
+            # Pass along the data and get a result
+            handler = getattr(self, str(action))
+            data = tornado.escape.json_decode(self.request.body)
+            handler(data)
+        except ApplicationError as e:
+            logger.warning(e.message, e.code)
+            self.respond(e.message, e.code)
+        except Exception as e:
+            logger.error(traceback.format_exc())
+            error = ServerError()
+            self.respond(error.message, error.code)
+
+
+    def respond(self, data, code=200):
+        self.set_status(code)
+        self.write(json.JSONEncoder().encode({
+            "status": code,
+            "data": data
+        }))
+        self.finish()

app/exceptions.py

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+"""
+Application Errors
+"""
+
+class ApplicationError(Exception):
+    def __init__(self, message, code):
+        self.message = message
+        self.code = code
+        super(Exception, self).__init__(message)
+
+
+class InvalidJSON(ApplicationError):
+    def __init__(self):
+        ApplicationError.__init__(self,
+            "No JSON object could be decoded.",
+            400
+        )
+
+
+class AuthError(ApplicationError):
+    def __init__(self):
+        ApplicationError.__init__(self,
+            "User not authenticated",
+            401
+        )
+
+
+class RouteNotFound(ApplicationError):
+    def __init__(self, action):
+        ApplicationError.__init__(self,
+            "%s route could not be found" % action,
+            404
+        )
+
+
+class ServerError(ApplicationError):
+    def __init__(self):
+        ApplicationError.__init__(self,
+            "we screwed up and have some debugging to do",
+            500
+        )

app/handler.py

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+"""
+Request Handlers
+"""
+
+import tornado.web
+from tornado import concurrent
+from tornado import gen
+from concurrent.futures import ThreadPoolExecutor
+
+from app.base_handler import BaseApiHandler
+from app.settings import MAX_MODEL_THREAD_POOL
+
+
+class IndexHandler(tornado.web.RequestHandler):
+    """APP is live"""
+
+    def get(self):
+        self.write("App is Live!")
+
+    def head(self):
+        self.finish()
+
+
+class IrisPredictionHandler(BaseApiHandler):
+
+    _thread_pool = ThreadPoolExecutor(max_workers=MAX_MODEL_THREAD_POOL)
+
+    def initialize(self, model, *args, **kwargs):
+        self.model = model
+        super().initialize(*args, **kwargs)
+
+    @concurrent.run_on_executor(executor='_thread_pool')
+    def _blocking_predict(self, X):
+        target_values = self.model.predict(X)
+        target_names = ['setosa', 'versicolor', 'virginica']
+        results = [target_names[pred] for pred in target_values]
+        return results
+
+
+    @gen.coroutine
+    def predict(self, data):
+        if type(data) == dict:
+            data = [data]
+
+        X = []
+        for item in data:
+            record  = (item.get("sepal_length"), item.get("sepal_width"), \
+                    item.get("petal_length"), item.get("petal_width"))
+            X.append(record)
+
+        results = yield self._blocking_predict(X)
+        self.respond(results)

app/server.py

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+# !/usr/bin/env python
+# -*- coding: utf-8 -*-
+import os
+import logging
+import logging.config
+
+import tornado.ioloop
+import tornado.web
+from tornado.options import options
+
+from sklearn.externals import joblib
+
+from app.settings import MODEL_DIR
+from app.handler import IndexHandler, IrisPredictionHandler
+
+
+MODELS = {}
+
+
+def load_model(pickle_filename):
+    return joblib.load(pickle_filename)
+
+
+def main():
+
+    # Get the Port and Debug mode from command line options or default in settings.py
+    options.parse_command_line()
+
+
+    # create logger for app
+    logger = logging.getLogger('app')
+    logger.setLevel(logging.INFO)
+
+    FORMAT = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+    logging.basicConfig(format=FORMAT)
+
+    # Load ML Models
+    logger.info("Loading IRIS Prediction Model...")
+    MODELS["iris"] = load_model(os.path.join(MODEL_DIR, "iris", "model.pkl"))
+
+    urls = [
+        (r"/$", IndexHandler),
+        (r"/api/iris/(?P<action>[a-zA-Z]+)?", IrisPredictionHandler,
+            dict(model=MODELS["iris"]))
+    ]
+
+    # Create Tornado application
+    application = tornado.web.Application(
+        urls,
+        debug=options.debug,
+        autoreload=options.debug)
+
+    # Start Server
+    logger.info("Starting App on Port: {} with Debug Mode: {}".format(options.port, options.debug))
+    application.listen(options.port)
+    tornado.ioloop.IOLoop.current().start()
+
+

app/settings.py

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+"""
+Appliction configuration settings
+"""
+import os
+
+from tornado.options import define
+
+define("debug", default=True, help="Debug settings")
+define("port", default=9000, help="Port to run the server on")
+
+_CUR_DIR = os.path.dirname(os.path.realpath(__file__))
+MODEL_DIR = os.path.join(_CUR_DIR, "..", "models")
+
+MAX_MODEL_THREAD_POOL = 10