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‎.gitattributes

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* text=auto

‎.gitignore

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‎LICENSE

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

‎README.md

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# Cookiecutter Starter Template to build and deploy Machine Learning model as Flask App
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_A logical, reasonably standardized, but flexible project structure for doing and sharing data science and deploy the model as flask app_
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### Requirements to use the cookiecutter template:
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-----------
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- Python 2.7 or 3.5
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- [cookiecutter Python package](http://cookiecutter.readthedocs.org/en/latest/installation.html) >= 1.4.0: `pip install cookiecutter`
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### To start a new project, run:
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------------
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cookiecutter https://github.com/sampathweb/cc-api-app
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### Credits:
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------
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* Based on the excellent CookieCutter Project (http://cookiecutter.readthedocs.org)
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* Template adopted from [Data Driven CookieCutter Project](http://drivendata.github.io/cookiecutter-data-science/)
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* Tornado App Structure inspired from Indico Server API (https://github.com/sihrc/tornado-boilerplate)

‎cookiecutter.json

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{
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"project_name": "project_name",
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"repo_name": "{{ cookiecutter.project_name|replace(' ', '_') }}",
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"author_name": "Your name (or your organization/company/team)",
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"description": "A short description of the project.",
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"year": "2016",
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"open_source_license": ["MIT", "BSD", "Not open source"]
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}

‎requirements.txt

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cookiecutter

‎{{cookiecutter.repo_name}}/.gitignore

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

‎{{cookiecutter.repo_name}}/LICENSE

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{% if cookiecutter.open_source_license == 'MIT' %}
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The MIT License (MIT)
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Copyright (c) {{ cookiecutter.year }}, {{ cookiecutter.author_name }}
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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:
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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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.
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{% elif cookiecutter.open_source_license == 'BSD' %}
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Copyright (c) {{ cookiecutter.year }}, {{ cookiecutter.author_name }}
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All rights reserved.
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice, this
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list of conditions and the following disclaimer in the documentation and/or
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other materials provided with the distribution.
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* Neither the name of {{ cookiecutter.project_name }} nor the names of its
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contributors may be used to endorse or promote products derived from this
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software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
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IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
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INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
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OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
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OF THE POSSIBILITY OF SUCH DAMAGE.
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{% endif %}

‎{{cookiecutter.repo_name}}/README.md

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# Sample IRIS API Application
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Build IRIS Machine Learning Model using Scikit-Learn and deploy using Tornado Web Framework on AWS.
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## Setup Environment on Local Machine
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### Installation
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```
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cookiecutter https://github.com/sampathweb/cc-iris-api
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cd <repo> # cd iris-api
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# Install Packages
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python env/create_env.py
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source activate env/venv # Windows users: activate env/venv
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python env/install_packages.py
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# Build the Model
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python ml_src/build_model.py
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# Run the App
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python run.py
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````
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### Test App
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1. Open Browser: (http://localhost:9000)
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2. Command Line:
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```
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curl -i http://localhost:9000/api/iris/predict -X POST -d '{ "sepal_length": 2, "sepal_width": 5, "petal_length": 3, "petal_width": 4}'
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```
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3. Jupyter Notebook:
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Open new terminal navigate to the new folder `iris-api`. Start `jupyter notebook`. Open ml_src -> `api_client.ipynb`. Test the API.
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Api works!
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### Push code to your own git repo. (Optional - We will not do in tutorial)
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```
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git init
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git add --all
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git commit -m "first commit"
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git remote add origin https://github.com/<your github username>/<remote repo name>.git
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git push --set-upstream origin master
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```
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## Deploy Steps for AWS Ubuntu 14.04 LTS EC2 Instance
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### Login to AWS Instance:
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`ssh -i <your AWS Pem key file> ubuntu@<aws ip>`
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### Install Python / Git
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```
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sudo apt-get update
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sudo apt-get upgrade
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# Install GIT
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sudo apt-get install git
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# Install Anaconda (Miniconda)
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wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
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bash Miniconda3-latest-Linux-x86_64.sh
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# To update the path (Make sure you said Yes when it asked to update path in the Miniconda install steps)
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source ~/.bashrc
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```
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### Download App Source Code:
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```
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git clone https://github.com/sampathweb/iris-api.git
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cd iris-api-app
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python env/create_env.py
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source activate env/venv
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python env/install_packages.py
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python ml_src/build_model.py
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python run.py (Confirm that App is running)
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sudo apt-get install supervisor
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sudo vi /etc/supervisor/conf.d/iris-api.conf
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<press i insert mode>
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[program:iris-api]
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autorestart = true
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command = /home/ubuntu/iris-api/env/venv/bin/python /home/ubuntu/iris-api/run.py --debug=False --port=80
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numprocs = 2
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startsecs = 10
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stderr_logfile = /var/log/supervisor/iris-api.log
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stdout_logfile = /var/log/supervisor/iris-api.log
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# stderr_logfile = syslog
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# stdout_logfile = syslog
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environment = PYTHONPATH="/home/ubuntu/iris-api/env/bin/"
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<escape :wq>
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sudo supervisorctl reload
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<Your APP is live now>
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```
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### Test the App
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1. Open Browser: http://<AWS IP> (App is Live!)
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2. Test API:
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curl -i http://<aws ip address>/api/iris/predict -X POST -d '{ "sepal_length": 2, "sepal_width": 5, "petal_length": 3, "petal_width": 4}'
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Congratulations you have deployed your App
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## Credits:
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Template from https://github.com/sampathweb/cc-iris-api
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### The End.

‎{{cookiecutter.repo_name}}/app/__init__.py

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‎{{cookiecutter.repo_name}}/app/base_handler.py

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

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