gcp-hello-ml

more stuff

Hello World.

1. Create Project

2. Activate cloud shell

3. Refer to hello world docs for python3 app engine

4. Run describe

verify project is working

gcloud projects describe $GOOGLE_CLOUD_PROJECT

output of command:

createTime: '2019-05-29T21:21:10.187Z'
lifecycleState: ACTIVE
name: helloml
projectId: helloml-xxxxx
projectNumber: '881692383648'

5. You may want to verify you have the correct project and if not, do this to switch:

gcloud config set project $GOOGLE_CLOUD_PROJECT

6. Create app engine app:

gcloud app create 

this will ask for the region. Go ahead and pick us-central [12]

Creating App Engine application in project [helloml-xxx] and region [us-central]....done.
Success! The app is now created. Please use `gcloud app deploy` to deploy your first app.

7. Clone the hello world sample app repo:

git clone https://github.com/GoogleCloudPlatform/python-docs-samples

8. cd into the repo:

cd python-docs-samples/appengine/standard_python37/hello_world

9. Update Cloudshell image [NOTE this is optional....you don't need this]

git clone https://github.com/noahgift/gcp-hello-ml.git
# Update .cloudshellcustomimagerepo.json with project and image name
# TIP: enable "Boost Mode" in in Cloudshell
cloudshell env build-local
cloudshell env push
cloudshell env update-default-image
# Restart Cloudshell VM

10. create and source the virtual environment:

virtualenv --python $(which python) venv
source venv/bin/activate

double check it works:

which python
/home/noah_gift/python-docs-samples/appengine/standard_python37/hello_world/venv/bin/python

10. activate cloud shell editor

11. install packages:

pip install -r requirements.txt

this should install flask

Flask==1.0.2

12. run flask locally

this runs flask locally in gcp shell

python main.py

13. preview

14. update main.py

from flask import Flask
from flask import jsonify

app = Flask(__name__)

@app.route('/')
def hello():
    """Return a friendly HTTP greeting."""
    return 'Hello I like to make AI Apps'

@app.route('/name/<value>')
def name(value):
    val = {"value": value}
    return jsonify(val)

if __name__ == '__main__':
    app.run(host='127.0.0.1', port=8080, debug=True)

15. Test out passing in parameters to exercise this function:

@app.route('/name/<value>')
def name(value):
    val = {"value": value}
    return jsonify(val)

For example, calling this route will take the word lion and pass into the name function in flask:

https://8080-dot-3104625-dot-devshell.appspot.com/name/lion

returns value in web browser:

{
value: "lion"
}

16. Now deploy the app

gcloud app deploy

Warning first deploy could take about 10 minutes FYI!!! you may also need to enable cloud build API.

Do you want to continue (Y/n)?  y
Beginning deployment of service [default]...
╔════════════════════════════════════════════════════════════╗
╠═ Uploading 934 files to Google Cloud Storage              ═╣

17. Now stream the log files:

gcloud app logs tail -s default

18. The production app is deployed and should like this:

Setting traffic split for service [default]...done.
Deployed service [default] to [https://helloml-xxx.appspot.com]
You can stream logs from the command line by running:
  $ gcloud app logs tail -s default

  $ gcloud app browse
(venv) noah_gift@cloudshell:~/python-docs-samples/appengine/standard_python37/hello_world (helloml-242121)$ gcloud app
 logs tail -s default
Waiting for new log entries...
2019-05-29 22:45:02 default[20190529t150420]  [2019-05-29 22:45:02 +0000] [8] [INFO] Starting gunicorn 19.9.0
2019-05-29 22:45:02 default[20190529t150420]  [2019-05-29 22:45:02 +0000] [8] [INFO] Listening at: http://0.0.0.0:8081
 (8)
2019-05-29 22:45:02 default[20190529t150420]  [2019-05-29 22:45:02 +0000] [8] [INFO] Using worker: threads
2019-05-29 22:45:02 default[20190529t150420]  [2019-05-29 22:45:02 +0000] [25] [INFO] Booting worker with pid: 25
2019-05-29 22:45:02 default[20190529t150420]  [2019-05-29 22:45:02 +0000] [27] [INFO] Booting worker with pid: 27
2019-05-29 22:45:04 default[20190529t150420]  "GET /favicon.ico HTTP/1.1" 404
2019-05-29 22:46:25 default[20190529t150420]  "GET /name/usf HTTP/1.1" 200

19. Add a new route and test it out

@app.route('/html')
def html():
    """Returns some custom HTML"""
    return """
    <title>This is a Hello World World Page</title>
    <p>Hello</p>
    <p><b>World</b></p>
    """

20. Install pandas and return json results

At this point, you may want to consider creating a Makefile and do this:

touch Makefile
#this goes inside that file
install:
	pip install -r requirements.txt

you also may want to setup lint:

pylint --disable=R,C main.py
------------------------------------
Your code has been rated at 10.00/10

Route looks like this:

add pandas import at top:

import pandas as pd

@app.route('/pandas')
def pandas_sugar():
    df = pd.read_csv("https://raw.githubusercontent.com/noahgift/sugar/master/data/education_sugar_cdc_2003.csv")
    return jsonify(df.to_dict())

When you call the route https://<yourapp>.appspot.com/pandas

you should get something like this:

21.Add this wikipedia route

import wikipedia

@app.route('/wikipedia/<company>')
def wikipedia_route(company):
    result = wikipedia.summary(company, sentences=10)
    return result

22. Add NLP to app:

A. https://github.com/noahgift/recommendations/blob/master/notebooks/NLP_GCP.ipynb B. Enable Cloud Natural Language API C. pip install google-cloud-language

test it out in IPython

In [1]: from google.cloud import language
In [2]: 
In [2]: text = "LeBron James plays for the Cleveland Cavaliers."
   ...: client = language.LanguageServiceClient()
   ...: document = language.Document(
   ...:         content=result,
   ...:         type_=language.Document.Type.PLAIN_TEXT)
   ...:         encoding_type = language.EncodingType.UTF8
   ...:         entities = client.analyze_entities(request = {'document': document, 'encoding_type': encoding_type}).entities
In [3]: entities

End to End AI API Example

from flask import Flask
from flask import jsonify
import pandas as pd
import wikipedia


app = Flask(__name__)

@app.route('/')
def hello():
    """Return a friendly HTTP greeting."""
    return 'Hello I like to make AI Apps'

@app.route('/name/<value>')
def name(value):
    val = {"value": value}
    return jsonify(val)

@app.route('/html')
def html():
    """Returns some custom HTML"""
    return """
    <title>This is a Hello World World Page</title>
    <p>Hello</p>
    <p><b>World</b></p>
    """
@app.route('/pandas')
def pandas_sugar():
    df = pd.read_csv("https://raw.githubusercontent.com/noahgift/sugar/master/data/education_sugar_cdc_2003.csv")
    return jsonify(df.to_dict())

@app.route('/wikipedia/<company>')
def wikipedia_route(company):

    # Imports the Google Cloud client library
    from google.cloud import language
    result = wikipedia.summary(company, sentences=10)

    client = language.LanguageServiceClient()
    document = language.Document(
        content=result,
        type_=language.Document.Type.PLAIN_TEXT)
    encoding_type = language.EncodingType.UTF8
    entities = client.analyze_entities(request = {'document': document, 'encoding_type': encoding_type}).entities
    return str(entities)


if __name__ == '__main__':
    app.run(host='127.0.0.1', port=8080, debug=True)

Reference

• Github Markdown Cheatsheet
• hello world python 3 docs michael was here
• cloudshell quick start
• how do I switch projects
• more information about project setup
• nlp google
• nlp gcp