https://github.com/noahgift/function-bike-rider
This is a repo for showing what you can do with a function
https://github.com/noahgift/function-bike-rider
Last synced: 7 months ago
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This is a repo for showing what you can do with a function
- Host: GitHub
- URL: https://github.com/noahgift/function-bike-rider
- Owner: noahgift
- Created: 2020-08-26T14:18:18.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2020-12-08T16:50:07.000Z (almost 5 years ago)
- Last Synced: 2025-03-01T04:24:01.142Z (8 months ago)
- Language: Python
- Size: 47.9 KB
- Stars: 31
- Watchers: 7
- Forks: 43
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# function-bike-rider
This is a repo for showing what you can do with a function
You can watch a Video Walkthrough here:
[](https://youtu.be/lN6OSIDpgyg)
## Building a CLI Workflow
1. Create scaffolding in Python (Makefile, virtualenv)
2. Write a function in a script file
3. Test it out in IPython
4. Write a test using pytest and test_hello.py
5. Write a Click commandline tool
6. Test all of it using the Click test runner
## Building a Computer Vision
1. Create scaffolding in Python (Makefile, virtualenv)
2. Write a function in a script file
3. Test it out in IPython
4. Write a test using pytest and test_hello.py
5. Write a Click CLI tool
6. Test all of it using the Click test runner
7. Build an AWS Lambda function
8. Create Trigger to S3 Bucket
## Building a Flask Application on GCP
1. Create scaffolding in Python (Makefile, virtualenv)
2. Write a function in a script file
3. Test it out in IPython
4. Write a test using pytest and test_hello.py
5. Test out in Google Cloud Shell
6. Deploy
7. `gcloud app create`
8. `gcloud app deploy`
9. create `app.yaml`
## Build out a GCP Cloud Function
1. Create scaffolding in Python (Makefile, virtualenv)
2. Write a function in a script file
3. Test it out in IPython
4. Write a test using pytest and test_hello.py
5. Test out in Google Cloud Shell
6. Create Google Cloud Function
7. Invoke via the cli:
`gcloud functions call ChangeMachineCloudFunction --data '{"amount":"11.44"}'`
```bash
executionId: akqyz3e60z6o
result: "This is the res: [{45: 'quarters'}, {1: 'dimes'}, {1: 'nickels'}, {4: 'pennies'}]"
```
8. Another way to invoke is via curl command
To invoke via curl
```bash
curl -d '{
"amount":"1.34"
}' -H "Content-Type: application/json" -X POST /function-3
```
## Invoke AWS Lambda
```bash
aws lambda invoke --function-name Marco128 --payload '{"name": "Marco" }' out.txt | less out.txt
```
## Setup Cloud Environment (AWS Cloud9)
`python3 -m venv ~/.function-bike-rider`
`source ~/.function-bike-rider/bin/activate`
## SSH Keys
`ssh-keygen -t rsa`
upload to github
## Create Scaffold (with Marco Polo function)
* Makefile
* hello.py
* requirements.txt
## Continuous Integration with Github Actions
* test_hello.py
* installed `pylint`, `pytest`, `black`
## Building a command-line tool
* use click to build a cli
https://github.com/noahgift/function-bike-rider/blob/master/cvcli.py
## Explored AWS Lambda
```python
def lambda_handler(event, context):
if event["name"] == "Marco":
return "Polo"
return "No!"
```
### Use Boto3
* install `boto3` and use `ipython`
### Build a computer vision cli
### Build a trigger that automatically runs a Lambda Function
```python
import boto3
from urllib.parse import unquote_plus
def label_function(bucket, name):
"""This takes an S3 bucket and a image name!"""
print(f"This is the bucketname {bucket} !")
print(f"This is the imagename {name} !")
rekognition = boto3.client("rekognition")
response = rekognition.detect_labels(
Image={"S3Object": {"Bucket": bucket, "Name": name,}},
)
labels = response["Labels"]
print(f"I found these labels {labels}")
return labels
def lambda_handler(event, context):
"""This is a computer vision lambda handler"""
print(f"This is my S3 event {event}")
for record in event['Records']:
bucket = record['s3']['bucket']['name']
print(f"This is my bucket {bucket}")
key = unquote_plus(record['s3']['object']['key'])
print(f"This is my key {key}")
my_labels = label_function(bucket=bucket,
name=key)
return my_labels
```
### GCP Cloud Function that Translates
```python
import wikipedia
from google.cloud import translate
def sample_translate_text(text="YOUR_TEXT_TO_TRANSLATE",
project_id="YOUR_PROJECT_ID", language="fr"):
"""Translating Text."""
client = translate.TranslationServiceClient()
parent = client.location_path(project_id, "global")
# Detail on supported types can be found here:
# https://cloud.google.com/translate/docs/supported-formats
response = client.translate_text(
parent=parent,
contents=[text],
mime_type="text/plain", # mime types: text/plain, text/html
source_language_code="en-US",
target_language_code=language,
)
print(f"You passed in this language {language}")
# Display the translation for each input text provided
for translation in response.translations:
print(u"Translated text: {}".format(translation.translated_text))
return u"Translated text: {}".format(translation.translated_text)
def translate_test(request):
"""Takes JSON Payload {"entity": "google"}
"""
request_json = request.get_json()
print(f"This is my payload: {request_json}")
if request_json and 'entity' in request_json:
entity = request_json['entity']
language = request_json['language']
sentences = request_json['sentences']
print(entity)
res = wikipedia.summary(entity, sentences=sentences)
trans=sample_translate_text(text=res, project_id="cloudai-194723",
language=language )
return trans
else:
return f'No Payload'
```
#### Example Output of GCP Cloud Function
Send payload in:
```
{
"entity":"google",
"language":"es",
"sentences":"3"
}
```
The result below:
Translated text: Google LLC es una empresa de tecnología multinacional estadounidense que se especializa en servicios y productos relacionados con Internet, que incluyen tecnologías de publicidad en línea, un motor de búsqueda, computación en la nube, software y hardware. Se considera una de las cuatro grandes empresas de tecnología junto con Amazon, Apple y Microsoft. Google fue fundada en septiembre de 1998 por Larry Page y Sergey Brin mientras eran Ph.D. estudiantes de la Universidad de Stanford en California. Juntos poseen alrededor del 14 por ciento de sus acciones y controlan el 56 por ciento del poder de voto de los accionistas a través de acciones de supervotación.
Finally, you can call from the CLI:
```bash
gcloud functions call translate-wikipedia --data '{"entity":"google", "sentences
": "20", "language":"es"}'
```