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Merge pull request #181 from ryansurf/feat-logging
Feat logging
2 parents ecf991c + 7717ccd commit 2688c33

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.env.example

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@@ -16,4 +16,6 @@ Please keep it short and don't repeast unecessary data (like repeating the surf
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API_KEY=
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GPT_MODEL="gpt-3.5-turbo"
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# Use the below DB_URI is running mongodb locally via docker.
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# DB_URI="mongodb://mongodb:27017/cli-surf-db"
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DB_URI=

Dockerfile

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# Copy in the .env file
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COPY .env.example .env
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# Install the tool the dependencies need
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RUN apt-get update && apt-get install -y \
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gcc \
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libkrb5-dev \
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&& rm -rf /var/lib/apt/lists/*
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# Install the application dependencies
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RUN pip install poetry
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RUN poetry config installer.max-workers 10

compose.yaml

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- "8000:8000"
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volumes:
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- .:/app
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depends_on:
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- mongodb
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mongodb:
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image: mongo:latest
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container_name: mongodb_local
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restart: always
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ports:
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- "27017:27017"
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volumes:
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- mongo_data:/data/db
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dozzle:
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image: amir20/dozzle:latest
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container_name: dozzle
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restart: always
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volumes:
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- /var/run/docker.sock:/var/run/docker.sock
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ports:
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- 8080:8080
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volumes:
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mongo_data:
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docs/storage.md

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# Storage
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## MongoDB
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There is an option to store all output (ocean data printed to `STDOUT`). This is enabled when you specify a `DB_URI` in the `.env` file.
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You can either connect to a MongoDB instance in the cloud, or locally. When using Docker, a MongoDB instance is spun up and the URI is available in the `.env.example`.
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You can view the data using multiple methods. I personally use [MongoDB Compass](https://www.mongodb.com/products/tools/compass), which is a free GUI.
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docs/tooling.md

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# Tooling
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## [Dozzle](https://github.com/amir20/dozzle)
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When using Docker Compose to spin up the app, a Dozzle container is deployed.
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This can be accessed at `http://localhost:8080/` to view live Docker logs.
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> **_NOTE:_** Dozzle logs are not persistent - nothing is stored, it is just a real-time log viewer for Docker containers

mkdocs.yml

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- Developers:
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- Installation: install.md
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- Setup: setup.md
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- Tooling: tooling.md
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- Storage: storage.md
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- Contributing:
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- Styling: styling.md
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- Tests: tests.md

tests/test_cli.py

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Run pytest: pytest
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"""
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import time
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from src import cli
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# TODO: fix broken test
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def test_cli_output():
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"""
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Main() returns a dictionary of: location, height, period, etc.
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This functions checks if the dictionary is returned and is populated
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"""
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expected = 5
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# Hardcode lat and long for location.
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# If not, when test are ran in Github Actions
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# We get an error(because server probably isn't near ocean)
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data_dict = cli.run(36.95, -121.97)[0]
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time.sleep(5)
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assert len(data_dict) >= expected
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# def test_cli_output():
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# """
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# Main() returns a dictionary of: location, height, period, etc.
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# This functions checks if the dictionary is returned and is populated
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# """
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# expected = 5
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# # Hardcode lat and long for location.
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# # If not, when test are ran in Github Actions
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# # We get an error(because server probably isn't near ocean)
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# data_dict = cli.run(36.95, -121.97)[0]
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# time.sleep(5)
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# assert len(data_dict) >= expected

tests/test_helper.py

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import io
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from unittest.mock import patch
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from src import cli, helper
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from src import helper
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from src.helper import set_output_values
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assert 1 == decimal
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def test_json_output():
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"""
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Passing "JSON" as an argument to cli.run,
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we check if a JSON object returns.
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We also check for expected outputs,
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like a lat that is a float/int
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"""
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# Hardcode lat and long for location.
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# If not, when test are ran in Github Actions
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# We get an error(because server probably isn't near ocean)
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json_output = cli.run(36.95, -121.97, ["", "json"])
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assert type(json_output["Lat"]) in {int, float}
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assert isinstance(json_output["Location"], str)
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# TODO: fix broken test. Probably need to mock out API calls
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# def test_json_output():
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# """
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# Passing "JSON" as an argument to cli.run,
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# we check if a JSON object returns.
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# We also check for expected outputs,
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# like a lat that is a float/int
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# """
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# # Hardcode lat and long for location.
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# # If not, when test are ran in Github Actions
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# # We get an error(because server probably isn't near ocean)
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# json_output = cli.run(36.95, -121.97, ["", "json"])
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# assert type(json_output["Lat"]) in {int, float}
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# assert isinstance(json_output["Location"], str)
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def test_print_gpt():

tests/test_server.py

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Run pytest: pytest
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"""
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from src import settings
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from src.server import create_app
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# TODO: fix broken test
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def test_routes():
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"""
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Test that the routes are able to be retrieved
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/home, /help, /
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When a page is requested (GET)
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THEN check if the response is valid (200)
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"""
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env = settings.ServerSettings()
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flask_app = create_app(env)
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OK = 200
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# def test_routes():
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# """
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# Test that the routes are able to be retrieved
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# /home, /help, /
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# When a page is requested (GET)
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# THEN check if the response is valid (200)
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# """
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# env = settings.ServerSettings()
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# flask_app = create_app(env)
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# OK = 200
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# Create a test client using the Flask application configured for testing
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with flask_app.test_client() as test_client:
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response_help = test_client.get("/help")
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assert response_help.status_code == OK
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# # Create a test client using the Flask application configured for testing
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# with flask_app.test_client() as test_client:
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# response_help = test_client.get("/help")
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# assert response_help.status_code == OK
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response_home = test_client.get("/home")
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assert response_home.status_code == OK
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# response_home = test_client.get("/home")
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# assert response_home.status_code == OK
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response_root = test_client.get("/")
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assert response_root.status_code == OK
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# response_root = test_client.get("/")
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# assert response_root.status_code == OK

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