cli-surf 2.3.1

Command-line surf report tool

cli-surf is a real-time ocean data and surf forecasting tool for the command line.

• Live wave height, swell direction, period, UV index, wind, and more
• Forecasts up to 7 days out
• Use as a CLI tool (surf) or query via HTTP API / browser
• Optional GPT-powered surf reports
• Supports metric and imperial units, custom colors, and JSON output

Inspired by wttr.in · Documentation · Discord

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Table of Contents

• Usage
• Setup
  • Poetry
  • Docker
  • Environment Variables
  • Email Server
  • MongoDB
• GPT Surf Report
• Tech Stack
• Architecture
• Contributing
• Contributors

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💻 Usage

There are several ways to use cli-surf: install it as a CLI tool via pipx, hit the public API, or run the server locally and access it via API/browser.

Installing via pipx (pypi)

brew install pipx
pipx install cli-surf

surf --help
surf --location scripps_pier --forecast 4

Hitting the public API

curl https://api.clisurf.com

Running the server locally and using via API

Start the server locally (see Setup below), then query it from your browser or CLI:

$ curl localhost:8000

Location:  San Diego

      .-``'.
    .`   .`
_.-'     '._ 

UV index:  6.4
Wave Height:  3.9
Wave Direction:  238.0
Wave Period:  9.8

API Examples

Arguments are separated by commas.

curl localhost:8000
curl localhost:8000?location=new_york,hide_height,hide_wave,show_large_wave
curl localhost:8000?fc=3,hdate,loc=trestles,c=light_blue
curl localhost:8000?show_past_uv,show_height_history,show_direction_history,show_period_history
curl localhost:8000?loc=malibu,gpt,color=yellow
curl localhost:8000?loc=nazare,json

For the full argument reference, see below or run:

curl localhost:8000/help

API Arguments

Display

Argument	Shorthand	Description
location	loc	Location for the forecast. Ex: loc=new_york_city or loc=nyc
hide_wave	hw	Hide the default wave art
show_large_wave	slw	Show the large wave art
color	c	Color of wave art. Ex: color=light_blue
hide_location	hl	Hide location name
hide_date	hdate	Hide date in forecast
metric	m	Use metric units (default: imperial)
decimal	dec	Specify decimal places in output
json	j	Output data as JSON. Must be the only argument

Surf Conditions

Argument	Shorthand	Description
hide_height	hh	Hide wave height
hide_direction	hdir	Hide swell direction
hide_period	hp	Hide swell period
hide_uv	huv	Hide UV index
show_air_temp	sat	Show air temperature
show_wind_speed	sws	Show wind speed
show_wind_direction	swd	Show wind direction
show_rain_sum	srs	Show rain sum
show_precipitation_prob	spp	Show max precipitation chance
show_cloud_cover	scc	Show hourly cloud cover
show_visibility	sv	Show hourly visibility

Historical Data

Argument	Shorthand	Description
show_past_uv	spuv	Show past UV index
hide_past_uv	—	Hide past UV index
show_height_history	shh	Show past wave height
hide_height_history	—	Hide past wave height
show_direction_history	sdh	Show past wave direction
hide_direction_history	—	Hide past wave direction
show_period_history	sph	Show past wave period
hide_period_history	—	Hide past wave period

GPT

Argument	Shorthand	Description
gpt	g	Activate GPT surf report. Customize via GPT_PROMPT in .env. Default: off

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🛠️ Setup

How to Start Locally with Poetry

1. Install Poetry.

2. Clone the repository.

   git clone https://github.com/ryansurf/cli-surf.git
   cd cli-surf
   

3. Install dependencies and activate the virtual environment.

   make install
   

4. Start the server.

   poetry run python src/server.py
   
   # Or via Makefile
   make run
   

How to Start with Docker

1. Install Docker and Docker Compose.

2. Clone the repository.

   git clone https://github.com/ryansurf/cli-surf.git
   cd cli-surf
   

3. Start the container.

   docker compose up -d
   
   # Or via Makefile
   make run_docker
   

Variables

When running locally with Poetry, create a .env file from the example:

cp .env.example .env

When starting with Docker, the .env file is created automatically from .env.example during the image build.

General

Variable	Description
PORT	Port to run the application on. Default: 8000
IP_ADDRESS	IP address the server runs on. Default: localhost

Email (optional — see Email Server)

Variable	Description
SMTP_SERVER	Email server. Default: smtp.gmail.com
SMTP_PORT	Email server port. Default: 587
EMAIL	Address to send the report from
EMAIL_PW	Sending email's password
EMAIL_RECEIVER	Address to receive the report
COMMAND	Command shown in the email. Default: localhost:8000
SUBJECT	Email subject line. Default: Surf Report

GPT (optional — see GPT Surf Report)

Variable	Description
GPT_PROMPT	Prompt sent to the model along with surf data. Ex: With this data, recommend what size board I should ride.
API_KEY	OpenAI API key. Create one here
GPT_MODEL	OpenAI model to use. Default: gpt-3.5-turbo (recommended: gpt-4o). See all models here

Database (optional — see MongoDB)

Variable	Description
DB_URI	MongoDB connection URI

Email Server

Optional — sends a surf report to a specified email on a schedule.

You'll need an email account with SMTP access. Gmail works; follow Method #1 here, then update the email variables in .env.

Note: The FastAPI server must be running to send emails.

# Send email locally (Poetry)
make send_email

# Send email via Docker
make send_email_docker

MongoDB

Optional — stores all request output in a MongoDB database.

See the MongoDB get started guide for setup, then set DB_URI in your .env.

Frontend

Note: The frontend is no longer maintained

Although this application was made with the CLI in mind, a frontend exists.

Streamlit Frontend

streamlit run src/dev_streamlit.py
# Available at http://localhost:8502

HTML/JS/CSS Frontend (legacy, no longer actively developed)

Available at http://localhost:8000/home or <ip_of_host>:<port>/home.

You may need to set IP_ADDRESS in .env to match the host's IP.

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🧠 GPT Surf Report

cli-surf can generate personalized surf reports using OpenAI's GPT models.

Setup

1. Get an OpenAI API key at platform.openai.com. Make sure a payment method is added.

2. Update .env:

   API_KEY=your_openai_api_key_here
   GPT_MODEL=gpt-3.5-turbo   # gpt-4o recommended for better results
   GPT_PROMPT=With this data, recommend what size board I should ride and nearby surf spots that may be better with the given conditions.
   

3. Use the gpt argument:

   curl localhost:8000?location=Malibu,gpt
   

Customizing the prompt

Change GPT_PROMPT in .env to get different types of reports:

GPT_PROMPT="Analyze the surf conditions and suggest the best time of day to surf."
GPT_PROMPT="What are some good places to eat around this surf spot?"

Notes

• A payment method is required — OpenAI will reject requests from free accounts.
• GPT responses consume tokens based on prompt and response size.
• Response time may be slower than standard output, especially during OpenAI outages.
• gpt-4o gives better results than gpt-3.5-turbo but costs more.

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🔧 Tech Stack

Layer	Technology
Language	Python 3.10+
Web framework	FastAPI + Uvicorn
CLI	Click
Weather data	Open-Meteo API
Optional AI	OpenAI GPT API
Optional database	MongoDB (pymongo)
Optional frontend	Streamlit
Packaging	Poetry, pipx
Containerization	Docker / Docker Compose
Cloud	AWS (Lambda, ECR, API Gateway), CloudFlare (DNS resolver), GoDaddy (register domain name)

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📐 Architecture

Architecture

📈 Contributing

Thank you for considering contributing to cli-surf!

See CONTRIBUTING.md to get started.

Questions? Comments?

• Discord
• Discussions
• GitHub

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✨ Contributors

Ryan Frederich 💻 📖 ⚠️ 🤔 💬	𝕂' 💻 📖 ⚠️ 🤔 💬	Corey L. 💻	Shaiful Azhar 💻	Hummus-Ful 🚇	Rajiv-Rago 💻	Ulises-Sanch3z 💻
Andrew Koller 💻	Michael McGrain 💻	SeanAverS 💻	Rabel Mervin 💻	Vaibhav Chouhan 💻	Nandani Thakur 💻	Brandon 🚇
ChristianToro 💻 🐛	Myles B. 💻	Balaji Ganapathy 🐛	chengjackjelly 🚇	Varun Singh 📖 🐛	macnult 💻	AITMAR-TAFE 💻
Latif Fetahaj 💻 ⚠️	Kim ⚠️ 💻	Devon Hebenton 💻	AristosKass ⚠️	Raza Khan 💻

License