Is the weather data real-time?

Yes — the endpoint returns current observations, updated continuously from worldwide weather stations.

Can I look up weather by coordinates instead of a city name?

Yes. Pass lat and lon query parameters instead of city — the natural fit when coordinates come from a browser, the Geocoding API, or the IP Lookup API.

What units does the API use?

Temperatures in Celsius, wind speed in meters per second, and sunrise/sunset as Unix timestamps in UTC. Convert to Fahrenheit with F = C × 9/5 + 32.

Does the API provide forecasts?

Yes — the companion /v1/weatherforecast endpoint returns forecast data for a location using the same API key.

How do I get past weather instead of current conditions?

This endpoint is current-conditions only. For the past, see our guide on historical weather data — it covers public archives plus logging this API on a schedule to build your own history.

How to Get Weather Data in Python

Prerequisites

You need three things:

Python 3.8 or newer.
The requests library.
A free API Ninjas API key — issued instantly, no credit card. If you already have an account, it's on your profile page.

shell

pip install requests

Step 1: Fetch current weather

The endpoint is /v1/weather — pass a city and you get the current observations:

weather.py

import requests

response = requests.get(
    'https://api.api-ninjas.com/v1/weather',
    params={'city': 'London'},
    headers={'X-Api-Key': 'YOUR_API_KEY'},
    timeout=10,
)
response.raise_for_status()
weather = response.json()

print(f"London: {weather['temp']}°C, humidity {weather['humidity']}%")
# London: 14°C, humidity 82%

The request on the wire and the full response:

api.api-ninjas.com

GET/v1/weather?city=London

200 OKapplication/json

{
  "cloud_pct": 75,
  "temp": 14,
  "feels_like": 13,
  "humidity": 82,
  "min_temp": 12,
  "max_temp": 16,
  "wind_speed": 4.63,
  "wind_degrees": 240,
  "sunrise": 1717645800,
  "sunset": 1717703400
}

Step 2: Read the response

Every field, with its unit:

Field	Unit	Meaning
`temp`, `feels_like`	°C	Current and apparent temperature.
`min_temp`, `max_temp`	°C	Today's range so far.
`humidity`, `cloud_pct`	%	Relative humidity and cloud cover.
`wind_speed`, `wind_degrees`	m/s, °	Wind speed and direction (0° = north).
`sunrise`, `sunset`	Unix (UTC)	Today's sun times as timestamps.

Metric units and Unix timestamps are deliberate — they convert cleanly instead of guessing your locale. The two conversions you'll actually write:

units.py

def c_to_f(celsius: float) -> float:
    return celsius * 9 / 5 + 32

from datetime import datetime, timezone

weather = get_weather('London')
sunrise = datetime.fromtimestamp(weather['sunrise'], tz=timezone.utc)
print(f"{c_to_f(weather['temp']):.1f}°F, sunrise {sunrise:%H:%M} UTC")

Wrapped as a client with the key in an environment variable:

weather_client.py

import os

import requests

API_URL = 'https://api.api-ninjas.com/v1/weather'

session = requests.Session()
session.headers['X-Api-Key'] = os.environ.get('API_NINJAS_KEY', 'YOUR_API_KEY')


def get_weather(city: str) -> dict:
    """Return current conditions for a city."""
    response = session.get(API_URL, params={'city': city}, timeout=10)
    response.raise_for_status()
    return response.json()


weather = get_weather('London')
print(f"Temperature: {weather['temp']}°C (feels like {weather['feels_like']}°C)")
print(f"Wind:        {weather['wind_speed']} m/s")
print(f"Cloud cover: {weather['cloud_pct']}%")

Step 3: Query by coordinates

When the location comes from a browser, GPS, or another API, skip the city name entirely and pass lat/lon:

by_coords.py

# Coordinates work in place of a city name — useful straight from
# GPS, the Geocoding API, or the IP Lookup API.
response = session.get(
    API_URL,
    params={'lat': 51.5074, 'lon': -0.1278},
    timeout=10,
)

The upstream sources pair naturally: the Geocoding API turns place names into coordinates, and the IP Lookup API turns a visitor's IP into them.

Step 4: Track multiple cities

A weather dashboard is a loop — the shared session keeps it fast:

cities.py

cities = ['London', 'Tokyo', 'New York', 'Sydney']

for city in cities:
    w = get_weather(city)
    print(f"{city:10} {w['temp']:>5}°C  {w['humidity']:>3}% humidity  {w['wind_speed']:>5} m/s")

If you schedule this and store each response with a timestamp, you're building your own weather history — the full pattern is in How to Get Historical Weather Data.

Step 5: Handle errors

The common failure is a city name the API doesn't recognize (400) — fall back to coordinates when you can. The rest are the standard pair: bad key (401) and rate limit (429):

errors.py

from requests.exceptions import HTTPError, RequestException

try:
    weather = get_weather('Atlantis')
except HTTPError as error:
    status = error.response.status_code
    if status == 400:
        print('Unknown city — check the spelling, or pass lat/lon instead')
    elif status == 401:
        print('Missing or invalid API key')
    elif status == 429:
        print('Rate limit exceeded — cache recent responses')
    else:
        print(f'HTTP {status}: {error.response.text}')
except RequestException as error:
    print(f'Network error: {error}')

Where to go from here

The same key serves /v1/weatherforecast for the forward view, the Air Quality API for PM2.5 and ozone at the same coordinates, and our historical weather guide for everything before today. The complete script is below.