Recently, Tomorrow.io and Postman ran the Harness the Weather Hackathon; this is the second blog post in our series featuring Tomorrow.io’s collection. The demo in the blog showcases what’s possible when working with Tomorrow.io and Postman.

This time, we’ll explore Tomorrow.io’s advanced alerting system that allows you to subscribe to locations of interest and national weather advisories with just a few steps. Following an official Tomorrow.io “recipe” on their docs, let’s walk through how to set up an alert for winter weather hazards, with the results in the tutorial theoretically notifying company staff in Boston via a Slack channel.

Follow along by forking the collection in Postman here.

1. Get your API key

Before we begin, sign up to their platform and, once logged in, grab your key.

2. Building parameters and body

Next, in our first request to create alerts, we will be running a pre-request script to build our options.

Choose an insight category

In our case, we will automatically notify the company employees to stay home and safe whenever there’s an event of “winter” type.

First, we need to choose an insight category covering the weather events we’d like to monitor with alerts:

Note: Our collection currently mainly covers US weather reports issued by NWS. This will be extended soon, so keep an eye out for updates.

Specify the name and notification details

Next, we will add some descriptive text for these specific alerts that we can pull directly from the webhook’s payload to enrich our message—without needing additional handling by the distribution service.

Alerts based on a custom insight can be sent PRIOR/START/END of the detected weather event because they are calculated throughout the day. However, category insight alerts rely on external sources and only trigger notifications as they are published.

3. Create a severe weather alert

Now that we have all of the parameters, we can create the alert in the system to be linked to our locations of interest later.

By default, all alerts are created as active. If you wish to activate them at a later stage, make sure to set isActive as false, and after that, use the /activate and /deactivate endpoints:

4. Link a predefined location to alert

Unlike custom insight alerts, these can be linked to any location type—be it Point, Polygon, or Polyline—as long as it is predefined in the system.

This uses the locationId of the Tomorrow.io headquarters neighborhood in Downtown Boston. When we set it up, we used a Polygon geometry to create a “geofence” around the office to ensure no nearby weather events were missed:

5. Configure the webhook URL

Finally, you need to connect the platform to your webhook URL, listen to incoming events, and parse the notification payload to distribute it to your chosen channel.

There are a few ways to go about this. Some are easier than others. Read our guide on Alert Listeners to learn how to set that up.

Using this, you can connect with other APIs for your Harness the Weather Hackathon project. Set up with Twilio to send text alerts or Slack to send notifications to office channels!

Give this a fork and a try, then create something cool.

The post Set Up Severe Weather Alerts Around A Geofence appeared first on Tomorrow.io.

Our team has been hard at work over the past couple of months, developing and refining new updates to our weather API to help you better navigate the ever-changing weather landscape and make more informed weather-related decisions.

Learn how these updates can transform the way you approach implementing weather intelligence and climate adaptation for your business or organization below. 

Weather API Updates 

1. Events Timeline API 

We are excited to bring insights on the fly to Tomorrow.io API users via our new Events_Timeline endpoint. 

The Events_Timeline is a new endpoint in our Monitoring API Solutions that allow our API customers to see when weather conditions are met for a specific location on-call without pre-creating insights and locations. 

Reach out to an account manager to start using this endpoint. 

View Events Timeline Documentation

2. Probabilistic Forecasting

Tomorrow.io’s weather API predicts the weather using a method called probabilistic forecasting. Instead of giving just one possible forecast, this method provides a range of potential outcomes with a level of certainty. 

Our weather API provides a list of seven different percentiles – 5%, 10%, 25%, 50%, 75%, 90%, and 95%. These percentiles allow users to paint a picture of the potential scenarios that can occur along with their likelihood of occurrence.

How to Access:  

For each field in our Weather Data Layers, you can see if the data layer is supported by Probabilistic Forecasting according to symbol (P) under the Availability column: 

• P: +    = it’s available for the field
• P: –     = it’s not available for the field.

View Probabilistic Forecasting Documentation

3. Lightning Alerts Available via Webhooks 

Using the Tomorrow.io Weather API, you can now send Lightning alerts through our webhooks system. 

How to Access:

When an Event is generated for an Insight being monitored with an Alert, the system will trigger a Webhook notification. There are three types of potential trigger events:

• Insight Categories (aka Severe Weather Events): monitor the issuance of weather hazards as reported by national authorities
• Custom Insights: tailor conditions to your exact use case from our collection of >80 data points
• Lightning Strike: get an alert for possible lightning, including cloud-to-cloud and cloud-to-ground lightning strikes. This is a paid API feature. 

Once your alerts are configured, make sure to set up proper Alert Listeners on your application side to handle these incoming events.

View Alerts API Documentation

4. New API Insights Syntax

We’re excited to share a new simple syntax that can be used to create insights with the Tomorrow.io Weather API. 

If you were wanting to create a simple insight to check for windspeed > 30 and temperature > 30, you would only have to use the following syntax: 

(windSpeed > 30 AND temperature > 30)

How to Access: 

An insight can be defined by either:

• Starting from scratch by configuring it with a combination of parameters, operators, and constants that determine if a matching Event is forecasted to occur
• Subscribing to an Insight Category (that encompasses various similar events reported by our sources)

You can create an insight by either our Rules language (which we recommend) or using conditions – AST Trees. 

View Insights API and Syntax Documentation

5. Historical Minutely Timeline 

We are excited to introduce API users to our most accurate data via an hourly CCL model that presents minute-by-minute data for up to 7 days in the past. 

API users have two options for past weather data: 

• Free minute-by-minute weather data for up to 24 hours in the past 
• Paid minute-by-minute weather data for up to a week in the past

Reach out to an account manager to start using paid minutely data. 

View Historical Weather API Documentation

6. Low-Level Winds & Temperatures 

Tomorrow.io now offers low-level wind and temperature data to API users. This data, currently available for the U.S. and Israel, provides insights on wind speed, wind direction, and temperature at eleven vertical altitudes – from 10 to 300 meters above the ground. 

Businesses in the construction, drone, aviation, or energy industries that need wind data at different heights for their operations can greatly benefit. It is available up to 14 days in the future.

View Low-Level Winds Documentation

What’s Next at Tomorrow.io? 

We’re thrilled to showcase the latest enhancements and features to the Tomorrow.io Weather API. We’re committed to providing you with the most accurate and accessible weather information. 

Stay tuned for more exciting updates and developments as we continue to innovate and improve our platform to empower you in making informed decisions for your safety, efficiency, and overall success. 

Ready to Take These Features for a Test Drive?

See Weather Intelligence In Action

The post Tomorrow.io Weather API Updates 2023 appeared first on Tomorrow.io.

Tomorrow.io is on a really cool mission to give you the most accurate real-time weather data, even going so far as launching their own satellite constellation to do so. Recently, they teamed up with Postman to present the Harness the Weather Hackathon that’s currently running through August 31, 2023 and features a top prize of US$1,000. The hack focuses on their versatile Weather API, which “offers a comprehensive collection of ultra-accurate data organized into endpoints for the utmost ease-of-use and efficiency.”

Some of the things you can do with the Weather API include:

• Ensuring employee safety through weather alerts
• Predicting future weather events
• Incorporating more reliable weather data in your own software application

Tomorrow.io offers up some helpful instructions showcasing their API use cases and developer possibilities; they call these walkthroughs “recipes.” In this blog post, let’s dig into their “Build Your Own Weather App With One Call” recipe. While a code example is displayed in the recipe, a single view in a Postman request can show the exact call and details.

Let’s first break down the Timelines endpoint call using Postman. The Timelines endpoint can query data points to your locations with a single call.

Be sure to fork the collection to play around with the endpoint as well.

We’re going to walk through the steps to make a query for a Point location defined by a simple latitude/longitude pair of one of our favorite places, Times Square in New York City, using the GET call.

Below is a screenshot of the call in Postman. In this call, there is already some code provided in the pre-request scripts to fill in the required data:

Let’s step through this call now!

1. Grab an API key

Before we begin, make sure to sign up to Tomorrow.io’s platform and, once logged in, grab your key.

If you register for the Harness the Weather Hackathon, you can get special API access here.

Once you have your API key, you can fork or pull their endpoint from the Tomorrow.io collection. Here, you can see in a single call that we can grab the climate data of any location we please.

Simply add your API key to the query parameters to be able to send the request:

Let’s break down the pre-request script. This script runs before the call is sent and stores all the data in the environment variables so it is available for the call to use:

2. Pick the location

var location = [40.758, -73.9855];

In this type of call, only two types of location values are supported—either a latlong pair (separated by a comma) or a locationId of a predefined location in the system (see the /locations endpoints).

In your app, you can change these per query dynamically, but we chose to only get the weather data for Times Square in New York City in this tutorial.

You can query using polygons and polylines, as part of their premium feature set.

3. List all the fields

var fields = [ "precipitationIntensity", 
"precipitationType", 
"windSpeed", 
"windGust", 
"windDirection", 
"temperature", 
"temperatureApparent", 
"cloudCover", 
"cloudBase", 
"cloudCeiling", 
"weatherCode"];

All accounts come with the Core data layer for free and with samples of the premium data layers, such as air quality and pollen.

The app we’re building requires only the basics, such as precipitation, wind, temperature, clouds, and weather code. But, if you’re interested in getting full access to premium data points like solar irradiance, soil moisture, or wave height, make sure to reach out to sales@tomorrow.io.

Note that some field values might be null when there isn’t a valid numerical value—like wind direction when there’s no wind.

4. Choose the unit system

var units = "imperial"

You can select either the imperial or metric unit system. This applies to all of the fields in the query. In the US, the common system is imperial, consisting of units such as the inch, the mile, and the pound—so that’s our choice.

The Timeline response payload is lean, flat, and language-agnostic by design, containing only the raw field values as numbers, enums, or ISO-8601 timestamps. This allows developers to use it on mobile devices and translate the field units’ representative strings to the language of their choice.

5. Set the timesteps

var timesteps = ["current", "1h"];

As mentioned, the Timelines endpoint allows you to request multiple timesteps with one call.

Any of the following values are supported to choose the interval for which the data is provided: 1m, 5m, 15m, 30m, 1h, 1d, and current (which provides realtime measurements).

For each field, you will find the applicable timestep for its time frame, whereas In any case of two different timesteps—like m (minutes), h (hours) or d (days)—the data is available for any timesteps options between them.

Given that we asked for the 1d timesteps, it’s important to highlight that whenever a Min/Max/Avg suffix is not added to the named field, the API will resolve the max value. You can always get more specific by adding Min/Max/Avg to get the values you want. Moreover, you can add MinTime and MaxTime if you want to know when at the earliest these values will be met in the day interval.

6. Configure the time frame

var startTime = moment.utc(now).add(0, 'minutes');
var endTime = moment.utc(endTime).add(1, 'day');

In this example, we’re only interested in getting the upcoming day, though most of our data points are supported up to six hours back and fifteen days out.

Check out the Frame annotation of each data point to learn more about its availability. Notice that we used UTC as the input time zone, but you can use whichever zone you want.

7. Specify the time zone

var timezone = "America/New_York"

Regardless of the input time zone, mentioned in the startTime and endTime timestamps, you can request the returned timestamps to be in a different zone. Just make sure to use the standard IANA Time Zone Database format.

Since we’re going to get the data for Times Square, we will want it in New York’s time zone.

8. Request the timelines

Clicking Send in Postman will run the pre-request script building values for all the variables.

Use the resulting JSON response to parse the intervals of the timelines, each for a single timestep, as defined in the request:

With just a single call, we are now able to get all the weather data we need to build a Postman Collection workflow powered by weather data.

Give this a fork and a try, then create something cool for the Harness the Weather Hackathon—you just might win the top prize of US$1,000 when winners are announced at ClimaCon!

The post Build Your Own Weather App With One API Call appeared first on Tomorrow.io.

Building a weather application entails leveraging these APIs and utilizing accurate hyper-local weather data to then present this information to a user in an easily digestible format. We’ll be exploring the basics of this process, using Tomorrow.io’s weather API,  and reviewing geolocation capture, weather data retrieval, data parsing, and finally, weather app creation.

Getting an API Key

To begin building a weather app, you need to get a weather API key from a weather API provider. Getting an API key from Tomorrow.io is easy, just sign up and create an account. When you create an account, your personal API key will be automatically created for you to use in your application.

After signing up, you are ready to make your first API call.

Getting the User’s Geolocation

A pivotal aspect of any weather application is accurately identifying the user’s geolocation. When building a weather app, you much determine what location you are creating this app experience for.

The HTML5 Geolocation API and IP Geolocation are the most common methods to identify a user’s geolocation.

The HTML5 Geolocation API allows developers to access geolocation data directly from a user’s device, provided they grant permission. Implementation is straightforward, involving a simple JavaScript call to the navigator.geolocation object.

On the other hand, IP Geolocation involves determining a user’s location based on their IP address. Various services provide this functionality, though accuracy may vary, particularly for mobile users.

However, both methods have their limitations. HTML5 Geolocation requires user consent; if not granted, the app fails to get the location. Similarly, VPN usage or mobile data networks can significantly influence IP geolocation’s accuracy.

Retrieving Weather Data

Once you’ve captured the user’s location, the next step involves retrieving weather data relevant to this location. You can do this by making API requests to a weather data service like Tomorrow.io. 

A sample API request using a GET request function may look like this:

curl --compressed --request GET --url \
'https://api.tomorrow.io/v4/timelines?location=40.75872069597532,-73.98529171943665&fields=temperature&timesteps=1h&units=metric&apikey=vToTXJJt0odoDGXt1mYI66IeT6X21Spg'

However, one challenge with retrieving weather data includes rate limiting, where the API provider restricts the number of requests you can make within a certain period. To overcome this, consider efficient call structuring or opting for a paid plan. 

Parsing Weather Data

After retrieving the weather data, you’ll need to parse it to extract the information you require. The data returned by most weather APIs is often in JSON format, which JavaScript can easily parse.

Commonly provided data types include current conditions, forecasts (hourly, daily), humidity, wind speed, UV index, and more.

Here is an example of parsing weather data to get current temperature:

javascript

fetch('https://api.tomorrow.io/v1/current.json?key=YOUR_API_KEY&q=' + latitude + ',' + longitude) .then(response => response.json()) .then(data => { let temperature = data.current.temp_c; console.log(temperature); })

Building a Weather App

Once you’ve got the data, it’s time to build the user interface (UI). The UI should present the weather data clearly, concisely, and aesthetically pleasingly. Pay special attention to the user experience (UX), ensuring the app is intuitive and responsive.

Displaying weather data should be done in a way that provides immediate understanding. For instance, the current weather condition should be the most prominent, with options to explore further details like hourly or weekly forecasts.

The main challenges here include:

• Ensuring your app’s responsiveness.
• Caching data for offline use.
• Updating weather data at appropriate intervals.

To overcome these, use responsive design frameworks like Bootstrap, caching techniques such as service workers, and periodic updates using JavaScript’s setInterval method.

Leveraging Accurate Weather Data

In summary, building a weather application involves:

• Capturing a user’s geolocation.
• Retrieving and parsing weather data from Tomorrow.io’s Weather API.
• Creating a user-friendly interface to display the data.

While this article provides an initial overview, the world of weather apps is vast and ripe with innovation opportunities. There is so much to be done with historical and real-time weather data, and with hyper-local weather information from Tomorrow.io, the possibilities are endless. Keep exploring and innovating; there’s always room for a new player in the market offering a unique take on weather data presentation.

Good luck with your weather app journey!

The post Building a Weather App with APIs: From Geolocation to Data Collection appeared first on Tomorrow.io.

Why Choose Tomorrow.io Climate API? 

The Tomorrow.io Climate API is designed for developers seeking to integrate comprehensive climate variables into their applications. Leveraging advanced weather models, this Climate API provides valid data sets to meet diverse climate-related challenges, aiding in climate change adaptation at a broader scale.

With a Climate API, you can access historical climate data that can aid you with improved weather-related decision-making for your business or organization. 

How to Utilize Tomorrow.io’s Climate API

Via the Climate Normals endpoint, this Climate API provides access to 20 years of high-resolution climate data. Developers can aggregate this data daily or over 20 years for various weather fields, including temperature, precipitation, wind speed and direction, and much more. When you sign up for Tomorrow.io’s weather API, you can retrieve up to two decades of climate data with a single API request.

Decoding Climate Data Fields

Climate Normals, as part of the entire Weather API from Tomorrow.io, provides access to various climate data fields and weather layers, including current temperature, base humidity, precipitation, air quality, wind speed, and direction. Developers can aggregate this data to extract valuable insights into long-term climate trends and patterns, collected from a combination of our extensive network of weather stations and publicly available data, processed through our proprietary modeling.

Leveraging Climate Data Insights for Optimal Business Strategy

The Tomorrow.io Climate API allows you to utilize hyperlocal climate data to enhance your business strategy and resource management. This data equips you to make data-driven decisions to mitigate climate change-associated risks and plan for the future efficiently.

Adapting to Climate Change Across Diverse Sectors

The Climate API is a valuable tool for businesses, governments, and individuals intending to understand and plan for climate change impacts. Industries ranging from general ESG goals, truck manufacturers, airlines, energy production, agriculture, and urban planning, can all benefit from our API by making data-driven decisions.

Understanding the Climate API

Our Climate API offers access to Climate Normals, which provides a comprehensive view of climate patterns over 20 years. Businesses, governments, and individuals looking to plan for the future can take advantage of these insights, as Climate Normals are a powerful solution for addressing climate change impacts.

How Businesses Can Benefit from the Climate API

Tomorrow.io’s Climate API is a vital tool for businesses and organizations needing to understand and manage climate change impacts. Companies can make informed decisions on resource allocation, supply chain management, and investment strategies by accessing insights into long-term climate trends and patterns with Climate Normals.

The Tomorrow.io Climate API is ideal for businesses, governments, and individuals looking to understand and plan for the impacts of climate change. Here’s where we imagine impacting the most:

General ESG goals: 

The Climate API can help businesses reduce carbon dioxide emissions, avoid carbon leakage, and comply with carbon price regulations/carbon taxation by providing accurate climate data for emissions reduction strategies.

Truck Manufacturers 

Trucking companies can use Climate APIs to optimize routes for zero-emission or cleaner fuel vehicles (or even zero-emission trucks), reducing their carbon footprint and operating costs.

Airlines 

The airline industry can benefit significantly from the Climate API by accessing real-time and historical weather data to optimize routes and fuel consumption. By analyzing climate patterns, airlines can make data-driven decisions around scheduling flights, reducing delays due to weather conditions, and improving overall customer experience.

Energy Production 

The Climate API is a valuable tool for the electricity and power sectors, allowing producers to optimize production based on historical climate data and long-term trends.

Agriculture 

Farmers can leverage Climate Normals to understand long-term climate trends and patterns, optimizing crop selection and timing for planting and harvesting.

Urban Planning 

Municipalities can use the Climate API to understand long-term climate trends and patterns to inform infrastructure planning and disaster risk reduction.

Climate API Frequently Asked Questions

What is the Climate API?

This tool offers access to Climate Normals, which provides a comprehensive view of climate patterns over 20 years. With an hourly temporal resolution, Climate Normals calculates and presents data between 2000 and 2020. Climate Normals offers valuable insights into long-term climate trends and patterns, making it an essential tool for businesses, governments, and individuals looking to understand and plan for the future. Climate Normals are a cutting-edge solution that can benefit those seeking to address the consequences of climate change, owing to high-resolution data and long-term perspective.

How Can Businesses Use the Climate API?

The Climate API is ideal for businesses and organizations that need to understand and manage the impacts of climate change. With the Climate API, companies can access valuable insights into long-term climate trends and patterns, making it an essential tool for businesses looking to understand and plan for the future. Many organizations can use Climate Normals to inform decision-making around resource allocation, supply chain management, and investment strategies.

What Weather Data is Available via Tomorrow.io’s Climate API?

The Climate API provides access to hourly weather data, including temperature, precipitation, wind speed, wind direction, and more. This data allows businesses to make data-driven decisions and prepare for future climate impacts, reducing risks and minimizing potential costs associated with extreme weather events.

Who Benefits from Tomorrow.io’s Climate API?

The Climate API can benefit various industries and use cases, including government agencies, renewable energy companies, heavy industry, and transportation companies. With Climate Normals, businesses can understand long-term climate trends and patterns, allowing them to make data-driven decisions to reduce risks, increase efficiency, and prepare for future climate impacts. The Climate API is a powerful tool for anyone interested in understanding and managing the effects of climate change.

Get Started With Historical Weather Data Today 

Tomorrow.io’s Climate API is an advanced tool for precise, long-term climate data, enabling better strategies and intelligent decisions. Regardless of whether you’re a developer, a business, or a government agency, leverage this technology to optimize your operations, mitigate risks, and enhance overall performance. 

Embark on your journey towards intelligent climate adaptation with Tomorrow.io’s Climate API. 

The post Tomorrow.io’s Climate API: Empower Your Business with Two Decades of Hyperlocal Climate Data appeared first on Tomorrow.io.

Why Choose Tomorrow.io’s Routes API?

Tomorrow.io’s Routes API is a beacon for developers who want to integrate ultra-accurate, real-time weather data into their routing algorithms. 

From determining route costs to choosing destination locations, the Routes API presents a comprehensive array of data to ensure optimal decision-making. This innovative tool allows you to navigate routes not only more efficiently, but also more safely.

The Mechanics of Tomorrow.io’s Routes API

The Routes API’s endpoint is designed to accept a standard output response typically used by popular navigation service APIs like Google Maps and Mapbox. Each segment of your journey, or “leg”, is represented by a location and duration. Using the startTime and timestep you provide, the API generates a compilation of intervals that illustrate the min/max/avg conditions along the route.

Using Legs for Weather on Routes

A route is mainly defined by a set of legs, each with the geometry that defines it (Point, Polyline, or Polygon) and the expected travel duration within it (in minutes). The legs are defined using the following structure:

Legs

[{

"duration": 54,

"location": {

"type": "LineString",

"coordinates": [

[-6.80897, 62.00008],

[-6.8047, 62.00069],

[-6.7996, 62.00181],

[-6.80149, 62.00293],

[-6.80207, 62.00349],

[-6.80226, 62.00375],

[-6.80237, 62.00414]

]

}

},

{

"location": {

"type": "LineString",

"coordinates": [

[100.0, 0.0],

[101.0, 0.0],

[101.0, 1.0],

[100.0, 1.0],

[100.0, 0.0]

]

},

"duration": 8

}

]

Developers can then extract valuable insights from each leg for a duration-optimized route, more efficient routes, and to better plan routes overall.

Harness Ultra-Accurate Weather Data for Route Optimization

Tomorrow.io’s Routes API grants you access to detailed weather data for your routes. This includes 80+ weather parameters like temperature, humidity, wind speed and direction, precipitation, and much more. You can use this data to optimize your routes, find eco-friendlier paths, and improve delivery times – all with the power of hyperlocal weather information.

Versatile Use Cases for Tomorrow.io’s Routes API

The Routes API is not only a tool but a solution for various industries that depend heavily on logistics and transportation. By having better weather data for route optimization, companies around the world can have improved insights into the routes their drivers take. Here are just a few examples of where this weather API could transform weather operations:

Transportation Companies 

With the Routes API, companies can minimize fuel consumption and costs by optimizing routes with hyperlocal weather insights.

Delivery Services

This API helps delivery services ensure the safe and efficient delivery of their products, avoiding weather-related delays or hazards.

Municipalities and Government Agencies 

These entities can use the Routes API to keep roads clear during winter weather, safeguarding drivers and pedestrians.

Construction Companies 

Those moving from one site to another can identify fallback routes and create more flexible routes based on quickly changing weather conditions.

Tourism Industry 

Tour operators can plan their itineraries to ensure guests can enjoy the best possible weather during their trips.

Tomorrow.io Routes API Frequently Asked Questions

What is a Routes API?

A Routes API is an application programming interface (API) that provides developers with access to geospatial data related to transportation routes, such as start and end points, estimated time of arrival, and travel distance. In the context of the Tomorrow.io API, the Routes API enables developers to integrate real-time weather data into their applications to optimize routes based on current weather conditions.

How does the Tomorrow.io Routes API work?

The Tomorrow.io Routes API takes the common output response of popular navigation service APIs (such as Google Maps Platform and Mapbox) as legs (each represented by a location and the duration within that route segment), the start time for the trip, and the timestep in which the developer is interested in sampling the conditions. The API then returns a collection of intervals that specify min/max/avg values throughout the route, considering the context (time spent in each leg).

Who Benefits from the Tomorrow.io Routes API?

The Tomorrow.io Routes API can benefit various industries and use cases that rely on transportation, including logistics and transportation companies, ride-hailing services, food delivery services, etc. By integrating real-time weather data into their routing and dispatching systems, these businesses can optimize their operations and improve efficiency, ultimately leading to cost savings and better customer experiences.

What Weather Data Is Available Via the Tomorrow.Io Routes API?

The Tomorrow.io Routes API provides a wide range of weather data and route parameters for any given route, including temperature, precipitation, wind speed and direction, and more. Developers can use this data to optimize their routes and delivery schedules, ensuring that their drivers or vehicles are not impacted by adverse weather conditions.

Get the Most of Weather on Routes 

In essence, Tomorrow.io’s Route API is a powerful tool that offers precise weather data, paving the way for better routes and smarter decisions. Whether you’re a developer, a transportation company, or a government agency, harness this technology to optimize your operations, ensure safety, and elevate user experience. Begin your journey towards intelligent routing today with Tomorrow.io’s Route API.

The post Tomorrow.io’s Routes API: Optimize Your Journey with Real-Time Weather Intelligence appeared first on Tomorrow.io.

Tomorrow.io’s high-precision Weather API provides real-time, forecast, and historical data for any location across the globe. But this is more than just a data repository; the API is loaded with the utility to drive specific use cases. 

Your mission, should you choose to accept it, is to create a powerful backend application using the Tomorrow.io API that fundamentally transforms how weather data can solve real-world problems. We’re not looking for just any solution; we’re seeking applications that think outside the box, leveraging the intrinsic value and versatility of the Weather API.

You will be expected to deliver a Postman Collection complete with detailed recipes or code guides along with your application. Your project should demonstrate a robust understanding of the API’s capabilities and illustrate creative and practical uses of weather data that can potentially transform industries, communities, and the world.

Whether it’s optimizing supply chain logistics, improving disaster management strategies, enhancing agricultural practices, or delivering personalized lifestyle recommendations, the possibilities are endless. However, your solution should be more than just inventive—it should be applicable, scalable, and valuable.

So, are you ready to shape the future of weather data utilization? Time to put on your coding caps, tap into your inner innovator, and show us how you would “harness the weather.”

Remember, this isn’t just a code fest; it’s a creativity challenge. Show us the power of weather data through your transformative backend solution. Read all the details below—and then let the coding begin!

Powered by Postman and Tomorrow.io

Submissions for the Harness the Weather Hackathon must be Postman Collections incorporating Tomorrow.io’s API suite hosted on the Public API Network. From chatbots powered by Postman Flows or Postman Monitors to your own custom API, we want to see how you would build with Tomorrow.io. 

How to Participate

1️. Register for the hackathon through the provided registration link and obtain a key to Tomorrow.io’s API.

2. Fork and watch Tomorrow.io’s Postman Collection in your own public workspace.

3️. Familiarize yourself with the Weather API and build your own weather-focused application in Postman using a Postman Collection with a Postman workflow.

4️. Create a two-minute demo video showcasing your Postman Collection and its outcomes. 

5️. Submit your link by August 1, 2023, 11:59pm (PT) via the submission link Postman will email all registrants in the final week of the hackathon.

Prizes and Recognition

Aside from the thrill of coding and collaborating with fellow weather enthusiasts, exciting prizes are up for grabs! The winner of the Harness the Weather Hackathon will receive the following:

• Tomorrow.io Incentive Prize: US$1,000
• US$100 Postman swag gift card: Show off your love for Postman with cool swag!
• Mention in a Postman blog post: Your project will get recognition on the Postman blog and gain exposure to a global audience of fellow developers and industry professionals.
• Recognition at ClimaCon: Your solution will be spotlighted at ClimaCon, the world’s leading weather and climate security conference, bringing together thousands of prominent voices in weather, ESG, and more.
• Social media recognition: You and your innovative solution will earn recognition on Tomorrow.io and Postman’s social media channels showcasing exemplary work to a broader audience.

Judging Criteria

Winners will be selected based on the following criteria:

• Postman Collection and recipes: Is your API call collection comprehensive? Are your code guides (or “recipes”) detailed and illustrative of your application’s function?
• Documentation: Does your Postman Collection have proper documentation that describes your project clearly? 
• Innovation and originality: Is your solution creative and innovative? Does it introduce new ways of thinking about or working with weather data?
• Presentation clarity: Have you effectively communicated your ideas, methodologies, and results in an engaging and coherent presentation?
• Real-world impact: Does your application offer practical benefits? Have you identified a problem and used the Weather API to address it effectively?
• API feature usage: How effectively have you utilized the unique features and capabilities of the Weather API?
• Code accessibility and transparency: As part of your submission, your code should be made available on a public repository, such as GitHub, for review and collaboration.
• API reference and acknowledgment: Your public posting must include the following disclaimer: This was powered by Tomorrow.io Weather API as part of the “Harness the Weather Hackathon” to enable others to understand the tools used for your application development.

Meet the Judges

Your solutions will be evaluated by an esteemed panel of judges, including:

• Cole Swain, VP of Product at Tomorrow.io
• Dan Slagen, Chief Marketing Officer at Tomorrow.io
• Luke Peffers, Chief Weather Office at Tomorrow.io

Stay tuned for more hackathon-related blog posts and updates for inspiration. We can’t wait to see how you code for a weather-informed future!

For support on any projects or questions, please email kyle.calica@postman.com.

*Originally published on Postman.com

The post Announcing the Harness the Weather Hackathon with Postman and Tomorrow.io appeared first on Tomorrow.io.

If you were a fan of Dark Sky’s Android app or pulled their weather data into your product at all, you need a Dark Sky API alternative. 

Tomorrow.io offers the best Dark Sky weather API alternative on the market.

This blog will fill you in on why we think Tomorrow.io’s weather API can meet the needs of your Dark Sky API gap and explain how much more it can do for you, your business, and your weather data needs.

What To Look For in a Dark Sky API Alternative

Suppose you’re looking for basic weather data for your app or business needs, including your simple temperature, precipitation, and humidity information. In that case, there are many APIs on the market that offer the data you’re looking for.

You can create a weather widget, for example, using the simplest weather data on the market and get daily updates on how cold or warm it’ll be outside, if it’s going to rain, and how humid it will be. 

Most weather providers simply pull in existing governmental data from sources like the National Oceanic and Atmospheric Administration (NOAA) and NASA, which are offering us global observations from the Join Polar Satellite System and a variety of other satellites in low earth orbit. 

But there is more weather data out there! So much more from sources including the thousands of weather stations in existence, regional automated weather sensors and networks, stationary ocean buoys, drifting buoys, aircraft, ships, and so many other interconnected networks. 

Tomorrow.io combines traditional weather data sources alongside new sensing technologies, including cell towers, not used by anyone else. This data has the following advantages over the data from traditional weather APIs, including:

• Hyperlocal Weather Observations: 500-meter radius observation vs. 2,000-4,000 meters
• Ground-Level Tracking: Precipitation as low as 30 feet off the ground vs. over 1,000 feet for radar.
• Up-to-date Data Delivery: Many Dark Sky API alternatives can deliver data every minute, but that data can be 5-20 minutes old (or older). Tomorrow.io provides updated data every minute and hour.
• NowCasting: Tomorrow.io provides minute-by-minute forecast data (aka minutely forecasts) for 0-6 hours out. Most other APIs provide this data in 1-hour chunks vs. 1-minute.

Why Use Tomorrow.io’s Weather API

Unlike other Dark Sky API alternatives, Tomorrow.io’s numerical data and map layers offer hyper-local, minute-by-minute weather data that allow you to build almost anything. When you see how much more data you can access, you may realize you can build something different or more ambitious than your original project.

What does that mean? The Tomorrow.io Weather API offers data in a variety of formats and timeframes, including:

• Historical Station Data – Weather data going on four weeks back.
• Historical Tomorrow.io Data – The last 6 hours of historical data are based on Tomorrow.io’s proprietary technology.
• Realtime Weather Data – Realtime weather based on our proprietary model
• Short-term Forecast (NowCast) – 6-hour proprietary NowCast data available in minute-by-minute intervals
• Near-term Forecast (Hourly) – Up to 96 hours of data available.
• Daily Forecast – Forecast of up to 15 days out

Tomorrow.io also provides data you might not expect to get from a Dark Sky Weather API alternative, including:

• Air Quality –  Data that helps you understand how increased air pollution impacts health
• Pollen – Tracking multiple types of pollen depending on your area
• Road risk – A scoring system to help you navigate through and around treacherous roads
• Fire Risk Index – The current risk of fire for a specific location

With Tomorrow.io’s complete suite of weather data and solutions far beyond your standard daily forecast, the options really expand and so does what you can do with weather data in your application or business. You can build even more interesting weather projects than you may have imagined with this type of data.

Build More with a Better Weather API

No matter what you’re building with your Dark Sky API alternative, you need quality weather data that is easy to work with.

Tomorrow.io Weather API is built on AWS, Autodesk, REST API using JSON for the requests and the responses, with HTTPS support, making it easily accessible and usable. 

Not sure where to start?

Tomorrow.io offers in-depth weather API documentation with a ton of information about how to use our weather API to build your project.

You can also find multiple pricing tiers available, from our free weather API up to enterprise plan, depending on your data needs.

But more importantly, you can do so much more with more in-depth and localized weather data. The use cases become far more interesting when you have a different kind of weather API like Tomorrow.io. For instance, you could:

• Monitor air pollution in your city with NodeJS
• Build a smart home device with a Raspberry Pi
• Create a weather chatbot
• …and much more

The limit of what you build is really on you — not the Dark Sky API alternative that you choose. Whether you’re looking to build a simple weather app or add an exciting pollen feature to your app, you have all the data you need to succeed.

Looking to get started? Try Tomorrow.io’s Weather API for free today.

The post Dark Sky Weather API Alternatives: Using Tomorrow.io Weather API appeared first on Tomorrow.io.

That’s exactly what Tomorrow.io hopes to offer developers today: a great Yahoo weather API replacement for your weather needs.

While there are many great free weather APIs available, there are a variety of features that some have, and others do not. From in-depth weather data to map layers and more, you have to carefully analyze the next weather API you choose to build with. If you start a project and run up against some serious limitations, you may have to start over again on another platform entirely.

So what’s the right choice?

We argue that Tomorrow.io is the best option on the market as a replacement for the Yahoo weather API.

As you determine which alternative to replacing the Yahoo Weather API, this blog will explain why Tomorrow.io’s weather API is the solution and dive into what you should consider when choosing the right replacement for you.

What Factors to Consider When Choosing a Weather API Replacement

If you’re just looking for basic weather data like temperature, precipitation, and humidity, there are many APIs out there that offer the data you’re looking for.

You can create a weather widget, for example, with just the simplest weather data on the market.

Most weather providers simply pull in existing governmental data from sources like the National Oceanic and Atmospheric Administration (NOAA). But there is more weather data out there.

When you’re seeking a Yahoo weather API replacement, you want to consider more than just current weather data for temperature, precipitation, and humidity. You want to ensure you’re getting the most robust weather data available and you should consider additional features.

Current Weather Conditions and Data Sources

A good weather API should provide real-time data on the current weather conditions and employ a diverse range of reliable data sources, more than just existing governmental data. 

Tomorrow.io stands out with its unique approach, integrating traditional weather data sources with advanced sensing technologies, including cell towers, data satellites, weather stations, and even connected vehicles. With the recent launch of Tomorrow-R1, the world’s first commercially built weather-radar satellite, Tomorrow.io’s data collection capabilities are increased tenfold and will only continue to grow with the growing constellation of sats. This constellation will provide global real-time precipitation mapping, effectively enhancing the accuracy and comprehensiveness of data available to users for nearly every point on Earth. 

Accuracy of Forecasts

Forecast accuracy is vital in an API. Inaccurate weather predictions can have severe implications, especially for businesses in weather-sensitive sectors such as agriculture, logistics, and outdoor events planning.

Tomorrow.io stays ahead of accuracy with advancements in Unified Precipitation, leveraging cutting-edge satellite data and machine learning to provide highly accurate real-time and nowcast (0-6 hours) global precipitation. Based on comparisons with similar satellite-based products, this solution offers 48-61% better precipitation intensity accuracy, delivering forecasts you can truly depend on.

Accessible Weather Maps

Accessible and detailed weather maps are a crucial feature of any weather API. They offer a spatial representation of weather conditions, assisting users in understanding and predicting weather patterns over a given area. Tomorrow.io’s weather API works with interactive weather maps to show you various data layers for a comprehensive understanding of current and forecasted weather conditions.

Severe Weather Alerts

Timely alerts for severe weather are essential in safeguarding people and operations. Utilizing a weather API that is connected to early warning systems will protect individuals and businesses. In fact, the United Nations have recently launched an initiative to get the world on early warning systems, making the need for it within an API crucial. 

Cost and Calls per Day Limits

When selecting a weather API, cost and usage limitations are essential considerations. These factors influence the financial feasibility and operational sustainability of your weather-based application. APIs, like Tomorrow.io, offer a variety of pricing tiers and usage limits, making them suitable for a range of users – from individual developers working on passion projects to large businesses with heavy data requirements. 

You can easily get started with a free version of a weather API and use your limited number of calls.

Why Use Tomorrow.io’s Weather API

At Tomorrow.io, we collect weather data differently and have launched our own weather-radar satellite into space, marking the start of a constellation of more than 20 satellites that will bring us proprietary weather data for global weather forecasting. 

Tomorrow.io combines traditional weather data sources alongside new sensing technologies, including cell towers, not used by anyone else. This data has the following advantages over data from traditional weather APIs, including:

• Space-based precision: Tomorrow.io recently launched the world’s first commercially built weather-radar satellite, which will provide near real-time scans of precipitation and atmospheric profiles for any point on Earth.
• Hyperlocal observation of weather: 500-meter radius observation vs. 2,000-4,000 meters
• Ground-level tracking: Precipitation as low as 30 feet off the ground vs. over 1,000 feet for radar.
• Up-to-date data delivery: Many weather APIs can deliver data every minute, but that data can be 5-20 minutes old (or older). Tomorrow.io delivers updated data every minute.
• NowCasting: Tomorrow.io provides minute-by-minute forecast data for 0-6 hours out. Most other APIs provide this data in 1-hour chunks vs. 1-minute.

Unlike other APIs, Tomorrow.io’s numerical data and map layers offer hyper-local, minute-by-minute weather data that allow you to build almost anything. When you see how much more data you can access, you may realize you can build something different or more ambitious than your original project.

What does that mean? The Tomorrow.io API offers data in a variety of formats and timeframes, including:

• Historical Station Data – Weather data going 4 weeks back.
• Historical Tomorrow.io Data – The last 6 hours of historical data are based on Tomorrow.io’s proprietary technology.
• Realtime – Realtime weather based on our proprietary model
• Short-term Forecast (NowCast) – 6-hour proprietary NowCast data available in minute-by-minute intervals
• Near-term Forecast (Hourly) – Up to 96 hours of data available.
• Daily Forecast – Forecast of up to 15 days out

Tomorrow.io also provides data you might not expect to get from a weather API, including:

• Air quality – Understanding how air pollution impacts health
• Pollen – Tracking multiple types of pollen depending on your area
• Road risk – A scoring system to help you navigate through and around treacherous roads
• Fire risk index – The current risk of fire for a specific location

With this complete suite of weather data and solutions far beyond your standard daily forecast, the options really expand. You can build even more interesting weather projects than you may have imagined with this type of data.

Build more with a better Weather API

No matter what you’re building, you need quality weather data that is easy to work with. That’s why the Tomorrow.io weather API is built on AWS, Autodesk, and REST API using JSON for the requests and the responses, with HTTPS support. 

Not sure where to start? Tomorrow.io offers in-depth weather API documentation with a ton of information about how to use our API to build your project. There are also multiple pricing tiers available, from our free weather API up to enterprise, depending on your data needs.

But more importantly, you can do so much more with more in-depth and localized weather data. The use cases become far more interesting when you have a different kind of weather API like Tomorrow.io. For instance, you could:

• Monitor air pollution in your city with NodeJS
• Build a smarthome device with a Raspberry Pi
• Create a weather chatbot
• …and much more

The limit of what you build is really on you — not the replacement for Yahoo weather API that you choose. Whether you’re looking to build a simple weather app or add an interesting pollen feature to your app, you have all the data you need to succeed.

Ready to start building? Get the Tomorrow.io weather API today.

The post How to Choose a Yahoo Weather API Replacement appeared first on Tomorrow.io.

What Does Locations API Provide? 

Tomorrow.io’s Locations API is most beneficial to developers seeking highly accurate weather data. It enables easy access to weather data for predefined locations, points, polygons, and polylines, all while delivering ultra-accurate, real-time weather insights for any location worldwide.

Utilizing the Tomorrow.io Locations API involves various endpoints that organize data conveniently, making it easy for developers to make API requests. You can get minute-by-minute, hour-by-hour, or customized timeframes to predict future events for your target geographic locations. Interestingly, locations can be queried in multiple ways based on your location type:

Predefined Locations: Tomorrow.io’s Location APIs allow you to query predefined locations in any of the data endpoints, making it easy to obtain weather data for specific cities, regions, or countries. This feature is particularly useful for Monitors, which stay updated on weather conditions for a specific location.

Linked Alert Locations: Locations linked to an Alert are constantly monitored to check if the Insight conditions are forecasted to be true. In such cases, an Event is created, and Notifications are triggered out to the webhook defined for the account, as configured.

Point Geometry: A point location is defined by a geometry object, according to the GeoJSON format, where the type is “Point,” and a single pair of long-lat coordinates array.

Polygon Geometry: A polygon location is defined by a geometry object, according to the GeoJSON format, where the type is “Polygon,” and an array of long-lat pairs coordinates.

Polyline Geometry: A polyline location is defined by a geometry object, according to the GeoJSON format, where the type is “LineString,” and an array of long-lat pairs coordinates.

Broadening Your Weather Horizon with 80+ Weather Parameters

Tomorrow.io’s Locations API offers a wide range of weather data for an array of locations. This includes data on 80+ weather parameters, including temperature, humidity, wind speed and direction, precipitation, and more. With Location APIs, you can access both current and forecasted weather data, giving you the insights you need specific to your business location.

Transforming Weather Data into Actionable Intelligence

There are countless ways to leverage Tomorrow.io’s Locations API to enhance your applications and drive better business decisions. Here are some potential use cases:

Agriculture: Farmers can use location-based weather data to optimize their crop yields and reduce waste.

Aviation: Airlines can use location-based weather data to optimize their flight routes and reduce fuel consumption.

Emergency Management: Emergency responders can use location-based weather data to prepare for natural disasters and respond more effectively.

Insurance: Insurance companies can use location-based weather data to better assess risks and prevent losses.

Retail: Retailers can use location-based weather data to optimize their inventory and pricing strategies based on weather trends.

Understanding Location APIs

Location APIs, like Tomorrow.io’s, are application programming interfaces that provide access to geographical data and information for an array of locations based on location address, location field values, postal codes, etc. They simplify the process of collecting and analyzing geographic information and are used for a wide range of applications, including mapping and geocoding services, location-based search engines, social media networks, real-time location tracking, and more.

To utilize a location API, developers write code that interacts with the underlying database to retrieve and store geographic information about locations. This information can include basic data such as latitude and longitude coordinates, as well as more detailed data such as street addresses, city names, states or provinces, postal codes, and country codes.

Location APIs are beneficial for various businesses and individuals. Companies specializing in logistics or transportation can use these APIs to track shipments, find the closest drivers and warehouses, and plan routes. Retailers can determine where customers are located to better target their marketing efforts. With weather-specific Location APIs like Tomorrow.io’s, the applications are endless.

Location APIs are necessary as they provide developers with easy access to accurate and up-to-date location data, such as geographic coordinates, addresses, points of interest, and more. This data can then be integrated into applications to provide users with location-based services, such as weather, real-time traffic updates, nearby points of interest, and more.

Utilizing Locations API to Your Advantage

In conclusion, Tomorrow.io’s Locations API is a robust tool that provides location-based weather data with great accuracy. Whether you’re a developer aiming to enhance your applications, a farmer looking to optimize crop yields, or an emergency responder preparing for natural disasters, this API is a game-changer. With the ability to query locations in various ways and access a wide range of weather parameters, the potential applications are virtually limitless. Harness the power of location-based weather intelligence today and drive better business decisions tomorrow.

The post Leveraging Tomorrow.io’s Locations API for Advanced Weather Intelligence appeared first on Tomorrow.io.

Weather APIs and Business Intelligence (BI) tools are powerful when combined, offering the ability to transform raw weather data into actionable insights. Here’s how: 

A weather API, like Tomorrow.io’s,  provides access to a wide array of weather data including real-time data such as current temperature, wind speed, humidity, and precipitation, historical data dating back two decades, as well as forecasts for these parameters.

BI tools are software applications designed to retrieve, analyze, transform, and present data to help users make informed decisions. BI tools including Tableau, Microsoft Power BI, and QlikView are capable of handling large amounts of data from various sources and presenting it in an easily understandable format, often through visualizations like charts, graphs, and dashboards.

When combined you are feeding the BI tool with weather data to do a variety of things. 

What Are the Benefits of Combining Weather API and BI Tools?

When you combine Tomorrow.io’s weather API with BI tools, many benefits open up for businesses across all sectors. Weather data has become increasingly important in recent years, with more and more businesses realizing its potential to optimize operations and drive revenue growth. For example, increasingly volatile weather is making logistics and transportation industries require better weather forecasting tools to improve driver safety and keep operations running. 

With APIs and BI tools, businesses can gain a competitive advantage when accessing high-quality, accurate data that can be visualized to help with decision-making. 

But what are the specific benefits and ways a weather API works with BI tools? Let’s take a closer look.

4 Ways Tomorrow.io’s Weather API Works With BI Tools

By incorporating Tomorrow.io’s weather API into BI tools, businesses can access highly accurate weather data that can be used to proactively monitor and analyze business operations, optimize resource allocation, and plan effectively for severe weather events.

1. Create Accurate Forecasts

Accurate weather forecasts are crucial for businesses in various industries, from agriculture to transportation.  With the power of BI tools, businesses can analyze multiple data sources, including satellite imagery and radar data to identify patterns and trends that can impact their operations. This information can be used to make more informed decisions about resource allocation and planning.

Accessing Multiple Data Sources

A weather API offers access to a variety of weather data sources, such as real-time measurements, historical data, and forecasted parameters. This broad range of data feeds into BI tools, providing a comprehensive view of weather patterns and trends. By using this diverse dataset, businesses and individuals can create forecasts that account for a wide range of variables, leading to more precise predictions.

Utilizing Quality Metrics to Improve Forecasting Accuracy

Quality metrics play a vital role in ensuring the accuracy of weather forecasts. Tomorrow.io’s weather API provides a range of quality metrics, including measures of forecast accuracy and data reliability. By feeding these metrics into your BI tool, you can continuously refine your forecasting models, ensuring that they remain accurate and reliable over time. This approach allows for a more data-driven, results-oriented weather forecasting strategy that can improve outcomes and inform decision-making processes.

2. Analyze Changes in Existing Conditions over Time

It is critical to stay on top of changes in existing conditions over time. Effectively analyzing these changes can enable businesses to make informed decisions, identify opportunities, and stay ahead of the competition. With the help of weather APIs and BI tools, analyzing changes in existing conditions has never been easier.

One key benefit of analyzing changes in existing conditions over time is the ability to identify trends. With a weather API and your  BI tool, you can delve deeper into the dynamics of weather patterns over time. 

Visualizing Historical Data with BI Tools and Weather APIs

Imagine having the ability to glance back in time and observe how weather patterns have shifted over the years. With a weather API and a BI tool, this is possible. You can access comprehensive historical weather data, then use the visualization capabilities of your BI tool to create engaging charts, graphs, or heat maps. 

Analyzing Long-Term Trends in Weather Patterns

Studying long-term trends offers valuable insights into how weather conditions are changing over time. By feeding data from the Weather API into your BI tool, you can identify recurring patterns, seasonal changes, and long-term shifts in weather conditions. This analysis can inform everything from strategic business decisions to individual projects that depend on understanding weather patterns.

Understanding the Impact of Extreme Events on Your Business Operations

Extreme weather events can significantly disrupt business operations. However, when you integrate Tomorrow.io’s Weather API with a BI tool, you gain a powerful tool for understanding the potential impact of these events. By examining historical data on similar events, you can predict potential challenges and prepare accordingly. Whether it’s rerouting logistics during a storm or ramping up product availability ahead of a heatwave, these insights allow you to navigate extreme weather events with confidence and agility.

3. Develop Severe Weather Alerts Systems

Extreme weather events can pose an immense threat to businesses, disrupting operations and causing significant revenue losses. As such, it’s crucial to have systems in place to monitor weather conditions and provide timely alerts when severe weather events are imminent. With a weather API, a BI tool, and specific coding knowledge, you can collect the data you need to develop a severe weather alerts system.

For example, a food service business may need to be alerted when there is a risk of power outages due to severe weather events, while a transportation company may need to monitor road conditions to ensure that their vehicles can operate safely. By developing customized severe weather alerts systems, businesses can minimize the impact of extreme weather events and continue to operate effectively.

With the help of Tomorrow.io’s weather API you can create sophisticated weather alert systems that ensure you’re always one step ahead. 

Collecting Real-Time Data from Multiple Sources

With the help of modern technology, collecting data from multiple sources in real time is easy. Whether it’s through social media, IoT sensors, weather APIs, or any other source, businesses can now collect and analyze vast amounts of data within seconds.

Tomorrow.io’s Weather API is your gateway to a wide array of real-time weather data that can help you and a variety of businesses. For example, let’s say you’re managing an agricultural business. By pulling real-time data on current rainfall and soil moisture levels, you could monitor for conditions that might lead to crop diseases or overwatering. These insights could then be fed into your BI tool, providing a real-time dashboard of the conditions most critical to your operations.

Automating Alerts Based on Predictive Analytics

Data is king. The ability to collect and analyze vast amounts of data in real-time is crucial to making informed decisions that keep businesses competitive and profitable. However, as the amount of data we’re collecting continues to grow, it can be challenging for businesses to keep up.

Thankfully, advancements in AI and ML have made it possible for businesses to automate their data analytics processes, especially for predictive analytics.With predictive analytics, businesses can not only identify current trends and patterns but can also predict future outcomes based on historical data. 

But what good is predictive analytics if businesses aren’t alerted to potential issues in real-time? That’s where automating alerts comes in. By setting up automated alerts based on predictive analytics, businesses can receive notifications when certain metrics or trends fall outside of an established threshold.

If you’re not wanting to build such a tool out, that’s where Tomorrow.io’s weather and climate security platform can do the heavy lifting for you. 

4. Risk Assessment and Contingency Planning

Risk assessment and contingency planning are crucial components of any business strategy. In this unpredictable business environment, it is essential for companies to be prepared for any potential risks that may arise. By conducting a thorough risk assessment and developing a contingency plan, businesses can mitigate the impact of unexpected events and ensure continuity of their operations.

How Weather and BI Support Strategic Planning

When businesses weave together real-time and forecasted weather data from the Weather API into their BI tools, they open a window into potential risks that could impact their operations. For instance, think of a construction company. With access to detailed forecasts, they can anticipate high wind conditions that might pose safety risks or disrupt scheduled work. In response, they can adjust their project timelines and ensure worker safety proactively.

We can also use the example of a restaurant, one with outdoor seating, where the unpredictability of weather can present a unique challenge. By leveraging forecast data from a weather API, they could predict periods of inclement weather, like rainfall or storms. With this knowledge in hand, they could then plan to increase indoor staffing during these periods, ensuring seamless customer service despite the weather outside.

In the retail industry, businesses can use weather data to optimize their inventory. For example, clothing retailers could anticipate a cold snap and ensure they have sufficient stock of winter clothing. Or, supermarkets could predict heat waves and increase the supply of cold beverages and ice cream.

With the potent combination of Tomorrow.io’s Weather API and BI tools, businesses can become resilient, weathering any storm that comes their way.

Weather API and BI Tools FAQ 

What are BI Tools?

Business Intelligence (BI) tools are software applications that allow businesses to collect, analyze, and visualize data to facilitate informed decision-making. These tools make it possible to transform raw data from various sources into meaningful insights. Whether it’s identifying trends, optimizing operations, or predicting future outcomes, BI tools play an integral role in many modern businesses.

How Can a Weather API Be Used with BI Tools?

A weather API, like the one provided by Tomorrow.io, offers access to a vast array of weather data, including real-time conditions, historical data, and future forecasts. When integrated with BI tools, this weather data can be analyzed and visualized in ways that provide actionable insights for businesses. From operational planning in the logistics industry to risk assessment in agriculture, the combination of a weather API and BI tools can unlock immense potential across various sectors.

What is Microsoft Power BI?

Microsoft Power BI is a popular BI tool that provides interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. It can connect to a wide variety of data sources, making it an excellent choice for businesses looking to derive insights from diverse data sets.

How to Connect a Weather API in Power BI

Connecting a weather API, like Tomorrow.io’s, in Power BI involves a few steps. First, you’ll need to generate an API key from Tomorrow.io. Next, in Power BI, you’ll use the ‘Get Data’ option to connect to a web data source, where you’ll input the API request URL. Once the connection is established, you can start pulling in weather data directly into Power BI for analysis and visualization.

How to Create Historical Data Visualizations in Power BI

Creating historical data visualizations in Power BI involves selecting the right visualization type for your data and then connecting it to your data source. If you’re looking to analyze rainfall patterns over the past decade, you might choose a line chart with years on the x-axis and rainfall amounts on the y-axis. Once you’ve set up your visualization, you can then use the Power BI interface to customize it to fit your needs, whether that’s adding trend lines, adjusting colors, or setting up filters.

By leveraging the power of Tomorrow.io’s Weather API with a BI tool like Power BI, businesses can turn weather data into a strategic asset, improving operations, reducing risks, and driving growth.

What is Tableau?

Tableau is a powerful BI tool that offers intuitive data visualization capabilities. It allows users to create interactive dashboards, reports, and charts, transforming complex datasets into insightful visuals. With an easy-to-use interface, Tableau enables both technical and non-technical users to explore and understand their data, making it a popular choice among businesses of all sizes.

How to Connect a Weather API in Tableau

Connecting a weather API, such as Tomorrow.io’s, to Tableau involves a series of steps. First, you need to obtain an API key from Tomorrow.io. In Tableau, you then select ‘Connect to a Server’ and choose ‘Web Data Connector.’ Here, you’ll input the API request URL that includes your unique API key. After establishing the connection, you can start pulling weather data into Tableau for analysis and visualization.

What is Looker?

Looker is a modern data platform that offers powerful data exploration capabilities. It allows users to access, visualize, and analyze data in a unified view. Looker stands out with its in-database architecture, meaning it queries the database directly without needing to move or transform the data. This leads to real-time insights and facilitates a single source of truth across organizations.

What is QlikView?

QlikView is a BI tool known for its associative data model that allows users to explore data intuitively and make discoveries. Unlike traditional BI tools, where users are limited to a linear exploration of data, QlikView enables users to make associations across multiple data sets easily. It offers powerful visualization capabilities, robust analytics features, and the ability to consolidate data from multiple sources, making it a comprehensive tool for business intelligence.

Remember, integrating Tomorrow.io’s Weather API with these BI tools opens up a wealth of opportunities for individuals and businesses to leverage weather data effectively. Whether it’s predicting demand in retail, optimizing supply chain operations, or mitigating weather-related risks, the combination of accurate weather data and powerful BI tools can provide crucial insights and foster informed decision-making.

Interested in connecting Tomorrow.io’s Weather API with your favorite BI tool? Explore our documentation or get a demo!

The post 4 Ways to Use Tomorrow.io Weather API With BI Tools appeared first on Tomorrow.io.

What is a Weather REST API?

As weather becomes increasingly volatile and costly, accurate everyday weather information is crucial for smooth day-to-day operations. Fortunately, weather APIs have made it easier than ever to integrate real-time weather data into various applications and services, providing users with instant access to critical weather information.

A Weather REST API is a service that follows the principles of Representational State Transfer (REST), which allow applications to request and exchange weather-related data over HTTP efficiently and standardized. In addition, a Weather REST API not only retrieves data but also allows for manipulation of the data to fit the needs of the application or service. Essentially, a Weather REST API acts as a conduit, retrieving weather information from a server and delivering it seamlessly to the client application.

What are the Benefits of Using a Weather REST API?

Weather is a crucial element in many industries, from transportation to agriculture, tourism, and emergency services. Accurate weather data can greatly improve decision-making processes and lead to more efficient operations. This is where a Weather REST API comes in handy.

A Weather REST API allows developers to integrate weather data into their applications seamlessly. Rather than collecting and processing the data themselves, developers can simply make requests to these APIs, receiving comprehensive responses on weather conditions, forecasts, and more. This saves time and also ensures that the data is accurate and up-to-date.

There are many benefits to using this API. It allows you to incorporate real-time, accurate weather data into your applications, improving their functionality and user experience. This can include providing current weather conditions and forecasting future trends.

A RESTful API is stateless, meaning that each request from the client to the server must contain all the necessary information to understand and fulfill the request. This leads to greater scalability and flexibility because the server doesn’t need to store any information about the client between requests.

Using a REST API can improve efficiency and productivity. Since REST utilizes standard HTTP methods, developers can use standard tools to interact with the API, reducing the learning curve and speeding up development time.

Getting Started with a Weather REST API

Starting with a Weather REST API might initially seem intimidating, but it can be straightforward with the right approach and resources. We’ll focus on getting started with Tomorrow.io’s Weather API for this guide.

Using Tomorrow.io’s API Key

To access the services provided by Tomorrow.io’s Weather API, you’ll need an API key. This key is a unique identifier that authenticates the user or application making a request. When you send a request to the Weather API, the key is used to verify your access privileges and track the usage of the service.

Accessing Your API Key

To access your Tomorrow.io weather API key, sign up for an account at Tomorrow.io. 

Once you’ve registered with Tomorrow.io and chosen the appropriate service tier for your needs, you can access your unique API key.

Log in to your account and navigate to your dashboard.

Here, you’ll find your API key. Remember, this key is sensitive information and should be kept confidential. Now that you have your key, you’re ready to start requesting the Weather API, opening a world of possibilities for integrating weather data into your applications.

In the next section, we’ll discuss how to work with a weather REST API, making requests, parsing responses, and using multiple APIs.

Working With a Weather REST API

After successfully obtaining your API key, the next step is working with the Weather REST API. The beauty of using a REST API lies in its versatility, allowing you to access historical data, make data requests, and parse responses to suit your application’s requirements. This section will walk you through these processes using Tomorrow.io’s Weather API.

Accessing Historical Data and Forecasts

One of the compelling features of Tomorrow.io’s Weather REST API is its ability to provide not only real-time weather data but also historical data and future forecasts. This data can be critical for various sectors, including agriculture, event planning, travel, and more.

To access the data you need, you must include specific endpoints in your API request. These endpoints depend on the type of data you want, such as using the /historical/ endpoint for past weather data or the/forecast/ endpoint for future weather predictions.

Making Requests for Data from Your Application Programming Interface (API)

Sending a request to Tomorrow.io’s Weather API is as simple as making an HTTP request from your application. These requests include your unique API key for authentication and may contain other parameters depending on the data you’re seeking.

Typically, a GET request to retrieve weather data might look something like this:

GET https://api.tomorrow.io/v4/timelines?location=42.3601,-71.0589&timesteps=1h&fields=temperature&timesteps=1h&apikey=YOUR_API_KEY

In this example, we’re requesting hourly temperature data for a specific location (latitude 42.3601, longitude -71.0589).

Parsing Responses from the API Server

After sending a request, the API server will respond with data in a structured format, usually JSON (JavaScript Object Notation). Parsing, or interpreting, this response involves extracting the required data from the JSON object for use in your application. Various programming languages offer different methods for parsing JSON data, so choose the one that best suits your application’s needs.

Utilizing Multiple APIs for Different Parameters

Tomorrow.io’s Weather API is incredibly versatile, providing a wealth of data beyond just temperature readings. By utilizing different API endpoints, you can access a plethora of weather parameters such as precipitation, wind speed, humidity, air quality, and many more.

Each parameter can be requested by specifying it in your API call. This means you can tailor your requests to the exact needs of your application, whether you require a broad overview of the weather or specific details for a particular aspect.

Through the process of accessing historical data and forecasts, making requests, parsing responses, and utilizing multiple APIs, you can harness the full power of Tomorrow.io’s Weather REST API. In the next section, we’ll delve into the best practices for integrating this API into your applications seamlessly.

Best Practices for Weather REST API Integration

Integrated weather data is a crucial component for many businesses and organizations, from aviation and construction companies to logistics and sports entertainment.. Weather forecasts can help them make informed decisions about scheduling, logistics, and resource allocation. However, integrating weather data can be a complex process, particularly when using REST APIs. By following some best practices for weather REST API integration, businesses and organizations can make the most out of the available resources to deliver reliable weather data to their users. Here are some key considerations to ensure successful integration.

Rate Limiting and Caching

In a fast-paced digital world, where data is being transferred between multiple devices and systems within milliseconds, rate limiting and caching have become essential tools for many businesses. Rate limiting controls how often a user can access an application programming interface (API), while caching stores frequently requested data temporarily, thus reducing the number of API requests needed.

Rate limiting can be used to prevent excessive calls to a weather API which can save costs and improve server performance. When the usage limit is reached, the rate-limiting mechanism can block any further requests for a set period. As such, it helps to prevent abuse or overload of the server and maintain data accuracy.

Caching, on the other hand, decreases server load and improves application performance by storing frequently used data in memory or on the disk. As more requests are sent for the same data, the data is retrieved from the cache instead of the server, which leads to a substantial reduction in time and resources needed to serve the requests. In the context of weather APIs, caching can significantly decrease the period between the data request and response.

Both rate-limiting and caching can significantly reduce the processing time and eliminate the possibility of overwhelming the server, resulting in better API performance with less downtime. Using a combination of rate limiting and caching can ensure that weather data is always available to those who need it, reducing the possibility of data loss and improving user experience.

Both rate-limiting and cashing are critical tools for businesses that rely on weather APIs to function efficiently. By regulating the number of requests made to the server and minimizing the load on the server with cached data, businesses can increase performance, reduce downtime, and lower costs. With the ever-increasing demand for real-time weather data, these mechanisms will continue to play a vital role in ensuring that weather data is available to everyone who needs it, without compromising on data accuracy, reliability, and overall user experience.

Error Handling and Retry Strategies

Developers using weather REST API services face a variety of challenges, ranging from predicting weather conditions to handling high volumes of requests. One critical aspect of managing these services is error handling. It’s crucial to have a mechanism in place to deal with errors that occur when weather data is requested. This can include server errors, network issues, or user input errors. A well-designed error-handling mechanism can improve the user experience and decrease the number of support requests.

Implementing a retry strategy is another tool in the developer’s toolbox when working with weather APIs. These services handle a vast amount of data, and sometimes errors occur due to network issues, server overload, or other factors outside of our control. This is where the retry strategy comes into play. If a request fails, it can be automatically retried after a set time interval, ensuring that the required data is eventually retrieved.

There are various retry strategies to choose from, including exponential backoff, which increases the wait time between each retry; fixed backoff, which maintains a constant time between retries; and jitter backoff, which adds random, fluctuating wait times to retries to alleviate server overload issues. Choosing the appropriate retry strategy for your application will depend on your specific use case, but by employing these strategies, developers can improve the reliability and uptime of their weather APIs.

As weather data is crucial to many industries, such as agriculture, transportation, and tourism, ensuring the accuracy of the data and reducing disruptions to the delivery of the data is paramount. By implementing a well-designed error-handling mechanism and retry strategy, developers can create more robust and efficient applications that rely on weather data APIs. Ultimately, this will improve user satisfaction and lead to better long-term business outcomes.

Optimizing API Calls

As APIs become an integral part of modern web development, it is essential to optimize API calls to improve performance and reduce overhead costs. In the context of weather APIs, optimizing API calls can significantly increase the accuracy and reliability of the data returned, leading to better-informed decision-making and enhanced user experiences.

One key way to optimize API calls is through caching. By storing frequently accessed data locally, developers can reduce the number of API calls required, thereby cutting down on the time and resources needed to retrieve data. This is especially beneficial for weather APIs, where many requests may be made for the same geographic areas. Caching can be implemented using client-side techniques, such as browser caching or local storage, or through server-side solutions like Redis or Memcached.

Another optimization technique is to utilize batch processing to reduce the number of individual API requests. With batch processing, multiple requests are grouped together, and a single request is sent to the API, returning all requested data in one response. This approach is particularly useful when requesting data from services that have limitations on the number of requests per day or per second. Batch processing can be achieved using methods such as GraphQL, REST API batch requests, or custom-designed batch processing solutions.

Finally, developers can optimize API calls by prioritizing the most critical data and reducing the amount of data requested. By focusing on essential data, developers can limit the amount of API calls made, reducing overhead and improving response times. Additionally, by using more targeted requests, developers can limit the amount of extraneous data returned, which can further improve performance.

In conclusion, optimizing API calls is crucial for improving the performance and reliability of weather APIs. By employing caching, batch processing, and targeted requests, developers can reduce overhead costs and enhance the overall user experience. The importance of API optimization will only continue to grow as APIs become even more critical to web development in the years to come.

Use Cases for Weather REST API

A weather REST API provides developers with a powerful and versatile tool for accessing real-time and historical weather data. From mobile applications to complex weather modeling systems, there is a wide range of use cases for Weather REST API that are essential for various industries.

By leveraging the capabilities of Weather REST API, developers can integrate accurate and reliable weather data into their applications, providing users with access to essential weather information to make informed decisions in their daily lives and for businesses to optimize their operations. Here are some use cases for Weather REST API.

Travel and Tourism

There’s no industry making a come back like the travel and tourism industry. Compared to the number of people traveling in 2020, things have been on the rise. With these numbers growing and with advances in technology, the way we travel has changed drastically in recent years.

Today, travelers can customize their own itineraries and access information about destinations with just a few clicks on their smartphones. From researching hotels and local restaurants to booking flights and excursions, everything can be done with the touch of a button. And most importantly, they can use the weather forecast as a determining factor. 

For the travel and tourism industry, accurate and timely weather data is crucial. Whether it’s helping tourists plan their activities or assisting airlines in managing their flight schedules, a Weather REST API can play a critical role. Travel apps can integrate Tomorrow.io’s REST weather API to provide users with real-time weather updates and forecasts, helping them make informed decisions about their travel plans.

Agriculture and Farming

Agriculture and farming have been integral to human survival for thousands of years. It has also been a key sector in the global economy, providing livelihoods for millions of people and contributing to food security. As the world’s population continues to grow, agriculture and farming will only become more important in ensuring that people have access to sufficient and nutritious food.

In recent years, there has been a growing interest in sustainable agricultural practices. This involves using techniques that minimize negative environmental impacts while still maintaining production levels, all while staying educated on current weather conditions. With accurate weather data from Tomorrow.io farmers in remote areas of the world can leverage insights to inform their farming. 

The agriculture sector can also significantly benefit from integrating a Weather REST API. Farmers can access historical weather data and future forecasts to make informed decisions about planting, irrigation, and harvesting. Moreover, this data can help manage risks related to weather, like droughts or floods, and aid in resource planning.

Outdoor Events

Outdoor events are loved around the world. From music festivals to sports tournaments, these gatherings offer a chance for people to come together and enjoy shared experiences. However, as we continue to grapple with the late effects of the COVID-19 pandemic, these events need to be informed with weather data and more. 

Organizers of outdoor events such as music festivals, sports events, or community gatherings can utilize a Weather REST API to plan their activities. By integrating Tomorrow.io’s REST weather API, they can receive real-time updates and forecasts, helping them ensure the safety and comfort of their attendees and make necessary arrangements in case of adverse weather conditions.

Risk Assessment and Insurance

In our volatile world, risk management and insurance play an important role in keeping individuals, businesses, and organizations protected against unexpected events. Whether it’s natural disasters, cyber-attacks, or litigation, having the right risk management plan can help minimize the impact of these events and help us bounce back faster.

Insurance companies, particularly those dealing with property and agriculture insurance, can leverage a Weather REST API in their risk assessment procedures. Access to historical weather data and future forecasts can provide valuable insights into risk levels associated with certain weather events, enabling more accurate policy pricing and claims processing.

Making Sense of REST API and Tomorrow.io Weather API

As the weather API industry continues to evolve, it is important to stay ahead of trends and innovations to provide valuable and relevant content. With the Tomorrow.io Weather API, we are providing people, businesses, and governments with weather technology to help communicate between apps, provide better weather forecasting, and make it easy to use.

See for yourself today: Try Tomorrow.io’s Weather API for free!

The post Mastering Weather Data: Your Guide to REST API appeared first on Tomorrow.io.

Using Tomorrow.io’s weather API, it’s easy to create a weather data app using the R programming language. R is the ideal language for this purpose because of its vast collection of packages and its aptitude for data analysis. In this article, we will walk you through the steps to create a weather data app by utilizing the Tomorrow.io weather API R package.

How to Set Up Your Developmental Environment With Tomorrow.io Weather API R Package

If you’re a developer working on mobile or web applications, you may have experience creating weather-related apps. But have you considered displaying weather forecasts with statistical analysis and plotting? In this post, we’ll explore how to achieve this using the Tomorrow.io weather API, which provides us with highly precise weather data.

Before delving into our weather data app development, let’s prepare our development environment. This guide focuses on using R, a popular programming language for statistical computing and graphics.

To follow along, ensure that you have R and R-Studio installed on your machine.

We’ll use several R packages to help us achieve our goal – just illustrations, not an endorsement.  Here’s a brief rundown:

1. Githubinstall: This aids developers in installing R packages hosted on GitHub.
2. Httr: An essential tool for working with HTTP, allowing us to make requests and handle responses.
3. Rtomorrow.io: This is a wrapper for the Tomorrow.io API, facilitating our interaction with the API.
4. Ggplot2: A powerful library that deals with data visualizations.

Once you’ve installed these packages, the next step is to get your unique API key from Tomorrow.io. This key authenticates your requests and allows you to access the weather data. Remember to securely store and access your secret key in the R application.

Once you get your unique API key from Tomorrow.io, you can store and access your secret key in the R application using this code sample:

#need to have an API for the authentication on Tomorrow API.
Sys.setenv(TOMORROW_API = "")
#in order to access the API key later this the way to do it print
(Sys.getenv("TOMORROW_API"))

How To Get Your Current Location for the API

Geolocation services use your device’s GPS and other location technologies to determine your current geographical location accurately. Most web browsers, including Google Chrome, Mozilla Firefox, and Microsoft Edge, support geolocation services. These services use the W3C Geolocation API, which is accessible through JavaScript code.

To get your current location using the Geolocation API, we first need to check if your browser supports geolocation services.

We can do this by using the `navigator.geolocation` object and checking if it’s not null.

```

function error() {

// Unable to get the current location

}

```

Once we have confirmed that your browser supports geolocation services, we can use the Geolocation API to retrieve your current location. We do this by calling the `getCurrentPosition()` method on the `navigator.geolocation` object.

The `getCurrentPosition()` method takes two parameters: `success` and `error`. The `success` parameter is a callback function that will be called if the API call is successful. It returns an object with your device’s current latitude and longitude.

On the other hand, the `error` parameter is also a callback function that will be called if the Geolocation API call fails.

You can also do this with R package.  

1. Install myip is an R package tool that determines your public IP address. You can install it using this command in the console: githubinstall::gh_install_packages(“myip”).
2. Use the httr library and request http://ip-api.com/ to get the coordinates.
3. Once you have these values ready, you will need to pass these as an argument to the Tomorrow functions. This will be done in a later section.

See the sample code below:

library(myip) #github package

library(stringr) #string library

library(httr) #httr library

#get our current IP address

ip <- substr(toString(myip("random")[1]),start =15, stop=28) 

#uncomment if you want to see your ip-address

#print(ip)

#get our coordinates

url <- gsub(" ","", paste('http://ip-api.com/json/',ip, "?fields=lat,lon"))

#store the results

result <- GET(url)

#store results as parsed

json <- content(result,as="parsed")

#uncomment if you want to see your coordinates

#print(json[1])

#print(json[2])

Once we have retrieved your device’s current latitude and longitude, we can use this information to retrieve the weather data for your location through the Tomorrow.io Weather API’s R package.

How To Use the Tomorrow.io Weather API and R Package

In this section, you need to pass the data that you prepared from the previous code samples, which requires invoking one of the Tomorrow.io wrapper API functions and, in this example, we’re going to use the tomorrow.io_temperature method.

Let us see the example below before we go into the code details.

library(myip) #github package
library(stringr) #string library
library(httr) #httr library
library(Rtomorrow.io) #tomorrow.io API wrapper library
library(lubridate) #date library

#need to have an API for the authentication on Tomorrow.io API.
Sys.setenv(tomorrow.io_API = "aFK9oVioFuoSJ51CzXm45acAn8pDOfak")

#get our current IP address
ip <- substr(toString(myip("all")[1]),start =15, stop=28) #if 'random' doesn't work use 'all'

#get our coordinates
url <- gsub(" ","", paste('http://ip-api.com/json/',ip, "?fields=lat,lon"))

#store the results
result <- GET(url)

#store results as parsed
json <- content(result,as="parsed")

start_time <- lubridate::now()
end_time <- st + lubridate::days(15)

#for the argument of timestep 'current','1m','5m','15m','30m','1h','1d' are the only acceptable values.

weather_result <- Tomorrow.io_temperature(api_key = Sys.getenv("tomorrow.io_API"),
                                lat = as.numeric(json[1]),
                                long = as.numeric(json[2]),
                                timestep = '1d',
                                start_time = start_time,
                                end_time = end_time)
print(weather_result)

As you can see from the code sample above, we have passed the required arguments to the tomorrow.io_temperature method, like the time and coordinates and, of course, the API key. It is a straightforward method. However, the next challenge is how we can plot an image to make weather temperature forecasts. 

But before that, please see the sample output below.

How to Use Tomorrow.io Weather API and R Package to Plot the Forecast Temperature

Before going even further, let me show the full code sample below.

library(myip) #github package
library(stringr) #string library
library(httr) #httr library
library(Rtomorrow.io) #Tomorrow API wrapper library
library(lubridate) #date library
library(ggplot2) #graph
library(hrbrthemes)#themes
library(extrafont)
loadfonts(device = "win")

#need to have an API for the authentication on Tomorrow API.
Sys.setenv(TOMORROW_API = "aFK9oVioFuoSJ51CzXm45acAn8pDOfak")

#get our current IP address
ip <- substr(toString(myip("all")[1]),start =15, stop=28) #if 'random' doesn't work use 'all'

#get our coordinates
url <- gsub(" ","", paste('http://ip-api.com/json/',ip, "?fields=lat,lon"))

#store the results
result <- GET(url)

#store results as parsed
json <- content(result,as="parsed")

start_time <- lubridate::now()
end_time <- st + lubridate::days(15)

#for the argument of timestep 'current','1m','5m','15m','30m','1h','1d' are the only acceptable values.

weather_result <- Tomorrow.io_temperature(api_key = Sys.getenv("tomorrow.io_API"),
                                lat = as.numeric(json[1]),
                                long = as.numeric(json[2]),
                                timestep = '1d',
                                start_time = start_time,
                                end_time = end_time)
glimpse(weather_result)

graph_result <- ggplot(data=weather_result, aes(x=start_time, y=humidity, group=1)) +
  geom_bar(stat = "identity", color="blue", fill="blue", width =5)+
  geom_line( color="#69b3a2", size=2, alpha=0.9, linetype=3) +
  scale_y_continuous("Humidity", sec.axis = sec_axis(~ . -30, name = "Temperature [°C]")) +
  theme(text=element_text(size=16,  family="serif")) +
  ggtitle("Weather Temperature for 15 days")

show(graph_result)

By setting the data, x- and y-axis values of the ggplot parameters from the weather_result, we have plotted the data given to us by the Tomorrow.io API forecast. Don’t forget the image results on your R Studio’s “Plots” tab.

Summary

Today, we have shown how to get started with Tomorrow.io’s API using the R language, and we have tried to demonstrate the following:

• Showed where to get your API key location via the dashboard.
• Get your current coordinates via a 3rd party Github package.
• Talk to Tomorrow.io’s API wrapper for R language to get the temperature.
• Showed how to plot the weather temperature forecasts using the R language.

In the future, using Tomorrow.io’s weather API can help you access current weather conditions and historical weather data to predict future weather temperatures, create weather reports, and visualize that information. 

To learn more about Tomorrow.io’s weather API and the types of data you can collect, check out our extensive API documentation.

The post Creating a Weather Data App Using Tomorrow.io Weather API R Package appeared first on Tomorrow.io.

• Tomorrow.io’s Weather API makes it easy to create a weather widget for Raspberry Pi using Python
• The process to create a weather widget for Raspberry Pi includes:
  • Using GUIs in Python (which are lightweight and easy to build)
  • Sending a request every 80 seconds to get the weather data at regular intervals
  • Using the guizero module to can pass your own data through and reflect the current weather values
  • Customizing the widget to your liking

Have you ever wanted to build your own weather widget to display real-time data from the comfort of your own desk?

Harnessing the power of Raspberry Pi and utilizing a simple weather API from Tomorrow.io, you can quickly create a personalized tool that not only looks good but also provides valuable information for creating updated weather forecasts that inform your daily activities and operations.

In this article, we will provide an introduction to Raspberry Pi, outline how to set things up, how to get started with acquiring the necessary weather data you need, and how to integrate things into a cohesive weather widget. 

Introduction to Raspberry Pi Weather Widget

Development boards have experienced significant advancements in recent years, transforming into powerful devices that can function as compact personal computers. One prime example of this evolution is the Raspberry Pi, a versatile single-board computer that has garnered immense popularity among hobbyists, educators, and developers.

Initially designed to promote computer science education, the Raspberry Pi has evolved into a multipurpose platform capable of handling tasks such as web browsing, document editing, and weather forecasting when used to create a weather widget.

The Raspberry Pi’s affordability, low power consumption, and extensive community support make it a great option for a wide range of projects, from simple automation tasks to complex robotics and IoT applications.

What Is a GUI Raspberry Pi Weather Widget?

A Raspberry Pi weather widget is a small application designed for the single-board computer platform, which allows users to display essential meteorological data such as temperature, humidity, and precipitation on various devices including monitors or e-ink displays. Combining raspberry pi display weather capabilities with efficient coding techniques in Python ensures smooth performance without compromising aesthetics.

What sets this project apart from pre-built solutions is its modularity and customizability. You have complete control over the widget’s appearance, sizing, and functionality through open-source software components – catering it specifically to your needs.

If you’re looking for a step-by-step guide on how to build a weather widget with Raspberry Pi, you’ve come to the right place.

We’ll outline setting up Raspberry Pi, how to get started with acquiring the necessary weather data, and how to integrate.

Building a Raspberry Pi Weather Widget with a Weather API 

In order for us to bring this Raspberry Pi weather radar display project to life, we’ll need some crucial components and follow these general steps:

1. Gathering necessary materials (hardware & API)
2. Setting up the Raspberry Pi
3. Retrieving weather data 
4. Configuring desktop shortcut settings
5. Assembling the final product

What You Need to Build the Weather Widget

Creating a Raspberry Pi weather widget involves gathering a few essential components. By assembling these elements properly, you’ll enjoy smooth access to accurate meteorological data right on your desktop. In this section, I will walk you through a concise list of components that are crucial for building an impeccable Raspberry Pi weather widget.

1. Raspberry Pi

First and foremost, you need a Raspberry Pi board. This compact device serves as the foundation for your project. Any version of the Raspberry Pi can be used to create the weather widget; however, I recommend opting for one of the latest models such as the Raspberry Pi 4 or Raspberry Pi Zero 2W for enhanced performance.

2. Micro SD Card

A micro SD card is necessary to store the operating system and Python scripts required for running your weather widget application. A storage capacity of at least 8GB is recommended to have ample space for storing additional files and future software updates.

3. Power Supply

To keep your Raspberry Pi up-and-running, it’s vital to have a reliable power supply with an appropriate voltage rating (5V for most models). You can choose between an official Raspberry Pi USB-C power supply or any compatible aftermarket option.

4. Display Monitor

This component allows you to view the information from your weather pages directly on screen. While it’s possible to use any HDMI-compatible monitor, selecting one with touchscreen capabilities will make interacting with your weather widget even more effortless.

5. Keyboard & Mouse Combo

Though optional, investing in a keyboard and mouse combo proves beneficial during both setup and continuous use of your Raspberry Pi weather widget interface—especially if you’re using multiple applications side by side.

6. Cables and Connectors

Connectivity cables are imperative when constructing any electronic gadget, so don’t forget them! For this specific endeavor, you’ll primarily require:

• HDMI cable (to link the Raspberry Pi to a display monitor)
• USB cables/extenders (for peripherals like a keyboard and mouse)

By gathering all these components, you’ll be one step closer to building your custom Raspberry Pi weather widget. The next section will guide you on setting up the Raspberry Pi before moving on to retrieving data from an Tomorrow.io’s API and creating a desktop shortcut for easy access. Armed with this knowledge and the appropriate equipment, you are well-prepared to embark upon constructing an innovative, informative weather widget of your own design!

Setting Up the Raspberry Pi

Before diving into creating a weather widget, it’s essential to properly set up your Raspberry Pi. This will ensure that your device is ready to handle the task of displaying real-time weather data on your screen. In this section, I will guide you through the process of setting up a new Raspberry Pi or updating an existing one so that it can run our desired Raspberry Pi weather widget.

Preparing the SD Card and Installing Raspbian OS

First things first – you’ll need a compatible micro SD card (preferably 8GB or larger) for your Raspberry Pi to store the operating system and other necessary files.

1. Format the SD card using a tool such as SD Memory Card Formatter.
2. Download Raspberry Pi OS Lite (formerly known as Raspbian) from the official website.
3. Extract the downloaded file and use an image writing tool like Balena Etcher to flash your formatted microSD card with Raspberry Pi OS Lite.
4. Safely eject the microSD card once completed.

Booting Up and Configuring Your Raspberry Pi

Now that we have prepared our micro SD card, we’re ready to turn on our Raspberry Pi:

1. Insert the microSD card into your Raspberry Pi.
2. Connect peripherals such as a keyboard, mouse, and monitor via HDMI to your device.
3. Lastly, power up your Raspberry Pi by attaching it to a proper power source.

Once booted-up, make sure you complete these steps:

• Update software packages by running sudo apt-get update followed by sudo apt-get upgrade in the terminal.
• Configure basic settings like language/locale, wireless LAN setup, and enable SSH using sudo raspi-config.

Installing Dependencies and Required Packages

Our Raspberry Pi weather widget will be powered by Python and fed data from Tomorrow.io’s weather API, so we need to start by installing the necessary packages. Run the following commands in the terminal to install tkinter (a Python module for creating graphical user interfaces), requests (an HTTP library for sending API calls), and PIL (a Python Imaging Library).

sudo apt-get install python3-tk python3-pil python3-requests

After the successful execution of these commands, your Raspberry Pi should have all the required packages installed for building your weather widget.

In conclusion, setting up the Raspberry Pi involves preparing an SD card with the latest operating system, configuring essential settings on the first boot, connecting peripherals, and installing necessary Python packages. With these measures completed, you are now ready to move forward with gathering data from Tomorrow.io’s Weather API and developing your custom Raspberry Pi weather widget.

Gathering Data from Tomorrow.io API

In order to display accurate weather data on your Raspberry Pi weather widget, you will need access to reliable and real-time information. This is where the Tomorrow.io Weather API comes into play. By using the Tomorrow.io Weather API, you can the world’s most accurate current weather conditions as well as forecast data for thousands of cities across the globe.

To get started, you’ll need to ensure you have a weather API key from Tomorrow.io. With your personal weather API key, you’ll be able to retrieve accurate, hyperlocal weather data for your Raspberry Pi weather widget.

Getting your weather API is easy to do! Follow these steps:

1. Create Tomorrow’s Account in order to get your free weather API key.
   
2. Tell us what kind of project you’re doing: After you sign up for an account, a screen will prompt you to share what kind of project using the API for.
3. Get your API key: Once you have created an account, you will automatically get your free weather API key right in the Tomorrow.io platform. Simply click on the “Development” icon in the navigation, then reveal your key.

We recommend you read our weather API documentation that explains more about our API and where you can find sample code to get started.

Once you’ve grabbed your API key from the Tomorrow.io Weather API, it’s time to get coding and get the weather data we want—temperature and humidity measured each minute in metric values—with the help of Python.

Start by placing the following code in a new .py file. You can name it: “weather_widget.py”

import requests 

import threading, time

from string import Template

In this project, we will require the packages above to facilitate weather data acquisition. These packages will enable us to send a request at regular intervals of 80 seconds, to obtain the latest weather information.

Our first step is to create a function that can effectively make this request and retrieve the most up-to-date weather forecast data.

def get_weather_data(lat,lon,apiKey):
    URL = Template('https://data.tomorrow.io/v4/timelines?location=$lat,$lon&apikey=$apiKey&fields=temperature&fields=humidity&timesteps=1m')
    r = requests.get(url = URL.substitute(lat=lat,lon=lon,apiKey=apiKey)) 
    data = r.json() 
    return data['data']['timelines'][0]['intervals'][0]

This function fetches weather data for a specified location (latitude and longitude) and returns the first interval of the first timeline, which should contain the current weather data (temperature and humidity) for that location.

If we call this function and enter the (latitude, longitude,) and our API key,

print(get_weather_data(45.6427,25.5887,’your_api_key’))

, then we should see the following output:

{‘startTime’: ‘2021-03-06T08:31:00Z’, ‘values’: {‘temperature’: -1.66, ‘humidity’: 84.62}}

Obtaining accurate weather data is crucial for this project, and to ensure the widget stays updated, we need to retrieve this information at consistent intervals.

As a result, we’ll need to continuously run this function to maintain accurate weather data on the widget.

To do this, we need to update our code with the following snippet:

def update_every_n_seconds(n=80):

    while True:
        weather_data = get_weather_data(45.6427,25.5887,'your_api_key')

        time.sleep(n)

thread = threading.Thread(target=update_every_n_seconds, daemon=True)
thread.start()

Here, you can pass your own data through the function get_weather_data.

Part II – The Widget

To create a widget we will use the guizero module. Guizero is designed to allow new learners, and anyone who needs a starter’s recap to quickly and easily create GUIs for their programs. In this case a GUI weather widget for Raspberry Pi with a weather API.

To get started with guizero you’ll need to install it. Installing it is as easy as downloading and unzipping a file—no special permissions or administrator rights are required.

To install it you can use the pip command: pip install guizero. Once installed, update the imports at the top with the following code:

app =App(title="Weather Widget", width=400, height=100)
temperature_msg = Text(app, text="")
humidity_msg = Text(app, text="")

These lines will create a new widget weather application with the title “Weather Widget” and will declare 2 text placeholders in which we will show the temperature and the humidity.

Lastly, to show this widget at the very end of our file, call the display() method.

app.display()

If we run our program now from the terminal using the command: python weather_widget.py

we should see something like this:

You can see that we only have the title, the content section is blank. That’s because the variables declared above are currently in an empty string. Within the update_every_n_seconds function, we need to update their values to reflect the current weather values.

For this, we need to update the update_every_n_seconds function with the following code snippet:

 def update_every_n_seconds(n=80):
    while True:
        weather_data = get_weather_data(45.6427,25.5887,'your_api_key')
        
        temperature_msg.value = "Temperature: " + str(weather_data['values']['temperature']) + '   °C'
        humidity_msg.value = 'Humidity: ' + str(weather_data['values']['humidity']) + '%'

        time.sleep(n)

In this section of our weather widget project with Raspberry Pi, we will create a function called update_every_n_seconds that continuously updates the weather data at regular intervals.

By default, our function will update the data every 80 seconds, but this interval can be customized by providing a different value for the n parameter. Inside the function, we use an infinite loop to call the get_weather_data function, passing in the latitude, longitude, and API key to retrieve the current weather data.

We then update the temperature and humidity messages with the latest values extracted from the weather data, converting them into strings with appropriate units (‘°C’ for temperature and ‘%’ for humidity).

Finally, we pause the loop for n seconds before proceeding to the next iteration, ensuring that our widget remains updated with the latest weather information at our desired interval.

Using the above code and knowing how this will change the weather application, if we run our program again now we should be able to see the temperature and humidity displayed as weather data in the weather application.

Diving into Raspberry Pi and GUIs is a breeze when you have the right tools to get accurate weather updates for your weather widget. With endless customization options for your weather widget, you can incorporate images and leverage the fact that the Tomorrow.io API provides a weather code. Utilize this code to determine the best image to preview based on current weather conditions for your selected zip code. Raspberry Pi offers a versatile platform for creating the most innovative projects, making it an ideal choice for enthusiasts and developers alike who want to create weather apps.

Integrating the Raspberry Pi Weather Display

To create an engaging Raspberry Pi clock and weather display, consider using a popular Python library like Tkinter or PyQt for creating graphical user interfaces. Here, you can create customizable fonts, colors or even use icons and images representing different weather conditions. Additionally, you can utilize cron jobs (for UNIX-based systems), Scheduled Task (in Windows environment), or libraries like schedule in Python to update the widget periodically with current weather details.

With all these elements combined, you have successfully built a Raspberry Pi Weather Widget that retrieves real-time data from the Tomorrow.io weather API while providing a visually appealing representation of the extracted information. Now you can monitor local weather conveniently on your device!

Conclusion

As we reach the end of this guide, I hope you have gained valuable insights on creating a Raspberry Pi weather widget using Tomorrow.io’s Weather API. Mastering these skills not only allows you to access real-time weather information conveniently but also serves as an excellent foundation for further exploring the diverse capabilities of Raspberry Pi applications.

If you’re interested in learning more about Tomorrow.io’s weather API, check out our extensive documentation or schedule a demo.

Happy tinkering!

The post How To Create a GUI Weather Widget for Raspberry Pi with a Weather API appeared first on Tomorrow.io.

Several years after Google discontinued its weather API (not including its use on the Android platform), users and developers are still grappling with their search for a viable solution for a Google weather API replacement. An alternative should ideally be free for basic and personal use, but also robust enough to provide both a comprehensive weather forecast and be capable of retrieving weather data spanning decades.

We will detail what to look for in an alternative to Google weather API and review some alternatives currently available today.

What To Look for in a Google Weather API Alternative

When searching for a weather API to use for your app or website, there are several factors to consider. A good weather API should have the following qualities:

Accuracy: The most important aspect of any weather API is its accuracy. Weather can have a huge impact on our daily lives, from planning outdoor activities to making important business decisions. It’s crucial that the weather information provided by the API is as reliable as possible.

Speed: Weather information can change rapidly, especially when severe weather is involved. A good API should be able to quickly deliver up-to-date information in real time.

Flexibility: Different users have a range of needs when it comes to weather information. A good weather API should offer a range of data options – from current conditions and hourly forecasts to radar maps and severe weather alerts.

Ease of Use: A weather API should be easy to navigate and integrate into your app or website.  Look for clear documentation, straightforward parameters, and user-friendly data formats.

Compatibility: Check for compatibility with your chosen weather API, your company’s programming language, and your framework. Some APIs may have restrictions, such as a limitation on the number of requests per day.

Additional Features: Consider what additional features the weather API offers. For example, Tomorrow.io’s API offers more data layers such as air quality and soil moisture data that could be useful to specific use cases.

Reliability: Finally, make sure the Google weather API replacement you choose has a track record of reliability and uptime. Downtime can have serious consequences for your business and your customers.

By taking these factors into account, you can ensure that you choose a Google weather API replacement that meets your needs and provides accurate, up-to-date weather information for your users.

What Is Data Coverage?

When it comes to choosing a weather API, one important factor is data coverage. In other words, where does the weather data come from and how comprehensive is it?

It’s important to look into the source of the weather data to which you have access. For instance, is it just from one source? This can impact its accuracy and reliability. Most available weather APIs leverage data from governmental organizations, such as the NOAA’s National Weather Service. 

You also want to consider the geographic coverage. Some APIs may only offer data for certain regions or countries. If your app or website is used by people in different parts of the world, you’ll want to make sure your API can provide data for all relevant locations.

Top Google Weather API Alternatives

If you’re looking for an alternative to Google Weather API, there are several great options available. While Google Weather API was a popular choice, it was not the only one on the market.

Tomorrow.io Weather API

Utilizing diverse data such as satellite imagery, radar maps, surface temps, and a forthcoming weather-radar satellite array, Tomorrow.io’s weather API provides immediate updates on current weather conditions and accurate forecasts around the globe, hour-by-hour and day-by-day.

You can try the weather API for free and upgrade to other features as your needs grow. 

OpenWeatherMap API

OpenWeatherMap API offers current weather conditions, hourly, and daily forecasts, along with alerts for severe weather conditions. This API stands out since weather data is collected from meteorological broadcast services worldwide and over 40,000 weather stations.

One great feature of OpenWeatherMap API is its ability to provide weather conditions for any location globally. It offers several search options such as city name, zip code, IP address, geographic coordinates, and more. This versatility makes the API widely popular as it can cater to several use cases such as mobile applications, websites, and IoT devices that rely on location-based weather data.

Note that while OpenWeatherMap API provides a wide variety of data from various sources, it upcharges for calls beyond the 1,000 free daily maximum. Together, these could pose limitations for developers needing heavy usage and high reliability.

Weatherbit API

The Weatherbit API offers a wide range of features and functionalities for those looking to integrate weather data into their applications.

One of the most notable features of Weatherbit API is its flexibility. The platform offers a wide range of endpoints, allowing developers to access a variety of weather data based on their specific needs. Whether you’re looking for current weather conditions, hourly and daily forecasts, or severe weather alerts, Weatherbit API has you covered.

In terms of accuracy, Weatherbit API is one of the more reliable weather data sources on the market. The platform uses data from over 120,000 weather stations worldwide, ensuring that the weather data you receive is up-to-date and accurate.

Meteomatics Weather API

Meteomatics is another popular choice for an alternative to Google Weather API, offering advanced machine learning algorithms that provide precise weather forecasts, allowing businesses to access real-time, accurate weather data, crucial for their operations.

This alternative also also offers a variety of additional features like hourly, daily, and weekly forecasts, and detailed weather conditions such as temperature, humidity, wind speed, and precipitation. This proves particularly beneficial for weather-sensitive sectors like agriculture and transportation.

The API is highly customizable, with support for multiple programming languages and easy integration into applications, bolstered by comprehensive documentation and support.

New users should consider the complexity of the Meteocache system, which requires a deeper understanding of weather data handling and building weather data products.

Tomorrow.io: The Best Google Weather API Alternative

If you’re on the hunt for a reliable, accurate weather API that can deliver comprehensive weather data for a wide range of locations, Tomorrow.io is a top contender. Formerly known as ClimaCell, Tomorrow.io’s weather intelligence platform is designed to help businesses and organizations across industries make data-driven decisions based on real-time and accurate weather forecasts.

Tomorrow.io’s weather API leverages a wide range of data sources, including satellite imagery, radar maps, surface temperatures, and our upcoming weather-radar satellite constellation, to deliver real-time updates on current conditions and hourly and daily forecasts for any location in the world.

Why Use Tomorrow.io’s Weather API?

With Tomorrow.io’s weather API, individual weather hobbyists and business developers alike will be able to access the most robust weather data available. Tomorrow.io offers the following features that make it a popular choice for a weather API.

• Hyperlocal Weather Data: Tomorrow.io’s API offers precise weather info down to city block level, aiding in informed decision-making.
• Cutting-Edge Forecasting: Utilizing advanced technology, Tomorrow.io combines various data for accurate forecasts up to 14 days ahead.
• Real-Time Weather Alerts: Tomorrow.io’s API can alert businesses about real-time weather changes, helping to mitigate potential operational impacts.
• Comprehensive API Documentation: Detailed documentation makes integration easy for developers, with technical support also available.
• Flexible Pricing Plans: Catering to different needs, Tomorrow.io offers pricing plans based on data volume, suitable for businesses of all sizes.

An easy-to-use API

Tomorrow.io’s Weather API is also easy to use and access, two features that could aid your search for a google weather API alternative. 

In order to use Tomorrow.io’s APIs, you will need your own personal API key. 

1. Create an account and sign up for an API key: With Tomorrow.io you get the best weather intelligence data available. In order to use our weather API, you will need to sign up for an API key.
2. Understand the API documentation: A product is only as good as its documentation. Tomorrow.io’s weather API documentation outlines how to use the API, what data is available, and how to format requests and responses. It’s important to read this documentation thoroughly to understand how to access and use the data.
3. Make API requests: Once you have your weather API key and understand how to use it through the API documentation, you can start making calls.
4. Integrate the API data into your application: The final step is to integrate the weather data into your application. This process will vary depending on your programming language and platform, but Tomorrow.io’s weather APIs offer code samples and libraries to help you get started.

And just like that you’re using Tomorrow.io’s weather API! 

Leveraging Accurate Data With Tomorrow.io’s WeatherAPI

There are many alternatives to the Google Weather API available in the market. This article is only highlighting a few and is by no means an exhaustive list.

Ultimately, choosing the right one for your needs will fully depend on your goals, preferences, and the scope of your project. As you determine which weather API will meet your needs the best, you must remember that your forecasting outputs are only as good as your data inputs and forecasting models.

Tomorrow.io has increasingly accurate weather data stemming from advancements in Global Unified Precipitation (UP), 1F Modeling, and an upcoming constellation of weather-radar satellites that will feed their modeling and improve forecasting capabilities.

With the most accurate weather data available you’ll be able to easily choose a Google Weather API alternative.

Curious about Tomorrow.io’s Weather API? Check out our extensive documentation.

The post Navigating the Forecast: Best Alternatives to Google Weather API appeared first on Tomorrow.io.

What You Need To Access a Weather API with Python

Let’s go through what you need to write and run this code successfully and make API requests.

1. Python3 must be installed on your computer

There are a few ways to install Python3: you can download official Python distributions from Python.org, install from a package manager, or install specialized distributions for scientific computing, embedded systems, or IoT.

2. Get an API Key for the Tomorrow.io Weather API

To get your weather API key from Tomorrow.io you must sign up and create an account. When you create an account, your personal API key will be automatically created for you to use in your application.

3. Find the coordinates of your desired location on earth

Finding the coordinates for your desired location is quite easy using your favorite online maps.

• Let’s use Google Maps as an example. To find the latitude and longitude of your location search or scroll your map to your place of interest.
• Right-click the specific spot on the map, and you’ll see two numbers, for example, “37.8199° N, 122.4783° W”.
• Click on the numbers, and they will get copied to your clipboard.

Our advice would be to store your desired coordinates in the text file as your API key for now.

Depending on your source, make sure that you don’t mix up latitude and longitude, or you’ll end up in another corner of our planet. Google Maps does use the same format as Tomorrow.io, making this a particularly suitable source.

How To Make a Basic Weather API Call in Python

In order to make a basic weather API request, or API Call, you’ll need two lines of code that are sufficient for a basic Python request:

import requests and response = requests.request(“GET”, url, params=querystring).

So, what is happening here?

import requests add a library that is not technically part of Python, but a de-facto standard, and used in millions of projects.

If you have not used it before, you can install it using pip install requests from the command line.

Next, let’s look at the one method we need to call: request().

In this basic use, the request takes three parameters:

• “GET”, the type of HTTP request you want to make
• url, a string containing the URL of your API,https://api.tomorrow.io/…in our case
• params, which is a dict containing the parameter of your query (for example, the location we looked up earlier will go here, among other things)

How To Use Tomorrow.io’s API Documentation to Generate Python Code

In the above example, we’ve left out two of the trickier parts:

• Choosing the right URL and
• Properly serializing your parameters as a JSON object.

This is where Tomorrow.io’s API documentation comes in handy and will enable you to better understand what you can do with the weather API.

We will work with this example for retrieving timelines.

In the second column, you see the actual documentation and a code snippet to the right.

Of the available languages, select Python, and you’ll see Python code.

Next, in the center of the screen look at the Query Parameters. The first one is location*, the asterisk denoting a required parameter.

In the text field, paste your coordinates from earlier, and closely watch what happens with the Python code. As you enter the coordinates, they are automatically added to the Python code as part of the dict that will be submitted as the parameters: Retrieve Timelines (Basic)

Looking back at our query parameters, we notice that the following parameter, fields*, is also required.

Click ‘Add’ and enter the temperature.

‘Try it’ again, and the query should now be successful, and return “200 OK”.

Just below, you can see the collapsed JSON object, and when you drill down, eventually, you’ll see “temperature”: xx.xx, which is your first value.

Yay, success!

Let’s go through the rest of the parameters:

• units: can be metric or imperial
• timesteps: time between data points. Let’s choose 1d (one day) so that we get a data point every 24 hours.
• startTime: If left empty, it defaults to now. Let’s do that.
• endTime: If left empty, it will go as far as the forecast reaches, which depends on a variety of factors. Let’s leave this empty as well for now.
• timezone: If left empty, will default to UTC.

Also, let’s add another field in addition to temperature: CloudCover.

Click ‘Try It’, one last time to make sure all is good.

Now that we’re all set, let’s copy the code (not the JSON result, just the Python code) by clicking into the code field and on the copy symbol that appears.

How To Expand a Code Snippet into a Python Weather Forecast Program

Open your favorite code editor, for example, Visual Studio Code, and create a file weather.py with the copied code.

We recommend putting the query string on multiple lines as below to make editing on the fly easier.

import requests

url = "https://api.tomorrow.io/v4/timelines"

querystring = {
"location":"33, -84",
"fields":["temperature", "cloudCover"],
"units":"imperial",
"timesteps":"1d",
"apikey":"xxxxxxxxxxxxxxx"}

response = requests.request("GET", url, params=querystring)
print(response.text)

How To Parse and  Format the Output of a Weather API

After creating a file with the code, you’ll want to pretty up the cryptic JSON object and print it in a nice table.

If you have experience with JSON, you will know that it can be unforgiving and that nested elements have to be parsed correctly.

You can head back to the documentation and study the returned object document.

It is a dict, containing a dict of “data,” containing an array of “timelines” containing dicts, containing an array “intervals” containing dicts, containing a dict “values” that finally contains our values.

Or simply put it in Python to get the temperature of the first data point:

t = response.json()['data']['timelines'][0]['intervals'][0]['values']['temperature']

Since ‘intervals’ is an array of unknown length, let’s cycle through it using a for loop:

    print("Weather Forecast")
print("================")

results = response.json()['data']['timelines'][0]['intervals']
for daily_result in results:
date = daily_result['startTime'][0:10]
temp = round(daily_result['values']['temperature'])
print("On",date,"it will be", temp, "F")

Resulting in something like this:

% python3 weather.py
Weather Forecast
================
On 2021-04-24 it will be 73 F
On 2021-04-25 it will be 73 F
On 2021-04-26 it will be 77 F
On 2021-04-27 it will be 80 F
On 2021-04-28 it will be 76 F
.
.
.
%

And just like that, with just a few simple lines of code, and a single Python Weather API call, we’ve created a weather forecast for your desired location for the next few days. This weather forecast can be used to stay up-to-date with current weather, create weather reports, and provide weather conditions to your application.

This is just a glimpse of what’s possible with the Tomorrow.io weather API.

The post How To Create Daily Forecasts with A Python Weather API appeared first on Tomorrow.io.

The post Visualizing Weather Data on ArcGIS: How to Integrate a Weather API Using Python appeared first on Tomorrow.io.

Climate Normals is a comprehensive view of climate patterns over a 20-year period. Using weather data with an hourly temporal resolution, the climate normals calculates and presents data for the period between 2000 and 2020. 

Data Set Details:

• Valuable insights into long-term climate trends to understand and plan for the future
• High-resolution data and long-term perspective
• Hourly temporal resolution
• Aggregate daily and 20-year data for each weather data field

Data Fields (temperature examples)

Accumulated Datasets (precipitation examples)

Access: See all Climate Normals API fields and start retrieving from our endpoint now!

The post Tomorrow.io Releases Climate Normals Weather API Endpoint appeared first on Tomorrow.io.

• Weather APIs provide developers with access to current, forecasted, and historical weather data.
• The best weather APIs for 2023 are judged based on functionality & scope, compatibility & ease of implementation, responsiveness & reliability, and cost.
• The all-around best Weather API for 2023 is Tomorrow.io’s Weather API , which offers 80+ data layers and a top-rated interface.

A weather API may not seem like an essential tool for business, but that couldn’t be further from the truth.

Accurate, actionable weather forecasts are vital to the success of many businesses. In fact, there are entire industries where weather conditions have a direct impact on day-to-day operations, including shipping, on-demand, energy, and the supply chain (to name just a few).

For example, a typical utility company sees up to $1.4B in storm damage costs and lost revenue due to outages from storms over a 20-year period, according to McKinsey. With actionable weather forecasts, businesses can better prepare for weather events, saving money, and improving operations.

And now that the popular Dark Sky API is shutting down (thanks, Apple), many people are looking for a new, better weather API for their weather data needs. But how do you know what’s the right choice for you?

Whether you’re building an app, adding weather data to your software platform, or creating a new Alexa skill, you may be looking for very different capabilities from a free weather API. That’s where we can help! Depending on your priorities, some APIs will be a better fit than others.

We looked at all the top weather APIs on the market in 2023 to help you choose the right one and get started faster. Here’s what you need to consider when choosing the best weather API for your project or business.

What is a Weather API?

As a developer, you already likely use many APIs to perform different tasks and functions in your apps or across your site. Weather APIs are similar to map APIs in terms of integration and versatility of data sources. Each service provider collects, aggregates, and processes meteorological and other relevant weather data then offers access to it via API. This includes data like:

• Temperature
• Humidity
• Wind Speed
• Precipitation
• Cloud cover
• Visibility
• …and more

If you are building a web or mobile app that needs to pull weather forecast data, for example, the right weather API makes this easy. With this data, you can create updates and alerts in web and mobile apps, creating solutions that are uniquely suited to your needs.

How to Choose a Weather API

There are quite a few weather APIs out there, each with a unique set of capabilities, varying costs, and different degrees of reliability. Some even target specific markets or communities with unique features for agricultural applications or air quality monitoring. With the broad options available, choosing a weather API can be a bit daunting. So what should you consider before you scroll down to our list of recommended weather data API providers? Here’s what we recommend.

Functionality and Scope

Like any API you integrate with your mobile or web app, the weather API you choose needs to do what you want and it needs to do it well. Overall, the majority of APIs will give you similar data, but will vary in resolution, the length of time back in historic weather records, as well as day and time formats. However, before you request an API key for each available service offering the functionality you need, be sure to define your scope as well.

For example, if your app users are only interested in marine weather conditions or the weather on Mars (yes, that’s a thing), there are specific APIs that will give you the data you need without any unnecessary features or capabilities packaged in.

That said, it’s worth noting that free APIs can only give you so much. Most free APIs are limited not only in the number of API calls, but also the functionality provided. The bottom line is that additional functionality comes with additional costs, which becomes especially relevant if your commercial app targets a vertical or business with specific needs that go beyond a general weekly forecast and current weather data.

Explore the Tomorow.io Weather API’s functionality ->

Compatibility and Ease of Implementation

Most weather APIs today are based on RESTful architecture, with a handful offering a SOAP alternative. Be sure to pay attention to those subtle differences in date and time formats, as well as well-tested compatibility with the app framework and language you’re coding in.

Another thing to take note of is documentation. While some services have in-depth tutorials and guides, others expect you to figure it out yourself or come armed with previous experience in implementing weather APIs. Depending on your level of expertise, you may need more or less documentation in order to set it up effectively.

Responsiveness and Reliability

You need a weather API to not only do what you want and well, but you want it to be fast and available. There are a number of sources for information on uptime and response speed of available weather APIs, but the information there is not very consistent or accurate.

The best way to find out which APIs are reliable and fast enough to make it into the production version of your app is to try them. Fortunately, the majority of them offer a free trial option or freemium subscription. This leads us to another important consideration: the price.

See Why 40,000+ Developers Trust the Tomorrow.io Weather API ->

Cost

Once you’ve figured out your needs and scope, and narrowed down your list of potential weather API providers, it’s time to consider the price tag. As one can expect, the features, uptime, capacity, and responsiveness offered by the free API services are inferior to those of paid options. That said, even the highest-priced APIs will become a significant expense only if and when the number of API requests made by your app is extremely high.

Now that you’ve got your checklist ready, let’s go more in-depth into the very best Weather APIs on the market in 2023.

Try the Tomorrow.io Weather AP for Free ->

Our Picks for the Best Weather APIs

Based on our research, here are the top weather APIs based on functionality, price, and data access:

1. Tomorrow.io API
2. OpenWeatherMap
3. Meteogroup
4. Weatherstack
5. Weatherbit
6. Weather2020
7. AerisWeather
8. Accuweather
9. Visual Crossing

But before we get into the details of each of these providers, let’s talk about how you should assess and decide on the right weather API for your project or business.

1. Tomorrow.io Weather API:

Tomorrow.io’s API offers an all-in-one endpoint with 80 different data fields, including weather, air quality, pollen, road risk, and fire index, and also includes historical, real-time, and forecast weather data, globally. A lean and flat payload creates a seamless developer experience with comprehensive documentation, cutting edge functionality and features, including:

• Polygon/polyline locations: Location types give developers the flexibility to choose the right bounding box to continuously observe inclement weather within that specific lat/long vicinity.
• Monitoring and alerts: Customize your own rules for what weather conditions you want to be monitored in which locations, and you can receive alerts through the Tomorrow.io Weather API for when those specific thresholds have been met.
• Dynamic routes: Get any of our data fields in realtime mapped to a travel route, with granularity in the forecast every step of the way.

Tomorrow.io’s Weather API is already trusted by top companies such as Uber, JetBlue, National Grid, AWS, Ford, and more.

App Integration/ Format: AWS, Autodesk, REST Weather API using JSON for the requests and the responses, with HTTPS support

2. OpenWeatherMap

OpenWeatherMap offers weather data APIs for different types of timeline data. In a solution inspired by crowdsourcing projects like Wikipedia, weather data is collected from meteorological broadcast services worldwide and over 40,000 weather stations. This freemium solution also has a feature-limited free option that allows access to the 5 days/3 hour forecast API, as well as weather alerts and a weather map.

One thing to consider is that the free account for OpenWeatherMap limits your app to 60 API calls a minute at most.

App Integration/Format: JSON / XML

Pricing: Varies. Free up to Enterprise.

3. Meteogroup

Priding themselves by specializing in UK-specific and nautical weather and environmental data, Meteogroup offers four different APIs: Nautical API (Beta), Point Forecast, Point Observations, and Radar Precipitation Forecast (Beta).

If you’re in search of weather data for nautical verticals and UK-based customers, then the MeteoGroup API could be a great fit.

App Integration/Format: JSON with HTTPS support

Pricing: Unknown

4. Weatherstack

Staying in the UK, The Weatherstack API is developed by a UK company that excels in SaaS with companies like Ipstack, Currencylayer, Invoicely, and Eversign. Aimed mostly at websites and mobile apps looking to include a live weather widget at minimal cost, offers real-time weather, historical weather, international weather, and more.

App Integration/Format: REST API returns JSON formatted responses, and supports JSONP callbacks. HTTPS is enabled for paid subscriptions.

Pricing: Varies. Free up to Enterprise.

5. Weatherbit

Weatherbit offers 5 different APIs for forecasts, historical data, and other weather data such as air quality, soil temperature, and soil moisture. Collecting data from weather stations and other traditional sources, Weatherbit uses machine learning and AI to help predict the weather.

Boasting a 95% uptime and highly responsive API servers, Weatherbit provides a free limited-functionality account for a single API key. If you’re looking to create a commercial app, note that the free API subscription will not be enough and you will have to upgrade to one of the paid plans.

App Integration/Format: JSON, HTTPS available for premium subscribers

Pricing: Premium pricing starts at $35 / month. The free version (not for use with commercial projects) is limited to 500 API calls/day.

6. Weather2020

Weather2020 brands itself as the only provider capable of delivering a 12-week forecast, so it’s great if you’re looking for long-term forecast data. However, there are some questions around the accuracy of forecasting after 10 days. The company also prides itself on being the weather data provider of leading weather apps like 1Weather.

If your focus is on long-range weather forecasting, and you’re willing to take your chances on famed meteorologist Gary Lezak’s forecasting model, Weather2020 is worth checking out.

App Integration/Format: JSON

Pricing: Premium pricing starts at $9.99 / month. The free version allows for up to 1000 API calls/day with each additional call priced at $0.002.

7. AerisWeather

AerisWeather API provides access to weather data and forecasts as well as storm reports, earthquake warnings, and other unique data for premium subscribers.

One of the main advantages of AerisWeather API is its documentation, as well as available developer toolkits for easier integration into your app.

App Integration/Format: RESTful calls and responses are formatted in JSON and JSONP

Pricing: Pricing starts at $23 / month. Free trial available (2 months).

8. Accuweather

Accuweather is probably one of the most well-known names in weather. They offer current, historical, and international weather data, along with other specific data like mosquito activity. But when it comes to their API, they’re most well known for their imagery endpoints.

Note that while you can use this API in both commercial and non-commercial applications, including the Accuweather logo is required.

App Integration/Format: RESTful calls and responses are formatted in JSON and JSONP.

Pricing: Limited trial offers up to 50 calls per day, then three pricing tiers of $25 to $500/month

9. Visual Crossing API

Visual Crossing provides instant access to both historical weather records and weather forecast data, globally. The company aims to bring low-cost data and analysis tools to the public for use in data science, business analytics, machine learning, and other applications.

App Integration/Format: CSV, JSON, & OData

Pricing: 1000 calls per day, then $35/month.

Choosing the Best Weather API

The weather API that works best for you as a developer depends heavily on your goals, preferences, project scope, and budget. There are numerous services available that offer data on topics ranging from air quality to earthquakes, fire risk index, and historical to forecast weather. The services and solutions we listed cover all and any need that you, as a developer, might have. Did we miss something? Let us know in the comments.

The post The Top 9 Weather APIs for 2023 appeared first on Tomorrow.io.

The news comes a year after the company announced it will be shutting down its Dark Sky API at the end of 2022. Though a timely replacement, WeatherKit still leaves a gap in the market for enterprise-grade developers looking for solutions that require more than basic weather data. That’s where Tomorrow.io can help.

Here’s what else you need to know and how to adapt:

What is WeatherKit?

WeatherKit enables developers to integrate Apple Weather forecast data into their apps and Xcode Cloud. Apple says it provides current weather, 10-day hourly forecasts, daily forecasts, and historical weather.

Who is WeatherKit for?

Currently in beta, WeatherKit is available only to Apple Developer Program members and has specific usage requirements. Websites and other platforms can use REST APIs while compatible operating systems are:

•  iOS 16
•  iPadOS 16
•  tvOS 16
•  watchOS 9

Given its technology and feature restrictions, WeatherKit is best for non-enterprise developers.

See how an enterprise-level alternative compares ->

What is WeatherKit’s availability and pricing?

WeatherKit beta testers get up to 500,000 API calls a month, which is standard in the Apple Developer Program membership. Additional API calls will also be available for purchase.

How does the Tomorrow.io Enterprise-Grade Weather API compare?

Unlike WeatherKit, Tomorrow.io’s Weather API uses proprietary technology and advanced features to deliver hyper-local, minute-by-minute weather data that allow you to build fully customized projects.

Compared to WeatherKit, Tomorrow.io stand out in a number of key ways both in our technology and feature set: 

Technology

Tomorrow.io draws on a combination of traditional and proprietary sources to deliver high-resolution data and modeling for any location on the globe. Compared to WeatherKit, Tomorrow.io’s Weather API offers more comprehensive, reliable, and globally available data.

Features

But data is only one part of the equation for enterprise-grade developers. Unlike WeatherKit, the Tomorrow.io Weather API also offers features you won’t find anywhere else, allowing you tobuild more innovative and scalable projects.

No matter your industry or use case, an enterprise-grade Weather API provides the data and features you need to take your project to the next level.

Try Tomorrow.io’s Enterprise-Grade Weather API Today

The post WeatherKit: What Enterprise-Grade Developers Need to Know appeared first on Tomorrow.io.