📊 Turn weather data into insights. Real-time weather, forecasts, charts, and analytics — all powered by WeatherAPI. ⚡ #WeatherAPI #DashboardDesign #DataVisualization #DeveloperTools #BuildInPublic #WeatherData

⚽💻 This is our stadium 😅 Some people watch the World Cup from the stands. Developers watch it with: ☕ Coffee 💻 VS Code 📱 Match on the second screen 🐛 A few bugs waiting to be fixed One eye on the code. One eye on the score #worldcup #qatsui #engineerproblems #weatherapi

The Future of Weather Services Is API-Driven 🌍 Weather data is becoming increasingly embedded in digital workflows. In many cases, forecasts are no longer consumed by people first – they are consumed by software. Route optimisation platforms, renewable energy management systems, agricultural applications, climate risk models, digital twins and urban planning tools all rely on weather data flowing directly into automated workflows. The result is a rapidly expanding market for weather APIs. Recent market analyses estimate the global weather API market at approximately USD 872 million in 2025, with projections exceeding USD 1.2 billion by 2034. Growth is being driven by digitalisation across sectors such as energy, transport, agriculture, insurance and climate risk management, alongside the increasing adoption of AI, IoT devices and real-time decision support systems. This evolution reflects a broader change in how weather information is used. Organisations are moving beyond simple forecast displays towards systems that continuously ingest meteorological data and convert it into operational decisions. In the energy sector, weather APIs support renewable generation forecasting, grid management and infrastructure protection. In logistics, they help optimise routing and anticipate disruptions. In agriculture, they contribute to irrigation planning, field operations and yield optimisation. As weather data becomes embedded deeper into operational processes, forecast quality becomes increasingly important. Access to weather data alone is no longer enough. Businesses need reliable forecasts, global coverage, high-resolution modelling, historical datasets, climate information, warnings and APIs capable of operating at scale across thousands of locations. This is where the future of weather services is heading: weather intelligence delivered directly into business systems, enabling faster and more informed decisions without manual interpretation at every step. ➡️ At meteoblue, we support this transition through a portfolio of APIs covering forecasts, historical weather data, climate information, measurements, warnings, weather maps and specialised datasets for sectors including energy, agriculture, transport, urban resilience and sustainability. Our modelling infrastructure combines more than 30 weather models and data from over 250,000 weather stations worldwide to deliver weather intelligence at global scale. ➡️ Learn more: business.meteoblue.com/produ… #WeatherAPI #WeatherData #ClimateTech #WeatherIntelligence #meteoblue

client: “I need a weather app live by 12am.” me: sleeps peacefully… me at 11:59pm: opens WeatherAPI, grabs clean JSON, ships the project. Built different. #WeatherAPI #DeveloperLife #APIDevelopment #BuildInPublic #CodeLife

We love free and instant weather data. Check out the OSINTCabal Weather Scraper for free on our website with exportable results! osintcabal.org/livecenter/we… #OSINT #OSINTtool #osinttools #opendata #openapi #apidata #weatherdata #weatherapi #scraping #osint4good

🌦️ Weather data in one API call. Real-time, forecast & historical weather with clean JSON/XML responses. Built for developers. ⚡ #WeatherAPI #DeveloperTools #APIIntegration #WeatherData

I didn't tell it which function to call. It figured it out. Full feature list: ✅ Live crypto prices (BTC, ETH, DOGE) in any currency ✅ Real-time weather for any city via WeatherAPI ✅ Persistent conversation memory across turns ✅ Multi-turn dialogue asks follow-ups naturally

Open-Meteo es el corazón del Dragón. Sin eso no existiríamos. Ensemble multi-modelo en free tier es un milagro. Complementamos con WeatherAPI para observaciones reales, NOAA para USA, y TAF de aviación para verificar forecasts. Wethr no lo tenemos. Lo analizamos esta semana para ver si lo añadimos como capa extra.

Day 05 - Styrae ✨🍻 worked on the ai stylist feature, with a full agentic experience and making the agent stateless, which will scale automatically when users grow. also migrated from openweather to weatherapi .com cause they are really cost efficient - 3M calls / month at 7$. thats how my day 5 was 😂

I built an AI predictor. It even uses all of windy, weather network, weatherapi, openweather, visualcrossing, windfinder, and weather canada. Scores each one. Tries to predict forecast. But garbage in, garbage out.

有个机器人在 Polymarket 的天气市场上，两个月就把 300 美元滚到了 10.1 万美元。 它的思路并不复杂：通过 WeatherAPI 同时盯着 20 个城市的天气预报，专门找那些市场定价极低的稀有事件（大概就 0.01 到 0.1 美分这种），然后下注。聊几个实际战绩： · 一笔 25 美元变 12452 美元 · 一笔 16 美元变 8106 美元 · 一笔 11 美元变 5752 美元 原理上就是接入几套主流天气模型（ECMWF、HRRR、METAR），算出期望值，再用凯利公式决定下注大小，系统还会自动校准。 想自己跑起来的话，步骤大概是： · 装好 Python 3.10 · 注册 Polymarket 账户，开通 API 权限 · 配好 config.json · 先跑一轮 1000 美元的模拟测试 另外，在平台官网提供流动性也能赚 LP 奖励。 如果想进一步提高准确率，还可以接入付费天气 API，比如 OpenWeather、Tomorrow、OpenMeteo。

A bot turned 300-101K in 2 months on Polymarket weather markets It scans forecasts across 20 cities via WeatherAPI and finds rare events (0.01¢–0.1¢) Results: $25 - $12,452 $16 - $8,106 $11 - $5,752 How it works: forecasts (ECMWF, HRRR, METAR), EV calculation, Kelly betting, auto‑calibration How to launch: > install Python 3.10 > create a Polymarket account and get API access > download github.com/alteregoeth-ai/we… > configure config.json > run a test ($1,000 dry‑run) You can earn LP rewards right here: polymarket.com/?r=dpool For higher accuracy, you can connect paid APIs: OpenWeather, Tomorrow, OpenMeteo

Um robô transformou US$ 300 em US$ 101 mil em 2 meses nos mercados meteorológicos da Polymarket. Analisando previsões meteorológicas em 20 cidades através da WeatherAPI em busca de eventos climáticos ultrarraros {0,01¢ -0,1¢} Encontrei um bot Python totalmente funcional e autocalibrável que executa exatamente essa estratégia. Os resultados dos bots são impressionantes: 25$ → 12.452$ 16$ → 8.106$ 11$ → 5.752$ O bot utiliza previsões (ECMWF, HRRR, METAR), calcula o valor esperado (EV), dimensiona as posições com Kelly e se autocalibra. Como configurar: • Instale o Python 3.10 no PC/Mac • Obtenha a API de previsão do tempo gratuita em { visualcrossing .com } • Configure a conta do Polymarket e obtenha a API em /profile • git clone { github .com/alteregoeth-ai/weatherbot } • configurar arquivo .json • Faça um teste com $1.000 em caixa → depois comece a usar USDC de verdade. • Deixe o sistema realizar mais de 100 transações para se autocalibrar. Para resultados mais precisos, adicione APIs pagas como OpenWeather, Tomorrow.io e OpenMeteo. Código-fonte completo no GitHub: github.com/alteregoeth-ai/we… Perfil do bot: polymarket.com/@coldmath FAÇA COPYTRADE COM KREO: t.me/KreoPolyBot?start=ref-d…

有位老哥搞了个天气预测机器人，在Polymarket上跑，两个月时间从300刀滚到了10万刀出头。 具体怎么玩的呢？ 他用WeatherAPI扫20个城市的数据，专盯那种定价只有零点几美分、概率极低的稀有天气事件。市场对这些小概率事件的报价往往不太准，偏差就是利润空间。 数据源方面，他拉的是ECMWF（欧洲中期天气预报中心）、HRRR（高分辨率快速刷新）和METAR（航空例行天气报告）这三套，然后算期望值，再用凯利公式定每次下多少注。跑够100笔交易之后，系统会开始自己校准参数，越跑越准。 随便挑几个实际单子看一眼： · 25刀进去，出来12452刀 · 16刀进去，出来8106刀 · 11刀进去，出来5752刀 整套代码在GitHub上开源了，Python 3.10写的，挂个免费天气API，再有个Polymarket账号，克隆下来配好就能跑。 想更进一步的话，可以换成付费的天气API，数据精度更高。不过免费版已经能跑出利润了。 那位老哥的主页在这：polymarket.com/zh/@ColdMath?… 想在Polymarket跟着跑的，可以用这个机器人跟单：t.me/PolyCop_BOT?start=ref_Y… #Polymarket

this guy's weather bot did $300 → $101K in 2 months flat on Polymarket scans 20 cities via WeatherAPI looking for ultra-rare weather events priced at fractions of a cent pulls ECMWF, HRRR and METAR data, calculates EV, sizes positions with Kelly, and self-calibrates over time his actual returns: $25 → $12,452 $16 → $8,106 $11 → $5,752 whole thing is open source on github. python 3.10, free weather API, polymarket account, clone the repo, config and go needs like 100 trades before the self-calibration kicks in properly you can add paid weather APIs for better edge but the free version already prints bot profile: polymarket.com/profile/0x594…

Day 35 of #100DaysOfCode Today's Build: Rain Alert Bot! Mastered API Keys & Authentication. Integrated Twilio for SMS automation. Used Environment Variables for security. Weather data parsing with OpenWeatherMap API. #Python #CodeNewbie #100DaysPython #Automation #WeatherAPI

Bot turned $300 → $101K in 2 months on Polymarket weather markets scanning forecasts across 20 cities via WeatherAPI hunting ultra-rare weather events {0.01¢ -0.1¢} I found a fully working, self-calibrating Python bot running this exact strategy bots results are crazy: 25$ → 12,452$ 16$ → 8,106$ 11$ → 5,752$ bot uses (ECMWF, HRRR, METAR) forecast, calculates EV, sizes positions with Kelly, and self-calibrates. how to set-up: • install python 3.10 on PC/Mac • get free weather API from { visualcrossing .com } • set polymarket account and get API in /profile • git clone { github .com/alteregoeth-ai/weatherbot } • setup config .json using article below • run $1,000 dry test → then go live with real USDC • give it 100 trades to self-calibrate for more accurate results add paid APIs like OpenWeather, Tomorrow .io, OpenMeteo bot profile: polymarket.com/profile/0x594…

Claude Weather = $1000/day on Polymarket If you'd told me this a month ago, I would have laughed. But it really does work. This guy created a script that monitors these APIs in real time: > Open-Meteo (GFS, ECMWF models) > OpenWeatherMap > WeatherAPI > Tomorrow(.)io > Visual Crossing Look at his profile: [polymarket.com/@coldmath?r=m…] He has a simply perfect chart. But how does he do it? It's simple: he uses the Claude bot to read data from the above platforms. Polymarket takes less than 1 second to update data. And that's enough time for the script to respond. Literally predicting the future. That's the advantage.

I’ve started populating it with tools/APIs across different categories, including things like Google APIs, arXiv, NASA, WeatherAPI, Slack, Twilio, and more. The goal is to keep expanding it over time.