Tanzania Business News API

Get the live top business headlines from Tanzania with one request to the Top Headlines endpoint of GNews API. Stories are selected by Google News rankings and returned as clean JSON.

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Request and live response

This request returns the current top business headlines from Tanzania. The response below is live: it was fetched when this page loaded. Every parameter is described in the Top Headlines endpoint documentation.

GET https://gnews.io/api/v4/top-headlines?category=business&country=tz&apikey=YOUR_API_KEY

curl --get "https://gnews.io/api/v4/top-headlines" \
  --data-urlencode "category=business" \
  --data-urlencode "country=tz" \
  --data-urlencode "apikey=YOUR_API_KEY"

import requests

API_KEY = "YOUR_API_KEY"

response = requests.get(
    "https://gnews.io/api/v4/top-headlines",
    params={"category": "business", "country": "tz", "apikey": API_KEY},
    timeout=10,
)
response.raise_for_status()

for article in response.json()["articles"]:
    print(article["title"])

const API_KEY = "YOUR_API_KEY";

const params = new URLSearchParams({
    category: "business",
    country: "tz",
    apikey: API_KEY,
});

const response = await fetch(`https://gnews.io/api/v4/top-headlines?${params}`);
if (!response.ok) {
    throw new Error(`Request failed: ${response.status}`);
}

const { articles } = await response.json();
for (const article of articles) {
    console.log(article.title);
}

<?php

$apiKey = "YOUR_API_KEY";

$query = http_build_query([
    "category" => "business",
    "country"  => "tz",
    "apikey"   => $apiKey,
]);

$response = file_get_contents("https://gnews.io/api/v4/top-headlines?" . $query);
if ($response === false) {
    throw new RuntimeException("Request failed");
}

$data = json_decode($response, true);
foreach ($data["articles"] as $article) {
    echo $article["title"] . PHP_EOL;
}

using System.Net.Http.Json;

const string ApiKey = "YOUR_API_KEY";

using var client = new HttpClient();

var url = $"https://gnews.io/api/v4/top-headlines?category=business&country=tz&apikey={ApiKey}";
var data = await client.GetFromJsonAsync<ApiResponse>(url)
           ?? throw new InvalidOperationException("Empty response");

foreach (var article in data.Articles)
{
    Console.WriteLine(article.Title);
}

record ApiResponse(List<Article> Articles);
record Article(string Title);

200 OK · Live JSON response

{
    "totalArticles": 24816,
    "articles": [
        {
            "id": "af7ec453a1aa2afcf990be6c0afcae85",
            "title": "Evidence for multi-Li+ clustering in lithium-ion battery electrolytes",
            "description": "In lithium-ion batteries, the bulk solvation structure of the electrolyte is a major determinant of the physical and electrochemical properties of the cell, for example, conductivity, viscosity, salt dissociation and subsequent reactivity, the electrochemical stability window (and thus solid electrolyte interphase formation), and the composition of the electrochemical double layer1–3. However, elucidation of this structure at an atomic level of detail has been challenging to accomplish via a purely experimental approach. Here we combine machine-learning-enabled atomistic simulations4–16, nuclear magnetic resonance spectroscopy, electrochemical data3,17–20 and quantum-chemical calculations to reveal previously unstudied multi-Li+ complexes without bound anions that are uniquely facile for reduction. This insight explains the success of empirically chosen ethylene-carbonate-containing solvent mixtures and provides a foundation for the rational design of improved electrolytes. Furthermore, our machine-learning force-field-based lithium-ion-battery electrolyte simulations accurately reproduce a wide range of condensed-phase experiments3,21–24, despite being parameterized to only quantum-chemical gas-phase cluster calculations, and hence provide a compelling demonstration that machine-learning force-field-based models developed from first principles can robustly represent a complex chemical system to atomic resolution. Machine-learning-enabled atomistic simulations, spectroscopy, electrochemical data and quantum-chemical calculations reveal previously unstudied multi-lithium-ion complexes without bound anions, improving understanding of lithium-ion-battery functionality at the atomic level.",
            "content": "Overview\nBelow we describe three complementary approaches to the validation of our QRNN model for the LIB electrolyte. First, we assess the accuracy with which the MLFF reproduces accurate quantum-chemical calculations for Li–Li distance scans and fo... [30304 chars]",
            "url": "https://www.nature.com/articles/s41586-026-11138-7?error=cookies_not_supported&code=a57397e5-2d40-4693-9ea5-02cc1dc61379",
            "image": "https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs41586-026-11138-7/MediaObjects/41586_2026_11138_Fig1_HTML.png",
            "publishedAt": "2026-10-14T22:55:28Z",
            "lang": "en",
            "source": {
                "id": "7abf0df285fbe93cdccffcc7c4088737",
                "name": "Nature",
                "url": "https://www.nature.com"
            }
        },
        {
            "id": "8645ac8b160a52fbec89d26732be065a",
            "title": "Stocks drop to their worst day since July as inflation worsens",
            "description": "U.S. stocks dropped to their worst day since July.",
            "content": "Stocks dropped to their worst day since July on Wednesday after the latest signal that inflation is worsening.\nThe Standard & Poor’s 500 index sank 1.1% for a fifth loss in the six days since setting its all-time high. The Dow Jones industrial averag... [4355 chars]",
            "url": "https://www.latimes.com/business/story/2026-10-14/stocks-drop-to-their-worst-day-since-july-as-inflation-worsens",
            "image": "https://ca-times.brightspotcdn.com/dims4/default/765bf1a/2147483647/strip/true/crop/3575x1877+0+253/resize/1200x630!/quality/75/?url=https%3A%2F%2Fcalifornia-times-brightspot.s3.amazonaws.com%2F3e%2Fce%2Fd400af004505a27ed6bace5958a9%2F364f7c4660a0475c83904ccfb002b73c.jpg",
            "publishedAt": "2026-10-14T21:06:34Z",
            "lang": "en",
            "source": {
                "id": "6c4fa75a787f2ec713503abb3f822104",
                "name": "Los Angeles Times",
                "url": "https://www.latimes.com"
            }
        },
        {
            "id": "78ca316f6f02c12fb2325df9f57b8584",
            "title": "OpenAI accuses employee who left for Apple of leaking plans for unreleased device",
            "description": "Hours before Apple and the ChatGPT maker were due to face off in court, a new allegation delayed the showdown",
            "content": "An ⁠OpenAI employee who left the ChatGPT maker for Apple sent more than 100 files about an unreleased product to a personal ⁠account and later ⁠made a presentation about the unreleased product to senior Apple leadership, a new filing in the lawsuit ... [1820 chars]",
            "url": "https://www.theguardian.com/technology/2026/oct/14/openai-apple-employee-leak-lawsuit",
            "image": "https://i.guim.co.uk/img/media/ebf66ef2fc761ca986ec34ee126faa393835c357/479_0_4771_3819/master/4771.jpg?width=1200&height=630&quality=85&auto=format&fit=crop&precrop=40:21,offset-x50,offset-y0&overlay-align=bottom%2Cleft&overlay-width=100p&overlay-base64=L2ltZy9zdGF0aWMvb3ZlcmxheXMvdGctZGVmYXVsdC5wbmc&enable=upscale&s=34fa29010b569757c13f906c40fa3bed",
            "publishedAt": "2026-10-14T21:04:00Z",
            "lang": "en",
            "source": {
                "id": "558a003a7a0164e924408edec7e99f99",
                "name": "The Guardian",
                "url": "https://www.theguardian.com"
            }
        }
    ]
}

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Tanzania Business News API

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Request and live response