Trouvez des données Recherche sur X/Twitter à partir d'une requête utilisateur et connectez les résultats à des interfaces de recherche, de catalogue ou d'exploration.
Utilisez « Publications par requête » lorsque vous ne connaissez pas l'identifiant exact de l'objet et devez d'abord trouver des candidats pertinents.
Examinez d'abord le résultat et les flux courants, puis passez aux paramètres et à un exemple de requête fonctionnel.
La réponse contient les Recherche correspondants, le contexte public et les données de pagination lorsque d'autres résultats sont disponibles.
Utilisez « Publications par requête » lorsque vous ne connaissez pas l'identifiant exact de l'objet et devez d'abord trouver des candidats pertinents.
Ajoutez la recherche dans les données X/Twitter aux interfaces clients et internes.
Trouvez des candidats par requête et conservez les objets pertinents pour un enrichissement ultérieur.
Collectez des ensembles de résultats pour analyser les sujets, les créateurs et la concurrence.
Les deux versions répondent au même besoin et acceptent les mêmes paramètres. Utilisez le sélecteur pour comparer la structure de la réponse et choisissez la version attendue par votre client.
Changez de version sur cette page pour comparer les structures de réponse sous la même URL de documentation.
L'authentification, les paramètres obligatoires et la forme de la requête sont identiques en V1 et V2. En pratique, vous choisissez la version en construisant le chemin de l'endpoint et en lisant la réponse.
La principale différence réside dans l'enveloppe de la réponse. Utilisez V2 pour les nouvelles intégrations et ne conservez V1 que si vous avez besoin de compatibilité avec un contrat client existant.
Utilisez le même en-tête de clé API et les mêmes paramètres de requête dans les deux versions. Cette documentation présente d'abord l'ensemble commun de paramètres, puis les chemins et extraits de code de chaque version.
| Paramètre | Obligatoire | Type | Exemple | Description |
|---|---|---|---|---|
query |
Oui | str |
technology |
Requête de recherche saisie par l'utilisateur. |
all_of_these_words |
Non | str | None |
AI robotics |
Optional words that must all appear in matching Twitter/X posts. Example: AI robotics. |
any_of_these_words |
Non | str | None |
launch release |
Optional words where any one may appear in matching Twitter/X posts. Example: launch release. |
cursor |
Non | str | None |
DAABCgABF4ABCD... |
Curseur de la page suivante issu de la réponse précédente. À omettre pour la première page. |
exact_phrase |
Non | str | None |
machine learning |
Optional exact phrase that must appear in matching Twitter/X posts. Example: machine learning. |
from_accounts |
Non | str | None |
technews xai |
Optional source accounts without or with @, separated by spaces or commas. Example: technews xai. |
hashtags |
Non | str | None |
#TechNews #AI |
Optional hashtags to require, separated by spaces or commas. Example: #TechNews #AI. |
language |
Non | str | None |
en |
Optional Twitter/X language code. Use 'any' to omit language filtering. Example: en. |
link_filter |
Non | include | only | exclude | None |
only |
Optional link filter: include all posts, only posts with links, or exclude links. Example: only. |
mentioning_accounts |
Non | str | None |
technews elonmusk |
Optional mentioned accounts without or with @, separated by spaces or commas. Example: technews elonmusk. |
min_likes |
Non | int | None |
100 |
Optional minimum like count. Example: 100. |
min_replies |
Non | int | None |
10 |
Optional minimum reply count. Example: 10. |
min_retweets |
Non | int | None |
25 |
Optional minimum repost/retweet count. Example: 25. |
none_of_these_words |
Non | str | None |
rumor leak |
Optional words to exclude from matching Twitter/X posts. Example: rumor leak. |
reply_filter |
Non | include | only | exclude | None |
exclude |
Optional reply filter: include all posts, only replies, or exclude replies. Example: exclude. |
since_date |
Non | date | None |
2026-01-01 |
Optional earliest post date in ISO YYYY-MM-DD format. Example: 2026-01-01. |
tag |
Non | Top | Latest | People | Photos | Videos | None |
Latest |
Optional Twitter/X search product filter. Example: Latest. |
to_accounts |
Non | str | None |
technews |
Optional reply target accounts without or with @, separated by spaces or commas. Example: technews. |
until_date |
Non | date | None |
2026-01-31 |
Optional latest post date in ISO YYYY-MM-DD format. Example: 2026-01-31. |
Choisissez une version lorsque vous copiez le chemin exact de l'endpoint, l'URL d'exemple et l'extrait de code. La liste des paramètres ci-dessus ne change pas.
GET /api/v2/twitter.com/search/tweets-by-querycurl --request GET \
--url "https://www.scrapestorm.net/api/v2/twitter.com/search/tweets-by-query" \
--header "X-API-Key: 00000000-0000-4000-8000-000000000000" \
--get --data-urlencode 'query=technology' \
# Optional parameters:
# --data-urlencode 'all_of_these_words=AI robotics'
# --data-urlencode 'any_of_these_words=launch release'
# --data-urlencode 'cursor=DAABCgABF4ABCD...'
# --data-urlencode 'exact_phrase=machine learning'
# --data-urlencode 'from_accounts=technews xai'
# --data-urlencode 'hashtags=#TechNews #AI'
# --data-urlencode 'language=en'
# --data-urlencode 'link_filter=only'
# --data-urlencode 'mentioning_accounts=technews elonmusk'
# --data-urlencode 'min_likes=100'
# --data-urlencode 'min_replies=10'
# --data-urlencode 'min_retweets=25'
# --data-urlencode 'none_of_these_words=rumor leak'
# --data-urlencode 'reply_filter=exclude'
# --data-urlencode 'since_date=2026-01-01'
# --data-urlencode 'tag=Latest'
# --data-urlencode 'to_accounts=technews'
# --data-urlencode 'until_date=2026-01-31'from urllib.parse import urljoin
import requests
BASE_URL = "https://www.scrapestorm.net"
ENDPOINT = "/api/v2/twitter.com/search/tweets-by-query"
HEADERS = {"Accept": "application/json", "X-API-Key": "00000000-0000-4000-8000-000000000000"}
params = {
"query": "technology",
}
# Optional parameters
# params["all_of_these_words"] = "AI robotics"
# params["any_of_these_words"] = "launch release"
# params["cursor"] = "DAABCgABF4ABCD..."
# params["exact_phrase"] = "machine learning"
# params["from_accounts"] = "technews xai"
# params["hashtags"] = "#TechNews #AI"
# params["language"] = "en"
# params["link_filter"] = "only"
# params["mentioning_accounts"] = "technews elonmusk"
# params["min_likes"] = "100"
# params["min_replies"] = "10"
# params["min_retweets"] = "25"
# params["none_of_these_words"] = "rumor leak"
# params["reply_filter"] = "exclude"
# params["since_date"] = "2026-01-01"
# params["tag"] = "Latest"
# params["to_accounts"] = "technews"
# params["until_date"] = "2026-01-31"
with requests.Session() as session:
response = session.request(
method="GET",
url=urljoin(BASE_URL, ENDPOINT),
headers=HEADERS,
params=params,
timeout=30,
)
response.raise_for_status()
payload = response.json()
print(payload)const BASE_URL = "https://www.scrapestorm.net";
const endpoint = "/api/v2/twitter.com/search/tweets-by-query";
const params = new URLSearchParams({
query: "technology",
});
// Optional parameters
// params.set("all_of_these_words", "AI robotics");
// params.set("any_of_these_words", "launch release");
// params.set("cursor", "DAABCgABF4ABCD...");
// params.set("exact_phrase", "machine learning");
// params.set("from_accounts", "technews xai");
// params.set("hashtags", "#TechNews #AI");
// params.set("language", "en");
// params.set("link_filter", "only");
// params.set("mentioning_accounts", "technews elonmusk");
// params.set("min_likes", "100");
// params.set("min_replies", "10");
// params.set("min_retweets", "25");
// params.set("none_of_these_words", "rumor leak");
// params.set("reply_filter", "exclude");
// params.set("since_date", "2026-01-01");
// params.set("tag", "Latest");
// params.set("to_accounts", "technews");
// params.set("until_date", "2026-01-31");
const response = await fetch(`${BASE_URL}${endpoint}?${params.toString()}`, {
method: "GET",
headers: {
Accept: "application/json",
"X-API-Key": "00000000-0000-4000-8000-000000000000",
},
});
if (!response.ok) {
throw new Error(`Request failed: ${response.status} ${response.statusText}`);
}
const payload = await response.json();
console.log(payload);import axios from "axios";
const client = axios.create({
baseURL: "https://www.scrapestorm.net",
timeout: 30000,
headers: {
Accept: "application/json",
"X-API-Key": "00000000-0000-4000-8000-000000000000",
},
});
const params = {
query: "technology",
};
// Optional parameters
// params.all_of_these_words = "AI robotics";
// params.any_of_these_words = "launch release";
// params.cursor = "DAABCgABF4ABCD...";
// params.exact_phrase = "machine learning";
// params.from_accounts = "technews xai";
// params.hashtags = "#TechNews #AI";
// params.language = "en";
// params.link_filter = "only";
// params.mentioning_accounts = "technews elonmusk";
// params.min_likes = "100";
// params.min_replies = "10";
// params.min_retweets = "25";
// params.none_of_these_words = "rumor leak";
// params.reply_filter = "exclude";
// params.since_date = "2026-01-01";
// params.tag = "Latest";
// params.to_accounts = "technews";
// params.until_date = "2026-01-31";
const { data: payload } = await client.request({
method: "GET",
url: endpoint,
params,
});
console.log(payload);<?php
declare(strict_types=1);
use GuzzleHttp\Client;
use GuzzleHttp\Exception\GuzzleException;
$client = new Client([
'base_uri' => "https://www.scrapestorm.net",
'timeout' => 30.0,
'headers' => [
'Accept' => 'application/json',
'X-API-Key' => "00000000-0000-4000-8000-000000000000",
],
]);
$query = [
"query" => "technology",
];
// Optional parameters
// $query["all_of_these_words"] = "AI robotics";
// $query["any_of_these_words"] = "launch release";
// $query["cursor"] = "DAABCgABF4ABCD...";
// $query["exact_phrase"] = "machine learning";
// $query["from_accounts"] = "technews xai";
// $query["hashtags"] = "#TechNews #AI";
// $query["language"] = "en";
// $query["link_filter"] = "only";
// $query["mentioning_accounts"] = "technews elonmusk";
// $query["min_likes"] = "100";
// $query["min_replies"] = "10";
// $query["min_retweets"] = "25";
// $query["none_of_these_words"] = "rumor leak";
// $query["reply_filter"] = "exclude";
// $query["since_date"] = "2026-01-01";
// $query["tag"] = "Latest";
// $query["to_accounts"] = "technews";
// $query["until_date"] = "2026-01-31";
try {
$response = $client->request("GET", "/api/v2/twitter.com/search/tweets-by-query", [
'query' => $query,
]);
$payload = json_decode(
(string) $response->getBody(),
true,
512,
JSON_THROW_ON_ERROR
);
var_dump($payload);
} catch (GuzzleException $e) {
throw $e;
}package main
import (
"encoding/json"
"fmt"
"net/http"
"net/url"
"time"
)
func main() {
baseURL := "https://www.scrapestorm.net"
endpoint := "/api/v2/twitter.com/search/tweets-by-query"
params := url.Values{}
params.Set("query", "technology")
// Optional parameters
// params.Set("until_date", "2026-01-31")
req, err := http.NewRequest(
"GET",
fmt.Sprintf("%s%s?%s", baseURL, endpoint, params.Encode()),
nil,
)
if err != nil {
panic(err)
}
req.Header.Set("Accept", "application/json")
req.Header.Set("X-API-Key", "00000000-0000-4000-8000-000000000000")
client := &http.Client{Timeout: 30 * time.Second}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
var payload any
if err := json.NewDecoder(resp.Body).Decode(&payload); err != nil {
panic(err)
}
fmt.Printf("%+v\n", payload)
}Choisissez une version lorsque vous copiez le chemin exact de l'endpoint, l'URL d'exemple et l'extrait de code. La liste des paramètres ci-dessus ne change pas.
GET /api/v1/twitter.com/search/tweets-by-querycurl --request GET \
--url "https://www.scrapestorm.net/api/v1/twitter.com/search/tweets-by-query" \
--header "X-API-Key: 00000000-0000-4000-8000-000000000000" \
--get --data-urlencode 'query=technology' \
# Optional parameters:
# --data-urlencode 'all_of_these_words=AI robotics'
# --data-urlencode 'any_of_these_words=launch release'
# --data-urlencode 'cursor=DAABCgABF4ABCD...'
# --data-urlencode 'exact_phrase=machine learning'
# --data-urlencode 'from_accounts=technews xai'
# --data-urlencode 'hashtags=#TechNews #AI'
# --data-urlencode 'language=en'
# --data-urlencode 'link_filter=only'
# --data-urlencode 'mentioning_accounts=technews elonmusk'
# --data-urlencode 'min_likes=100'
# --data-urlencode 'min_replies=10'
# --data-urlencode 'min_retweets=25'
# --data-urlencode 'none_of_these_words=rumor leak'
# --data-urlencode 'reply_filter=exclude'
# --data-urlencode 'since_date=2026-01-01'
# --data-urlencode 'tag=Latest'
# --data-urlencode 'to_accounts=technews'
# --data-urlencode 'until_date=2026-01-31'from urllib.parse import urljoin
import requests
BASE_URL = "https://www.scrapestorm.net"
ENDPOINT = "/api/v1/twitter.com/search/tweets-by-query"
HEADERS = {"Accept": "application/json", "X-API-Key": "00000000-0000-4000-8000-000000000000"}
params = {
"query": "technology",
}
# Optional parameters
# params["all_of_these_words"] = "AI robotics"
# params["any_of_these_words"] = "launch release"
# params["cursor"] = "DAABCgABF4ABCD..."
# params["exact_phrase"] = "machine learning"
# params["from_accounts"] = "technews xai"
# params["hashtags"] = "#TechNews #AI"
# params["language"] = "en"
# params["link_filter"] = "only"
# params["mentioning_accounts"] = "technews elonmusk"
# params["min_likes"] = "100"
# params["min_replies"] = "10"
# params["min_retweets"] = "25"
# params["none_of_these_words"] = "rumor leak"
# params["reply_filter"] = "exclude"
# params["since_date"] = "2026-01-01"
# params["tag"] = "Latest"
# params["to_accounts"] = "technews"
# params["until_date"] = "2026-01-31"
with requests.Session() as session:
response = session.request(
method="GET",
url=urljoin(BASE_URL, ENDPOINT),
headers=HEADERS,
params=params,
timeout=30,
)
response.raise_for_status()
payload = response.json()
print(payload)const BASE_URL = "https://www.scrapestorm.net";
const endpoint = "/api/v1/twitter.com/search/tweets-by-query";
const params = new URLSearchParams({
query: "technology",
});
// Optional parameters
// params.set("all_of_these_words", "AI robotics");
// params.set("any_of_these_words", "launch release");
// params.set("cursor", "DAABCgABF4ABCD...");
// params.set("exact_phrase", "machine learning");
// params.set("from_accounts", "technews xai");
// params.set("hashtags", "#TechNews #AI");
// params.set("language", "en");
// params.set("link_filter", "only");
// params.set("mentioning_accounts", "technews elonmusk");
// params.set("min_likes", "100");
// params.set("min_replies", "10");
// params.set("min_retweets", "25");
// params.set("none_of_these_words", "rumor leak");
// params.set("reply_filter", "exclude");
// params.set("since_date", "2026-01-01");
// params.set("tag", "Latest");
// params.set("to_accounts", "technews");
// params.set("until_date", "2026-01-31");
const response = await fetch(`${BASE_URL}${endpoint}?${params.toString()}`, {
method: "GET",
headers: {
Accept: "application/json",
"X-API-Key": "00000000-0000-4000-8000-000000000000",
},
});
if (!response.ok) {
throw new Error(`Request failed: ${response.status} ${response.statusText}`);
}
const payload = await response.json();
console.log(payload);import axios from "axios";
const client = axios.create({
baseURL: "https://www.scrapestorm.net",
timeout: 30000,
headers: {
Accept: "application/json",
"X-API-Key": "00000000-0000-4000-8000-000000000000",
},
});
const params = {
query: "technology",
};
// Optional parameters
// params.all_of_these_words = "AI robotics";
// params.any_of_these_words = "launch release";
// params.cursor = "DAABCgABF4ABCD...";
// params.exact_phrase = "machine learning";
// params.from_accounts = "technews xai";
// params.hashtags = "#TechNews #AI";
// params.language = "en";
// params.link_filter = "only";
// params.mentioning_accounts = "technews elonmusk";
// params.min_likes = "100";
// params.min_replies = "10";
// params.min_retweets = "25";
// params.none_of_these_words = "rumor leak";
// params.reply_filter = "exclude";
// params.since_date = "2026-01-01";
// params.tag = "Latest";
// params.to_accounts = "technews";
// params.until_date = "2026-01-31";
const { data: payload } = await client.request({
method: "GET",
url: endpoint,
params,
});
console.log(payload);<?php
declare(strict_types=1);
use GuzzleHttp\Client;
use GuzzleHttp\Exception\GuzzleException;
$client = new Client([
'base_uri' => "https://www.scrapestorm.net",
'timeout' => 30.0,
'headers' => [
'Accept' => 'application/json',
'X-API-Key' => "00000000-0000-4000-8000-000000000000",
],
]);
$query = [
"query" => "technology",
];
// Optional parameters
// $query["all_of_these_words"] = "AI robotics";
// $query["any_of_these_words"] = "launch release";
// $query["cursor"] = "DAABCgABF4ABCD...";
// $query["exact_phrase"] = "machine learning";
// $query["from_accounts"] = "technews xai";
// $query["hashtags"] = "#TechNews #AI";
// $query["language"] = "en";
// $query["link_filter"] = "only";
// $query["mentioning_accounts"] = "technews elonmusk";
// $query["min_likes"] = "100";
// $query["min_replies"] = "10";
// $query["min_retweets"] = "25";
// $query["none_of_these_words"] = "rumor leak";
// $query["reply_filter"] = "exclude";
// $query["since_date"] = "2026-01-01";
// $query["tag"] = "Latest";
// $query["to_accounts"] = "technews";
// $query["until_date"] = "2026-01-31";
try {
$response = $client->request("GET", "/api/v1/twitter.com/search/tweets-by-query", [
'query' => $query,
]);
$payload = json_decode(
(string) $response->getBody(),
true,
512,
JSON_THROW_ON_ERROR
);
var_dump($payload);
} catch (GuzzleException $e) {
throw $e;
}package main
import (
"encoding/json"
"fmt"
"net/http"
"net/url"
"time"
)
func main() {
baseURL := "https://www.scrapestorm.net"
endpoint := "/api/v1/twitter.com/search/tweets-by-query"
params := url.Values{}
params.Set("query", "technology")
// Optional parameters
// params.Set("until_date", "2026-01-31")
req, err := http.NewRequest(
"GET",
fmt.Sprintf("%s%s?%s", baseURL, endpoint, params.Encode()),
nil,
)
if err != nil {
panic(err)
}
req.Header.Set("Accept", "application/json")
req.Header.Set("X-API-Key", "00000000-0000-4000-8000-000000000000")
client := &http.Client{Timeout: 30 * time.Second}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
var payload any
if err := json.NewDecoder(resp.Body).Decode(&payload); err != nil {
panic(err)
}
fmt.Printf("%+v\n", payload)
}L'aperçu contient les champs clés et les premiers éléments de la collection pour vous permettre de vérifier rapidement la forme de la réponse. Le format JSON change avec la version.
Cet exemple JSON compact provient de la dernière vérification réussie de V2.
{
"success": true,
"status": "ok",
"pagination": {
"cursor": "QVFB...",
"has_more": true
},
"search_context": {
"query": "Python code",
"tag": "Top"
},
"data": {
"tweets": {
"count": 20,
"items": [
{
"url": "https://x.com/freeCodeCamp/status/2078389573567050090",
"tweet_id": "2078389573567050090",
"text": "Learning to code can feel overwhelming when you don't know where to start.\n\nSo here's a course for you: Sunny teaches you Python from the ground up.\n\nYou'll install Python, writ…",
"hashtags": [],
"emails": [],
"created_at": "2026-07-18T08:01:03Z",
"language": "en",
"source": "Buffer",
"author": {
"url": "https://x.com/freeCodeCamp",
"user_id": "1668100142",
"username": "freeCodeCamp",
"display_name": "freeCodeCamp.org",
"description": "We're a community of millions of people who are building new skills and getting new jobs together. A 501(c)(3) public charity. Tweets by @abbeyrenn.",
"emails": [],
"external_links": [],
"location": "Just here on Earth... for now",
"created_at": "2013-08-13T15:27:51Z",
"is_verified": false,
"is_blue_verified": true,
"is_protected": false,
"possibly_sensitive": false,
"default_profile": false,
"default_profile_image": false,
"followers_count": 1204998,
"following_count": 159,
"tweet_count": 36772,
"media_count": 5153,
"listed_count": 6833,
"like_count": 72305,
"professional_type": null,
"professional_category_name": null,
"affiliated_account": null,
"_more_fields": "5 more fields"
},
"is_from_automated_account": null,
"media": {
"images": [
"…"
],
"videos": [],
"gifs": []
},
"external_links": [],
"user_mentions": [],
"is_reply": false,
"reply": null,
"is_quote": false,
"quote_tweet_id": null,
"is_retweet": false,
"retweeted_tweet_id": null,
"reply_count": 4,
"retweet_count": 108,
"quote_count": 3,
"like_count": 599,
"bookmark_count": 455,
"_more_fields": "2 more fields"
},
{
"url": "https://x.com/PythonPr/status/2078910492068786514",
"tweet_id": "2078910492068786514",
"text": "Pyramids in Python Code Examples for Beginners ⭐ https://t.co/QngwbiMVkb",
"hashtags": [],
"emails": [],
"created_at": "2026-07-19T18:31:00Z",
"language": "en",
"source": "Twitter Web App",
"author": {
"url": "https://x.com/PythonPr",
"user_id": "855384627975831553",
"username": "PythonPr",
"display_name": "Python Programming",
"description": "#python #programming",
"emails": [],
"external_links": [],
"location": "United States",
"created_at": "2017-04-21T11:36:02Z",
"is_verified": false,
"is_blue_verified": true,
"is_protected": false,
"possibly_sensitive": false,
"default_profile": true,
"default_profile_image": false,
"followers_count": 208924,
"following_count": 1162,
"tweet_count": 9883,
"media_count": 4108,
"listed_count": 1243,
"like_count": 20597,
"professional_type": null,
"professional_category_name": null,
"affiliated_account": null,
"_more_fields": "5 more fields"
},
"is_from_automated_account": null,
"media": {
"images": [
"…"
],
"videos": [],
"gifs": []
},
"external_links": [],
"user_mentions": [],
"is_reply": false,
"reply": null,
"is_quote": false,
"quote_tweet_id": null,
"is_retweet": false,
"retweeted_tweet_id": null,
"reply_count": 3,
"retweet_count": 8,
"quote_count": 0,
"like_count": 62,
"bookmark_count": 39,
"_more_fields": "2 more fields"
},
{
"_more_items": 18
}
]
}
}
}Cet exemple JSON compact provient de la dernière vérification réussie de V1.
{
"success": true,
"status": "ok",
"pagination": {
"cursor": "QVFB...",
"has_more": true
},
"search_context": {
"tag": "Top",
"query": "Python code"
},
"data": {
"data": {
"search_by_raw_query": {
"search_timeline": {
"timeline": {
"instructions": [
"…"
],
"responseObjects": {
"feedbackActions": "…"
}
}
}
}
}
}
}Utilisez cette documentation comme premier point de décision, puis vérifiez les prix, la couverture de la plateforme et les règles d'intégration avant de connecter l'endpoint pour un usage récurrent.
Utilisez ces réponses pour décider si cette méthode d'API convient à votre flux, à votre choix de version et à votre plan de déploiement.
La méthode exécute « Publications par requête » pour Recherche. L'exemple de réponse compact ci-dessous montre la structure exacte des champs.
Choisissez V2 pour les nouvelles intégrations, car elle fournit une structure normalisée. N'utilisez V1 que pour la compatibilité avec des clients qui traitent déjà le format natif de la plateforme.
Créez une clé API, envoyez-la dans l'en-tête de la requête et renseignez les paramètres obligatoires du tableau. Les exemples de code contiennent déjà le bon chemin et la bonne structure de requête.