
Twitter Posts Scraper
2 hours trial then $5.00/month - No credit card required now

Twitter Posts Scraper
2 hours trial then $5.00/month - No credit card required now
The **Twitter Posts Scraper** extracts detailed information from any public Twitter post. Simply provide the URL, and the scraper will gather data like post text, user info, engagement metrics, and more. Perfect for analyzing trends and tracking social media interactions.
Actor Metrics
15 Monthly users
No reviews yet
3 bookmarks
69% runs succeeded
26 days response time
Created in Jul 2024
Modified a month ago
You can access the Twitter Posts Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1{
2 "openapi": "3.0.1",
3 "info": {
4 "version": "0.0",
5 "x-build-id": "npW58hH7Ul4g00ldH"
6 },
7 "servers": [
8 {
9 "url": "https://api.apify.com/v2"
10 }
11 ],
12 "paths": {
13 "/acts/pratikdani~twitter-posts-scraper/run-sync-get-dataset-items": {
14 "post": {
15 "operationId": "run-sync-get-dataset-items-pratikdani-twitter-posts-scraper",
16 "x-openai-isConsequential": false,
17 "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
18 "tags": [
19 "Run Actor"
20 ],
21 "requestBody": {
22 "required": true,
23 "content": {
24 "application/json": {
25 "schema": {
26 "$ref": "#/components/schemas/inputSchema"
27 }
28 }
29 }
30 },
31 "parameters": [
32 {
33 "name": "token",
34 "in": "query",
35 "required": true,
36 "schema": {
37 "type": "string"
38 },
39 "description": "Enter your Apify token here"
40 }
41 ],
42 "responses": {
43 "200": {
44 "description": "OK"
45 }
46 }
47 }
48 },
49 "/acts/pratikdani~twitter-posts-scraper/runs": {
50 "post": {
51 "operationId": "runs-sync-pratikdani-twitter-posts-scraper",
52 "x-openai-isConsequential": false,
53 "summary": "Executes an Actor and returns information about the initiated run in response.",
54 "tags": [
55 "Run Actor"
56 ],
57 "requestBody": {
58 "required": true,
59 "content": {
60 "application/json": {
61 "schema": {
62 "$ref": "#/components/schemas/inputSchema"
63 }
64 }
65 }
66 },
67 "parameters": [
68 {
69 "name": "token",
70 "in": "query",
71 "required": true,
72 "schema": {
73 "type": "string"
74 },
75 "description": "Enter your Apify token here"
76 }
77 ],
78 "responses": {
79 "200": {
80 "description": "OK",
81 "content": {
82 "application/json": {
83 "schema": {
84 "$ref": "#/components/schemas/runsResponseSchema"
85 }
86 }
87 }
88 }
89 }
90 }
91 },
92 "/acts/pratikdani~twitter-posts-scraper/run-sync": {
93 "post": {
94 "operationId": "run-sync-pratikdani-twitter-posts-scraper",
95 "x-openai-isConsequential": false,
96 "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
97 "tags": [
98 "Run Actor"
99 ],
100 "requestBody": {
101 "required": true,
102 "content": {
103 "application/json": {
104 "schema": {
105 "$ref": "#/components/schemas/inputSchema"
106 }
107 }
108 }
109 },
110 "parameters": [
111 {
112 "name": "token",
113 "in": "query",
114 "required": true,
115 "schema": {
116 "type": "string"
117 },
118 "description": "Enter your Apify token here"
119 }
120 ],
121 "responses": {
122 "200": {
123 "description": "OK"
124 }
125 }
126 }
127 }
128 },
129 "components": {
130 "schemas": {
131 "inputSchema": {
132 "type": "object",
133 "required": [
134 "url"
135 ],
136 "properties": {
137 "url": {
138 "title": "Twitter Post URL",
139 "type": "string",
140 "description": "URL of the Twitter post to scrape"
141 }
142 }
143 },
144 "runsResponseSchema": {
145 "type": "object",
146 "properties": {
147 "data": {
148 "type": "object",
149 "properties": {
150 "id": {
151 "type": "string"
152 },
153 "actId": {
154 "type": "string"
155 },
156 "userId": {
157 "type": "string"
158 },
159 "startedAt": {
160 "type": "string",
161 "format": "date-time",
162 "example": "2025-01-08T00:00:00.000Z"
163 },
164 "finishedAt": {
165 "type": "string",
166 "format": "date-time",
167 "example": "2025-01-08T00:00:00.000Z"
168 },
169 "status": {
170 "type": "string",
171 "example": "READY"
172 },
173 "meta": {
174 "type": "object",
175 "properties": {
176 "origin": {
177 "type": "string",
178 "example": "API"
179 },
180 "userAgent": {
181 "type": "string"
182 }
183 }
184 },
185 "stats": {
186 "type": "object",
187 "properties": {
188 "inputBodyLen": {
189 "type": "integer",
190 "example": 2000
191 },
192 "rebootCount": {
193 "type": "integer",
194 "example": 0
195 },
196 "restartCount": {
197 "type": "integer",
198 "example": 0
199 },
200 "resurrectCount": {
201 "type": "integer",
202 "example": 0
203 },
204 "computeUnits": {
205 "type": "integer",
206 "example": 0
207 }
208 }
209 },
210 "options": {
211 "type": "object",
212 "properties": {
213 "build": {
214 "type": "string",
215 "example": "latest"
216 },
217 "timeoutSecs": {
218 "type": "integer",
219 "example": 300
220 },
221 "memoryMbytes": {
222 "type": "integer",
223 "example": 1024
224 },
225 "diskMbytes": {
226 "type": "integer",
227 "example": 2048
228 }
229 }
230 },
231 "buildId": {
232 "type": "string"
233 },
234 "defaultKeyValueStoreId": {
235 "type": "string"
236 },
237 "defaultDatasetId": {
238 "type": "string"
239 },
240 "defaultRequestQueueId": {
241 "type": "string"
242 },
243 "buildNumber": {
244 "type": "string",
245 "example": "1.0.0"
246 },
247 "containerUrl": {
248 "type": "string"
249 },
250 "usage": {
251 "type": "object",
252 "properties": {
253 "ACTOR_COMPUTE_UNITS": {
254 "type": "integer",
255 "example": 0
256 },
257 "DATASET_READS": {
258 "type": "integer",
259 "example": 0
260 },
261 "DATASET_WRITES": {
262 "type": "integer",
263 "example": 0
264 },
265 "KEY_VALUE_STORE_READS": {
266 "type": "integer",
267 "example": 0
268 },
269 "KEY_VALUE_STORE_WRITES": {
270 "type": "integer",
271 "example": 1
272 },
273 "KEY_VALUE_STORE_LISTS": {
274 "type": "integer",
275 "example": 0
276 },
277 "REQUEST_QUEUE_READS": {
278 "type": "integer",
279 "example": 0
280 },
281 "REQUEST_QUEUE_WRITES": {
282 "type": "integer",
283 "example": 0
284 },
285 "DATA_TRANSFER_INTERNAL_GBYTES": {
286 "type": "integer",
287 "example": 0
288 },
289 "DATA_TRANSFER_EXTERNAL_GBYTES": {
290 "type": "integer",
291 "example": 0
292 },
293 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
294 "type": "integer",
295 "example": 0
296 },
297 "PROXY_SERPS": {
298 "type": "integer",
299 "example": 0
300 }
301 }
302 },
303 "usageTotalUsd": {
304 "type": "number",
305 "example": 0.00005
306 },
307 "usageUsd": {
308 "type": "object",
309 "properties": {
310 "ACTOR_COMPUTE_UNITS": {
311 "type": "integer",
312 "example": 0
313 },
314 "DATASET_READS": {
315 "type": "integer",
316 "example": 0
317 },
318 "DATASET_WRITES": {
319 "type": "integer",
320 "example": 0
321 },
322 "KEY_VALUE_STORE_READS": {
323 "type": "integer",
324 "example": 0
325 },
326 "KEY_VALUE_STORE_WRITES": {
327 "type": "number",
328 "example": 0.00005
329 },
330 "KEY_VALUE_STORE_LISTS": {
331 "type": "integer",
332 "example": 0
333 },
334 "REQUEST_QUEUE_READS": {
335 "type": "integer",
336 "example": 0
337 },
338 "REQUEST_QUEUE_WRITES": {
339 "type": "integer",
340 "example": 0
341 },
342 "DATA_TRANSFER_INTERNAL_GBYTES": {
343 "type": "integer",
344 "example": 0
345 },
346 "DATA_TRANSFER_EXTERNAL_GBYTES": {
347 "type": "integer",
348 "example": 0
349 },
350 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
351 "type": "integer",
352 "example": 0
353 },
354 "PROXY_SERPS": {
355 "type": "integer",
356 "example": 0
357 }
358 }
359 }
360 }
361 }
362 }
363 }
364 }
365 }
366}
Twitter Posts Scraper OpenAPI definition
OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Twitter Posts Scraper from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: