Instagram Comments Scraper
Under maintenance
Try for free
1 day trial then $5.00/month - No credit card required now
Go to Store
This Actor is under maintenance.
This Actor may be unreliable while under maintenance. Would you like to try a similar Actor instead?
See alternative ActorsInstagram Comments Scraper
pratikdani/instagram-comments-scraper
Try for free
1 day trial then $5.00/month - No credit card required now
The Instagram Comments Scraper is a tool designed to extract detailed comments from valid Instagram posts and reels. This actor provides a structured way to gather insights from user interactions on Instagram, making it easier to analyze engagement and sentiment.
You can access the Instagram Comments Scraper programmatically from your own applications by using the Apify API. You can choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1{
2 "openapi": "3.0.1",
3 "info": {
4 "version": "0.0",
5 "x-build-id": "H0z5KgB8kh3f8LBSp"
6 },
7 "servers": [
8 {
9 "url": "https://api.apify.com/v2"
10 }
11 ],
12 "paths": {
13 "/acts/pratikdani~instagram-comments-scraper/run-sync-get-dataset-items": {
14 "post": {
15 "operationId": "run-sync-get-dataset-items-pratikdani-instagram-comments-scraper",
16 "x-openai-isConsequential": false,
17 "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
18 "tags": [
19 "Run Actor"
20 ],
21 "requestBody": {
22 "required": true,
23 "content": {
24 "application/json": {
25 "schema": {
26 "$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~instagram-comments-scraper/runs": {
50 "post": {
51 "operationId": "runs-sync-pratikdani-instagram-comments-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~instagram-comments-scraper/run-sync": {
93 "post": {
94 "operationId": "run-sync-pratikdani-instagram-comments-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": "Instagram Posts/Reels Url",
139 "type": "string",
140 "description": "URL of the Instagram Post/Reel"
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}Instagram Comments 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 Instagram Comments 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:
Developer
Pratik DaniMaintained by Community
Actor Metrics
22 monthly users
-
2 bookmarks
97% runs succeeded
Created in Jan 2025
Modified 17 days ago
Categories
