
Log Scanner
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Log Scanner
No credit card required
Log scanner helps you to find particular text in your log files. It can scan [Apify](https://apify.com/) runs, tasks, or actors but also arbitrary text files. If you ever had a problem finding that one error in a thousand runs, this is a tool to use.
Actor Metrics
1 monthly user
No reviews yet
3 bookmarks
84% runs succeeded
Created in Oct 2020
Modified a year ago
You can access the Log Scanner 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": "8evKeizU6o9ymr7S0"
6 },
7 "servers": [
8 {
9 "url": "https://api.apify.com/v2"
10 }
11 ],
12 "paths": {
13 "/acts/lukaskrivka~log-scanner/run-sync-get-dataset-items": {
14 "post": {
15 "operationId": "run-sync-get-dataset-items-lukaskrivka-log-scanner",
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 "$ref": "#/components/schemas/inputSchema"
27 }
28 }
29 }
30 },
31 "parameters": [
32 {
33 "name": "token",
34 "in": "query",
35 "required": true,
36 "schema": {
37 "type": "string"
38 },
39 "description": "Enter your Apify token here"
40 }
41 ],
42 "responses": {
43 "200": {
44 "description": "OK"
45 }
46 }
47 }
48 },
49 "/acts/lukaskrivka~log-scanner/runs": {
50 "post": {
51 "operationId": "runs-sync-lukaskrivka-log-scanner",
52 "x-openai-isConsequential": false,
53 "summary": "Executes an Actor and returns information about the initiated run in response.",
54 "tags": [
55 "Run Actor"
56 ],
57 "requestBody": {
58 "required": true,
59 "content": {
60 "application/json": {
61 "schema": {
62 "$ref": "#/components/schemas/inputSchema"
63 }
64 }
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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"
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86 }
87 }
88 }
89 }
90 }
91 },
92 "/acts/lukaskrivka~log-scanner/run-sync": {
93 "post": {
94 "operationId": "run-sync-lukaskrivka-log-scanner",
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": {
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102 "content": {
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106 }
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112 "name": "token",
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114 "required": true,
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117 },
118 "description": "Enter your Apify token here"
119 }
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123 "description": "OK"
124 }
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126 }
127 }
128 },
129 "components": {
130 "schemas": {
131 "inputSchema": {
132 "type": "object",
133 "properties": {
134 "runIdsOrUrls": {
135 "title": "Rud IDs (or text file ULRs)",
136 "type": "array",
137 "description": "List of runs to check. Also can be URLs to any text files.",
138 "items": {
139 "type": "string"
140 }
141 },
142 "regexes": {
143 "title": "Matching regexes",
144 "type": "array",
145 "description": "List of regexes to match on each line of the text. Can be in plain string format (Error) or in regex format that allows regex flags (/error/i)",
146 "items": {
147 "type": "string"
148 }
149 },
150 "actorOrTaskId": {
151 "title": "Actor or task ID",
152 "type": "string",
153 "description": "Actor or task ID"
154 },
155 "dateFrom": {
156 "title": "Date from",
157 "type": "string",
158 "description": "Optional date to limit from which date the run will be scanned. The date should be in ISO standard (e.g. 2020-10-01)"
159 },
160 "dateTo": {
161 "title": "Date to",
162 "type": "string",
163 "description": "Optional date to limit to which date the run will be scanned. The date should be in ISO standard (e.g. 2020-10-15)"
164 }
165 }
166 },
167 "runsResponseSchema": {
168 "type": "object",
169 "properties": {
170 "data": {
171 "type": "object",
172 "properties": {
173 "id": {
174 "type": "string"
175 },
176 "actId": {
177 "type": "string"
178 },
179 "userId": {
180 "type": "string"
181 },
182 "startedAt": {
183 "type": "string",
184 "format": "date-time",
185 "example": "2025-01-08T00:00:00.000Z"
186 },
187 "finishedAt": {
188 "type": "string",
189 "format": "date-time",
190 "example": "2025-01-08T00:00:00.000Z"
191 },
192 "status": {
193 "type": "string",
194 "example": "READY"
195 },
196 "meta": {
197 "type": "object",
198 "properties": {
199 "origin": {
200 "type": "string",
201 "example": "API"
202 },
203 "userAgent": {
204 "type": "string"
205 }
206 }
207 },
208 "stats": {
209 "type": "object",
210 "properties": {
211 "inputBodyLen": {
212 "type": "integer",
213 "example": 2000
214 },
215 "rebootCount": {
216 "type": "integer",
217 "example": 0
218 },
219 "restartCount": {
220 "type": "integer",
221 "example": 0
222 },
223 "resurrectCount": {
224 "type": "integer",
225 "example": 0
226 },
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228 "type": "integer",
229 "example": 0
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231 }
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233 "options": {
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235 "properties": {
236 "build": {
237 "type": "string",
238 "example": "latest"
239 },
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241 "type": "integer",
242 "example": 300
243 },
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245 "type": "integer",
246 "example": 1024
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248 "diskMbytes": {
249 "type": "integer",
250 "example": 2048
251 }
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254 "buildId": {
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256 },
257 "defaultKeyValueStoreId": {
258 "type": "string"
259 },
260 "defaultDatasetId": {
261 "type": "string"
262 },
263 "defaultRequestQueueId": {
264 "type": "string"
265 },
266 "buildNumber": {
267 "type": "string",
268 "example": "1.0.0"
269 },
270 "containerUrl": {
271 "type": "string"
272 },
273 "usage": {
274 "type": "object",
275 "properties": {
276 "ACTOR_COMPUTE_UNITS": {
277 "type": "integer",
278 "example": 0
279 },
280 "DATASET_READS": {
281 "type": "integer",
282 "example": 0
283 },
284 "DATASET_WRITES": {
285 "type": "integer",
286 "example": 0
287 },
288 "KEY_VALUE_STORE_READS": {
289 "type": "integer",
290 "example": 0
291 },
292 "KEY_VALUE_STORE_WRITES": {
293 "type": "integer",
294 "example": 1
295 },
296 "KEY_VALUE_STORE_LISTS": {
297 "type": "integer",
298 "example": 0
299 },
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302 "example": 0
303 },
304 "REQUEST_QUEUE_WRITES": {
305 "type": "integer",
306 "example": 0
307 },
308 "DATA_TRANSFER_INTERNAL_GBYTES": {
309 "type": "integer",
310 "example": 0
311 },
312 "DATA_TRANSFER_EXTERNAL_GBYTES": {
313 "type": "integer",
314 "example": 0
315 },
316 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
317 "type": "integer",
318 "example": 0
319 },
320 "PROXY_SERPS": {
321 "type": "integer",
322 "example": 0
323 }
324 }
325 },
326 "usageTotalUsd": {
327 "type": "number",
328 "example": 0.00005
329 },
330 "usageUsd": {
331 "type": "object",
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340 },
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343 "example": 0
344 },
345 "KEY_VALUE_STORE_READS": {
346 "type": "integer",
347 "example": 0
348 },
349 "KEY_VALUE_STORE_WRITES": {
350 "type": "number",
351 "example": 0.00005
352 },
353 "KEY_VALUE_STORE_LISTS": {
354 "type": "integer",
355 "example": 0
356 },
357 "REQUEST_QUEUE_READS": {
358 "type": "integer",
359 "example": 0
360 },
361 "REQUEST_QUEUE_WRITES": {
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363 "example": 0
364 },
365 "DATA_TRANSFER_INTERNAL_GBYTES": {
366 "type": "integer",
367 "example": 0
368 },
369 "DATA_TRANSFER_EXTERNAL_GBYTES": {
370 "type": "integer",
371 "example": 0
372 },
373 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
374 "type": "integer",
375 "example": 0
376 },
377 "PROXY_SERPS": {
378 "type": "integer",
379 "example": 0
380 }
381 }
382 }
383 }
384 }
385 }
386 }
387 }
388 }
389}
Log Scanner 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 Log Scanner 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: