Pricing
$30.00/month + usage
π« All-in-One Reddit.com Scraper β¬πͺπ¦π©π¨π§π₯π«
0.0 (0)
Pricing
$30.00/month + usage
10
237
20
Issues response
11 hours
Last modified
14 days ago
You can access the Reddit Explorer 3.0 programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, youβll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.2", "x-build-id": "U75hsRrc7I4dFnhhq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jupri~reddit/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jupri-reddit", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jupri~reddit/runs": { "post": { "operationId": "runs-sync-jupri-reddit", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jupri~reddit/run-sync": { "post": { "operationId": "run-sync-jupri-reddit", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "query": { "title": "β Query", "type": "array", "description": "π‘ <b> Query, Search Terms or URL", "items": { "type": "string" } }, "filters.mode": { "title": "π Mode", "enum": [ "posts", "communities", "comments", "media", "people" ], "type": "string", "description": "π‘ Search Products" }, "limit": { "title": "βΎοΈ Limit", "type": "integer", "description": "π‘ Number of results (per query)" }, "filters.types": { "title": "π Post Types", "type": "array", "description": "π‘ For <b>posts</b> search <i><code>(mode=posts)</code></i>", "items": { "type": "string", "enum": [ "text", "image", "video", "gif", "link", "poll" ], "enumTitles": [ "Text", "Image", "Video", "GIF", "Link", "Poll" ] } }, "filters.sort": { "title": "πΆ Sorting", "enum": [ "RELEVANCE", "HOT", "NEW", "TOP", "COMMENTS", "CONTROVERSIAL" ], "type": "string", "description": "" }, "filters.timing": { "title": "π Timing", "enum": [ "all", "year", "month", "week", "day", "hour" ], "type": "string", "description": "" }, "filters.safe": { "title": "Exclude", "type": "boolean", "description": "π‘ Exclude NSFW contents" }, "filters.title": { "title": "π·οΈ Title", "type": "string", "description": "π‘ The submission title" }, "filters.text": { "title": "π Text", "type": "string", "description": "π‘ The body of the post" }, "filters.author": { "title": "βοΈ Author", "type": "string", "description": "π‘ The user(s) who submitted the post, separated by space, without /u prefix<br><b>example:</b> <code>\"elonmusk billgates\"</code>" }, "filters.subreddit": { "title": "π¬ Subreddit", "type": "string", "description": "π‘ The submission's subreddit(s) separated by space, without /r prefix<br><b>example:</b> <code>\"Python JavaScript\"</code>" }, "filters.flair": { "title": "βοΈ Flair", "type": "string", "description": "π‘ The text of the link flair(s) on the post<br><b>example:</b> <code>\"webscraping\"</code>" }, "filters.site": { "title": "π Site", "type": "string", "description": "π‘ The domain(s) of the submitted URL<br><b>example:</b> <code>\"youtube.com\"</code>" }, "filters.url": { "title": "π URL", "type": "string", "description": "π‘ The submission's URL (the website's address)" }, "dev_custom_headers": { "title": "π HTTP HEADERS", "type": "array", "description": "π‘ Additional HTTP Headers", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_custom_cookies": { "title": "π° HTTP COOKIES", "type": "array", "description": "π‘ Additional HTTP Cookies", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_transform_fields": { "title": "β»οΈ CUSTOM FIELD", "type": "array", "description": "π‘ <b>Transform the resulting output. Select only needed fields.</b><br><br>For nested object use <b>DOT</b>. For example: <pre>address.streetAddress</pre><br>For nested array use <b>NUMBER</b> <i>(index of array element starting from index=0)</i>. For example: <pre>images.0.url</pre>", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_dataset_name": { "title": "π CUSTOM STORAGE", "type": "string", "description": "π‘ <b>Save results into custom named Dataset, use mask to customize dataset name</b><br><br><code>{ACTOR} = actor name<br>{DATE} = date (YYYYMMDD)<br>{TIME} = time (HHMMSS)</code><br><br>This masks can be used to autogenerate Dataset Name.<br><br>example: <i><code>data-{DATE}</code></i><br>Depending on today date the dataset name will be: <code>data-20230603</code><i><br><br>default: <code>data-{ACTOR}-{DATE}-{TIME}</code></i>" }, "dev_dataset_clear": { "title": "Clear Storage", "type": "boolean", "description": "Clear Dataset before insert/update." }, "dev_no_strip": { "title": "Disable data cleansing", "type": "boolean", "description": "π‘ Keep/Save empty values <i><code>(NULL, FALSE, empty ARRAY, empty OBJECT, empty STRING)</code></i>" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } }}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 Reddit Explorer 3.0 from the options below:
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