# Reddit Comments Scraper - Low-cost💲🔥🌐🧠 (`delectable_incubator/reddit-comments-scraper-low-cost`) Actor

Search and scrape Reddit comments with ease! 💬 Collect comment text, authors 👤, scores ⬆️, subreddits 📌, timestamps 🕒, URLs 🔗, awards 🏆, replies 💭 & more. Perfect for 📊 market research, 💡 sentiment analysis, 📈 trend discovery, 🕵️ competitor insights, brand monitoring & audience research.

- **URL**: https://apify.com/delectable\_incubator/reddit-comments-scraper-low-cost.md
- **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community)
- **Categories:** Social media, Automation, Videos
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.00005 / actor start

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

<p align="center">
  <img src="https://i.ibb.co/jkNS73wX/readme.png" alt="Reddit Comments Scraper" width="100%">
</p>

---

## 💬📥 Reddit Comments Scraper | Bulk Reddit Comment Scraper | Apify Actor

### 🚀 Extract Reddit Comments in Seconds (No Code)

The **Reddit Comments Scraper** is a powerful, scalable and SEO-optimized Apify Actor built to extract **Reddit comments in bulk** from keyword searches.

Collect thousands of comments across Reddit, analyze public opinion, monitor discussions, build AI datasets, perform sentiment analysis, or automate social listening with clean, structured data.

Perfect for researchers, marketers, AI engineers, agencies, startups and data analysts.

---

## 🔥 Why Choose This Reddit Comments Scraper?

✔ Best Reddit Comments Scraper on Apify

✔ Supports **Bulk Keyword Scraping**

✔ Supports **Bulk Reddit URL Scraping**

✔ Multiple sorting options

✔ Time filtering

✔ Fast & scalable extraction engine

✔ Structured JSON / CSV / Excel output

✔ Perfect for AI datasets & sentiment analysis

✔ No coding required

✔ No proxy required

---

## 🎯 What This Scraper Does

This Apify Actor extracts Reddit comments from keyword searches or Reddit URLs.

#### 📌 Core Features

✅ Scrape Reddit comments

✅ Bulk keyword scraping (multi-search)

✅ Bulk Reddit URL scraping

✅ Time filtering (hour, day, week, month, year, all)

✅ Sort by relevance

✅ Sort by top

✅ Sort by new

✅ Sort by controversial

✅ Automatic pagination

✅ Extract comment text

✅ Extract author

✅ Extract score

✅ Extract timestamps

✅ Extract subreddit

✅ Extract parent IDs

✅ Extract original post information

✅ High-speed extraction engine

---

## ⚡ Input Configuration

### 🔥 BULK KEYWORD MODE

````

{
"keywords": \[
"chatgpt",
"artificial intelligence",
"tesla",
"bitcoin",
"football",
"python"
],
"time": "month",
"sort": "top",
"max\_items": 500
}

```


---

## 📊 Extracted Comment Data

| Field | Description |
|--------|-------------|
| comment_id | Reddit comment ID |
| post_id | Parent Reddit post ID |
| post_title | Reddit post title |
| subreddit_id | Subreddit ID |
| subreddit_name | Subreddit name |
| text | Comment text |
| timestamp | UTC timestamp |
| parent_id | Parent comment or post |
| score | Comment score |
| author | Reddit username |

---

## 💡 Use Cases

This Reddit Comments Scraper is ideal for:

🧠 Sentiment analysis

📊 Market research

📢 Brand monitoring

📈 Trend analysis

🤖 AI training datasets

💬 Opinion mining

🛡️ Toxicity detection

🏢 Competitive intelligence

📡 Social listening

⚙️ Automation workflows

---

## 🚀 Key Features

⚡ Bulk keyword scraping

🌍 Bulk Reddit URL scraping

📊 Multi-search support

🧠 Clean structured datasets

📈 Sentiment-ready output

📌 Smart pagination

🔁 Auto retry system

⚡ High-speed scraping engine

💾 Export-ready datasets

☁️ Scalable Apify cloud execution

---

## 📤 Output Formats

✔ JSON

✔ CSV

✔ Excel (XLSX)

✔ XML

✔ HTML

---

## 📦 Example Output

```

{
"comment\_id": "t1\_nealob9",
"post\_id": "t3\_1nhbvn6",
"post\_title": "AITA for not wanting my 4 year old daughter to join a soccer team...",
"subreddit\_id": "t5\_2xhvq",
"subreddit\_name": "AmItheAsshole",
"text": "If the in-laws think soccer is so important, they can volunteer...",
"timestamp": "2025-09-15T04:01:00.032000+0000",
"parent\_id": "t3\_1nhbvn6",
"score": 24049,
"author": "swiftiebookworm22"
}

````

---

## 📊 Built-in Views

✔ Overview

✔ Top Scored Comments

✔ By Subreddit

✔ By Author

✔ By Keyword

✔ Recent Comments

All datasets are fully exportable to JSON, CSV and Excel.

---

## 🔥 Why This is One of the Best Reddit Comment Scrapers on Apify?

✔ Optimized for Apify Marketplace SEO

✔ Bulk keyword support

✔ Bulk Reddit URL support

✔ High-performance scraping engine

✔ Structured datasets

✔ Enterprise-ready

✔ Reliable pagination

✔ Excellent for AI, NLP and market intelligence

✔ Built for researchers, agencies, developers and businesses

---

## 💸 Pricing

This scraper runs on a **pay-per-result pricing model**.

You only pay for successfully extracted records.

💳 **Price:** $2.69 / 1,000 results

---

## ❓ FAQ

#### Can I scrape multiple keywords?

Yes. Bulk keyword mode is fully supported.

#### Can I scrape multiple Reddit URLs?

Yes. Bulk URL mode is fully supported.

#### Does it support pagination?

Yes. Pagination is handled automatically.

#### Can I filter by time?

Yes.

Supported filters include:

- hour
- day
- week
- month
- year
- all

#### Can I sort the results?

Yes.

Supported sorting:

- relevance
- top
- new
- controversial

#### Can I export the data?

Yes.

Supported formats include JSON, CSV, Excel, XML and HTML.

#### Is coding required?

No.

This is a fully no-code Apify Actor.

---

## ⚠️ Disclaimer

This project is an independent data extraction tool and is not affiliated with, endorsed by, or associated with Reddit.

---

## 🔗 Related Actors

More PrimeScrape scrapers are coming soon.

🚀 Reddit Intelligence

🚀 Social Media Scrapers

🚀 Product Intelligence

🚀 Company Intelligence

🚀 AI Dataset Builders

---

## 🌍 PrimeScrape Ecosystem

Built for large-scale data extraction, automation, AI datasets and market intelligence.

💬 Social media intelligence

📊 Market research

🤖 AI datasets

📈 Trend analysis

⚙️ Automation pipelines

☁️ Cloud scraping

---

## 📬 Support

⭐⭐⭐⭐⭐

If you enjoy this actor, please leave a 5-star review.

📩 Need a custom scraper or enterprise solution?

Contact us through Apify.

# Actor input Schema

## `keywords` (type: `array`):

One or more keywords to search for on Reddit. Each keyword is scraped separately.
## `time` (type: `string`):

Select the time period for the search results
## `sort` (type: `string`):

Select how to sort the search results
## `maxitems` (type: `integer`):

Limits how many posts will be scraped from Reddit per keyword

## Actor input object example

```json
{
  "keywords": [
    "soccer"
  ],
  "time": "year",
  "sort": "relevance",
  "maxitems": 80
}
````

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "soccer"
    ],
    "time": "year",
    "sort": "relevance",
    "maxitems": 80
};

// Run the Actor and wait for it to finish
const run = await client.actor("delectable_incubator/reddit-comments-scraper-low-cost").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keywords": ["soccer"],
    "time": "year",
    "sort": "relevance",
    "maxitems": 80,
}

# Run the Actor and wait for it to finish
run = client.actor("delectable_incubator/reddit-comments-scraper-low-cost").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "keywords": [
    "soccer"
  ],
  "time": "year",
  "sort": "relevance",
  "maxitems": 80
}' |
apify call delectable_incubator/reddit-comments-scraper-low-cost --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=delectable_incubator/reddit-comments-scraper-low-cost",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Reddit Comments Scraper - Low-cost💲🔥🌐🧠",
        "description": "Search and scrape Reddit comments with ease! 💬 Collect comment text, authors 👤, scores ⬆️, subreddits 📌, timestamps 🕒, URLs 🔗, awards 🏆, replies 💭 & more. Perfect for 📊 market research, 💡 sentiment analysis, 📈 trend discovery, 🕵️ competitor insights, brand monitoring & audience research.",
        "version": "0.0",
        "x-build-id": "aJq7OsOZJpyJy8EqW"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/delectable_incubator~reddit-comments-scraper-low-cost/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-delectable_incubator-reddit-comments-scraper-low-cost",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/delectable_incubator~reddit-comments-scraper-low-cost/runs": {
            "post": {
                "operationId": "runs-sync-delectable_incubator-reddit-comments-scraper-low-cost",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/delectable_incubator~reddit-comments-scraper-low-cost/run-sync": {
            "post": {
                "operationId": "run-sync-delectable_incubator-reddit-comments-scraper-low-cost",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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",
                "required": [
                    "keywords",
                    "time",
                    "sort",
                    "maxitems"
                ],
                "properties": {
                    "keywords": {
                        "title": "Search Keywords 🔍",
                        "type": "array",
                        "description": "One or more keywords to search for on Reddit. Each keyword is scraped separately.",
                        "default": [
                            "soccer"
                        ],
                        "items": {
                            "type": "string"
                        }
                    },
                    "time": {
                        "title": "Time Period ⏰",
                        "enum": [
                            "all",
                            "hour",
                            "day",
                            "week",
                            "month",
                            "year"
                        ],
                        "type": "string",
                        "description": "Select the time period for the search results",
                        "default": "year"
                    },
                    "sort": {
                        "title": "Sort By 📊",
                        "enum": [
                            "relevance",
                            "hot",
                            "top",
                            "new",
                            "comments"
                        ],
                        "type": "string",
                        "description": "Select how to sort the search results",
                        "default": "relevance"
                    },
                    "maxitems": {
                        "title": "Maximum number of posts to scrape 💬",
                        "type": "integer",
                        "description": "Limits how many posts will be scraped from Reddit per keyword",
                        "default": 80
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```