Tweet Scraper is a fast, cost-efficient solution for collecting public Twitter (X) data at scale. It enables reliable tweet scraping with advanced filters, helping analysts, marketers, and developers turn live conversations into actionable insights.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for tweet-scraper-0-1-1k-tweets-pay-per-result-no-rate-limits you've just found your team — Let’s Chat. 👆👆
Tweet Scraper collects structured Twitter (X) data such as tweets, authors, and engagement metrics based on URLs, search queries, or conversation IDs. It removes the complexity and cost barriers of large-scale Twitter scraping while maintaining speed, accuracy, and flexibility. This project is built for data teams, growth marketers, researchers, and developers who need dependable access to Twitter data.
- Supports keyword, URL, and conversation-based tweet discovery
- Enables precise time-range filtering for historical analysis
- Extracts rich engagement and author metadata
- Designed for scalable, high-throughput data workflows
| Feature | Description |
|---|---|
| URL-based scraping | Extract tweets directly from specific tweet or profile URLs. |
| Advanced search queries | Collect tweets using custom search operators and keywords. |
| Time range filtering | Fetch tweets before or after a specific UTC datetime. |
| Engagement filters | Filter results by minimum likes, retweets, or replies. |
| Media filters | Limit results to images, videos, quotes, or replies only. |
| User qualification | Restrict results to verified or premium users. |
| Structured output | Clean, analysis-ready JSON format for downstream systems. |
| Field Name | Field Description |
|---|---|
| id | Unique identifier of the tweet. |
| url | Direct URL to the tweet on X. |
| text | Full text content of the tweet. |
| createdAt | Tweet creation timestamp (UTC). |
| lang | Language code of the tweet. |
| retweetCount | Number of retweets. |
| replyCount | Number of replies. |
| likeCount | Number of likes. |
| quoteCount | Number of quotes. |
| viewCount | Total views count. |
| author | Detailed information about the tweet author. |
| conversationId | Identifier for the related tweet thread. |
[
{
"type": "tweet",
"id": "1896710161546506732",
"url": "https://x.com/themainsquid1/status/1896710161546506732",
"text": "@SOLAXYTOKEN We shall see",
"retweetCount": 0,
"replyCount": 1,
"likeCount": 0,
"quoteCount": 2,
"viewCount": 35,
"createdAt": "Mon Mar 03 23:51:56 +0000 2025",
"lang": "en",
"isReply": true,
"conversationId": "1895950135865327920",
"author": {
"userName": "themainsquid1",
"isVerified": false,
"followers": 79,
"following": 54
}
}
]
Tweet Scraper|$0.1/1K Tweets | Pay-Per Result |No Rate Limits )/
├── src/
│ ├── main.py
│ ├── search/
│ │ ├── query_builder.py
│ │ └── filters.py
│ ├── parsers/
│ │ ├── tweet_parser.py
│ │ └── user_parser.py
│ ├── utils/
│ │ ├── time_utils.py
│ │ └── validation.py
│ └── exporters/
│ └── json_exporter.py
├── data/
│ ├── sample_input.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- Marketing teams use it to track keyword mentions, so they can monitor brand sentiment in real time.
- Crypto and finance analysts use it to follow conversations and influencers, enabling faster market insights.
- Researchers use it to collect large tweet datasets, supporting social and behavioral analysis.
- Growth hackers use it to analyze competitor engagement, improving campaign strategies.
- Developers use it to feed live Twitter data into dashboards, bots, or AI pipelines.
Can I scrape tweets from a specific time period? Yes, you can define precise start and end UTC timestamps to collect tweets only within a chosen timeframe.
Does it support advanced Twitter search operators? Absolutely. You can use operators like from:, since:, until:, and filters for replies or media.
Is media-only tweet extraction supported? Yes, tweets can be filtered to include only images, videos, quotes, or replies.
What output format does the scraper provide? All results are delivered in structured JSON, ready for analytics, storage, or automation workflows.
Primary Metric: Processes thousands of tweets per minute under standard search conditions.
Reliability Metric: Maintains a success rate above 99% for valid queries and URLs.
Efficiency Metric: Optimized request handling ensures low overhead even during high-volume runs.
Quality Metric: Extracted datasets consistently include complete tweet, author, and engagement fields.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
|
"Exceptional results, clear communication, and flawless delivery. Syed
|