We extract airline reviews, credit card sign-up bonuses, route updates, and community comments from One Mile at a Time. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Articles & News objects from onemileatatime.com. All fields typed and schema-versioned.
"article_id": "post-149281", "url": "https://onemileatatime.com/news/qatar-airways-qsuite-next-gen/", "title": "Qatar Airways Unveils Qsuite Next Gen", "author": "Ben Schlappig", "publish_date": "2024-07-22T08:14:00Z", "category": "Aviation News", "comment_count": 142
| # | article_id | url | title | author | publish_date | update_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Flight & Hotel Reviews objects from onemileatatime.com. All fields typed and schema-versioned.
"review_id": "rev-84921", "airline_hotel_name": "Qatar Airways", "cabin_class": "Business Class", "aircraft_type": "Boeing 777-300ER", "rating_overall": 4.8, "flight_number": "QR 84", "route": "JFK-DOH"
| # | review_id | url | title | airline_hotel_name | cabin_class | aircraft_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Credit Card Offers objects from onemileatatime.com. All fields typed and schema-versioned.
"card_name": "Chase Sapphire Preferred", "issuer": "Chase", "annual_fee": 95, "signup_bonus": 60000, "bonus_currency": "Ultimate Rewards", "minimum_spend": 4000, "earning_rates": "3x Dining, 2x Travel"
| # | card_name | issuer | card_type | annual_fee | signup_bonus | bonus_currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Comment Threads objects from onemileatatime.com. All fields typed and schema-versioned.
"comment_id": "comm-992814", "article_id": "post-149281", "author_name": "FrequentFlyer99", "comment_date": "2024-07-22T09:30:12Z", "comment_text": "Will these be retrofitted on the A350s as well?", "is_author_reply": false, "upvotes": 14
| # | comment_id | article_id | parent_comment_id | author_name | comment_date | comment_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Loyalty Programs objects from onemileatatime.com. All fields typed and schema-versioned.
"program_name": "Aeroplan", "airline_alliance": "Star Alliance", "point_valuation": 0.015, "transfer_partners": "['Chase', 'Amex', 'Capital One']", "transfer_ratios": "1:1", "elite_tiers": "['25K', '35K', '50K', '75K', 'Super Elite']", "source_url": "https://onemileatatime.com/guides/air-canada-aeroplan/"
| # | program_name | airline_alliance | point_valuation | transfer_partners | transfer_ratios | elite_tiers |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our scraper handles every layer of the publication: article archives, credit card offer tables, dynamic comment threads, and affiliate link resolution, with anti-bot circumvention built in.
Extract historical archives dating back to 2008. Capture titles, author attributions, publication dates, and full HTML body text.
Monitor changes in sign-up bonuses, minimum spend requirements, and annual fees across all featured credit card reviews.
Extract cabin class, aircraft type, flight numbers, routes, and specific ratings for seat, food, and service from flight reviews.
Reconstruct nested discussions and author replies. Capture reader sentiment, questions, and community data points.
Trace outbound credit card links through redirect chains to identify final issuer destinations and offer codes.
Structured extraction of new flight routes, frequency changes, and aircraft retirements mentioned in news articles.
Track changes in point valuations, transfer ratios, and elite status qualification requirements as published by the authors.
Map articles to specific airlines, alliances, and hotel chains using the site's internal taxonomy.
Run continuous pipelines at hourly or daily cadences to capture breaking aviation news and limited-time credit card offers.
Brief in. Clean data out.
Provide category URLs, specific article lists, or historical date ranges. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and Cloudflare bypass for onemileatatime.com.
Schema validation, null-rate checks, and comment hierarchy verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
High-traffic travel blogs deploy aggressive bot protection. Here is how we stay resilient and deliver clean data.
One Mile at a Time uses Cloudflare to block automated traffic. Our crawlers use residential ISP proxies with realistic browser fingerprints and automated Turnstile solving to maintain access without triggering blocks.
Comment threads are loaded dynamically via JavaScript as users scroll. We run full Playwright browser sessions to trigger lazy-loading and capture the complete discussion hierarchy.
Flight reviews contain structured data buried in unstructured text. We use custom regex and DOM parsing rules to extract flight numbers, aircraft types, and sub-category ratings consistently.
Credit card application links use complex redirect chains for affiliate tracking. Our pipeline follows these chains to the final issuer URL, capturing the exact offer code and landing page.
We maintain a hash index of last-seen values for credit card tables and point valuations. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Airlines monitor premium cabin reviews and community sentiment to benchmark their hard and soft products against competitors.
Issuers track competitor sign-up bonuses, minimum spend requirements, and affiliate placements across top travel media.
Analysts track devaluation trends, transfer bonus histories, and elite status changes across major airline and hotel programs.
Data teams perform NLP analysis on reader comments to gauge consumer reaction to route cuts, dynamic pricing, and loyalty changes.
Aviation analysts aggregate global route announcements and frequency changes to map shifting network strategies.
Machine learning teams use high-quality flight and hotel reviews to train recommendation engines and travel planning models.
"One Mile at a Time holds the internet's most detailed archive of premium cabin reviews and credit card loyalty strategies. Extracting it requires navigating aggressive bot protection."
Aviation data moves fast. Credit card offers change overnight, and route announcements generate immediate community reaction. DataFlirt builds resilient pipelines that bypass Cloudflare, execute JavaScript for dynamic comments, and deliver structured JSON so your team can focus on analysis rather than infrastructure maintenance.
Everything supported by our onemileatatime.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright manages JavaScript rendering and Cloudflare challenges.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions for complex redirect chains.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About onemileatatime.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public articles, comments, and offers. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and automated solvers to bypass Turnstile challenges without manual intervention.
Yes. We can traverse the site's pagination and sitemaps to extract the complete historical archive dating back to 2008.
Yes. Our pipeline captures the parent-child relationship of comments, author attribution, timestamps, and upvote metrics.
Yes. We run scheduled pipelines to monitor specific credit card review pages, detecting changes in sign-up bonuses and minimum spend requirements.
Pipelines can be configured to run hourly for breaking aviation news, or daily for comprehensive sweeps of new comments and updated reviews.
Yes. We can deliver the clean structured JSON alongside the raw HTML payload for your own downstream processing or NLP tasks.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a historical archive of flight reviews or a daily feed of credit card offers, we scope, build, and operate the pipeline. Tell us what you need.
