We extract medicine catalogues, pricing signals, lab test packages, and alternative drug mappings from PharmEasy. 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 Medicine Catalogue objects from pharmeasy.in. All fields typed and schema-versioned.
"medicine_id": "MED123", "name": "Dolo 650mg Tablet", "brand": "Micro Labs Ltd", "mrp": 30.91, "sale_price": 26.27, "discount_pct": 15, "stock_status": "IN_STOCK", "prescription_required": false, "packaging": "Strip of 15 tablets"
| # | medicine_id | name | brand | manufacturer | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Lab Tests objects from pharmeasy.in. All fields typed and schema-versioned.
"test_id": "LAB456", "name": "Comprehensive Full Body Checkup", "lab_name": "Thyrocare", "mrp": 2999, "price": 1499, "discount_pct": 50, "turnaround_time": "24-48 hours", "fasting_required": true, "sample_type": "Blood"
| # | test_id | name | lab_name | category | preparation | sample_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Alternative Medicines objects from pharmeasy.in. All fields typed and schema-versioned.
"primary_medicine_id": "MED123", "primary_name": "Dolo 650mg Tablet", "substitute_id": "MED789", "substitute_name": "Paracip 650 Tablet", "substitute_brand": "Cipla Ltd", "substitute_mrp": 28.5, "price_difference_pct": -7.8, "active_ingredients": "['Paracetamol (650mg)']"
| # | primary_medicine_id | primary_name | substitute_id | substitute_name | substitute_brand | substitute_mrp |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Healthcare OTC objects from pharmeasy.in. All fields typed and schema-versioned.
"product_id": "OTC987", "title": "Accu-Chek Active Blood Glucose Test Strips", "brand": "Accu-Chek", "category": "Devices", "mrp": 1049, "price": 923, "rating": 4.5, "review_count": 1248, "stock_status": "IN_STOCK"
| # | product_id | title | brand | category | sub_category | mrp |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from pharmeasy.in. All fields typed and schema-versioned.
"product_id": "MED123", "pin_code": "560001", "mrp": 30.91, "sale_price": 26.27, "discount_pct": 15, "bank_offers": "HDFC 10% off", "coupon_code": "FLAT15", "timestamp": "2026-05-12T09:14:00Z"
| # | product_id | pin_code | mrp | sale_price | discount_abs | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our PharmEasy pipeline handles location-based rendering, rate limits, and complex medical schemas to deliver clean, normalised healthcare data ready for analysis.
Extract full active ingredient lists, manufacturer details, packaging types, and usage instructions for prescription and OTC drugs.
Bypass default location prompts to scrape accurate availability, pricing, and delivery estimates for specific Indian pin codes.
Extract substitute medicines and calculate price differentials for identical pharmacological compositions.
Capture diagnostic package details, individual parameter lists, fasting requirements, and turnaround times from partner labs.
Track MRP versus sale price, monitor discount percentages, and capture bank offers across different delivery zones.
Track out-of-stock statuses across regional pharmacy nodes to understand supply chain gaps.
Extract bank offers, wallet cashbacks, and applicable promo codes visible on product pages.
Scrape healthcare devices, supplements, and personal care products including user ratings and review counts.
Run daily pipelines that only output changed prices or stock statuses, reducing compute and storage bloat.
Brief in. Clean data out.
Provide target categories, specific pin codes, or medicine IDs. We design the schema together.
We configure Scrapy crawlers, handle location cookies, and manage residential proxy rotation for Indian IPs.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting healthcare data requires precise location simulation and schema handling. Here is how our infrastructure manages the complexity.
PharmEasy alters pricing and availability based on the user's location. We inject specific pin code cookies and headers into every request session to simulate exact geographic delivery zones.
Aggressive crawling triggers IP bans. We route requests through a pool of thousands of Indian residential ISP proxies, rotating per request to maintain high throughput without detection.
Prescription drugs, OTC products, and lab tests have entirely different DOM structures. Our parsers use distinct logic branches for each category, ensuring high data completion rates.
Where possible, we bypass HTML parsing entirely by intercepting the JSON payloads from PharmEasy's internal APIs, resulting in faster extraction and cleaner data.
Instead of dumping the full catalogue daily, our pipeline calculates hashes for price and stock fields, emitting only the records that have changed since the previous run.
Pharmacies and e-health aggregators track competitor pricing, discount strategies, and bank offers to optimise their own margins.
Health insurers map standard medicine MRPs and diagnostic test costs to validate claims and prevent overbilling.
Drug manufacturers monitor brand visibility, out-of-stock events, and regional distribution across major Indian pin codes.
Digital health platforms build their own drug databases using normalised catalogue data for prescription generation.
Researchers track generic versus branded drug price differentials and efficacy mappings.
Distributors monitor stock availability signals across regional nodes to optimise inventory allocation.
"PharmEasy holds the most comprehensive map of India's retail pharmacy pricing and diagnostic catalogues, but extracting it requires navigating aggressive location gating and rate limits."
Most engineering teams fail at healthcare scraping because pricing and availability change per pin code. You need distributed residential proxies, precise cookie management for location simulation, and a schema that handles both prescription drugs and OTC products. DataFlirt manages this infrastructure so you just query the data.
Everything supported by our pharmeasy.in scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Custom cookie injection and header manipulation to simulate multiple geographic pin codes simultaneously, ensuring accurate regional data.
We maintain pools of residential ISP proxies across India. Rotation happens per-request to bypass aggressive rate limits and regional blocks.
Pipelines run on AWS Lambda for high-frequency price tracking. Airflow handles scheduling, dependency management, and alerting.
Data delivered to where your team already works — no new tooling required.
About pharmeasy.in scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and catalogue data is generally permissible. DataFlirt targets only public, non-authenticated medicine, lab test, and pricing data. We strictly avoid extracting PII, patient records, or prescription uploads.
We simulate user locations by injecting specific pin code cookies and geographic headers into our crawler sessions. This allows us to extract exact pricing and availability for any target delivery zone in India.
Yes. Our pipeline extracts PharmEasy's alternative drug suggestions, including the substitute brand, active ingredients, and the calculated price difference percentage.
For targeted ASIN/medicine lists, we can run hourly pipelines. Full catalogue refreshes typically run on a daily or weekly cadence depending on your specific requirements.
Yes. We capture diagnostic package details, individual parameter lists, fasting requirements, sample types, and turnaround times from partner labs.
No. We only extract public catalogue data. Private consultation records and user prescription uploads are strictly out of scope.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off medicine database or continuous price tracking across 50 pin codes, we build and operate the pipeline.
