Use Myntra Fashion Catalog Finder by Category & Brand with Python

Search Myntra's fashion catalog by keyword, category, or brand, or fetch specific products, for MRP, price, discount, ratings, sizes, colors, and category detail.

1. Choose the data you need

Review the published README for supported collection modes, examples, and limits. The recipe below uses the current published input definition.

2. Prepare a source-based input

This JSON contains published prefills and required-field defaults. Review every value for your task before running it; it is not a promise of successful collection.

{
  "brands": [],
  "categories": [],
  "containsKeyword": "",
  "gender": "",
  "includeDetails": true,
  "includeReviews": false,
  "maxItems": 2,
  "maxPrice": 0,
  "maxReviewsPerProduct": 1,
  "minDiscount": 0,
  "minPrice": 0,
  "minRating": 0,
  "mode": "search",
  "productIds": [],
  "proxyConfiguration": {},
  "searchQueries": [
    "tshirts"
  ],
  "sortBy": "",
  "splitLargeSearches": false,
  "startUrls": []
}

Download input.example.json and save your reviewed copy as input.json.

Field	Type	Required	Description
`mode`	string	optional	What to fetch. Each mode has its own input list below.
`searchQueries`	array	optional	One or more keyword searches (mode=search), e.g. `tshirts`, `printed kurtas`, `nike running shoes`. Each query is fetched separately and duplicates are removed.
`categories`	array	optional	One or more category listings (mode=browseByCategory).
`brands`	array	optional	One or more brands to browse (mode=browseByBrand), e.g. `nike`, `levis`, `tommy hilfiger`. Spaces and punctuation are normalized automatically.
`startUrls`	array	optional	Myntra listing, search, category, brand, or product URLs (mode=byUrl). Product URLs are fetched as products; everything else is fetched as a listing.
`productIds`	array	optional	Numeric Myntra product IDs or product URLs (mode=byProductIds), e.g. `36674095`.
`gender`	string	optional	Restrict listing results to one gender segment. Applied on Myntra's side.
`sortBy`	string	optional	How Myntra orders listing results.
`minPrice`	integer	optional	Only products whose selling price is at least this amount. 0 means no minimum.
`maxPrice`	integer	optional	Only products whose selling price is at most this amount. 0 means no maximum.
`minDiscount`	integer	optional	Only products discounted by at least this percentage. 0 means no minimum.
`minRating`	number	optional	Only products rated at least this value (0-5). Products without a rating are excluded when this is above 0.
`containsKeyword`	string	optional	Only products whose name contains this keyword (case-insensitive). Leave empty for all products.
`includeDetails`	boolean	optional	Open each product page to add sellers, addresses, per-size stock and measurements, specifications, rating breakdown, policies, videos, and tags. Slower but much richer. URL and product-ID modes always fetch details.
`includeReviews`	boolean	optional	Emit one row per written review with recordType `review`, in addition to product rows.
`maxReviewsPerProduct`	integer	optional	Review rows to fetch for each product when written reviews are enabled (1-2000).
`maxItems`	integer	optional	Total product rows to save across all queries, categories, brands, and URLs (1-10000). Review rows are additional.
`splitLargeSearches`	boolean	optional	Go past the per-filter result cap by fetching gender, price-band, and sort slices, then removing duplicates. Recommended for deep exports.
`proxyConfiguration`	object	optional	Optional override. Leave untouched and the actor selects a working connection automatically.

3. Start an Actor run

Set APIFY_TOKEN in your environment. Python 3.10 or newer is sufficient; this recipe uses no third-party packages.

Execution may incur charges. Review current pricing on Apify. The request asks for a 120-second timeout and a charge limit; these settings are subject to Apify’s pricing and do not guarantee an all-inclusive spending cap.

import json
import os
import urllib.request

# Save the schema-derived example as input.json; review and edit it first.
with open("input.json", encoding="utf-8") as stream:
    actor_input = json.load(stream)

token = os.environ["APIFY_TOKEN"]
request = urllib.request.Request(
    "https://api.apify.com/v2/acts/VF1ZCnsosUQJo2e7b/runs?timeout=120&maxTotalChargeUsd=0.50",
    data=json.dumps(actor_input).encode("utf-8"),
    headers={"Authorization": "Bearer " + token, "Content-Type": "application/json"},
    method="POST",
)
# This starts a potentially billable run. Do not automatically retry this POST.
with urllib.request.urlopen(request, timeout=40) as response:
    run = json.load(response)["data"]
print("Run ID:", run["id"])
print("Status:", run["status"])
# Inspect and download results in Apify Console once the run succeeds.

4. Inspect the actual results

Open the run in Apify Console and wait for a successful completion. Use the published output schema to locate results and the dataset schema to understand declared views. Missing or optional record fields must not be treated as guaranteed values.

Myntra products with prices, discounts, coupons, ratings, sellers, per-size stock, specifications, policies, media, and optional written-review rows.

Questions before you run

Which inputs are required?

No top-level fields are marked required in the published schema. Conditional requirements can still apply; check the README.

What does this guide verify?

The fields, prefills, and schema links are rendered from the published build. This is a usage recipe, not a paid live extraction test. Source availability and collection results can vary.

What if the run request times out?

Check Apify Console before retrying. The first request may already have created a run. Do not automatically repeat a run-creation POST.

Open on Apify Full Actor reference

Generated from source build 1mGy2E6jqPmXqgRby and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.