PriceCharting Python API & Scraper — Historical Sales, PSA/BGS Graded Comps & Game Valuations

A production-ready Python client, CLI utility, and market analytics suite for extracting comprehensive pricing data, historical sales time-series, PSA/BGS/CGC/TAG/ACE graded comps, POP reports, and 1600px high-resolution images from PriceCharting via the Apify Actor: incognito_mode/pricecharting-product-scraper.

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🎯 Why This Exists: The Problem with the Official API

Feature	Official PriceCharting API	This Scraper / Wrapper
Monthly Subscription	$49.00 / month minimum	$0 / month (Apify free tier covers hundreds of items)
Price History Time Series	❌ Omitted (today's price only)	✅ Full historical time series per condition
High-Res Images	❌ Omitted	✅ Full 1600px photos (box, manual, card front/back)
Complete Grading Ladder	❌ Basic tiers only	✅ Every grade: TAG 10, ACE 10, CGC Pristine, BGS Black Label
Sold Comps & POP Reports	❌ Omitted	✅ eBay/TCGPlayer sold listings & PSA/CGC POP report
Failed Lookup Billing	⚠️ Billed against monthly quota	✅ Zero cost on failed/missing lookups

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🚀 Quickstart (Python)

1. Installation

git clone https://github.com/arman-007/pricecharting-api-python.git
cd pricecharting-api-python
pip install -r requirements.txt

2. Extract Data in 4 Lines of Code

import os
from apify_client import ApifyClient

client = ApifyClient(os.getenv("APIFY_API_TOKEN"))

run_input = {
    "products": [
        "https://www.pricecharting.com/game/pokemon-base-set/charizard-4",
        "https://www.pricecharting.com/game/gameboy-advance/pokemon-emerald",
        "7141" # Direct numeric product ID
    ],
    "scrapeDetails": True,
    "includeRecentSales": False
}

run = client.actor("incognito_mode/pricecharting-product-scraper").call(run_input=run_input)
dataset_items = list(client.dataset(run["defaultDatasetId"]).iterate_items())

for item in dataset_items:
    print(f"{item['productName']}: Loose=${item['prices']['loose']} | PSA 10=${item['prices']['manualOnly']}")

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📊 Google Sheets Live Integration (Zero Code)

No Python knowledge required. You can stream live PriceCharting market valuations directly into Google Sheets:

=IMPORTDATA("https://api.apify.com/v2/datasets/<DATASET_ID>/items?format=csv")

Whenever the actor executes its scheduled run, your spreadsheet recalculates automatically.

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🏷️ Price Slot Mapping Reference

PriceCharting maps 6 unified columns across all categories. This wrapper normalizes them into stable keys:

JSON Key	Video Games	Trading Cards (Pokémon / MTG / Sports)
prices.loose	Loose (cartridge / disc)	Ungraded (Raw NM)
prices.cib	Complete in Box	Grade 7
prices.new	Factory Sealed	Grade 8
prices.graded	Graded Sunk Box	Grade 9
prices.boxOnly	Box Only	Grade 9.5
prices.manualOnly	Manual Only	PSA 10 Gem Mint

For company-specific grades (BGS 10 Black Label, CGC 10 Pristine, TAG 10, ACE 10, SGC 10), use the fullPrices object where labels are delivered verbatim.

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📈 Jupyter Notebook Market Analytics

A pre-built analytics notebook is available under notebooks/pricecharting_market_analysis.ipynb:

1. Grading Multiplier Calculation:

   multiplier = psa10_price / raw_price

   Automates profitability analysis before submitting raw cards to PSA/CGC.
2. Sum-of-Parts Video Game Assembly: Calculates whether buying Loose + Box + Manual separately is cheaper than purchasing an assembled CIB copy.
3. Time-Series Charting: Visualizes multi-year appreciation curves for high-demand collectibles.

Run the notebook:

jupyter notebook notebooks/pricecharting_market_analysis.ipynb

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💻 CLI Usage

The repository includes a ready-to-run CLI tool:

# 1. Run offline against bundled samples (no API token required)
python extract_prices.py --sample charizard_base_set --spread

# 2. Extract live data by URL or numeric ID
python extract_prices.py --products https://www.pricecharting.com/game/pokemon-base-set/charizard-4 6861 --output market_comps.csv

# 3. Compute PSA 10 grading arbitrage margins
python extract_prices.py --sample charizard_base_set --spread

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📦 Output JSON Schema Sample

{
  "productId": 630417,
  "productName": "Charizard #4",
  "consoleName": "Pokemon Base Set",
  "category": "pokemon-cards",
  "url": "https://www.pricecharting.com/game/pokemon-base-set/charizard-4",
  "releaseDate": "January 9, 1999",
  "imageUrl": "https://storage.googleapis.com/images.pricecharting.com/hpgpcpsd42huitud/1600.jpg",
  "images": [
    "https://storage.googleapis.com/images.pricecharting.com/hpgpcpsd42huitud/1600.jpg",
    "https://storage.googleapis.com/images.pricecharting.com/kmwn5qjyipwzbuwm/1600.jpg"
  ],
  "prices": {
    "loose": 338.42,
    "cib": 749.50,
    "new": 1199.03,
    "graded": 3175.04,
    "boxOnly": 3403.50,
    "manualOnly": 30085.73
  },
  "fullPrices": {
    "Ungraded": 338.42,
    "PSA 10": 30085.73,
    "BGS 10": 39111.00,
    "BGS 10 Black": 195555.00,
    "CGC 10 Pristine": 27475.00
  },
  "salesVolume": {
    "Ungraded": 48,
    "PSA 10": 30
  },
  "priceHistory": {
    "used": [
      { "date": "2024-01-01", "price": 295.00 },
      { "date": "2026-01-01", "price": 338.42 }
    ],
    "manualOnly": [
      { "date": "2024-01-01", "price": 24500.00 },
      { "date": "2026-01-01", "price": 30085.73 }
    ]
  }
}

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🔗 Related Resources & Deep-Dives

• Apify Actor: PriceCharting Product Scraper
• Technical Guide (Hashnode): Extracting PriceCharting Market Data: Historical Sales, Graded Comps & Game Valuations into JSON
• Substack Deep-Dive: Extracting PriceCharting Market Data
• Twitter / X Discussion: @armanirfan007 Thread on Historical Comps & PSA Arbitrage

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📄 License

Distributed under the MIT License. See LICENSE for more details.

Author: Arman Hosen