CoinGecko - Data Extraction

https://api.coingecko.com/api/v3 - no API key needed for free tier. Pure JSON REST API, no browser required.

Do this first

Use the API directly with http_get - no browser, no parsing, fully structured JSON.

import json
data = json.loads(http_get("https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd"))
print(data['bitcoin']['usd'])   # 76286

Rate limit is tight: ~3 calls per minute on the free tier. The API returns HTTP 429 with Retry-After: 60 when you exceed it. Always add time.sleep(5) between calls in a loop. Confirmed: rapid-fire calls hit 429 on call 3-4 with no delay; with 5s gaps you stay safe.

Rate limits (confirmed live)

• Free tier: ~3 calls/minute per IP (no API key)
• 429 response: includes Retry-After: 60 header - wait 60 seconds before retrying
• Coin ID lookup (/coins/list) counts against the limit - call it once and cache
• /ping still counts - don't use it as a keep-alive

import time, urllib.error, json
 
def safe_get(url, retries=2):
    for attempt in range(retries + 1):
        try:
            return json.loads(http_get(url))
        except urllib.error.HTTPError as e:
            if e.code == 429 and attempt < retries:
                print(f"Rate limited, sleeping 65s...")
                time.sleep(65)
            else:
                raise

Coin ID vs symbol - critical distinction

IDs are kebab-case strings, not ticker symbols. The API ignores symbols entirely.

• Unknown or wrong IDs return an empty {} dict - no error, no warning
• Symbols are not unique: 17+ coins share the symbol sol (bridged versions, wrapped, etc.)
• Use /coins/list to resolve symbol → id, or just know the canonical id

# Resolve symbol to id
coins_list = json.loads(http_get("https://api.coingecko.com/api/v3/coins/list"))
# 17,564 entries as of April 2026
# Each: {'id': 'bitcoin', 'symbol': 'btc', 'name': 'Bitcoin'}
sol_coins = [c for c in coins_list if c['symbol'].lower() == 'sol']
# Returns 5+ entries — pick by name to get the real Solana: id='solana'

Common workflows

Simple price (one or many coins)

import json
data = json.loads(http_get(
    "https://api.coingecko.com/api/v3/simple/price"
    "?ids=bitcoin,ethereum,solana"
    "&vs_currencies=usd,eur"
    "&include_market_cap=true"
    "&include_24hr_change=true"
))
for coin, info in data.items():
    print(f"{coin}: ${info['usd']:,.0f} | 24h: {info['usd_24h_change']:.1f}% | MCap: ${info['usd_market_cap']/1e9:.1f}B")
# bitcoin: $76,286 | 24h: 1.4% | MCap: $1528.0B
# ethereum: $2,361 | 24h: 0.8% | MCap: $284.9B
# solana: $87 | 24h: -1.0% | MCap: $50.2B

Response keys for each coin (when all flags enabled): usd, usd_market_cap, usd_24h_change, eur, eur_market_cap, eur_24h_change

Top coins by market cap (paginated)

import json
data = json.loads(http_get(
    "https://api.coingecko.com/api/v3/coins/markets"
    "?vs_currency=usd"
    "&order=market_cap_desc"
    "&per_page=10"       # max 250
    "&page=1"            # 1-indexed; page=2 gives ranks 11-20 etc.
    "&sparkline=false"
    "&price_change_percentage=1h,7d,30d"  # optional extra columns
))
for c in data:
    print(f"#{c['market_cap_rank']} {c['symbol'].upper()} ${c['current_price']:,.2f} | {c['price_change_percentage_24h']:.1f}%")
# #1 BTC $76,281.00 | 1.4%
# #2 ETH $2,360.45 | 0.8%

Full fields per entry: id, symbol, name, image, current_price, market_cap, market_cap_rank, fully_diluted_valuation, total_volume, high_24h, low_24h, price_change_24h, price_change_percentage_24h, market_cap_change_24h, market_cap_change_percentage_24h, circulating_supply, total_supply, max_supply, ath, ath_change_percentage, ath_date, atl, atl_change_percentage, atl_date, roi, last_updated

Extra columns added by price_change_percentage=1h,7d,30d: price_change_percentage_1h_in_currency, price_change_percentage_7d_in_currency, price_change_percentage_30d_in_currency

Pagination: use page=2, page=3, etc. with per_page up to 250. Results are 1-indexed - page 2 with per_page=5 returns ranks 6–10.

Coin detail (full metadata)

import json
data = json.loads(http_get(
    "https://api.coingecko.com/api/v3/coins/bitcoin"
    "?localization=false"    # skip 40+ language translations
    "&tickers=false"         # skip exchange ticker list (can be huge)
    "&market_data=true"
    "&community_data=false"
    "&developer_data=false"
))
print(data['name'])                                    # Bitcoin
print(data['symbol'])                                  # btc
print(data['market_cap_rank'])                         # 1
print(data['market_data']['current_price']['usd'])     # 76279
print(data['market_data']['ath']['usd'])               # 126080
print(data['market_data']['ath_date']['usd'])          # 2025-10-06T18:57:42.558Z
print(data['market_data']['circulating_supply'])       # 20017459.0
print(data['description']['en'][:200])

Top-level keys: id, symbol, name, web_slug, asset_platform_id, platforms, categories, description, links, image, genesis_date, sentiment_votes_up_percentage, market_cap_rank, market_data, last_updated

market_data sub-keys include: current_price, ath, ath_change_percentage, ath_date, atl, atl_change_percentage, atl_date, market_cap, fully_diluted_valuation, total_volume, high_24h, low_24h, price_change_percentage_24h, price_change_percentage_7d, price_change_percentage_14d, price_change_percentage_30d, price_change_percentage_60d, price_change_percentage_200d, price_change_percentage_1y, circulating_supply, total_supply, max_supply

All price/market fields are objects keyed by currency code: data['market_data']['current_price']['usd'], ['eur'], ['btc'], etc.

Historical OHLCV

import json
# OHLCV candles: granularity auto-determined by `days`
# 1d = 30-min candles, 7d = 4-hr candles, 14d+ = daily candles
data = json.loads(http_get(
    "https://api.coingecko.com/api/v3/coins/ethereum/ohlc?vs_currency=usd&days=7"
))
print(len(data))         # 42 candles for 7-day window
print(data[-1])          # [1776499200000, 2407.32, 2412.96, 2402.21, 2405.03]
#                         [timestamp_ms,   open,    high,    low,     close]
 
# Convert timestamp:
import datetime
ts_ms = data[-1][0]
dt = datetime.datetime.fromtimestamp(ts_ms / 1000, tz=datetime.timezone.utc)

days options: 1, 7, 14, 30, 90, 180, 365, max

Market chart (price + volume + market cap time series)

import json
# interval='daily' gives one point per day; omit for auto (hourly for <=90 days)
chart = json.loads(http_get(
    "https://api.coingecko.com/api/v3/coins/bitcoin/market_chart"
    "?vs_currency=usd&days=7&interval=daily"
))
# Keys: 'prices', 'market_caps', 'total_volumes'
# Each is a list of [timestamp_ms, value]
print(len(chart['prices']))           # 8 points for 7-day daily
print(chart['prices'][-1])            # [1776508393000, 76286.699...]
print(chart['total_volumes'][-1])     # [1776508393000, 80459560788.47...]

Market chart by date range

import json, time
now = int(time.time())
thirty_days_ago = now - 30 * 86400
chart = json.loads(http_get(
    f"https://api.coingecko.com/api/v3/coins/bitcoin/market_chart/range"
    f"?vs_currency=usd&from={thirty_days_ago}&to={now}"
))
# Granularity: <1 day → minutely, 1-90 days → hourly, >90 days → daily
print(len(chart['prices']))    # 174 points for 7-day range (hourly)

Search

import json
results = json.loads(http_get("https://api.coingecko.com/api/v3/search?query=solana"))
# Top-level keys: 'coins', 'exchanges', 'icos', 'categories', 'nfts'
for c in results['coins'][:3]:
    print(f"{c['id']} | {c['symbol']} | rank {c['market_cap_rank']}")
# solana | SOL | rank 7
# solana-name-service | SNS | rank 1902

Search returns coins ordered by relevance, not market cap. First result is usually the canonical coin.

Trending (top 7 searched in last 24h)

import json
trending = json.loads(http_get("https://api.coingecko.com/api/v3/search/trending"))
# Top-level keys: 'coins', 'nfts', 'categories'
for item in trending['coins']:
    c = item['item']
    print(f"{c['name']} ({c['symbol']}) #{c['market_cap_rank']}")
# Item keys: id, coin_id, name, symbol, market_cap_rank, thumb, small, large,
#            slug, price_btc, score, data

data sub-object includes sparkline image URL, price/volume/market cap info if available.

Global market overview

import json
global_data = json.loads(http_get("https://api.coingecko.com/api/v3/global"))
gd = global_data['data']
print(f"Total market cap: ${gd['total_market_cap']['usd']/1e12:.2f}T")   # $2.66T
print(f"24h volume: ${gd['total_volume']['usd']/1e9:.1f}B")              # $156.6B
print(f"BTC dominance: {gd['market_cap_percentage']['btc']:.1f}%")       # 57.3%
print(f"Active coins: {gd['active_cryptocurrencies']}")                   # 17,564
print(f"Active exchanges: {gd['markets']}")                               # 1,475

Coin categories (market cap by sector)

import json
cats = json.loads(http_get(
    "https://api.coingecko.com/api/v3/coins/categories?order=market_cap_desc"
))
# 691 categories as of April 2026
for cat in cats[:5]:
    print(f"{cat['name']}: ${cat['market_cap']/1e9:.1f}B | 24h: {cat['market_cap_change_24h']:.1f}%")
# Smart Contract Platform: $2204.8B | 24h: 0.9%
# Layer 1 (L1): $2171.5B | 24h: 1.1%
 
# Category keys: id, name, market_cap, market_cap_change_24h, content,
#                top_3_coins_id, top_3_coins, volume_24h, updated_at

Token price by contract address (ERC-20 and other chains)

import json
# Platform IDs: ethereum, binance-smart-chain, polygon-pos, avalanche, solana, etc.
token = json.loads(http_get(
    "https://api.coingecko.com/api/v3/simple/token_price/ethereum"
    "?contract_addresses=0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48"  # USDC
    "&vs_currencies=usd"
))
print(token)
# {'0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48': {'usd': 0.999861}}
# Key is the lowercased contract address

vs_currencies options

63 currencies supported (confirmed live). Common ones:

Fiat: usd, eur, gbp, jpy, aud, cad, chf, cny, inr, krw, brl, mxn, sgd, hkd, nok, sek, dkk, nzd, zar, thb, try, aed, sar, myr, php, idr, pln, czk, huf, ron

Crypto: btc, eth, ltc, bch, bnb, eos, xrp, xlm, link, dot, yfi, sol

Commodities: xag (silver), xau (gold)

Get the full list:

currencies = json.loads(http_get("https://api.coingecko.com/api/v3/simple/supported_vs_currencies"))
# Returns list of 63 strings

Endpoints that require Pro API (return HTTP 401)

• /coins/{id}/history?date=DD-MM-YYYY - historical price on a specific date
• /coins/markets with category= filter (the parameter is silently ignored, not 401)
• /coins/{id}/contract/{address} - full contract token details

Free tier alternatives:

• For historical price on date: use /market_chart/range with a narrow time window
• For category filtering: fetch /coins/markets unfiltered and filter client-side using id from /coins/categories

Ping / health check

import json
ping = json.loads(http_get("https://api.coingecko.com/api/v3/ping"))
print(ping)   # {'gecko_says': '(V3) To the Moon!'}

Note: ping still counts against the rate limit. Don't use it to check if a 429 has resolved - just wait 65 seconds and retry your actual call.

Gotchas

• Rate limit is much stricter than advertised - The official docs say "30 calls/min" but in practice you get 429 on call 3-4 with no delay between calls. Observed Retry-After: 60 in the response header. Treat it as "3 calls/minute, wait 65s on 429." Using time.sleep(5) between calls in a loop is safe.

• Unknown coin IDs return {}, not an error - ?ids=BTC (uppercase) and ?ids=not_a_real_coin both return an empty dict {}. Always check that the key you expect exists before accessing it.

• Symbol lookup requires /coins/list + client-side filter - There's no "get by symbol" endpoint. Multiple coins share any given symbol. After fetching the list (17,564 entries), filter by symbol and pick by name.

• Coin ID casing matters - IDs are always lowercase kebab-case: bitcoin, ethereum, shiba-inu. Uppercase or camelCase will silently return {}.

• OHLCV granularity is automatic - The days parameter determines candle size automatically: 1 → 30-min candles, 7/14 → 4-hr candles, 30+ → daily candles. You cannot override this on the free tier.

• interval=daily in market_chart affects point count - Without interval=daily, a 7-day window returns hourly data (~168 points). With it, you get ~8 points. Choose based on whether you need resolution or summary.

• market_chart timestamps are in milliseconds - Divide by 1000 for standard Unix time: datetime.fromtimestamp(ts / 1000).

• /coins/list is expensive (rate-limit-wise) - It returns 17,564 entries and costs one API call. Fetch once, store in a variable, filter locally. Don't call it in a loop.

• Pagination is 1-indexed - page=1 returns items 1–N, page=2 returns N+1–2N. page=0 returns the same as page=1 (it doesn't error).

• per_page max is 250 - Requesting more than 250 per page silently returns 250. To get the full top-500, make two calls: page=1&per_page=250 then page=2&per_page=250.

• Contract address keys are lowercased - When using /simple/token_price, the response key is the lowercased contract address regardless of what case you sent. Always call .lower() before using addresses as dict keys.

• tickers=false is important for /coins/{id} - Without it, the response includes a massive list of exchange tickers that can make the payload very large and slow to parse. Always set tickers=false unless you specifically need exchange data.

• ETH priced against BTC is supported - vs_currencies=btc works: ethereum returns {'btc': 0.03095861}. Crypto-to-crypto pairs work the same as fiat pairs.

scraping.md · updated Apr 28, 2026 · 1,667 words