Get Doge (DOGE) - N/A Historical Prices using this API: retrieve daily OHLCV for 2026 analysis

Metals-API 8 min read
Get Doge (DOGE) - N/A Historical Prices using this API: retrieve daily OHLCV for 2026 analysis

You need reliable daily Doge (DOGE) history to backtest a strategy, draw a 2026 performance chart, or reconcile PnL. By the end of this guide you will retrieve DOGE historical daily prices (and daily OHLC candles) from Metals-API, transform the JSON into date/value pairs for analytics, and apply practical handling for UTC dates, caching, and non-trading-day edge cases.

What you’ll build and which endpoints you’ll use

We will pull:

Illustration: Get Doge (DOGE) - N/A Historical Prices using this API: retrieve daily OHLCV for 2026 analysis
  • Single-date historical quotes for DOGE (for point-in-time checks or reconciliations).
  • A daily time series across a 2026 date range (for charts and backtests).
  • Daily OHLC (open, high, low, close) for DOGE on a given date (for candle charts and day-level analytics).

Metals-API responses are base-USD by default. For currency-like symbols such as DOGE, you’ll typically see both: DOGE (DOGE per USD) and USDDOGE (USD per DOGE). That makes it trivial to price in either direction without extra math.

If you are new to Metals-API, scan the reference first: Metals-API Documentation, the full Metals-API Supported Symbols, and the MCP overview. You’ll need an API key; if you don’t have one, Register for free.

Single-date historical DOGE price: point-in-time retrieval

Use the Historical Rates endpoint by appending a date (YYYY-MM-DD). Query symbols DOGE and USDDOGE to get both directions (DOGE per USD and USD per DOGE) in one call. Base is USD by default.

curl example (copy/paste)

curl "https://metals-api.com/api/2026-10-14?access_key=YOUR_API_KEY&base=USD&symbols=DOGE,USDDOGE,USD"

Below is a real response example you can expect from Metals-API when requesting DOGE data. Use it to validate your parser and downstream transformations:

{"success":true,"timestamp":1791936660,"date":"2026-10-14","base":"USD","rates":{"DOGE":11.837121212121,"USD":1,"USDDOGE":0.08448000000000151}}

What these fields mean and how you’ll use them

  • success: Boolean indicating a valid response.
  • timestamp: Unix epoch seconds; align this to your system’s timezone logic (treat it as UTC when building candles or EOD snapshots).
  • date: The historical date you requested, as YYYY-MM-DD.
  • base: Base currency for the rates (USD). All numbers in rates are expressed relative to this base.
  • rates:
    • DOGE: Number of DOGE per 1 USD. For the sample, 1 USD ≈ 11.8371 DOGE.
    • USDDOGE: Reciprocal, USD per 1 DOGE. For the sample, 1 DOGE ≈ 0.08448 USD.
    • USD: Always 1 when base=USD; useful to sanity-check the base setting.

Practical tip: When building backtests that expect “price as USD per DOGE,” prefer the USDDOGE field directly. If you only pull DOGE, compute price as_usd = 1.0 / DOGE.

Daily DOGE time series for 2026

Use the Time-Series endpoint to retrieve daily DOGE data across a date range. For many analytics pipelines, you will want USDDOGE (USD per DOGE) for charting and dollar-denominated PnL.

curl example for a 2026 span

curl "https://metals-api.com/api/timeseries?access_key=YOUR_API_KEY&base=USD&start_date=2026-01-01&end_date=2026-12-31&symbols=DOGE,USDDOGE"

Python example: turn the series into (date, usd_per_doge)

import os
import requests
from datetime import date

API_KEY = os.getenv("METALS_API_KEY", "YOUR_API_KEY")

params = {
"access_key": API_KEY,
"base": "USD",
"start_date": "2026-01-01",
"end_date": "2026-12-31",
"symbols": "DOGE,USDDOGE"
}

resp = requests.get("https://metals-api.com/api/timeseries", params=params, timeout=30)
resp.raise_for_status()
data = resp.json()

if not data.get("success", False):
raise RuntimeError(f"API error: {data}")

# The response structure is:
# {
# "success": true,
# "timeseries": true,
# "start_date": "...",
# "end_date": "...",
# "base": "USD",
# "rates": {
# "YYYY-MM-DD": {"DOGE": <doge_per_usd>, "USDDOGE": <usd_per_doge>},
# ...
# }
# }
rates_by_day = data.get("rates", {})

# Build a clean list of (date, usd_per_doge) tuples for charting/backtests.
series = []
for d, symbols in sorted(rates_by_day.items()):
# Prefer direct USDDOGE if present; else invert DOGE.
usd_per_doge = None
if "USDDOGE" in symbols and symbols["USDDOGE"] not in (None, 0):
usd_per_doge = symbols["USDDOGE"]
elif "DOGE" in symbols and symbols["DOGE"]:
usd_per_doge = 1.0 / symbols["DOGE"]
else:
continue # skip days without a price

series.append((d, usd_per_doge))

# Example: print first 5 rows
for row in series[:5]:
print(row)

# Now 'series' can be loaded into pandas, plotted, or fed into a backtest engine.

Downstream tips:

  • Keep both directions in your store (DOGE and USDDOGE). It saves recomputation and rounding artifacts later.
  • Lock your analytics to UTC day boundaries to match API dates. Document your candle convention (e.g., “EOD at 00:00:00 UTC next day”).
  • Cache the time series locally (e.g., parquet or SQLite) to avoid repeated pulls when re-running notebooks or CI pipelines.

Daily DOGE OHLC for charting

For day-level candles, use the Open/High/Low/Close endpoint. Request a specific date to obtain that day’s OHLC data. For DOGE, price directionality follows the same convention as above (base=USD), so USDDOGE represents USD per DOGE. If you prefer DOGE per USD candles, request DOGE instead or invert values as needed for your chart library.

curl example for daily OHLC

curl "https://metals-api.com/api/open-high-low-close/2026-10-14?access_key=YOUR_API_KEY&base=USD&symbols=USDDOGE,DOGE"

Response fields you will map into your charting code:

  • For each symbol (DOGE or USDDOGE), the API returns:
    • open: price at the start of the day (UTC)
    • high: high price during the UTC day
    • low: low price during the UTC day
    • close: price at the end of the day (UTC)

Note: Volume (V) is not part of this endpoint. If you need OHLCV, you can compute V from your own order flow or a separate data source. Metals-API covers O/H/L/C for this use case.

Field mapping: build exactly what your analytics need

When working with DOGE in Metals-API:

  • Base is USD by default. Confirm base in each response (base = "USD").
  • DOGE: Number of DOGE per 1 USD (useful when pricing USD budgets in DOGE units).
  • USDDOGE: Number of USD per 1 DOGE (most charting and backtests prefer this direction).
  • Historical single-date: /YYYY-MM-DD returns a one-day snapshot with “rates”.
  • Time-series: /timeseries returns daily “rates” keyed by date.
  • OHLC: /open-high-low-close/YYYY-MM-DD returns O, H, L, C per symbol for that day (UTC).

Practical details that will save you time

  • Units and direction:
    • Metals typically use “per troy ounce.” For DOGE, treat values as currency-like quotes relative to USD.
    • Prefer USDDOGE when you need USD-denominated charts and PnL; it avoids repeated inversion.
  • Timezone and timestamps:
    • Timestamps are Unix epoch seconds; treat them as UTC for daily boundaries.
    • For daily analyses, align your resampling to UTC to prevent off-by-one-day errors in candles.
  • Weekends and holidays:
    • DOGE trades 24/7. Day-over-day series should not have traditional market-closure gaps, but always code defensively for days that may be missing due to maintenance or upstream issues.
    • Backfill missing dates with previous close if your model requires continuous daily inputs; document that choice.
  • Range limits and pagination:
    • Query the largest practical range your plan allows for initial backfills, then incrementally update by day.
    • If you hit range limits, chunk your requests by month or quarter. Refer to the Documentation for plan-specific constraints.
  • Caching and re-runs:
    • Cache daily JSON to disk or write normalized rows to a database to eliminate duplicate API calls in notebooks and CI.
    • Set a lightweight ETag or last-modified cache layer in your data service to avoid refetching unchanged days.
  • Validation and monitoring:
    • Assert base == "USD" in every response.
    • Assert reciprocal consistency within a tolerance: abs((1 / DOGE) - USDDOGE) < epsilon.
    • Alert on anomalous gaps or zero/None quotes before sending data to backtests.

Why DOGE on a metals API? A quick note on convergence and digital transformation

Commodity risk, currency risk, and digital assets continue to converge in pricing systems and analytics stacks. DOGE support in the same API you use for metals simplifies your integration surface: one base currency, one response schema, one permissioning model. That lets you apply the same observability, caching, and downstream pipelines to both materials and digital assets—useful in multi-asset research, treasury, or e-commerce price engines.

If you work across metal procurement, jewelry manufacturing, or fintech product pricing, this unified approach helps you model FX-like DOGE exposures next to copper or gold inputs without switching data providers. Explore how these ideas map to your pipelines on metals-api.com.

End-to-end example workflow for 2026 analysis

  • Backfill:
    • Call /timeseries for 2026-01-01 to 2026-12-31 with symbols=DOGE,USDDOGE.
    • Persist normalized rows: date (YYYY-MM-DD), usd_per_doge (USDDOGE), doge_per_usd (DOGE).
  • Daily candles:
    • For each date requiring candles, call /open-high-low-close/YYYY-MM-DD with symbols=USDDOGE.
    • Store O/H/L/C as floats, with date and base fields for auditing.
  • Reconciliation:
    • For a specific trade date, call /YYYY-MM-DD with symbols=USDDOGE to confirm your stored close and your PnL snapshot.
  • Incremental update:
    • Each UTC midnight, query the previous day’s data (or run an hourly job that only requests the minimal missing range).
    • Apply idempotent upserts keyed by (date, symbol).

Troubleshooting and data hygiene

  • Unexpected base or missing USDDOGE:
    • Explicitly pass base=USD and request both DOGE,USDDOGE whenever you need both directions.
    • If USDDOGE is missing on a given day, invert DOGE with appropriate floating-point tolerances.
  • Outliers:
    • Apply simple outlier z-scores or rolling median filters before feeding strategies; keep a raw vs. cleaned column for audit.
  • Downstream consistency:
    • Centralize symbol mapping for DOGE and USDDOGE so transformations don’t diverge across services.

Where to go next

  • Full parameter docs and additional endpoints (e.g., fluctuation) are in the Documentation.
  • Confirm availability and naming in the Supported Symbols list before automating.
  • If you need a quick conceptual primer on market connectivity, check metals-api.com or the MCP page.

FAQ

  • Does the OHLC endpoint include volume (V)?
    No. The Open/High/Low/Close endpoint returns O/H/L/C but not volume. If your strategy needs OHLCV, source volume separately and join on date.
  • Which direction should I chart? DOGE or USDDOGE?
    Most frontends and PnL models prefer USD per DOGE (USDDOGE). If you need DOGE per USD, request DOGE or invert USDDOGE as needed.
  • What timezone do daily dates use?
    Treat dates and timestamps as UTC. Align your candles and EOD logic to UTC to avoid off-by-one issues across timezones.
  • What if some days are missing?
    Code defensively. Skip missing dates or forward-fill previous close based on your model requirements. Log anomalies and review alerts before re-running backtests.
  • How much history can I pull in one request?
    This depends on your plan. If you hit limits, chunk by month or quarter. See the Documentation for details.

Ready to fetch DOGE history and daily OHLC for your 2026 analysis? Get your API key in minutes and start shipping: Register.