Lebanese Pound (LBP) Price History — Daily close series extraction via API

You need a daily close history of the Lebanese Pound (LBP) that you can drop straight into a chart, model, or alerting pipeline. In this guide, you’ll query the latest LBP rate, understand the base/quote conventions, and outline how to pull a daily time series and daily close (EOD) with Indices-API—so you can backfill, plot, and monitor the LBP efficiently.

What you will build: a reproducible LBP daily-close series

By the end of this walkthrough, you will be able to:

• Fetch the current LBP rate relative to USD and understand how to interpret rates.LBP and rates.USDLBP.
• Plan a daily close backfill using the time-series and OHLC endpoints for LBP.
• Handle practical details: base currency, timestamps, weekends/holidays, caching, and the “end_date cannot be today” constraint.

If you need to confirm the exact symbol codes you plan to use, check the Symbols page first. For account creation and keys, go to Register. You can also browse the API overview and endpoint specifics in the Documentation.

Understand the LBP “base/quote” convention you will receive

Indices-API defaults to USD as the base currency. That means:

• rates.LBP is quoted as LBP per 1 USD (LBP/USD).
• rates.USDLBP is quoted as USD per 1 LBP (USD/LBP), typically a very small number.

This dual availability is useful depending on your downstream math. For example, if your app expects “how many LBP you get for 1 USD,” use rates.LBP. If your model expects the inverse—“how many USD for 1 LBP”—use rates.USDLBP. The field base will be "USD" when these values are returned.

Quick symbol reference you’ll use while extracting LBP

Always confirm up-to-date symbol availability on the Indices-API Supported Symbols page before shipping to production.

Fetch the latest LBP rate (copy-paste curl)

The latest endpoint returns current rates relative to USD. Depending on your subscription, the update frequency can be every 60 minutes, every 10 minutes, or at a higher cadence. The PRO plan is $49.99/mo with a 7-day trial.

Run the following curl call to get the latest LBP quote. Replace YOUR_API_KEY with your key from Register.

curl -s "https://indices-api.com/api/latest?access_key=YOUR_API_KEY"

Below is the official response fixture for LBP. Use these exact values to wire up your parsing and tests:

{"data":{"success":true,"timestamp":1791610800,"date":"2026-10-10","base":"USD","rates":{"LBP":89555.2753175,"USD":1,"USDLBP":1.1166288043386653e-5}}}

How to interpret these fields

• success: Boolean indicating the call worked.
• timestamp: UNIX seconds since epoch. Treat it as UTC.
• date: ISO-8601 (YYYY-MM-DD). This represents the effective date for the rates payload.
• base: Base currency of all rates (USD here).
• rates: The quote map:
  • rates.LBP = 89555.2753175 → LBP per 1 USD
  • rates.USDLBP = 1.1166288043386653e-5 → USD per 1 LBP
  • rates.USD = 1 → USD per 1 USD (identity)

For charting LBP value versus time, most dashboards will pick one convention and stick to it. If your Y-axis is “LBP per USD,” then plot rates.LBP. If you prefer “USD per LBP,” plot rates.USDLBP.

Minimal Python example to read the latest LBP close

This sample requests the same endpoint, extracts the date and both LBP/USD and USD/LBP, and prints a normalized row ready for persistence.

import os
import requests
from datetime import datetime, timezone

API_URL = "https://indices-api.com/api/latest"
API_KEY = os.environ.get("INDICES_API_KEY", "YOUR_API_KEY")

def fetch_latest_lbp():
    r = requests.get(API_URL, params={"access_key": API_KEY}, timeout=10)
    r.raise_for_status()
    payload = r.json().get("data", {})
    if not payload.get("success"):
        raise RuntimeError("API reported success=false")

    ts = int(payload["timestamp"])
    date = payload["date"]           # YYYY-MM-DD, end-of-day snapshot in UTC
    base = payload["base"]           # "USD"
    rates = payload["rates"]

    lbp_per_usd = rates.get("LBP")   # LBP per 1 USD
    usd_per_lbp = rates.get("USDLBP")# USD per 1 LBP

    # Normalize to a record for storage
    iso_ts = datetime.fromtimestamp(ts, tz=timezone.utc).isoformat()
    return {
        "timestamp": iso_ts,
        "date": date,
        "base": base,
        "lbp_per_usd": lbp_per_usd,
        "usd_per_lbp": usd_per_lbp
    }

if __name__ == "__main__":
    row = fetch_latest_lbp()
    print(row)

Notes:

• Use timestamp for exact ordering and caching windows; date is your daily bucket label.
• If your chart expects close-of-day values, stick to date as your X-axis and the rate as Y, and ignore intra-day refreshes unless you explicitly want them.

Backfill a daily close LBP series with the Time-Series and OHLC endpoints

To build a historical daily close series (e.g., for a line chart or factor model inputs), you’ll typically use:

• Time-Series endpoint: returns daily historical rates between start_date and end_date. Use this to populate contiguous daily points.
• OHLC endpoint: returns open/high/low/close for a date range or a given date. Use this when you specifically need the “close” distinct from any intra-day refresh.

The Time-Series endpoint yields daily snapshots keyed by date, similar to how the latest endpoint provides a date and base. The OHLC endpoint returns fields open, high, low, close for each supported symbol. When reconstructing a “daily close” chart, you can either:

• Use the Time-Series daily value as your “close” (simple and sufficient for many dashboards).
• Use the OHLC close specifically if your logic depends on the close versus open/high/low.

Important details you should account for when calling Time-Series:

• end_date cannot be today. Request up to yesterday’s date to avoid empty or partial data.
• Weekend/holiday behavior: currency markets typically have reduced or no settlement on weekends and certain holidays. Expect flat or repeated values, or missing days depending on coverage; normalize your time axis and forward-fill cautiously if your use case requires a uniform grid.
• Base remains USD unless you specify otherwise. That means each historical rate you receive is LBP per 1 USD, with USD/LBP also typically available in rates.

The precise resource paths and parameter names for Time-Series and OHLC are documented in the Documentation. Structure your requests to include:

• Your access_key
• start_date and end_date (YYYY-MM-DD), with end_date set to yesterday
• The symbol(s) you want to retrieve (confirm on Symbols)

Once the series is in hand, persist it as an ordered list of (date, close) where close is either the daily value from the time-series endpoint or the close field from the OHLC endpoint. Use timestamp only for quality checks, caching, or to reconcile late data corrections; rely on date for chart axis bucketing.

Data hygiene: units, clocks, caching, and update windows

There are a few integration gotchas worth handling from the start:

• Units and base: With base=USD, rates.LBP is LBP per 1 USD. If your app expects LBP as a base, you can invert as needed (use rates.USDLBP) instead of computing it yourself.
• Timezone: Treat date as UTC. The timestamp is also UTC. When mapping to your own EOD schedule, align your cron or ETL to run after the provider’s daily consolidation window.
• Update frequency: The latest endpoint refresh cadence depends on plan (e.g., every 60 minutes or every 10 minutes). If you only need EOD, schedule your pulls once per day; if you need intraday monitoring, poll accordingly.
• Caching: Respect the timestamp and avoid hammering the API more frequently than necessary. Cache results until the next expected update window.
• Non-trading days: For weekends/holidays, fill strategies depend on your product. Many dashboards forward-fill to keep a continuous line; for research accuracy, you may prefer to leave gaps or annotate non-business days.

How this fits in your pipeline

Typical pipelines for a currency series like LBP look like this:

1. Backfill: Use the Time-Series endpoint to populate a historical daily set from your desired start_date to yesterday (end_date). Store (date, LBP/USD) and optionally (date, USD/LBP) if you need both orientations.
2. Daily refresh: Nightly job that:
   • Calls latest to confirm the most recent date and rate.
   • Calls OHLC if you require explicit “close.”
   • Persists a single row for the last completed UTC day.
3. Intraday alerts (optional): If you monitor LBP threshold moves, poll latest during market hours and compare against yesterday’s close to compute deltas.

Keep your business logic stable by always reading base and date from the response and never assuming local time equals the API day boundary.

When to use Latest vs. Time-Series vs. OHLC for LBP

• Use Latest when:
  • You need the current reference rate to render an up-to-the-minute widget.
  • You only store one record per day and can rely on the daily consolidation later.
• Use Time-Series when:
  • You’re backfilling or fetching a contiguous range of daily closes.
  • You’re driving a sparkline or multi-year chart.
• Use OHLC when:
  • You need the explicit close distinct from any intraday refresh.
  • You compute volatility or need open/high/low for indicators.

Endpoint specifics, parameters, and pagination/limits (if any) are available in the Indices-API Documentation. If you are exploring broader data coverage, the MCP page is a good complement.

Validation tips for LBP consumers

To keep your LBP series reliable:

• Check success before using any payload, and log unexpected shapes if rates.LBP or rates.USDLBP is missing.
• Guard against “today” requests on Time-Series. Always request up to yesterday’s date to avoid partial-day artifacts.
• Normalize to one convention across your stack (either LBP/USD or USD/LBP) and derive the inverse only if needed in a specific downstream module.
• When your pipeline uses both Latest and OHLC, prefer OHLC close as the canonical daily close and treat Latest as a convenience for current context and delta calculations.

Production checklist

• Access key management: Store your key securely (e.g., environment variables, secrets manager). Rotate on schedule.
• Retry/backoff: Add modest retry logic with exponential backoff for network blips.
• Monitoring: Alert on unexpected gaps in dates, sudden zeroes, or NaN values in rates.
• Caching: Memoize responses within your polling cadence and queue downstream writes (e.g., append-only partitioned by date).
• Docs and symbols: Keep a deploy-time check that confirms LBP is present on Symbols and that your endpoint usage matches the Documentation.

Why Indices-API for LBP

Indices-API centralizes real-time and historical market values behind a single JSON model and consistent fields (success, timestamp, date, base, rates). For currency series like LBP, that saves you from reconciling multiple vendor formats or rolling your own inversion math. Start with Latest for quick state, add Time-Series and OHLC for a robust daily close pipeline, and scale to additional symbols as needed.

Explore more at indices-api.com, and keep the Documentation handy while you wire up parameters and schedules.

FAQ

Can I request the time series up to today’s date?
No. Set end_date to yesterday. The API does not guarantee complete data for the current day, and requests that end on today may return partial or empty values.

Which field should I chart: LBP or USDLBP?
Pick the convention your product needs and stick to it. rates.LBP is LBP per 1 USD (LBP/USD). rates.USDLBP is USD per 1 LBP (USD/LBP). Avoid flipping back and forth across your stack to prevent confusion.

How often do LBP values update?
The Latest endpoint updates depend on your plan (for example, every 60 minutes or every 10 minutes). If you only need EOD closes, a single daily pull after the consolidation window is sufficient.

What should I do on weekends and holidays?
Expect flat or unchanged values for some days or gaps depending on coverage. For charts, forward-fill is common; for research-grade datasets, keep the gaps or annotate them explicitly.

Where do I confirm the exact LBP symbol?
Use the Symbols page. Do this before deploying to production to avoid symbol mismatches.

Ready to pull your first LBP daily close? Create your key and start integrating in minutes: Register. Keep indices-api.com open for quick navigation while you build.