BCRP — Central Reserve Bank of Peru

The BCRP module lets you download, cache, and work with any time-series published by the Peruvian Central Reserve Bank through its public statistics API.

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What it does

Capability	Details
Fetch data	Pulls one or many series in a single HTTP call
Multi-frequency	Daily (D), Monthly (M), Quarterly (Q), Annual (A)
Metadata validation	Warns about unknown codes before making any API request
SQLite caching	Re-running with the same parameters hits the local cache, not the network
Pandas-ready	Returns tidy DataFrame objects with a datetime index

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Architecture overview

BCRPSeries          ← define your query (codes + date range)
    │
    ▼
BCRPDataSeries      ← orchestrates fetch, cache, and date parsing
    ├── BCRPMetadata   validates codes against the scraped catalogue
    └── BCRPCache      reads / writes the SQLite cache

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Quick example

from perustats.BCRP.models import BCRPSeries
from perustats.BCRP.fetcher import BCRPDataSeries

series = BCRPSeries(
    codes=["RD16085DA", "PD04657MD", "RD14266DQ"],
    start_date="2015-01-01",
    end_date="2024-12-31",
)

result = BCRPDataSeries(series).fetch_data()

# result.result is a dict keyed by frequency
daily_df     = result.result["D"]
monthly_df   = result.result["M"]
quarterly_df = result.result["Q"]

print(daily_df.head())

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Series code format

Every BCRP series code encodes its own frequency in the last character:

Suffix	Frequency
D	Daily
M	Monthly
Q	Quarterly
A	Annual

Example: RD16085D**A** → annual series. The library reads this suffix automatically and routes each code to the correct API endpoint and date format.

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Pages in this section

Page	Description
Quickstart	Installation and a working end-to-end example
BCRPDataSeries	Full API reference for the main fetcher class
BCRPSeries model	Query model — codes, date range, and frequency grouping
BCRPMetadata	Catalogue management and code search
BCRPCache	SQLite cache internals
Examples	Real-world usage patterns