boxtime 3.1.1

Cointime economics framework implementation for the Ergo blockchain.

boxtime

Cointime economics framework implementation for the Ergo blockchain.

Description

Boxtime is a Python library that implements the Cointime Economics framework for Ergo. It reads pre-computed coinblocks created, destroyed, and stored — plus daily ERG/USD prices — from a database populated by the boxtime indexer.

Two connection paths are supported:

1. Default (Supabase) — uses the hosted Supabase project via PostgREST with an embedded publishable API key. No setup needed.
2. Custom (Postgres) — connect directly to your own Postgres instance via asyncpg.

Installation

pip install boxtime

Prerequisites

• Python 3.10+

Quickstart

Default (Supabase — no setup needed)

from boxtime import Cointime

ct = Cointime()  # uses the hosted Supabase database

# Coinblocks created at a single height (= circulating supply in nanoERGs)
cbc = ct.coinblocks_created(500_000)

# Coinblocks destroyed at a single height
cbd = ct.coinblocks_destroyed(500_000)

# Coinblocks stored (CBC - CBD)
cbs = ct.coinblocks_stored(500_000)

# Totals over a range
total_cbc = ct.total_coinblocks_created(500_000, 500_100)
total_cbd = ct.total_coinblocks_destroyed(500_000, 500_100)
total_cbs = ct.total_coinblocks_stored(500_000, 500_100)

Custom Postgres

ct = Cointime(database_url="postgresql://user:pass@localhost:5432/boxtime")
cbc = ct.coinblocks_created(500_000)

Price data

import datetime

ct = Cointime()

# Daily ERG/USD price
price = ct.get_price(datetime.date(2024, 6, 15))

# Price range
prices = ct.get_price_range(datetime.date(2024, 1, 1), datetime.date(2024, 12, 31))
for date, usd in prices:
    print(date, usd)

Time series data (for plotting)

The get_coinblocks_* methods return a CointimeSeries object optimized for plotting:

# All blocks in range (no prices)
series = ct.get_coinblocks_created(500_000, 510_000)

# Access as parallel arrays
print(series.heights)      # [500000, 500001, ...]
print(series.timestamps)   # [1704067200000, ...]
print(series.values)       # [cbc values]

# Or iterate as data points
for dp in series:
    print(dp.height, dp.timestamp, dp.value)

# Convert timestamps to dates for plotting
import matplotlib.pyplot as plt
plt.plot(series.dates, series.values)

Price-enriched time series

# One data point per day with price enrichment
series = ct.get_coinblocks_created(500_000, 510_000, with_price=True)

for dp in series:
    print(f"Height {dp.height}: {dp.value} nanoERGs @ ${dp.price:.2f}")

# Clean up when done
ct.close()

API Overview

Cointime(database_url=None, *, supabase_url=..., supabase_key=...)

Parameter	Default	Description
database_url	None	If set, use direct Postgres via asyncpg
supabase_url	Hosted URL	Supabase project URL (default path)
supabase_key	Publishable key	Supabase API key (safe to embed)

Primitive metrics (single height):

• coinblocks_created(height) — circulating supply at height
• coinblocks_destroyed(height) — sum of input.value × lifespan for all inputs
• coinblocks_stored(height) — CBC − CBD

Aggregate metrics (height range, inclusive):

• total_coinblocks_created(start_height, end_height)
• total_coinblocks_destroyed(start_height, end_height)
• total_coinblocks_stored(start_height, end_height)

Price methods:

• get_price(date) — daily ERG/USD price (datetime.date)
• get_price_range(start_date, end_date) — List[Tuple[date, float]]

Time series methods (returns CointimeSeries):

All accept an optional with_price=True parameter to include daily prices.

• get_coinblocks_created(start_height, end_height, *, with_price=False)
• get_coinblocks_destroyed(start_height, end_height, *, with_price=False)
• get_coinblocks_stored(start_height, end_height, *, with_price=False)

Cumulative time series (absolute cumulative sums from genesis):

• get_total_coinblocks_created(start_height, end_height, *, with_price=False) — TCBC
• get_total_coinblocks_destroyed(start_height, end_height, *, with_price=False) — TCBD
• get_total_coinblocks_stored(start_height, end_height, *, with_price=False) — TCBS

Utility:

• get_max_height() — check data freshness
• close() — clean up connection pool / client

CointimeSeries

Returned by time series methods. Optimized for plotting with parallel arrays:

Attribute	Type	Description
heights	List[int]	Block heights
timestamps	List[int]	Block timestamps (ms since epoch)
values	List[int]	Cointime values (nanoERG-blocks)
prices	List[float] | None	ERG/USD prices (if with_price=True)

Methods:

• __iter__() — iterate as CointimeDataPoint objects
• __len__() — number of data points
• dates — property returning List[datetime.date] for plotting

CointimeDataPoint

Individual data point from iterating a CointimeSeries:

Attribute	Type	Description
height	int	Block height
timestamp	int	Block timestamp (ms since epoch)
value	int	Cointime value
price	float | None	ERG/USD price (if available)

Development

# Install with test dependencies
pip install -e ".[test]"

# Run tests
pytest

License

This project is licensed under the MIT License.