dataforge-labs/bitcoin-mining-pool-templates

Bitcoin mining pool templates

What each mining pool is building on, at the moment it was building it.

Pools issue work to their miners describing the block they are extending, the coinbase they will claim, and whether previous work should be abandoned. That work is replaced every few seconds. Once a block is found, the templates every pool was building are gone.

Contents

name	one row is
e20_stratum_jobs_direct	one job from one pool: the block it extends, its nTime, coinbase, merkle branch count and clean-jobs flag

Templates

Pools building on the same block do not agree, and the disagreement is structural rather than cosmetic. In one observation across eleven endpoints on a single block, nTime spread across 30 seconds, coinbase length ranged from 318 to 1,488 characters, and merkle branch counts split between 10 and 13, meaning some pools were assembling materially smaller blocks than others at the same moment. Two endpoints run by the same operator differed by 10 seconds.

pool is the endpoint connected to rather than an identity inferred from the data. operator collapses endpoints belonging to the same operator, and rows should usually be grouped on it.

Before you build on this

• One vantage point, roughly 120 peers out of tens of thousands reachable. This is a sample of the network, not the network.
• nTime is the pool's own clock and pools do not all update it on the same cadence. It indicates when a pool rebuilt its template. For arrival ordering use observed_ts, which is consistent across pools.
• Eleven endpoints across ten operators. Pools running regional endpoints may serve different work elsewhere, so this is a sample of what each operator was building, not a census of it.
• Merkle branches are stored as a count and first entry. The count with the coinbase identifies a distinct template; the full list is large and mostly redundant.
• clean_jobs = true marks a pool switching blocks. Sorting those by observed_ts gives the order in which pools reacted.

Partitions are parquet, one file per collection window, under dataset/YYYY/MM/. Every dataset here carries a FIXED 7-day sample WINDOW starting at its own first day of collection, together spanning 2026-08-28 to 2026-09-03, so you can check schema, coverage and quality before asking for more. It does not advance, so there is nothing to gain by re-downloading it. The full history is held privately, available on request.

from huggingface_hub import snapshot_download
import pandas as pd, glob

path = snapshot_download("dataforge-labs/bitcoin-mining-pool-templates", repo_type="dataset",
                         allow_patterns="e20_stratum_jobs_direct/**")
df = pd.concat(map(pd.read_parquet,
                   glob.glob(f"{path}/e20_stratum_jobs_direct/**/*.parquet", recursive=True)))

Coverage

e0_run_manifest lists every collection window with its poll counts and failure counts, and is published in full rather than windowed. Gaps between windows are real, cannot be filled in afterwards, and nothing here is interpolated.

License and contact

ODC-BY: use it freely, credit "DataForge (dataforge-labs)". Questions and requests for the full history via the discussions tab.