From ca8c6a526644e68fb92f673815fb611e9965eb27 Mon Sep 17 00:00:00 2001
From: joshg <30822255+joshavenue@users.noreply.github.com>
Date: Tue, 20 Oct 2026 11:52:55 +0800
Subject: [PATCH 1/2] docs(readme): add Reservoir as a bulk historical data
 source

Added section on bulk historical data as an alternative source for backtesting.
---
 README.md | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 7abc0e5..6d8261f 100644
--- a/README.md
+++ b/README.md
@@ -238,6 +238,12 @@ let candles = info_client
 // Supported coins: BTC, ETH, SOL, AVAX, MATIC, ATOM, and many more
 ```
 
+### Bulk Historical Data (Alternative Source)
+
+The examples above pull candles from the Hyperliquid info API. If you need longer or more granular history for backtests, such as trade-level fills or order book state, pre-built Parquet datasets are another option:
+
+- **[Hydromancer Reservoir](https://docs.hydromancer.xyz/reservoir)**: Hyperliquid historical data on AWS S3 (`s3://hydromancer-reservoir`, region `ap-northeast-1`, requester pays), stored as Parquet and partitioned by `date=YYYY-MM-DD`. It includes trade fills (with liquidation, ADL and TWAP subsets), 1-second OHLCV candles, 20-level order book snapshots at 1-minute cadence, and daily position snapshots, for Hyperliquid perps and HIP-3 dexes. Any Parquet reader (DuckDB, Polars, or the `arrow`/`parquet` crates) can load it into the OHLC vectors used in the backtesting example above. It does not include funding rates, so keep using the API for those.
+
 ### Trading Modes
 
 The library supports multiple trading modes through the unified interface:
@@ -574,4 +580,4 @@ This software is for educational and research purposes only. Trading cryptocurre
 
 - **Issues**: [GitHub Issues](https://github.com/xsa-dev/hyperliquid-backtest/issues)
 - **Discussions**: [GitHub Discussions](https://github.com/xsa-dev/hyperliquid-backtest/discussions)
-- **Documentation**: [docs.rs](https://docs.rs/hyperliquid-backtest)
\ No newline at end of file
+- **Documentation**: [docs.rs](https://docs.rs/hyperliquid-backtest)

From ba60aceb35ed34d0773643a1afe33500da0d993e Mon Sep 17 00:00:00 2001
From: joshg <30822255+joshavenue@users.noreply.github.com>
Date: Tue, 20 Oct 2026 12:02:38 +0800
Subject: [PATCH 2/2] docs: point Reservoir link to overview post

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 6d8261f..eae5de8 100644
--- a/README.md
+++ b/README.md
@@ -242,7 +242,7 @@ let candles = info_client
 
 The examples above pull candles from the Hyperliquid info API. If you need longer or more granular history for backtests, such as trade-level fills or order book state, pre-built Parquet datasets are another option:
 
-- **[Hydromancer Reservoir](https://docs.hydromancer.xyz/reservoir)**: Hyperliquid historical data on AWS S3 (`s3://hydromancer-reservoir`, region `ap-northeast-1`, requester pays), stored as Parquet and partitioned by `date=YYYY-MM-DD`. It includes trade fills (with liquidation, ADL and TWAP subsets), 1-second OHLCV candles, 20-level order book snapshots at 1-minute cadence, and daily position snapshots, for Hyperliquid perps and HIP-3 dexes. Any Parquet reader (DuckDB, Polars, or the `arrow`/`parquet` crates) can load it into the OHLC vectors used in the backtesting example above. It does not include funding rates, so keep using the API for those.
+- **[Hydromancer Reservoir](https://hydromancer.xyz/hyperliquid-historical-data)**: Hyperliquid historical data on AWS S3 (`s3://hydromancer-reservoir`, region `ap-northeast-1`, requester pays), stored as Parquet and partitioned by `date=YYYY-MM-DD`. It includes trade fills (with liquidation, ADL and TWAP subsets), 1-second OHLCV candles, 20-level order book snapshots at 1-minute cadence, and daily position snapshots, for Hyperliquid perps and HIP-3 dexes. Any Parquet reader (DuckDB, Polars, or the `arrow`/`parquet` crates) can load it into the OHLC vectors used in the backtesting example above. It does not include funding rates, so keep using the API for those.
 
 ### Trading Modes