---
license: mit
task_categories:
- time-series-forecasting
language:
- en
tags:
- tsfile
- timeseries
- time-series
pretty_name: Crypto Trading Bot Data (TsFile)
configs:
- config_name: default
  data_files:
  - split: btc_dominance
    path: btc_dominance.tsfile
  - split: fear_greed
    path: fear_greed.tsfile
  - split: features_d
    path: features_d.tsfile
  - split: funding_rates
    path: funding_rates.tsfile
  - split: klines_1h
    path: klines_1h.tsfile
  - split: macro_indicators
    path: macro_indicators.tsfile
  - split: ohlcv_1
    path: ohlcv_1.tsfile
  - split: ohlcv_1m_1
    path: ohlcv_1m_1.tsfile
  - split: ohlcv_1m_10
    path: ohlcv_1m_10.tsfile
  - split: ohlcv_1m_11
    path: ohlcv_1m_11.tsfile
  - split: ohlcv_1m_12
    path: ohlcv_1m_12.tsfile
  - split: ohlcv_1m_13
    path: ohlcv_1m_13.tsfile
  - split: ohlcv_1m_14
    path: ohlcv_1m_14.tsfile
  - split: ohlcv_1m_15
    path: ohlcv_1m_15.tsfile
  - split: ohlcv_1m_16
    path: ohlcv_1m_16.tsfile
  - split: ohlcv_1m_17
    path: ohlcv_1m_17.tsfile
  - split: ohlcv_1m_18
    path: ohlcv_1m_18.tsfile
  - split: ohlcv_1m_19
    path: ohlcv_1m_19.tsfile
  - split: ohlcv_1m_2
    path: ohlcv_1m_2.tsfile
  - split: ohlcv_1m_20
    path: ohlcv_1m_20.tsfile
  - split: ohlcv_1m_21
    path: ohlcv_1m_21.tsfile
  - split: ohlcv_1m_22
    path: ohlcv_1m_22.tsfile
  - split: ohlcv_1m_23
    path: ohlcv_1m_23.tsfile
  - split: ohlcv_1m_24
    path: ohlcv_1m_24.tsfile
  - split: ohlcv_1m_25
    path: ohlcv_1m_25.tsfile
  - split: ohlcv_1m_3
    path: ohlcv_1m_3.tsfile
  - split: ohlcv_1m_4
    path: ohlcv_1m_4.tsfile
  - split: ohlcv_1m_5
    path: ohlcv_1m_5.tsfile
  - split: ohlcv_1m_6
    path: ohlcv_1m_6.tsfile
  - split: ohlcv_1m_7
    path: ohlcv_1m_7.tsfile
  - split: ohlcv_1m_8
    path: ohlcv_1m_8.tsfile
  - split: ohlcv_1m_9
    path: ohlcv_1m_9.tsfile
  - split: ohlcv_2
    path: ohlcv_2.tsfile
  - split: ohlcv_3
    path: ohlcv_3.tsfile
  - split: ohlcv_4
    path: ohlcv_4.tsfile
  - split: ohlcv_5
    path: ohlcv_5.tsfile
  - split: open_interest
    path: open_interest.tsfile
---

# Crypto Trading Bot Data (TsFile)

Apache TsFile version of [`jponfiru/crypto-trading-bot-data`](https://huggingface.co/datasets/jponfiru/crypto-trading-bot-data).

## Overview

OHLCV market data and derived features for a Binance spot trading bot: 1-minute klines for the top-20 USDT pairs (2024 onward), 5-minute klines for 2026, 1-hour klines, funding rates, open interest, macro indicators, the Fear & Greed index, BTC dominance, and a labelled feature table for the project's Model D.

- **TsFile shards:** 37 (1054.2 MB total, 29,706,465 rows across 9 table(s)).
  - `btc_dominance` — 6 rows in 1 shard(s), 2026-05-18 01:06:09.359000 → 2026-05-21 12:34:43.211000 (UTC)
  - `fear_greed` — 3,028 rows in 1 shard(s), 2018-02-01 00:00:00 → 2026-05-21 00:00:00 (UTC)
  - `features_d` — 219,043 rows in 1 shard(s), 2024-01-09 08:00:00 → 2026-05-10 14:00:00 (UTC)
  - `funding_rates` — 57,360 rows in 1 shard(s), 2024-01-01 00:00:00 → 2026-05-21 12:00:00 (UTC)
  - `klines_1h` — 383,190 rows in 1 shard(s), 2024-01-01 00:00:00 → 2026-05-11 15:00:00 (UTC)
  - `macro_indicators` — 54 rows in 1 shard(s), 2026-05-11 04:00:00 → 2026-05-21 07:00:00 (UTC)
  - `ohlcv` — 4,610,042 rows in 5 shard(s), 2024-01-01 00:00:00 → 2026-05-14 03:00:00 (UTC)
  - `ohlcv_1m` — 24,432,100 rows in 25 shard(s), 2024-01-01 00:00:00 → 2026-05-21 12:34:00 (UTC)
  - `open_interest` — 1,642 rows in 1 shard(s), 2026-05-18 02:00:00 → 2026-05-21 12:00:00 (UTC)

## Conversion notes

- The source stores its series inside two SQLite databases; TsFile cannot read SQLite, so every table is streamed out of its database into a TsFile table of its own. Table list, row counts and skipped tables are recorded in `conversion_summary.json`.
- Tables with a `pair` (or `symbol`) column — `ohlcv_1m`, `ohlcv`, `klines_1h`, `funding_rates`, `open_interest`, `macro_indicators` and `features_d` — declare it as the TAG, so each instrument is one TsFile device with its own timeline; `fear_greed` and `btc_dominance` are single-device tables.
- Time = the source timestamp column at millisecond precision: `ts_ms` is already epoch milliseconds, `ts` is epoch seconds, and `ohlcv.timestamp` is an ISO-8601 string.
- No column and no row is dropped. `ohlcv_1m` (2024 onward) and `ohlcv` (2026) overlap; both are kept as separate tables rather than merged, and no duplicate key is removed because the two tables cover different timeframes.
- Not converted: `download_state (data_2026.db), download_progress (data_extended.db)` — bookkeeping tables recording the crawler's own progress, not time series.
- Not converted: `features_extended.csv` — 2.1 GB CSV of event features that was not downloaded for this conversion; the compact `features_d.csv` subset (219,043 rows) is included instead.
- The TsFiles are written with the `zstd` compressor. The Apache TsFile **Java** SDK reads every compressor, but the **Python** SDK (`pip install tsfile`) implements only `UNCOMPRESSED`, `SNAPPY`, `GZIP` and `LZ4`; opening these files with it returns no rows. Read them with the Java SDK, as shown below.

## Usage

> **Read this dataset with the Java SDK.** It is written with the `zstd` compressor. The Apache TsFile Java SDK reads every compressor, but the Python SDK (`pip install tsfile`) implements only `UNCOMPRESSED`, `SNAPPY`, `GZIP` and `LZ4`; opening this file with it yields no rows.

Read a converted file with the Apache TsFile Java SDK (`org.apache.tsfile:tsfile`):

```java
import org.apache.tsfile.file.metadata.IDeviceID;
import org.apache.tsfile.read.TsFileReader;
import org.apache.tsfile.read.TsFileSequenceReader;
import org.apache.tsfile.read.common.Path;
import org.apache.tsfile.read.expression.QueryExpression;
import org.apache.tsfile.read.query.dataset.QueryDataSet;
import org.apache.tsfile.write.schema.MeasurementSchema;

import java.util.ArrayList;
import java.util.List;

String path = "btc_dominance.tsfile";
try (TsFileReader reader = new TsFileReader(new TsFileSequenceReader(path))) {
    for (String deviceId : reader.getAllDeviceIds()) {
        IDeviceID device = IDeviceID.Factory.DEFAULT_FACTORY.create(deviceId);
        List<Path> paths = new ArrayList<>();
        for (MeasurementSchema schema : reader.getMeasurement(device)) {
            String name = schema.getMeasurementName();
            if (name != null && !name.isEmpty() && !name.equalsIgnoreCase("Time")) {
                paths.add(new Path(device, name, true));
            }
        }
        QueryDataSet dataSet = reader.query(QueryExpression.create(paths, null));
        while (dataSet.hasNext()) {
            System.out.println(dataSet.next());
        }
    }
}
```

## Source & license

- Original dataset: [`jponfiru/crypto-trading-bot-data`](https://huggingface.co/datasets/jponfiru/crypto-trading-bot-data)
- License: mit (as declared by the original dataset).