This examples directory contains scripts that demonstrate
how to use the toolkit for processing OHLC data.
First, clone the ohlc-toolkit repository:
git clone https://github.com/ff137/ohlc-toolkit.git
Set up a virtual environment and install the dependencies:
python -m venv .venv
source .venv/bin/activate
pip install poetry
poetry install
New: We now have a helper method in the example script which will automatically download a sample dataset for you. See below for details. Skip to Running the Example if you just want to get started.
Before running the examples, you need a sample dataset to work with.
On a separate repo, we host up-to-date BTC/USD 1-minute data from Bitstamp, which can be found at the following link:
Inspect the above link to verify that you’re happy downloading the data.
We recommend the above dataset because it is real, recent, and has passed data integrity checks. You’re of course welcome to use your own dataset instead.
We have included a helper class, BitstampDatasetDownloader, in the toolkit to help automate the download process.
Here is how you can use it (this is included in the example script and doesn’t need to be done manually):
from ohlc_toolkit.bitstamp_dataset_downloader import BitstampDatasetDownloader
# Initialize the downloader
downloader = BitstampDatasetDownloader(data_dir="data") # Configure your desired output directory
# Download the latest dataset
df = downloader.download_bitstamp_btcusd_minute_data(recent=True, bulk=False) # Set bulk to True to also download the full historical dataset (~90MB)
You can also download the data manually using curl:
cd ohlc-toolkit # Move to the project
mkdir -p data # Create a data directory
curl -L -o data/btcusd_bitstamp_1min_latest.csv https://github.com/ff137/bitstamp-btcusd-minute-data/raw/main/data/updates/btcusd_bitstamp_1min_latest.csv
Once you have downloaded the data, you can run the basic_usage.py script
to see how the ohlc-toolkit processes the data.
Run the following command in your terminal:
python examples/basic_usage.py
The basic_usage.py script performs the following actions:
ohlc_toolkit module.read_ohlc_csv function.That’s it for now! More features will be added soon.