mirror of
https://github.com/aljazceru/hummingbot-dashboard.git
synced 2026-01-06 15:04:25 +01:00
72 lines
3.0 KiB
Markdown
72 lines
3.0 KiB
Markdown
## Requirements
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You will need to install [StreamLit](https://streamlit.io/). For information about Streamlit installation, see the instructions located at https://docs.streamlit.io/library/get-started/installation.
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You will also need to install either [Anaconda](https://www.anaconda.com/) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html) to get Conda:
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* [Anaconda](https://www.anaconda.com/) is a comprehensive Python distribution that includes a large number of pre-installed data science libraries and packages. It is designed to be an all-in-one solution for data science and machine learning tasks. When you install Anaconda, it comes with a collection of popular Python packages like NumPy, pandas, matplotlib, scikit-learn, and more.
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* [Miniconda](https://docs.conda.io/en/latest/miniconda.html) is a minimal version of Anaconda. It includes only the essential components, such as Python interpreter and Conda package manager. Unlike Anaconda, Miniconda doesn't come with pre-installed packages, which makes its download size much smaller.
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This repository is maintained by Hummingbot Foundation as a companion for users of [Hummingbot](https://github.com/hummingbot/hummingbot), the open source framework for building high-frequency crypto trading bots.
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Watch this video to understand how it works:
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https://www.loom.com/share/72d05bcbaf4048a399e3f9247d756a63
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## Installation
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1. Install Steamlit and Conda packages utilizing their instructions for your specific environment:
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* Install [StreamLit](https://docs.streamlit.io/library/get-started/installation)
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* Install [Anaconda](https://docs.anaconda.com/free/anaconda/install/index.html) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html)
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2. Clone this repo and navigate to the created directory
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```bash
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git clone https://github.com/hummingbot/dashboard.git
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cd dashboard
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```
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3. Run command to create an isolated `conda` environment and install dependencies
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```
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make env_create
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```
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4. Activate the isolated 'conda' environment
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```bash
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conda activate dashboard
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```
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5. Run the app
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```bash
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streamlit run main.py
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```
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## Data Feed
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Your `dashboard` environment needs to have access to the database for your Hummingbot environment. This is done by setting up a symbolic link to the 'data' directory of your running Hummingbot instance.
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The data directory differs for Docker versus Source installed Hummingbot. Data directory for each is as follows:
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* Docker installed: /path/to/hummingbot/hummingbot_files/data
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* Source installed: /path/to/hummingbot/data
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Create a symlink to your Hummingbot `/data` directory
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```bash
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# replace `/path/to/hummingbotdata` with the actual path
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ln -s /path/to/hummingbotdata data
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# if you need to remove the symlink
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unlink data
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```
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## Updating Dependencies
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To update the `dashboard` environment for changes to dependencies defined in `environment.yml`, remove the environment and re-create it:
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```
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make env_remove
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make env_create
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```
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To updated the `dashboard` source for latest version, run:
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```
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cd dashboard
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git pull
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```
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