By: Rahim Khoja (rahim@khoja.ca)
The Crypto Trade Finder Notebook makes it easy to analyze the performance of cryptocurrency trading with Jupyter Notebook, Lab, or Hub. Simply install a few required tools, select the market, time period, and exchange you want to analyze, and the notebook takes care of the rest. The analysis is based on technical indicators, and you can easily access a list of all indicators and get help on any individual one. The results of your analysis are beautifully visualized, giving you a clear understanding of your trades' performance. With just a few clicks, you can gain valuable insights into the world of cryptocurrency trading.
Jupyter Notebook is an open-source web-based interactive computing platform that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It's often used in data science and machine learning, but it can be used in many other domains as well.
High-Performance Computing (HPC) refers to the use of supercomputing systems to solve complex computational problems. Jupyter Notebook can be used in conjunction with HPC systems to perform computationally intensive tasks. For example, you can use Jupyter Notebook to write code that runs on a cluster of HPC machines to process large datasets. This can be useful when you need to perform a large number of calculations in parallel or when you need access to more computational resources than a single machine can provide.
In conclusion, Jupyter Notebook is a tool for interactive computing and data analysis, while HPC is a field that involves using powerful computing systems to solve complex problems. The two can be combined to perform complex computations on large datasets, making Jupyter Notebook a valuable tool for HPC applications
- On Windows: Download the Docker Desktop for Windows from the official website and follow the installation instructions.
- On Mac: Download the Docker Desktop for Mac from the official website and follow the installation instructions.
- On Linux: Follow the instructions specific to your distribution from the official Docker website.
Once installed, start the Docker application on your computer.
Open the terminal or command prompt and run the following command to pull the datascience Docker image:
docker pull jupyter/datascience-notebookRun the following command to start a Jupyter server with the datascience environment:
docker run --rm -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes jupyter/datascience-notebook start.sh jupyter lab --ip=0.0.0.0 --no-browser --allow-root --NotebookApp.token=''Once the command has completed, just go to the following URL on your browser to access Jupyter.
Open the URL in your web browser and start using Jupyter. You can create new notebooks, open existing notebooks, and run code in the datascience environment.
That's it! Now you should be able to run Jupyter using the datascience Docker image on your local machine.
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From the Jupyter homepage, click on the "New" button on the right and select "Terminal".
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In the terminal, run the following commands to clone the Git repository:
git clone https://github.com/rahimkhoja/Crypto-Currency-Trade-Finder.git-
Return to the Jupyter homepage and navigate to the cloned repository in the file browser on the left.
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Click on the file CCXT Crypto Currency Trade Finder Notebook.ipynb to open it.
Since I am extremely lazy I am not going to offer any support. Well maybe every once-n-a while. It really depends on my mood.
That being said, time was spent documenting each command in the scripts. This should allow the scripts to be easily understood and modified if needed.
Many Bothans died getting this Jupyter Notbook Crypto Trade Finder to you, honor them by sending me some Crypto. ;)
ETH Mainnet: 0x1F4EABD7495E4B3D1D4F6dac07f953eCb28fD798
BNB Chain: 0x1F4EABD7495E4B3D1D4F6dac07f953eCb28fD798
Released under the GNU General Public License v3.