sbloggugl.blogg.se - Jupyterlab docker image

#JUPYTERLAB DOCKER IMAGE HOW TO#

Useful RHCSAv8 Linux commands, files and configs.

#JUPYTERLAB DOCKER IMAGE HOW TO#

How to get list of companies in S&P 500 with python.How to use GNU screen with SSH sessions.Synchronize local git project with github repository.Run miniconda3 locally in Docker container.

Volume Profile for stocks in python (VPVR indicator, Volume Profile Visible Range).Detect double bottom in stocks with python.Detect double top in stocks with Python.Create multiple wordpress websites with Docker-Compose.Find peaks and valleys in dataset with python.Activation functions – sigmoid, tanh, ReLU.How to get price data for Bitcoin and cryptocurrencies with python (JSON RESTful API).Aggregate daily OHLC stock price data to weekly (python and pandas).Build custom Miniconda Docker image with Dockerfile.Load stock data from sqlite3 database to Pandas dataframe.Save stock price data from Pandas dataframe to sqlite3 database.Get Stochastic RSI for stocks with Python.Compute weekly RSI from daily stock data.Compute RSI for stocks with python (Relative Strength Index).Compute Bollinger Bands for stocks with Python and Pandas.Compute MACD indicator for stocks with Python.Build simple stock trading bot/advisor in python.

Predict stock price trend with machine learning (random forest, scikit, python).

# sudo docker run -name custom_miniconda -i -t -p 8888:8888 -v "$:/notebooks" custom_minicondaĪnd in separate terminal get the sign in token: docker exec -it custom_miniconda conda run -n trading_env jupyter notebook list Source: # we can specify for example numpy, pandas, matplotlib. Conda is having issues activating within the same shell, so workaround described in the Dockerfile needed to be used (using conda run -n env_name).ĭockerfile # custom miniconda build that contains only libraries that we really need The centos 8 image is using Python 3.7 by default, but to install ta-lib library we needed to create virtual environment with Python 3.5. Here we will create docker image that is using miniconda and jupyterlab as our development environment for Machine Learning tasks and stock trading technical analysis.