/MHW-2022

Miami Hack Week 2022

Primary LanguagePython

Miami Hack Week 2022

Hello! Welcome to Miami and thanks for joining the Space Eyes house. Here are some instructions on how to setup your development environment to start building your project.

Setup up docker environment

Pre-requisites:

  • Docker for Desktop 🐳
  • Git

First, you will need to clone this repository to your computer:

git clone https://github.com/Channel-Logistics/MHW-2022.git

Open the folder in your favorite IDE, then please create a branch with your own name to develop on:

git branch <name>
git checkout <name>

Next, open up the credentials file under the /depend directory. Input your AWS access key and secret access key that was provided to you during orientation. If you do not have these, please ask a Space Eyes employee for help.

Assuming you have docker properly configured for your system (checkout the docker instructions if unsure), build the docker image with the following command:

docker build -t <image_name> .

The build process will take 5-7 minutes to complete. After the build has completed, start a container with the following command:

docker run -it –name <container_name> -v <source_dir>:<target_dir> <image_name>

Make sure you use the absolute path of your local src folder as the source_dir parameter and then the "/src" directory as the target_dir parameter.

Quick note - sometimes gdal will throw the following error if you try to import it from python:

ImportError: libgdal.so: cannot open shared object file: No such file or directory

If you see this, the LD_LIBRARY_PATH environment variable is not set. Run the following command to correct it:

export LD_LIBRARY_PATH=/usr/local/lib

This is automatically done on startup, so you shouldn't have to worry about it.

This should complete your development environment! If you have any questions, ask a Space Eyes employee or feel free to DM Alex on Discord.

Reading data from S3

Reading data from S3 is really easy if you're using the provided docker environment:

df = pd.read_parquet(<s3_uri>)

If this did not work, you are either missing the ffspec and/or s3fs python dependencies or you are missing valid credentials under the ~/.aws directory.