curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.5/install.sh | bash
To test that nvm was properly installed, close and re-open Terminal and enter nvm. If you get a nvm: command not found message, your OS may not have the necessary .bash_profile file. In Terminal, enter touch ~/.bash_profile and run the above install script again. For Windows users, navigate to https://github.com/coreybutler/nvm-windows/releases and download nvm-setup.exe.
nvm install 21
For Windows users
The above command may only work in administrator mode. After installing, return to your standard command prompt and run
nvm use 21
For non-Windows users
In order to access node and npm as sudo (in order to have <1024 ports) you should run
n=$(which node)
n=${n%/bin/node}
chmod -R 755 $n/bin/*
sudo cp -r $n/{bin,lib,share} /usr/local
npm install -g serverless
(May only work in administrator mode for Windows users)
For non-Windows users
Create AWS Credentials file ~/.aws/credentials and populate it with:
[default]
aws_access_key_id=<ACCESS-KEY>
aws_secret_access_key=<SECRET-ACCESS-KEY>
and replace <ACCESS-KEY> and <SECRET-ACCESS-KEY> with your keys.
Create AWS Config file ~/.aws/config and populate it with:
[default]
region=us-east-1
output=json
For Windows users
Installing AWS command-line interface (if not installed already):
msiexec.exe /i https://awscli.amazonaws.com/AWSCLIV2.msi
Confirm installation:
aws --version
To configure credentials and config files, run the following command:
aws configure
You will be prompted to enter your access and secret access keys, followed by the default region name (us-east-1) and output format (json). The ~/.aws/credentials and ~/.aws/config files will be automatically generated with the correct information.
Make sure you are in the current project directory.
In order to deploy with dashboard, you need to first login/register with:
serverless login
install dependencies with:
npm install
and
pip install -r requirements.txt
and then perform deployment with:
serverless deploy
After running deploy, you should see output similar to:
Deploying "aws-python-flask-api" to stage "dev" (us-east-1)
Using Python specified in "runtime": python3.9
Packaging Python WSGI handler...
✔ Service deployed to stack aws-python-flask-api-dev (104s)
endpoints:
ANY - https://xxxxxxxxxe.execute-api.us-east-1.amazonaws.com/dev/
ANY - https://xxxxxxxxxx.execute-api.us-east-1.amazonaws.com/dev/{proxy+}
functions:
api: aws-python-flask-api-dev-api (41 MB)
Note: In current form, after deployment, your API is public and can be invoked by anyone. For production deployments, you might want to configure an authorizer. For details on how to do that, refer to http event docs.
After successful deployment, you can call the created application via HTTP:
curl https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/
Which should result in the following response:
{ "message": "Hello from root!" }Calling the /hello path with:
curl https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/hello
Should result in the following response:
{ "message": "Hello from path!" }Calling the /read_csv path with:
curl -X POST -H "Content-Type: application/json" -d '{"file_name": "path_to_your_csv_file.csv"}' https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/read_csv
Should return data of csv files in JSON format.
Thanks to capabilities of serverless-wsgi, it is also possible to run your application locally, however, in order to do that, you will need to first install werkzeug dependency, as well as all other dependencies listed in requirements.txt. It is recommended to use a dedicated virtual environment for that purpose. You can install all needed dependencies with the following commands:
pip install werkzeug
pip install -r requirements.txt
At this point, you can run your application locally with the following command:
serverless wsgi serve
For additional local development capabilities of serverless-wsgi plugin, please refer to corresponding GitHub repository.
Ideal setup: User selects what they would like to look up (either from a dropdown menu, or separate sections for each lookup). Options:
- Look up a stat leader for a given year (select pitching/batting). User enters stat and year
- Look up a stat leader for a given time period (select pitching/batting). User enters stat, start year, and end year (leaving start year and end year blank should default to start year of 1871, end year of 2023)
- Get information for a given team in a given year
- Visualize stat leaders for a given time period in a bar chart (select pitching/batting). User enters stat, number of leaders (e.g. top 5) they wish to see, start year, and end year (same default for start and end year applies)