infologistix/docker-selenium-python Docker 镜像 - 轩辕镜像

docker-selenium-python

Docker base image to run python based scripts for selenium in one container. Compiled on top of base python image build on alpine. This method uses chromium in headless.

Usage

Build docker-image from scratch. This may take a while, because numpy and pandas must be compiled from source. This is indeed a point, where improvements can begin.

Basic requirements are pandas, numpy and selenium. Simply change your requirements to your needs.

• Create a python script to trigger selenium based events or crawl the web
• Copy your files to the specified locations
• Run docker run -it --rm --shm-size=128m infologistix/docker-selenium-python:latest python main.py

Intended usage is for crawling scheduled sites on AWS ECS and Azure ACR. Simply build the container as base and add your scripts to it. Add --shm.size=128m to it to ensure running correctly. See Docker Run specifications. For some webpages Chrome needs extra memory.

Example

To run the given example execute the following:

docker run -it --rm --shm-size=128m infologistix/docker-selenium-python:latest python ./examples/main.py

This example scrapes our homepage and writes the services of our company human readable to console. This can be extended using a MS Teams Channel do be sent to. Documentation can be found here.

Advanced Usage

Triggering your script directly at the start of the container requires you to fiddle with the Dockerfile. Simply add your requirements to a requirements.txt and copy your source files to the image.

We provide an example script located in examples folder. Use this as a reference guide provided.

Dockerfile
FROM infologistix/docker-selenium-python:alpine

WORKDIR /usr/src/app

COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt

COPY your/app/ ./

CMD "python main.py"

Simply build this file to suit your applicational use.

When using Machine learning tools use one of our other selenium based Containers by changing the tag:

• bullseye, latest, 3.10, 3.10-bullseye
• alpine, 3.10-alpine

For Machine Learning applications we recommend the bullseye tag to install every library there is. Make sure to install only necessary things.

This image was developed for infologistix GmbH