Flex Cols

Description

The flex cols component renders a section of two to four columns, in a responsive format.

Sample Flex Column

Rendered


This is the header

This is the body. Tristique Sem Quam Adipiscing.

Built for Python


When CircleCI detects a Python project, it automatically uses virtualenv and pip to create an isolated Python environment with all of the dependencies specified in your requirements.txt file. This helps ensure that your Python projects can be set up quickly and easily and that your CircleCI enviroment is configured correctly.

Intelligent test running


CircleCI intelligently determines the best way to run your tests using nosetests, tox, or Django. We also provide complete flexibility to override our inferred commands with your own custom commands via the circle.yml.

Easy continuous delivery


CircleCI makes setting up Continuous Delivery for your Python application simple and easy. We offer first-class support for deployment to platforms like Heroku, Elastic Beanstalk, and Google App Engine as well as using tools like Fabric, Ansible, Salt, and others.


Options

classes : string

header : string

body : string

data : array
The data value takes an array of data, set in a `_data` file.

num_cols : two | three | four
This value sets the number of columns to be rendered. These columns do stack, so that 2 cols with four entries creates two rows of two.


Sample Flex Column

Code


{% assign data = site.data.pages.python %} {% include components/flex-cols.html num_cols='three' header="This is the header" body="This is the body. Tristique Sem Quam Adipiscing." data=data %}

Rendered


This is the header

This is the body. Tristique Sem Quam Adipiscing.

Built for Python


When CircleCI detects a Python project, it automatically uses virtualenv and pip to create an isolated Python environment with all of the dependencies specified in your requirements.txt file. This helps ensure that your Python projects can be set up quickly and easily and that your CircleCI enviroment is configured correctly.

Intelligent test running


CircleCI intelligently determines the best way to run your tests using nosetests, tox, or Django. We also provide complete flexibility to override our inferred commands with your own custom commands via the circle.yml.

Easy continuous delivery


CircleCI makes setting up Continuous Delivery for your Python application simple and easy. We offer first-class support for deployment to platforms like Heroku, Elastic Beanstalk, and Google App Engine as well as using tools like Fabric, Ansible, Salt, and others.