Quick Start#

To quickly install Covalent and run a short demo, follow the four steps below.

Before you start

Ensure you are using a compatible OS and Python version. See the Compatibility page for supported Python versions and operating systems.

1. Use Pip to install the Covalent server and libraries locally.

Type the following in a terminal window:

$ pip install covalent
2. Start the Covalent server.

In the terminal window, type:

$ covalent start
Covalent server has started at http://localhost:48008
3. Run a workflow.

Open a Jupyter notebook or Python console and run the following Python code:

import covalent as ct

# Construct manageable tasks out of functions
# by adding the @covalent.electron decorator
@ct.electron
def add(x, y):
   return x + y

@ct.electron
def multiply(x, y):
   return x*y

@ct.electron
def divide(x, y):
   return x/y

# Construct the workflow by stitching together
# the electrons defined earlier in a function with
# the @covalent.lattice decorator
@ct.lattice
def workflow(x, y):
   r1 = add(x, y)
   r2 = [multiply(r1, y) for _ in range(4)]
   r3 = [divide(x, value) for value in r2]
   return r3

# Dispatch the workflow
dispatch_id = ct.dispatch(workflow)(1, 2)
result = ct.get_result(dispatch_id)
print(result)
4. View the workflow progress.

Navigate to the Covalent UI at http://localhost:48008 to see your workflow in the queue:

../../_images/qs_ui_queue.png

Click on the dispatch ID to view the workflow graph:

../../_images/qs_ui_graph.png

Note that the computed result is displayed in the Overview.

What to Do Next#

Read Concepts gain a deeper understanding of how Covalent works.

See the Tutorials to see how to apply Covalent to real-world machine learning problems in a variety of subject domains.

See the API Reference for usage information on electron, lattice, and ready-to-use executors.

See AWS Plugins to see how you can specify an executor to run this example on an AWS node using only two more lines of code.