# Installing Prefect
Prefect requires Python 3.6+. If you're new to Python, we recommend installing the Anaconda distribution.
To install Prefect, run:
pip install prefect
or, if you prefer to use
conda install -c conda-forge prefect
pipenv install --pre prefect
# Optional dependencies
Prefect ships with a number of optional dependencies, which can be installed using "extras" syntax:
pip install "prefect[extra_1, extra_2]"
Examples of extra packages include:
all_extras: includes all of the optional dependencies
dev: tools for developing Prefect itself
templates: tools for working with string templates
viz: tools for visualizing Prefect flows
aws: tools for interacting with Amazon Web Services
azure: tools for interacting with Microsoft Azure
kubernetes: tools for interacting with Kubernetes API objects
airtable: tools for interacting with the Airtable API
spacy: tools for building NLP pipelines using Spacy
redis: tools for interacting with a Redis database
Prefect support for Python 3.9 is experimental and extras are not expected to work yet as we wait for required packages to be updated.
# Running the local server and UI
Prefect includes an open-source server and UI for orchestrating and managing flows. The local server stores flow metadata in a Postgres database and exposes a GraphQL API. The local server requires Docker and Docker Compose to be installed. If you have Docker Desktop on your machine, you've got both of these.
Once you are ready to deploy into production, you can use Prefect Cloud to orchestrate your workflows.
Before running the server for the first time, run:
prefect backend server
This configures Prefect for local orchestration, and saves the configuration in your local
Next, to start the server, UI, and all required infrastructure, run:
prefect server start
Once all components are running, you can view the UI by opening a browser and visiting http://localhost:8080.
Please note that executing flows from the server requires at least one Prefect Agent to be running:
prefect agent local start.
Finally, to register any flow with the server, call
flow.register(). For more detail, please see the orchestration docs.
If you want Prefect provides Docker images for master builds and versioned releases here.
To run the latest Prefect Docker image:
docker run -it prefecthq/prefect:latest
Image tag breakdown:
|Tag||Prefect Version||Python Version|
|latest||most recent PyPi version||3.7|
|latest-python3.8||most recent PyPi version||3.8|
|latest-python3.7||most recent PyPi version||3.7|
|latest-python3.6||most recent PyPi version||3.6|
|core||most recent PyPi version||3.8|
All Prefect images besides those tagged with
core contain all extra dependencies necessary for flow
orchestration when running with a backend API. This includes libraries required to work with
storage objects and
core tagged images only include the base dependencies of the Prefect library that
can be found here.