Note
Click here to download the full example code
Using Raw Containers#
This example demonstrates how to use arbitrary containers in 5 different languages, all orchestrated in flytekit seamlessly. Flyte mounts an input data volume where all the data needed by the container is available and an output data volume for the container to write all the data which will be stored away.
The data is written as separate files, one per input variable. The format of the file is serialized strings. Refer to the raw protocol to understand how to leverage this.
import logging
from typing import Tuple, Any, Mapping, List, Set
from flytekit import task, workflow
from flytekit import ContainerTask, kwtypes, workflow
logger = logging.getLogger(__file__)
Container Tasks#
A flytekit.ContainerTask
denotes an arbitrary container. In the following example, the name of the task
is calculate_ellipse_area_shell
. This name has to be unique in the entire project. Users can specify:
input_data_dir
-> where inputs will be written tooutput_data_dir
-> where Flyte will expect the outputs to exist.
inputs and outputs specify the interface for the task, thus it should be an ordered dictionary of typed input and output variables.
calculate_ellipse_area_shell = ContainerTask(
name="ellipse-area-metadata-shell",
input_data_dir="/var/inputs",
output_data_dir="/var/outputs",
inputs=kwtypes(a=float, b=float),
outputs=kwtypes(area=float, metadata=str),
image="ghcr.io/flyteorg/rawcontainers-shell:v1",
command=[
"./calculate-ellipse-area.sh",
"/var/inputs",
"/var/outputs",
],
)
calculate_ellipse_area_python = ContainerTask(
name="ellipse-area-metadata-python",
input_data_dir="/var/inputs",
output_data_dir="/var/outputs",
inputs=kwtypes(a=float, b=float),
outputs=kwtypes(area=float, metadata=str),
image="ghcr.io/flyteorg/rawcontainers-python:v1",
command=[
"python",
"calculate-ellipse-area.py",
"/var/inputs",
"/var/outputs",
],
)
calculate_ellipse_area_r = ContainerTask(
name="ellipse-area-metadata-r",
input_data_dir="/var/inputs",
output_data_dir="/var/outputs",
inputs=kwtypes(a=float, b=float),
outputs=kwtypes(area=float, metadata=str),
image="ghcr.io/flyteorg/rawcontainers-r:v1",
command=[
"Rscript",
"--vanilla",
"calculate-ellipse-area.R",
"/var/inputs",
"/var/outputs",
],
)
calculate_ellipse_area_haskell = ContainerTask(
name="ellipse-area-metadata-haskell",
input_data_dir="/var/inputs",
output_data_dir="/var/outputs",
inputs=kwtypes(a=float, b=float),
outputs=kwtypes(area=float, metadata=str),
image="ghcr.io/flyteorg/rawcontainers-haskell:v1",
command=[
"./calculate-ellipse-area",
"/var/inputs",
"/var/outputs",
],
)
calculate_ellipse_area_julia = ContainerTask(
name="ellipse-area-metadata-julia",
input_data_dir="/var/inputs",
output_data_dir="/var/outputs",
inputs=kwtypes(a=float, b=float),
outputs=kwtypes(area=float, metadata=str),
image="ghcr.io/flyteorg/rawcontainers-julia:v1",
command=[
"julia",
"calculate-ellipse-area.jl",
"/var/inputs",
"/var/outputs",
],
)
@task
def report_all_calculated_areas(
area_shell: float,
metadata_shell: str,
area_python: float,
metadata_python: str,
area_r: float,
metadata_r: str,
area_haskell: float,
metadata_haskell: str,
area_julia: float,
metadata_julia: str,
):
logger.info(f"shell: area={area_shell}, metadata={metadata_shell}")
logger.info(f"python: area={area_python}, metadata={metadata_python}")
logger.info(f"r: area={area_r}, metadata={metadata_r}")
logger.info(f"haskell: area={area_haskell}, metadata={metadata_haskell}")
logger.info(f"julia: area={area_julia}, metadata={metadata_julia}")
As can be seen in this example, ContainerTasks can be interacted with like normal python functions, whose inputs correspond to the declared input variables. All data returned by
@workflow
def wf(a: float, b: float):
# Calculate area in all languages
area_shell, metadata_shell = calculate_ellipse_area_shell(a=a, b=b)
area_python, metadata_python = calculate_ellipse_area_python(a=a, b=b)
area_r, metadata_r = calculate_ellipse_area_r(a=a, b=b)
area_haskell, metadata_haskell = calculate_ellipse_area_haskell(a=a, b=b)
area_julia, metadata_julia = calculate_ellipse_area_julia(a=a, b=b)
# Report on all results in a single task to simplify comparison
report_all_calculated_areas(
area_shell=area_shell,
metadata_shell=metadata_shell,
area_python=area_python,
metadata_python=metadata_python,
area_r=area_r,
metadata_r=metadata_r,
area_haskell=area_haskell,
metadata_haskell=metadata_haskell,
area_julia=area_julia,
metadata_julia=metadata_julia,
)
Note
Raw containers cannot be run locally at the moment.
Scripts#
The contents of each script mentioned above:
calculate-ellipse-area.sh#
#! /usr/bin/env sh
a=$(cat $1/a)
b=$(cat $1/b)
echo "4*a(1) * $a * $b" | bc -l | tee $2/area
echo "[from shell rawcontainer]" | tee $2/metadata
calculate-ellipse-area.py#
import math
import sys
def read_input(input_dir, v):
with open(f'{input_dir}/{v}', 'r') as f:
return float(f.read())
def write_output(output_dir, output_file, v):
with open(f'{output_dir}/{output_file}', 'w') as f:
f.write(str(v))
def calculate_area(a, b):
return math.pi * a * b
def main(input_dir, output_dir):
a = read_input(input_dir, 'a')
b = read_input(input_dir, 'b')
area = calculate_area(a, b)
write_output(output_dir, 'area', area)
write_output(output_dir, 'metadata', '[from python rawcontainer]')
if __name__ == '__main__':
input_dir = sys.argv[1]
output_dir = sys.argv[2]
main(input_dir, output_dir)
calculate-ellipse-area.R#
library(readr)
args = commandArgs(trailingOnly=TRUE)
input_dir = args[1]
output_dir = args[2]
a = read_lines(sprintf("%s/%s", input_dir, 'a'))
b = read_lines(sprintf("%s/%s", input_dir, 'b'))
area <- pi * as.double(a) * as.double(b)
print(area)
writeLines(as.character(area), sprintf("%s/%s", output_dir, 'area'))
writeLines("[from R rawcontainer]", sprintf("%s/%s", output_dir, 'metadata'))
calculate-ellipse-area.hs#
import System.IO
import System.Environment
import Text.Read
import Text.Printf
calculateEllipseArea :: Float -> Float -> Float
calculateEllipseArea a b = pi * a * b
main = do
args <- getArgs
let input_a = args!!0 ++ "/a"
input_b = args!!0 ++ "/b"
a <- readFile input_a
b <- readFile input_b
let area = calculateEllipseArea (read a::Float) (read b::Float)
let output_area = args!!1 ++ "/area"
output_metadata = args!!1 ++ "/metadata"
writeFile output_area (show area)
writeFile output_metadata "[from haskell rawcontainer]"
calculate-ellipse-area.jl#
using Printf
function calculate_area(a, b)
π * a * b
end
function read_input(input_dir, v)
open(@sprintf "%s/%s" input_dir v) do file
parse.(Float64, read(file, String))
end
end
function write_output(output_dir, output_file, v)
output_path = @sprintf "%s/%s" output_dir output_file
open(output_path, "w") do file
write(file, string(v))
end
end
function main(input_dir, output_dir)
a = read_input(input_dir, 'a')
b = read_input(input_dir, 'b')
area = calculate_area(a, b)
write_output(output_dir, "area", area)
write_output(output_dir, "metadata", "[from julia rawcontainer]")
end
# the keyword ARGS is a special value that contains the command-line arguments
# julia arrays are 1-indexed
input_dir = ARGS[1]
output_dir = ARGS[2]
main(input_dir, output_dir)
Total running time of the script: ( 0 minutes 0.000 seconds)