Script
Execute a Python script.
type: "io.kestra.plugin.scripts.python.Script"Execute a Python script and generate an output.
id: python_demo
namespace: company.team
tasks:
- id: python
type: io.kestra.plugin.scripts.python.Script
beforeCommands:
- pip install requests
script: |
from kestra import Kestra
import requests
response = requests.get('https://kestra.io')
print(response.status_code)
Kestra.outputs({'status': response.status_code, 'text': response.text})
Log messages at different log levels using Kestra logger.
id: python_logs
namespace: company.team
tasks:
- id: python_logger
type: io.kestra.plugin.scripts.python.Script
allowFailure: true
warningOnStdErr: false
script: |
import time
from kestra import Kestra
logger = Kestra.logger()
logger.debug("DEBUG is used for diagnostic info.")
time.sleep(0.5)
logger.info("INFO confirms normal operation.")
time.sleep(0.5)
logger.warning("WARNING signals something unexpected.")
time.sleep(0.5)
logger.error("ERROR indicates a serious issue.")
time.sleep(0.5)
logger.critical("CRITICAL means a severe failure.")
Execute a Python script with a file stored in Kestra's local storage created by a previous task.
id: pass_data_between_tasks
namespace: company.team
tasks:
- id: download
type: io.kestra.plugin.core.http.Download
uri: https://huggingface.co/datasets/kestra/datasets/raw/main/csv/orders.csv
- id: python
type: io.kestra.plugin.scripts.python.Script
script: |
with open('{{ outputs.download.uri }}', 'r') as f:
print(f.read())
Execute a Python script that outputs a file.
id: python_output_file
namespace: company.team
tasks:
- id: python
type: io.kestra.plugin.scripts.python.Script
outputFiles:
- "myfile.txt"
script: |
f = open("myfile.txt", "a")
f.write("Hello from a Kestra task!")
f.close()
If you want to generate files in your script to make them available for download and use in downstream tasks, you can leverage the outputFiles property as shown in the example above. Files will be persisted in Kestra's internal storage. The first task in this example creates a file 'clean_dataset.csv' and the next task can access it by leveraging the syntax {{outputs.yourTaskId.outputFiles['yourFileName.fileExtension']}}.
id: python_outputs
namespace: company.team
tasks:
- id: clean_dataset
type: io.kestra.plugin.scripts.python.Script
containerImage: ghcr.io/kestra-io/pydata:latest
outputFiles:
- "clean_dataset.csv"
script: |
import pandas as pd
df = pd.read_csv("https://huggingface.co/datasets/kestra/datasets/raw/main/csv/messy_dataset.csv")
# Replace non-numeric age values with NaN
df["Age"] = pd.to_numeric(df["Age"], errors="coerce")
# mean imputation: fill NaN values with the mean age
mean_age = int(df["Age"].mean())
print(f"Filling NULL values with mean: {mean_age}")
df["Age"] = df["Age"].fillna(mean_age)
df.to_csv("clean_dataset.csv", index=False)
- id: read_file_from_python
type: io.kestra.plugin.scripts.shell.Commands
taskRunner:
type: io.kestra.plugin.core.runner.Process
commands:
- head -n 10 {{ outputs.clean_dataset.outputFiles['clean_dataset.csv'] }}
Which interpreter to use.
The inline script content. This property is intended for the script file's content as a (multiline) string, not a path to a file. To run a command from a file such as bash myscript.sh or python myscript.py, use the Commands task instead.
The target operating system where the script will run.
A list of commands that will run before the commands, allowing to set up the environment e.g. pip install -r requirements.txt.
The task runner container image, only used if the task runner is container-based.
Deprecated - use the 'taskRunner' property instead.
Only used if the taskRunner property is not set
Additional environment variables for the current process.
The files to create on the local filesystem. It can be a map or a JSON object.
Inject namespace files.
Inject namespace files to this task. When enabled, it will, by default, load all namespace files into the working directory. However, you can use the include or exclude properties to limit which namespace files will be injected.
The files from the local filesystem to send to Kestra's internal storage.
Must be a list of glob expressions relative to the current working directory, some examples: my-dir/**, my-dir/*/** or my-dir/my-file.txt.
Deprecated - use the 'taskRunner' property instead.
Only used if the taskRunner property is not set
The task runner to use.
Task runners are provided by plugins, each have their own properties.
The exit code of the entire flow execution.
The output files' URIs in Kestra's internal storage.
The value extracted from the output of the executed commands.
A list of filters to exclude matching glob patterns. This allows you to exclude a subset of the Namespace Files from being downloaded at runtime. You can combine this property together with include to only inject a subset of files that you need into the task's working directory.
A list of filters to include only matching glob patterns. This allows you to only load a subset of the Namespace Files into the working directory.
The maximum amount of kernel memory the container can use.
The minimum allowed value is 4MB. Because kernel memory cannot be swapped out, a container which is starved of kernel memory may block host machine resources, which can have side effects on the host machine and on other containers. See the kernel-memory docs for more details.
The maximum amount of memory resources the container can use.
Make sure to use the format number + unit (regardless of the case) without any spaces.
The unit can be KB (kilobytes), MB (megabytes), GB (gigabytes), etc.
Given that it's case-insensitive, the following values are equivalent:
"512MB""512Mb""512mb""512000KB""0.5GB"
It is recommended that you allocate at least 6MB.
Allows you to specify a soft limit smaller than memory which is activated when Docker detects contention or low memory on the host machine.
If you use memoryReservation, it must be set lower than memory for it to take precedence. Because it is a soft limit, it does not guarantee that the container doesn’t exceed the limit.
The total amount of memory and swap that can be used by a container.
If memory and memorySwap are set to the same value, this prevents containers from using any swap. This is because memorySwap includes both the physical memory and swap space, while memory is only the amount of physical memory that can be used.
A setting which controls the likelihood of the kernel to swap memory pages.
By default, the host kernel can swap out a percentage of anonymous pages used by a container. You can set memorySwappiness to a value between 0 and 100 to tune this percentage.
Docker image to use.
Docker configuration file.
Docker configuration file that can set access credentials to private container registries. Usually located in ~/.docker/config.json.
Limits the CPU usage to a given maximum threshold value.
By default, each container’s access to the host machine’s CPU cycles is unlimited. You can set various constraints to limit a given container’s access to the host machine’s CPU cycles.
Docker entrypoint to use.
Extra hostname mappings to the container network interface configuration.
Docker API URI.
Limits memory usage to a given maximum threshold value.
Docker can enforce hard memory limits, which allow the container to use no more than a given amount of user or system memory, or soft limits, which allow the container to use as much memory as it needs unless certain conditions are met, such as when the kernel detects low memory or contention on the host machine. Some of these options have different effects when used alone or when more than one option is set.
Docker network mode to use e.g. host, none, etc.
The image pull policy for a container image and the tag of the image, which affect when Docker attempts to pull (download) the specified image.
Size of /dev/shm in bytes.
The size must be greater than 0. If omitted, the system uses 64MB.
User in the Docker container.
List of volumes to mount.
Must be a valid mount expression as string, example : /home/user:/app.
Volumes mount are disabled by default for security reasons; you must enable them on server configuration by setting kestra.tasks.scripts.docker.volume-enabled to true.
The registry authentication.
The auth field is a base64-encoded authentication string of username: password or a token.
The identity token.
The registry password.
The registry URL.
If not defined, the registry will be extracted from the image name.
The registry token.
The registry username.
A list of capabilities; an OR list of AND lists of capabilities.
Driver-specific options, specified as key/value pairs.
These options are passed directly to the driver.