opentaskpy 0.7.0

A framework for automation execution of commands and transferring files between hosts

Open Task Framework (opentaskpy)

• Installation
• Configuration
  • Command Line Arguments
  • Environment Variables
  • Logging
  • Variables
    • Lookup plugins
      • Adding your own
    • Example Variables
• Task Definitions
  • Transfers
  • Executions
  • Batches
• Development
  • Quickstart for development
    • Building and uploading to PyPi

Open Task Framework (OTF) is a Python based framework to make it easy to run predefined file transfers and scripts/commands on remote machines.

Currently the framework is primarily based around being able to use SSH to communicate with remote hosts in order to manipulate files and run commands. This is done via the use of SSH keys, which must be set up in advance.

OTF has 3 main concepts for tasks. These are:

• Transfers
• Executions
• Batches

For more details, see the task types doc

Installation

OTF can be run either as an installed script, or via a docker container

Install via pip:

pip install opentaskpy

The task-run script will be added to your PATH, and you can invoke it directly.

To run via docker, use the Dockerfile to create your own base image using just the standard opentaskpy library. However if you want to install addons, you'll need to customise this, to install the additional packages first, before bundling it as a Docker image.

docker build -t opentaskpy -f Dockerfile . # Build the image
docker run --rm --volume /opt/otf/cfg:/cfg --volume /var/log/otf:/logs--volume /home/<USER>/.ssh/id_rsa:/id_rsa -e OTF_SSH_KEY=/id_rsa -e OTF_LOG_DIRECTORY=/logs task-run -t <TASK NAME> -c /cfg # Run a task

The default opentaskpy library is only really designed to use SSH for executions and file transfers. To do this, you need to make sure that the host/container that is running the task-run script has a private RSA key, that is trusted on all remote hosts that you're running against.

An environment variable OTF_SSH_KEY can be used to define a default SSH key to use for all SSH connectivity. This can be overridden at the transfer/execution level by specifying a keyFile in the credentials section of the protocol definition.

Configuration

There are several ways to customise the running of tasks.

Command Line Arguments

The following details the syntax of the task-run command:

usage: task-run [-h] -t TASKID [-r RUNID] [-v VERBOSITY] [-c CONFIGDIR]

options:
  -h, --help            show this help message and exit
  -t TASKID, --taskId TASKID
                        Name of the JSON config to run
  -r RUNID, --runId RUNID
                        Unique identifier to correlate logs with. e.g. if being triggered by an external scheduler
  -v VERBOSITY, --verbosity VERBOSITY
                        Increase verbosity
  -c CONFIGDIR, --configDir CONFIGDIR
                        Directory containing task configurations

-t, --taskId

This relates to the specific task that you want to run. It is the name of the configuration file to load (without the .json suffix), contained under the CONFIGDIR

-r, --runId

A log aggregation mechanism to bundle logs for several steps in a batch together. e.g. if you pass in -r some_job_name, the log files for all executions and transfers will be placed under <logdir>/some_job_name/

-v, --verbosity

There are 3 levels of logging, beyond the default INFO level. These are VERBOSE1 (1), VERBOSE2 (2), and DEBUG (3).

VERBOSITY is an integer; 1, 2 or 3

-c, --configDir

The directory containing all of the config files. These are the task definition JSON files, as well as the variables Jinja2 template file.

In order for the process to run, you must have at least one task, and a variables.json.j2 file, even if it's just an empty object definition

Environment Variables

These are some environment variables that can be used to customise the behaviour of the application. There are some internally used variables too, but changing them without a full understanding of the code is not advised.

• OTF_NO_LOG - Disable logging to file. Only log to stderr
• OTF_LOG_DIRECTORY - Path under which log files are written
• OTF_RUN_ID - (meant for internal use) An aggregator for log files. When set, all log files for a run will go under this sub directory. E.g. running a batch, all execution and transfer logs will be dropped into this sub directory, rather than a directory for each task name. This is equivalent to using -r or --runId command line arguments, which is generally preferred.
• OTF_SSH_KEY - The private SSH key to use by default for all SSH connections. This is essential when using a basic docker container to trigger OTF. If not specified, it will default to use any private SSH keys available to the user executing the application.

Logging

By default, OTF will log to a directory called logs in the current working directory. For the docker containers, unless overridden by OTF_LOG_DIRECTORY, it will write to /logs using a symlink at /app/logs

Variables

Variables can exist at a global level, and also on a per-task basis.

You must always have a variables.json.j2 file defined at the root of your configDir.

Variables can be used using the Jinja2 template syntax within task definitions. They can also be nested.

Individual tasks can have their own local variables too

Lookup plugins

Static variables are useful, however sometimes you need to look up something a bit more dynamic, or secret, that you don't want to hard code into the variables file.

There are 2 default lookup plugins available:

• File
• HTTP JSON

The file plugin will load the content of a file into the variable e.g.

"{{ lookup('file', path='/tmp/variable_lookup.txt') }}"

The HTTP JSON plugin will perform a very basic HTTP GET request, expecting a JSON response. The value to extract is defined by a jsonpath e.g.

"{{ lookup('http_json', url='https://jsonplaceholder.typicode.com/posts/1', jsonpath='$.title') }}"

This will hit the typicode.com side, and extract the title attribute from from the returned JSON file

Adding your own

OTF will look for plugins that are either available as an installed module (under the opentaskpy.plugins.lookup namespace), or dropped in a plugins under the config directory.

An example Python module might be: opentaskpy.plugins.lookup.aws.ssm. This can then be referenced as a variable in a template like so:

"{{ lookup('aws.ssm', name='my_test_param') }}"

Alternatively a lookup plugin could be placed under cfg/plugins named my_lookup.py, and used in a template:

"{{ lookup('my_lookup', name='my_param') }}"

Example Variables

Below are examples of some useful variables to start with:

"YYYY": "{{ now().strftime('%Y') }}",
"MM": "{{ now().strftime('%m') }}",
"DD": "{{ now().strftime('%d') }}",
"TODAY": "{{ YYYY }}{{ MM }}{{ DD }}",
"MONTH_SHORT": "{{ now().strftime('%b') }}",
"DAY_SHORT": "{{ now().strftime('%a') }}",
"PREV_DD": "{{ (now()|delta_days(-1)).strftime('%d') }}",
"PREV_MM": "{{ (now()|delta_days(-1)).strftime('%m') }}",
"PREV_YYYY": "{{ (now()|delta_days(-1)).strftime('%Y') }}"

Usage:

"fileRegex": "somefile.*{{ YYYY }}\\.txt"

Task Definitions

Task definitions are validated using the JSON Schemas defined within src/opentaskpy/config/schemas/. These are split up to make them more readable. The top level schema for each task type is defined within the schemas.py file, one level above.

At a later date, I plan to automate the creation of the JSON schema documentation.

Transfers

Transfers consist of a source definition, and an optional destination.

The easiest way to see usage is to look at the examples under the examples directory

Below is an example of all the options available for a transfer:

{
  "type": "transfer",
  "source": {
    "hostname": "{{ HOST_A }}",
    "directory": "/tmp/testFiles/src",
    "fileRegex": ".*\\.txt",
    "fileWatch": {
      "timeout": 15,
      "directory": "/tmp/testFiles/src",
      "fileRegex": "fileWatch\\.txt"
    },
    "logWatch": {
      "timeout": 15,
      "directory": "/tmp/testFiles/src",
      "log": "log{{ YYYY }}Watch1.log",
      "contentRegex": "someText[0-9]",
      "tail": true
    },
    "conditionals": {
      "size": {
        "gt": 10,
        "lt": 20
      },
      "age": {
        "gt": 60,
        "lt": 600
      }
    },
    "postCopyAction": {
      "action": "move",
      "destination": "/tmp/testFiles/archive"
    },
    "protocol": {
      "name": "ssh",
      "credentials": {
        "username": "{{ SSH_USERNAME }}"
      }
    }
  },
  "destination": [
    {
      "hostname": "{{ HOST_B }}",
      "directory": "/tmp/testFiles/dest",
      "permissions": {
        "group": "operator"
      },
      "protocol": {
        "name": "ssh",
        "credentials": {
          "username": "{{ SSH_USERNAME }}"
        }
      }
    },
    {
      "hostname": "{{ HOST_B }}",
      "directory": "/tmp/testFiles/dest",
      "transferType": "pull",
      "rename": {
        "pattern": "^(.*)\\.txt$",
        "sub": "\\1-2.txt"
      },
      "protocol": {
        "name": "ssh",
        "credentials": {
          "username": "{{ SSH_USERNAME }}",
          "transferUsername": "{{ SSH_USERNAME }}"
        }
      }
    }
  ]
}

An explaination of what's going on in the order it will handled:

1. Tail the log file matching named: /tmp/testFiles/src/log{{ YYYY }}Watch1.log for lines matching containing the regex someText[0-9], for up to 15 seconds, before giving up.
2. Poll for a file matching the regex /tmp/testFiles/src/fileWatch\.txt for up to 15 seconds.
3. Find all files matching the regex /tmp/testFiles/src/.*\.txt, with the conditions that the are >10B and <20B in size, as well as being older than 60 seconds, but newer than 600 seconds since last modification
4. Transfer the files that were found to 2 destinations.
   1. The first destination is a simple SCP from HOST_A to HOST_B where the file is placed under /tmp/testFiles/dest. The group ownership of the file(s) is then set to operator
   2. The second destination is done via a pull from the destination server into the same directory. The SCP connects to HOST_A as transferUsername. Once the file has been retrieved, it is renamed using the following regex match ^(.*)\.txt$ and substitution \1-2.txt
5. Transferred files are moved into /tmp/testFiles/archive on HOST_A

Executions

Executions are the simplest task to configure. They consist of a list of hosts to run on, the username to run/connect as, and the command to run.

Executions do not currently have a timeout, so can in theory run forever, or until they are killed. If a timeout is required, either use a wrapper script on the host the command is being executed on, or they should be wrapped inside a batch.

{
  "type": "execution",
  "hosts": [
    "{{ HOST_A }}"
  ],
  "directory": "/tmp/testFiles/src",
  "command": "touch touchedFile.txt",
  "protocol": {
    "name": "ssh",
    "credentials": {
      "username": "{{ SSH_USERNAME }}"
    }
  }
}

The above is running the command touch touchedFile.txt on {{ HOST_A }}, from within the /tmp/testFiles/src directory.

If multiple hosts are defined, a thread is spawned in parallel for each host. If the command fails on any of the hosts in the list, it will cause the task run to fail, once all processes have returned a result.

Batches

Batches are a little more complex. They do not contain any task definitions, only the list, and order of excecution for each task.

A batch task can have multiple options set that determine the execution order and conditions, as well as how failures and task reruns are handled.

Each task in a batch has an order_id, this is a unique ID for each task, and is primarily used to define dependencies.

dependencies can be applied to any task, and are simply a list of other tasks that must be completed before it is triggered.

continue_on_fail is a boolean that defines whether a failure would cause the whole batch to fail immediately (after existing tasks have finished executing), or whether following steps get run. This defaults to false if not defined.

retry_on_rerun is a boolean that determines whether a successful task is run a second time following a failed run. If a batch exits with a failure, and then the script is reun later on that same day, by default only the steps that failed will be run. All steps can be forced to run by setting this to true

timeout specifies the number of seconds a task is allowed to be running before it gets terminated. This counts as a failure. The default timeout, if not specified is 300 seconds.

Development

This repo has been primarily configured to work with GitHub Codespaces devcontainers, though it can obviously be used directly on your machine too.

Dev and runtime packages are defined via pipenv, with a requirements.txt for the runtime package requirements

Quickstart for development

• Clone this repo
• pip install pipenv
• pipenv --python 3.10 && pipenv install && cd src && pipenv install --editable .

Building and uploading to PyPi

python3 -m build
python3 -m twine upload --repository testpypi dist/*