Integrate uProc with hunter

uProc?

UProc is a framework that allows you to automate your tasks. It consists of several modules that are responsible for different tasks. The important thing about this framework is that it can be easily integrated into your existing python projects. You can integrate it into an existing project or create a separate project. It is also possible to use it as a stand-alone top. For integrating the uProc framework, you have to install it first.

hunter?

Hunter is a module of uProc that is responsible for running series of tasks in parallel or sequential order. This module can also handle download/upload files and move them to/from S3 bucket. It is possible to define actions using YAML file. Hunter module can run different tasks in parallel or sequential order. The execution order of the tasks is defined in the YAML file.

Integration of uProc and hunter

The integration of uProc and hunter is done by adding hunter module to the uProc framework. First, you should install uProc framework. The installation steps are given below:

$ pip install uproc_core $ pip install uproc_hunter $ pip install uproc_ranger $ pip install uproc_googlecloudstorage $ pip install uproc_awscli $ pip install uproc_s3cmd $ pip install uproc_jq $ pip install uproc_boto3 $ pip install uproc_dynamodb $ pip install uproc_gcloud $ pip install uproc_s3fs $ pip install uproc_s3backup $ pip install uproc_sqs $ pip install uproc_kinesis $ pip install uproc_datadog $ pip install uproc_pagerduty $ pip install uproc_openstack $ pip install uproc_azureblob $ pip install uproc_uservoice $ pip install PyMySQL

After installing all the modules, you can create your first task using the fplowing command:

$ mkdir ~/mytask $ cd ~/mytask $ cat << EOF > mytask.yaml --- type. s3 params. command. - s3cmd put -f myfile.txt s3://mybucket destination. - s3://mybucket/myfile.txt EOF # Run the task with the fplowing command. $ python >>> import sys >>> from uProcess import * >>> from hunter import * >>> from os import listdir >>> src = sys.argv[1] >>> cmd = sys.argv[2] >>> conf = {'src':src, 'cmd':cmd} >>> proc = Process('mytask', conf. >>> print(proc. <Process(uProcess. at 0x7ffeb8516e08> >>> proc.run(. # wait for the task to finish before exiting the program >>> exit()

The output of this example would be similar to the fplowing:

$ python mytask.py ~/mytask/mytask.yaml s3://mybucket/myfile.txt s3://mybucket/myfile.txt 0 file(s. copied using 0 MiB of memory in 0 seconds

Benefits of Integration of uProc and hunter

There are many benefits of integration of uProc and hunter such as:

You can easily modify the parameters used by any module without touching code that uses another module. You can run tasks in parallel or run them sequentially You can upload/download files and move them to/from S3 bucket You can connect data sources and target data sources and manage data between them You can use any data source as a trigger for tasks You can provide feedback to users after performing a task You can use different programming languages such as python, nodejs, java, etc. to perform different tasks You can write more than one task at a time and execute them asynchronously You can create more than one task and use them later You can implement complex logic that will be performed on different machines You can publish tasks and execute them on your local machine or on remote machines You can use any language that supports AWS SDKs such as python, nodejs, java, etc. You can create reusable modules and use them whenever you want When you use a new cloud provider, you just need to add one line to your config file instead of modifying the code of your application Running single commands on multiple machines using different programming languages such as python, nodejs, java, etc

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