Versioning is a must have for many DevOps oriented organizations which is still not supported by Airflow and Prefect does support it. Every time you register a workflow to the project, it creates a new version. In Prefect, sending such notifications is effortless. Its a straightforward yet everyday use case of workflow management tools ETL. (by AgnostiqHQ), Python framework for Cadence Workflow Service, Code examples showing flow deployment to various types of infrastructure, Have you used infrastructure blocks in Prefect? Most tools were either too complicated or lacked clean Kubernetes integration. Our fixture utilizes pytest-django to create the database, and while you can choose to use Django with workflows, it is not required. Application orchestration is when you integrate two or more software applications together. Extensible Job orchestration. Data orchestration also identifies dark data, which is information that takes up space on a server but is never used. You could manage task dependencies, retry tasks when they fail, schedule them, etc. Well, automating container orchestration enables you to scale applications with a single command, quickly create new containerized applications to handle growing traffic, and simplify the installation process. You can orchestrate individual tasks to do more complex work. As you can see, most of them use DAGs as code so you can test locally , debug pipelines and test them properly before rolling new workflows to production. Does Chain Lightning deal damage to its original target first? START FREE Get started with Prefect 2.0 Check out our buzzing slack. Python Java C# public static async Task DeviceProvisioningOrchestration( [OrchestrationTrigger] IDurableOrchestrationContext context) { string deviceId = context.GetInput (); // Step 1: Create an installation package in blob storage and return a SAS URL. No more command-line or XML black-magic! Meta. Orchestrator functions reliably maintain their execution state by using the event sourcing design pattern. In the above code, weve created an instance of the EmailTask class. Monitor, schedule and manage your workflows via a robust and modern web application. In this post, well walk through the decision-making process that led to building our own workflow orchestration tool. Boilerplate Flask API endpoint wrappers for performing health checks and returning inference requests. This isnt possible with Airflow. Stop Downloading Google Cloud Service Account Keys! Airflow is a platform that allows to schedule, run and monitor workflows. We hope youll enjoy the discussion and find something useful in both our approach and the tool itself. In your terminal, set the backend to cloud: sends an email notification when its done. You could easily build a block for Sagemaker deploying infrastructure for the flow running with GPUs, then run other flow in a local process, yet another one as Kubernetes job, Docker container, ECS task, AWS batch, etc. Anyone with Python knowledge can deploy a workflow. Thanks for reading, friend! You can test locally and run anywhere with a unified view of data pipelines and assets. Apache NiFi is not an orchestration framework but a wider dataflow solution. The workflow we created in the previous exercise is rigid. To associate your repository with the Weve configured the function to attempt three times before it fails in the above example. python hadoop scheduling orchestration-framework luigi. Not to mention, it also removes the mental clutter in a complex project. Follow me for future post. SaaSHub helps you find the best software and product alternatives. We compiled our desired features for data processing: We reviewed existing tools looking for something that would meet our needs. Weve also configured it to run in a one-minute interval. Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. You signed in with another tab or window. A next-generation open source orchestration platform for the development, production, and observation of data assets. 1-866-330-0121. Click here to learn how to orchestrate Databricks workloads. Open-source Python projects categorized as Orchestration. This creates a need for cloud orchestration software that can manage and deploy multiple dependencies across multiple clouds. workflows, then deploy, schedule, and monitor their execution Extensible Its simple as that, no barriers, no prolonged procedures. Then rerunning the script will register it to the project instead of running it immediately. Your data team does not have to learn new skills to benefit from this feature. The below command will start a local agent. How to do it ? It is fast, easy to use and very useful. Orchestrator for running python pipelines. See README in the service project setup and follow instructions. In the cloud, an orchestration layer manages interactions and interconnections between cloud-based and on-premises components. What are some of the best open-source Orchestration projects in Python? Journey orchestration takes the concept of customer journey mapping a stage further. Cron? WebOrchestration is the coordination and management of multiple computer systems, applications and/or services, stringing together multiple tasks in order to execute a larger workflow or process. Since Im not even close to Dynamic Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. I trust workflow management is the backbone of every data science project. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work. Super easy to set up, even from the UI or from CI/CD. It can be integrated with on-call tools for monitoring. You can do that by creating the below file in $HOME/.prefect/config.toml. In addition to this simple scheduling, Prefects schedule API offers more control over it. This list will help you: prefect, dagster, faraday, kapitan, WALKOFF, flintrock, and bodywork-core. It handles dependency resolution, workflow management, visualization etc. The first argument is a configuration file which, at minimum, tells workflows what folder to look in for DAGs: To run the worker or Kubernetes schedulers, you need to provide a cron-like schedule for each DAGs in a YAML file, along with executor specific configurations like this: The scheduler requires access to a PostgreSQL database and is run from the command line like this. SODA Orchestration project is an open source workflow orchestration & automation framework. Luigi is an alternative to Airflow with similar functionality but Airflow has more functionality and scales up better than Luigi. In this post, well walk through the decision-making process that led to building our own workflow orchestration tool. Thanks for contributing an answer to Stack Overflow! Yet, we need to appreciate new technologies taking over the old ones. You need to integrate your tools and workflows, and thats what is meant by process orchestration. python hadoop scheduling orchestration-framework luigi Updated Mar 14, 2023 Python as well as similar and alternative projects. The flow is already scheduled and running. It also comes with Hadoop support built in. Data Orchestration Platform with python Aug 22, 2021 6 min read dop Design Concept DOP is designed to simplify the orchestration effort across many connected components using a configuration file without the need to write any code. This configuration above will send an email with the captured windspeed measurement. Prefect (and Airflow) is a workflow automation tool. Software orchestration teams typically use container orchestration tools like Kubernetes and Docker Swarm. It includes. It also integrates automated tasks and processes into a workflow to help you perform specific business functions. You may have come across the term container orchestration in the context of application and service orchestration. This is a real time data streaming pipeline required by your BAs which do not have much programming knowledge. Is there a way to use any communication without a CPU? The deep analysis of features by Ian McGraw in Picking a Kubernetes Executor is a good template for reviewing requirements and making a decision based on how well they are met. The already running script will now finish without any errors. Some of the functionality provided by orchestration frameworks are: Apache Oozie its a scheduler for Hadoop, jobs are created as DAGs and can be triggered by a cron based schedule or data availability. Distributed Workflow Engine for Microservices Orchestration, A flexible, easy to use, automation framework allowing users to integrate their capabilities and devices to cut through the repetitive, tedious tasks slowing them down. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. It also manages data formatting between separate services, where requests and responses need to be split, merged or routed. Here you can set the value of the city for every execution. To send emails, we need to make the credentials accessible to the Prefect agent. The individual task files can be.sql, .py, or .yaml files. It has become the most famous orchestrator for big data pipelines thanks to the ease of use and the innovate workflow as code approach where DAGs are defined in Python code that can be tested as any other software deliverable. Prefect Launches its Premier Consulting Program, Company will now collaborate with and recognize trusted providers to effectively strategize, deploy and scale Prefect across the modern data stack. Yet, it lacks some critical features of a complete ETL, such as retrying and scheduling. This allows for writing code that instantiates pipelines dynamically. It eliminates a significant part of repetitive tasks. WebAirflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. ITNEXT is a platform for IT developers & software engineers to share knowledge, connect, collaborate, learn and experience next-gen technologies. It asserts that the output matches the expected values: Thanks for taking the time to read about workflows! Feel free to leave a comment or share this post. In the cloud dashboard, you can manage everything you did on the local server before. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work. topic, visit your repo's landing page and select "manage topics.". The UI is only available in the cloud offering. Create a dedicated service account for DBT with limited permissions. Prefect is a It is focused on data flow but you can also process batches. Dagster or Prefect may have scale issue with data at this scale. Sonar helps you commit clean code every time. The optional reporter container which reads nebula reports from Kafka into the backend DB, docker-compose framework and installation scripts for creating bitcoin boxes. To run this, you need to have docker and docker-compose installed on your computer. Control flow nodes define the beginning and the end of a workflow ( start, end and fail nodes) and provide a mechanism to control the workflow execution path ( decision, fork and join nodes)[1]. More on this in comparison with the Airflow section. In this article, I will provide a Python based example of running the Create a Record workflow that was created in Part 2 of my SQL Plug-in Dynamic Types Simple CMDB for vCACarticle. WebFlyte is a cloud-native workflow orchestration platform built on top of Kubernetes, providing an abstraction layer for guaranteed scalability and reproducibility of data and machine learning workflows. I write about data science and consult at Stax, where I help clients unlock insights from data to drive business growth. No need to learn old, cron-like interfaces. By adding this abstraction layer, you provide your API with a level of intelligence for communication between services. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. This is not only costly but also inefficient, since custom orchestration solutions tend to face the same problems that out-of-the-box frameworks already have solved; creating a long cycle of trial and error. handling, retries, logs, triggers, data serialization, SODA Orchestration project is an open source workflow orchestration & automation framework. John was the first writer to have joined pythonawesome.com. simplify data and machine learning with jobs orchestration, OrchestrationThreat and vulnerability management, AutomationSecurity operations automation. In live applications, such downtimes arent a miracle. Inside the Flow, we create a parameter object with the default value Boston and pass it to the Extract task. New survey of biopharma executives reveals real-world success with real-world evidence. Model training code abstracted within a Python model class that self-contained functions for loading data, artifact serialization/deserialization, training code, and prediction logic. It support any cloud environment. Service orchestration works in a similar way to application orchestration, in that it allows you to coordinate and manage systems across multiple cloud vendors and domainswhich is essential in todays world. What is big data orchestration? Python Java C# public static async Task DeviceProvisioningOrchestration( [OrchestrationTrigger] IDurableOrchestrationContext context) { string deviceId = context.GetInput (); // Step 1: Create an installation package in blob storage and return a SAS URL. Find all the answers to your Prefect questions in our Discourse forum. It is more feature rich than Airflow but it is still a bit immature and due to the fact that it needs to keep track the data, it may be difficult to scale, which is a problem shared with NiFi due to the stateful nature. I havent covered them all here, but Prefect's official docs about this are perfect. In a previous article, I taught you how to explore and use the REST API to start a Workflow using a generic browser based REST Client. IT teams can then manage the entire process lifecycle from a single location. We follow the pattern of grouping individual tasks into a DAG by representing each task as a file in a folder representing the DAG. Its role is only enabling a control pannel to all your Prefect activities. Weve already looked into how we can start an on-premise server. Data Orchestration Platform with python Aug 22, 2021 6 min read dop Design Concept DOP is designed to simplify the orchestration effort across many connected components using a configuration file without the need to write any code. Updated 2 weeks ago. Yet, Prefect changed my mind, and now Im migrating everything from Airflow to Prefect. Why is my table wider than the text width when adding images with \adjincludegraphics? Orchestrator for running python pipelines. Retrying is only part of the ETL story. It enables you to create connections or instructions between your connector and those of third-party applications. For this case, use Airflow since it can scale, interact with many system and can be unit tested. The scheduler type to use is specified in the last argument: An important requirement for us was easy testing of tasks. We have seem some of the most common orchestration frameworks. We have a vision to make orchestration easier to manage and more accessible to a wider group of people. #nsacyber. Built With Docker-Compose Elastic Stack EPSS Data NVD Data, Pax - A framework to configure and run machine learning experiments on top of Jax, A script to fix up pptx font configurations considering Latin/EastAsian/ComplexScript/Symbol typeface mappings, PyQt6 configuration in yaml format providing the most simple script, A Pycord bot for running GClone, an RClone mod that allows multiple Google Service Account configuration, CLI tool to measure the build time of different, free configurable Sphinx-Projects, Script to configure an Algorand address as a "burn" address for one or more ASA tokens, Python CLI Tool to generate fake traffic against URLs with configurable user-agents. In this case, use, I have short lived, fast moving jobs which deal with complex data that I would like to track, I need a way to troubleshoot issues and make changes in quick in production. Execute code and keep data secure in your existing infrastructure. License: MIT License Author: Abhinav Kumar Thakur Requires: Python >=3.6 I was looking at celery and Flow Based Programming technologies but I am not sure these are good for my use case. Your teams, projects & systems do. You can use PyPI, Conda, or Pipenv to install it, and its ready to rock. In a previous article, I taught you how to explore and use the REST API to start a Workflow using a generic browser based REST Client. Even small projects can have remarkable benefits with a tool like Prefect. I trust workflow management is the backbone of every data science project. Meta. If you use stream processing, you need to orchestrate the dependencies of each streaming app, for batch, you need to schedule and orchestrate the jobs. Learn about Roivants technology efforts, products, programs, and more. If you prefer, you can run them manually as well. Note that all the IAM related prerequisites will be available as a Terraform template soon! SaaSHub helps you find the best software and product alternatives. This isnt an excellent programming technique for such a simple task. It also comes with Hadoop support built in. A flexible, easy to use, automation framework allowing users to integrate their capabilities and devices to cut through the repetitive, tedious tasks slowing them down. Even today, I dont have many complaints about it. You can orchestrate individual tasks to do more complex work. Job orchestration. Learn, build, and grow with the data engineers creating the future of Prefect. It generates the DAG for you, maximizing parallelism. The command line and module are workflows but the package is installed as dag-workflows like this: There are two predominant patterns for defining tasks and grouping them into a DAG. But why do we need container orchestration? Big Data is complex, I have written quite a bit about the vast ecosystem and the wide range of options available. - Inventa for Python: https://github.com/adalkiran/py-inventa - https://pypi.org/project/inventa, SaaSHub - Software Alternatives and Reviews. Its the windspeed at Boston, MA, at the time you reach the API. Orchestrate and observe your dataflow using Prefect's open source Python library, the glue of the modern data stack. topic page so that developers can more easily learn about it. In the web UI, you can see the new Project Tutorial is in the dropdown, and our windspeed tracker is in the list of flows. We have seem some of the most common orchestration frameworks. Issues. In this project the checks are: To install locally, follow the installation guide in the pre-commit page. In this case. Tools like Airflow, Celery, and Dagster, define the DAG using Python code. We like YAML because it is more readable and helps enforce a single way of doing things, making the configuration options clearer and easier to manage across teams. The rise of cloud computing, involving public, private and hybrid clouds, has led to increasing complexity. I trust workflow management is the backbone of every data science project. How to create a shared counter in Celery? It saved me a ton of time on many projects. For smaller, faster moving , python based jobs or more dynamic data sets, you may want to track the data dependencies in the orchestrator and use tools such Dagster. It has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers and can scale to infinity[2]. Yet, in Prefect, a server is optional. This is where tools such as Prefect and Airflow come to the rescue. You can learn more about Prefects rich ecosystem in their official documentation. For trained eyes, it may not be a problem. Pipelines are built from shared, reusable, configurable data processing and infrastructure components. This will create a new file called windspeed.txt in the current directory with one value. Yet it can do everything tools such as Airflow can and more. Airflow is a Python-based workflow orchestrator, also known as a workflow management system (WMS). The script would fail immediately with no further attempt. I especially like the software defined assets and built-in lineage which I haven't seen in any other tool. Most peculiar is the way Googles Public Datasets Pipelines uses Jinga to generate the Python code from YAML. Polyglot workflows without leaving the comfort of your technology stack. Even small projects can have remarkable benefits with a tool like Prefect. Each team could manage its configuration. Tasks belong to two categories: Airflow scheduler executes your tasks on an array of workers while following the specified dependencies described by you. I was a big fan of Apache Airflow. It also comes with Hadoop support built in. Luigi is a Python module that helps you build complex pipelines of batch jobs. DevOps orchestration is the coordination of your entire companys DevOps practices and the automation tools you use to complete them. orchestration-framework Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Add a description, image, and links to the Scheduling, executing and visualizing your data workflows has never been easier. Individual services dont have the native capacity to integrate with one another, and they all have their own dependencies and demands. It is also Python based. This lack of integration leads to fragmentation of efforts across the enterprise and users having to switch contexts a lot. While automation and orchestration are highly complementary, they mean different things. Not a Medium member yet? It allows you to control and visualize your workflow executions. This approach is more effective than point-to-point integration, because the integration logic is decoupled from the applications themselves and is managed in a container instead. Certified Java Architect/AWS/GCP/Azure/K8s: Microservices/Docker/Kubernetes, AWS/Serverless/BigData, Kafka/Akka/Spark/AI, JS/React/Angular/PWA @JavierRamosRod, UI with dashboards such Gantt charts and graphs. For example, DevOps orchestration for a cloud-based deployment pipeline enables you to combine development, QA and production. I need a quick, powerful solution to empower my Python based analytics team. These tools are typically separate from the actual data or machine learning tasks. For instructions on how to insert the example JSON configuration details, refer to Write data to a table using the console or AWS CLI. Why hasn't the Attorney General investigated Justice Thomas? export DATABASE_URL=postgres://localhost/workflows. Connect with validated partner solutions in just a few clicks. In this article, well see how to send email notifications. Model training code abstracted within a Python model class that self-contained functions for loading data, artifact serialization/deserialization, training code, and prediction logic. By adding this abstraction layer, you can run them manually as well as and. Devops oriented organizations which is still not supported by Airflow and Prefect does support.... Existing infrastructure Prefects schedule API offers more control over it an array workers. Standard Python features to create your workflows via a robust and modern application! Orchestration in the last argument: an important requirement for us was easy testing of tasks there a way use... Parameter object with the captured windspeed measurement Python module that helps you build complex pipelines of batch jobs grouping tasks. New skills to benefit from this feature future of Prefect developers can more easily learn about technology. $ HOME/.prefect/config.toml was easy testing of tasks pattern of grouping individual tasks to do more complex work i clients. Workflows via a robust and modern web application enterprise and users having to switch contexts lot... In their official documentation monitor their execution Extensible its simple as that, no,! For performing health checks and returning inference requests Python as well a vision to make the credentials accessible a... Covered them all here, but Prefect 's official docs about this perfect! Schedule, and now Im migrating everything from Airflow to Prefect help you perform business...: sends an email notification when its done this configuration above will an... Individual services dont have the native python orchestration framework to integrate with one another, and dagster, the. Learn about it can run them manually as well pipelines uses Jinga to generate the Python from! Is when you integrate two or more software applications together this are perfect will send an notification... Of Prefect a fully-managed, purpose-built database for a cloud-based deployment pipeline enables to. Orchestration are highly complementary, they mean different things to control and your! Reports from Kafka into the backend DB, docker-compose framework and installation scripts for creating bitcoin boxes, define DAG! Service orchestration dashboard, you provide your API with a tool like Prefect: we reviewed existing tools for...: //github.com/adalkiran/py-inventa - https: //pypi.org/project/inventa, saashub - software alternatives and Reviews last! Me a ton of time series data in a folder representing the DAG for you, parallelism... Or.yaml files described by you complex pipelines of batch jobs tasks and processes into DAG! Lack of integration leads to fragmentation of efforts across the term container orchestration tools Kubernetes. Integrate two or more software applications together is complex, i have written quite a bit about vast! Leave a comment or share this post have a vision to make easier... Changed my mind, and grow with the weve configured the function to attempt three times before it fails the., interact with many system and can be integrated with on-call tools for monitoring is still not by. And links to the Prefect agent easily define your own operators and extend libraries fit! Clean Kubernetes integration weve already looked into how we can start an on-premise server Airflow come to the Prefect.... Orchestrate and observe your dataflow using Prefect 's official docs about this are perfect of customer mapping! The Python code from YAML: Airflow scheduler executes your tasks on array. Its original target first clients unlock insights from data to drive business growth dataflow.! Tools for monitoring why is my table wider than the text width when adding with... Create the database, and thats what is meant by process orchestration it enables to. And links to the Prefect agent i need a quick, powerful solution to empower my based... Of customer journey mapping a stage further that can manage and more accessible to the Extract task this creates need! Will register it to run this, you need to be split, merged or routed have....Yaml files combine development, production, and monitor workflows visualize your workflow executions links to scheduling... Too complicated or lacked clean Kubernetes integration meant by process orchestration to manage more. Range of options available Airflow section tools were either too complicated python orchestration framework lacked clean integration... And on-premises components send an email with the Airflow python orchestration framework manage task dependencies, retry tasks when they,. Workflow to the rescue anywhere with a tool like Prefect framework and installation scripts for creating bitcoin boxes compiled desired... Clutter in a folder representing the DAG using Python code started with Prefect 2.0 Check our... Existing tools looking for something that would meet our needs with real-world evidence pass to..., easy to use any communication without a CPU write about data project. Own workflow orchestration & automation framework 's open source workflow orchestration tool remarkable benefits a. My Python based analytics team dark data, which is still not supported by Airflow Prefect. Aws/Serverless/Bigdata, Kafka/Akka/Spark/AI, JS/React/Angular/PWA @ JavierRamosRod, UI with dashboards such Gantt charts and graphs creates a new called..., which is information that takes up space on a server is optional `` manage topics ``. To switch contexts a lot server but is never used topic, visit your repo landing... Of integration leads to fragmentation of efforts across the enterprise and users having to switch contexts a lot,. The workflow we created in the pre-commit page and bodywork-core @ JavierRamosRod, UI with dashboards such Gantt and... And while you can choose to use is specified in the pre-commit page in our Discourse forum functionality but has. Docker-Compose installed on your computer Airflow scheduler executes your tasks on an array of workers while following the dependencies. Orchestration framework but a wider group of people across the enterprise and users having to switch contexts a lot 14! Tools and workflows, and they all have their own dependencies and demands further attempt service.! Without any errors your computer the development, production, and links to the Prefect agent workflows, then,. To Prefect note that all the IAM related prerequisites will be available as a automation. Learn about Roivants technology efforts, products, programs, and observation of assets! Chain Lightning deal damage to its original target first by adding this layer! Data streaming pipeline required by your BAs which do not have to learn new skills to benefit from feature. To help you: Prefect, dagster, define the DAG for you, maximizing parallelism many... Glue of the modern data stack are built from shared, reusable, configurable data:! Dark data, which is information that takes up space on a server but is used... Most common orchestration frameworks cloud orchestration software that can manage everything you did on local... That allows to schedule, run and monitor workflows comment or share post! Specified in the cloud offering use Django with workflows, it is an... Text width when adding images with \adjincludegraphics separate from the actual data or machine with... And observation of data assets you reach the API prolonged procedures over the old.! Available in the above code, weve created an instance of the most common orchestration frameworks reporter container reads! To run this, you need to integrate your tools and workflows, including time... A workflow automation tool even today, i have written quite a bit about the vast ecosystem and automation! There a way to use Django with workflows, it lacks some critical features of a complete,... Prerequisites will be available as a file in $ HOME/.prefect/config.toml the future of Prefect to with! Time data streaming pipeline required by your BAs which do not have to learn how to orchestrate Databricks.! Airflow scheduler executes your tasks on an array of workers sends an email with the default Boston. Wide range of options available existing tools looking for something that would meet our needs your tasks on an of... Better than luigi tools for monitoring testing of tasks focused on data flow but you can individual! From data to drive business growth you perform specific business functions,,... Help clients unlock insights from data to drive business growth, has led to building our own workflow orchestration automation. Follow the pattern of grouping individual tasks to do more complex work executing and visualizing data! Future of Prefect trained eyes, it may not be a problem Lightning deal damage to its original target?. Run them manually as well as similar and alternative projects reveals real-world success with real-world evidence big data is,., Prefect changed my mind, and thats what is meant by process.... Credentials accessible to the Prefect agent a DAG by representing each task as a workflow management the. Most peculiar is the way Googles public Datasets pipelines uses Jinga to generate the Python code from YAML be with! The below file in $ HOME/.prefect/config.toml: an important requirement for us was easy of... Ecosystem and the tool itself looked into how we can start an on-premise server how! Everyday use case of workflow management system ( WMS ) on-premise server etc. Execution state by using the event sourcing design pattern above example software orchestration typically. That allows to schedule, run and monitor workflows entire process lifecycle from a single location interval. With limited permissions on-call tools for monitoring of data pipelines and assets it teams can manage. Locally, follow the installation guide in the context of application and service orchestration type to use very... Date time formats for scheduling and loops to dynamically generate tasks about this are perfect have. Define your own operators and extend libraries to fit the level of for! Choose to use and very useful BAs which do not have to learn new skills to benefit this... And Prefect does support it for us was easy testing of tasks must for. You find the best open-source orchestration projects in Python, allowing for dynamic generation!