This is a feature I find personally valuable. I agree with several underlying issues, particularly resource management, Py4J, dependency handling, and the difficulty of maintaining a framework that spans both the JVM and Python ecosystems.
Where I disagree is with the conclusion that these issues necessarily point toward deprecating Python Processor support itself. I think there is an important distinction between the value of Python as an extension model and the architecture currently used to implement it. To be solution oriented one way to look at this is to consider what users would do in the absence of Python Processor support. In many cases, the alternative is not to rewrite the functionality in Java. It is likely to become something like: Apache NiFi -> HTTP/gRPC -> Python microservice -> NiFi That architecture still has independent Python processes, Python dependency management, memory and CPU consumption outside the JVM, and a Python software supply chain. We have not eliminated any of those concerns; we have moved them outside NiFi and made every operator build and manage that integration themselves. There are also costs to that approach: additional network boundaries, deployment artifacts, authentication, service discovery, observability, retry semantics, and operational complexity. From a governance perspective, NiFi may actually have less visibility and control over that external Python workload than it would if Python execution remained part of a defined NiFi extension model. That makes me wonder whether the better direction is to reconsider the Python runtime architecture rather than Python support itself. For example, instead of treating the current Py4J-based implementation as something that must be preserved indefinitely, we could define a stronger process boundary around Python execution. A future implementation could use a well-defined IPC or RPC contract, potentially based on gRPC/protobuf, Unix domain sockets, shared memory, Arrow, or another mechanism designed around coarse-grained operations. NiFi does not need to become a Python integrated application, but I think there is substantial value in allowing those workloads to participate directly in a governed NiFi dataflow without requiring users to construct a separate microservice architecture for every Python integration. For that reason, I would favor separating two questions: 1. Is the current Python Processor implementation the architecture we want to support long term? 2. Should NiFi continue to provide a first-class Python extension capability? I could see a strong argument that the answer to the first question is no, particularly if Py4J is becoming a maintenance risk. I am much less convinced that the answer to the second question should also be no. With that said I distinctly understand that time is limited and we would all develop the coolest of things with infinite resources, so I yield to those with more influence, but would happy to contribute to a better architecture if others find it valuable. Thanks, Marc On Wed, Aug 12, 2026 at 12:10 AM Joe Witt <[email protected]> wrote: > You are totally fine to engage on this thread Sean. We appreciate it > > > On Tue, Aug 11, 2026 at 8:17 PM Sean Hunter via dev <[email protected]> > wrote: > > > Hi David, > > > > As a user, rather than contributor, I think my primary concern is one of > > operations and implementation. What alternative would be available? We > used > > the 1.x version and were quite excited to move to 2.0 with its more > native > > integration that was easier to troubleshoot. We also do build a NAR as > part > > of our pipeline process, and I suspect since we used a blog as guidance > to > > develop that process, that others likely do as well. Our use case is a > > particularly nasty data transform (Windows logs of some sort, naturally) > > that’s reasonable to write and execute in Python. It’s readable, while > > still being performant enough for our needs, and seemingly not causing > > system stability issues for us. > > > > I do understand and take your points. What I’d like to better understand > > are the options users have. Do you have any thoughts? > > > > Thank you and have a great day! > > Sean > > > > PS - Please let me know if this is too far off topic for the dev mailing > > list and I’ll take it elsewhere. > > > > From: David Handermann <[email protected]> > > Date: Tuesday, August 11, 2026 at 8:38 PM > > To: [email protected] <[email protected]> > > Subject: [DISCUSS] Future Support for Python Processors? > > > > Be Careful: Email is from an External Source > > Use caution when opening emails and do not click on links or attachments > > from unknown senders. For more resources, visit > security.cat.com/phishing. > > > > > > Team, > > > > The introduction of support for Python Processors was one of the major > > new features of Apache NiFi 2. In light of experience, however, I > > believe it is time to reconsider future support for this extension > > strategy. The idea of removing this feature may raise some concerns, > > but it is important to consider the options based on scalability, > > security, and supportability. > > > > One of the greatest benefits of Python-based Processors is rapid > > iteration. Although this is a strength during the development phase, > > it can become a serious weakness when moving to production. > > > > NiFi is fundamentally a Java-based application, thus tuning resource > > allocation is a key part of maintaining a production system. Running a > > Python Processor requires one or more independent Python processes, > > each with their own memory consumption and CPU usage patterns. What > > might work at a small scale on a development machine breaks down when > > attempting to run at production scale, without careful tuning. This is > > challenging enough with Java-based components, but global settings > > like heap and non-heap memory provide clear boundaries. Python > > Processors, as currently implemented, do not support this level of > > control. Beyond process control, operations that require communicating > > between the NiFi JVM and Python processes involve socket > > communication, which can be expensive for frequent calls. Thus an > > apparent initial advantage of Python Processors becomes a major > > problem when moving beyond limited types of operations. > > > > When it comes to security, Python Processors can involve more serious > > risks than bundled Java extensions. > > > > With NiFi support for downloading dependencies at runtime, it is > > essential for an administrator to provide a secure supply chain > > strategy for retrieving these dependencies. Although the NiFi > > framework also supports packaging Python Processors as NAR bundles, > > this packaging capability is not currently part of the Apache NiFi > > project. The project could build on third party work, but as Python > > packaging is less opinionated, this is an additional maintenance > > question that quickly becomes more involved. This combination of > > supply chain security and lack of packaging support raises security > > challenges. > > > > Supportability is always a question for any feature in an open source > > project, but Python Processors are a particular point of concern. > > Providing NiFi framework support requires a strong knowledge of the > > NiFi project itself, and a strong knowledge of Python. Project > > maintainers and contributors usually have expertise in particular > > areas, but it is rare to find both. More to the point, however, the > > Py4J project, which NiFi depends on for integration, has seen limited > > maintenance, with the last tagged version dating to January 2025. > > Without robust architecture support, the NiFi project cannot provide a > > strong framework for future implementation. > > > > Taking these issues together, I believe the project should consider > > deprecating support for Python Processors. Similar to other > > deprecations, actual removal would not occur until a major release > > version, and that would be a separate conversation. > > > > Rather than continuing to extend the life of Python Processor support, > > it seems better to invest limited project resources into maintaining > > and improving core functionality. > > > > Regards, > > David Handermann > > Apache NiFi PMC Chair > > > > >
