Hi, I also agree with Marc on this. From the user interactions, I got the feeling that Python processors are quite valuable to the community, and I would be hesitant to deprecate and remove them when the main problems are related to the underlying implementation.
I agree with several of the problems David mentioned, particularly around scalability and dependency installation. These issues were not foreseen with the initial release of NiFi 2.0 and only became apparent as these processors started being used more extensively by the community, especially with heavy AI libraries. The problem is that, after the initial release of 2.0, there has been very little development on the Python side, so these issues were never addressed. >From a user's point of view, I think the Python processor API is simple and easy to use. Even with the current implementation, there are several use cases for which it is sufficient, so I would not remove the option to use Python processors. Deprecating them would discourage people from creating and using Python processors, even for use cases where they make sense. In my opinion, the documentation for Python processors should instead be extended to clearly explain the caveats of using them, including what problems users can expect in terms of dependency management, scalability, etc., and which use cases are recommended for these processors. In the future, I would support developing an alternative implementation under the hood, replacing Py4J, if we decide to pursue IPC communication, use an embedded interpreter, or adopt any of the other solutions Matt mentioned. In MiNiFi C++, we went with an embedded interpreter solution, which provides much better performance, with the caveat that only one interpreter can be embedded in a MiNiFi process and is therefore shared between processors. The dependency management issue is still a challenge in MiNiFi C++ as well, and I would support creating a packaging solution that could work for both projects. As Marc said, from a user's point of view, in many cases it is not really an option to rewrite a processor in Java, as many libraries, especially AI libraries, are only available in Python. If the decision is made to deprecate and eventually remove Python processor support from NiFi, forcing users to create a separate Python microservice based on Marc's suggestion of a "Apache NiFi -> HTTP/gRPC -> Python microservice -> NiFi" architecture, we could consider officially recommending MiNiFi C++ as an interim solution, since it retains Python support. The same approach could potentially be used for anything requiring C/C++ or Rust support as well. Regards, Gabor On Thu, 13 Aug 2026 at 21:51, Mark Payne <[email protected]> wrote: > > Kevin, > > Py4J is the glue that bridges the NiFi JVM to the python process that runs > python processors. So there’s a py4j server that is run in a separate python > process. Then a py4j client that runs in the JVM. Py4J handles the RPC to > make it possible to call the Python processors as if they were Java objects. > > Thank > -Makr > > > > On Aug 13, 2026, at 3:37 PM, Kevin Doran <[email protected]> wrote: > > > > Can someone clarify where Py4J is used today vs where subprocesses > > that invoke a configurable python executable are used? My > > understanding was that the Py4J was mostly restricted to the scripting > > processors, but if that is not the case I would be interested in > > hearing more. > > > > On Thu, Aug 13, 2026 at 1:42 PM David Handermann > > <[email protected]> wrote: > >> > >> Dan, > >> > >> Thanks for the substantive reply and consideration of the various > >> issues surrounding support for native Python Processors. > >> > >> As you highlighted, the scalability issue is foundational. Although > >> Processor authors can work with self-imposed constraints, the NiFi > >> framework does not provide the same level of safeguards. Any future > >> solution would need to account for these types of production-level > >> concerns. > >> > >> Regarding supply chain security, you are correct that there are > >> potential paths forward on the packaging strategy. The framework could > >> remove support for runtime loading as a safety measure. Right now, > >> lack of pip or uv effectively disables runtime loading. Adjusting the > >> default project container configuration would strengthen the standard > >> position, and thus require Python Processors to be packaged using a > >> NAR. The project could provide tooling, similar to the NiFi NAR Maven > >> Plugin, but this broadens the maintenance scope in a meaningful way. > >> Thus before going in this direction, the future support strategy needs > >> to be considered. > >> > >> The Py4J architecture remains a critical concern and high risk for > >> future maintainability. Considering an alternative architecture would > >> require a substantial redesign and rewrite of Python Processor > >> support, abandoning a majority of the current implementation. Current > >> tooling makes this more plausible in theory, but is a significant > >> undertaking that is difficult to justify without serious commitment on > >> the part of multiple project maintainers. To be clear, deprecating the > >> current implementation for removal does not preclude future redesign. > >> These two questions should be considered independently. > >> > >> Deprecation and removal without replacement will have a different > >> impact depending on the current scope of usage. Simpler Python > >> Processors should be easier to convert to Java, but more complex > >> implementations would likely require something outside of NiFi, as you > >> mentioned. Although these are difficult questions, it ultimately comes > >> down to project focus and available maintenance cycles. Apache NiFi > >> has historically done many things. NiFi 2 served as a focusing > >> function. Going forward, maintaining project health and stability is > >> paramount, which may at times involve removing certain capabilities. > >> > >> Regards, > >> David Handermann > >> > >> On Wed, Aug 12, 2026 at 3:27 PM Daniel Weidman via dev > >> <[email protected]> wrote: > >>> > >>> David, > >>> > >>> Thanks for raising this directly rather than letting it drift, and for > >>> laying > >>> out the reasoning rather than just the conclusion. > >>> > >>> On scalability, your point lands. In my experience the memory behavior of > >>> a > >>> Python Processor is largely a function of how it is written, and > >>> disciplined > >>> implementations can be well behaved. But I recognize that is an argument > >>> about > >>> good citizenship, not about enforcement, and it does not give an operator > >>> the > >>> equivalent of a heap ceiling. That is a real gap. It does seem > >>> addressable at > >>> the process supervision layer, through cgroup or rlimit bounds on spawned > >>> interpreters, rather than being inherent to Python as an extension > >>> language. > >>> > >>> On security, I would offer a friendly amendment. The meaningful > >>> difference does > >>> not seem to be Python versus Java, but when and where third party > >>> dependencies > >>> land. A NAR resolves its tree at build time and ships self contained, so > >>> it can > >>> be scanned, signed, and deployed into an air gapped environment, and > >>> unpacking > >>> it executes nothing. The current Python path resolves dependencies at > >>> runtime > >>> via pip on the NiFi host, and pip installation does execute packaging > >>> code. > >>> That is a real governance gap, and I will concede PyPI carries risks Maven > >>> Central does not. > >>> > >>> But as you noted, the framework already supports loading Python Processors > >>> packaged as NARs. What is missing is project-provided tooling to build > >>> them. > >>> Sean's note about relying on a blog post to produce one seems telling. > >>> Closing > >>> that gap looks like a smaller undertaking than removing the extension > >>> point, > >>> and it would address the supply chain concern directly rather than by > >>> subtraction. > >>> > >>> I will admit I had not realized the current implementation still rests on > >>> Py4J. > >>> That reframes a good deal of this for me, and it tracks with Matt's read > >>> that > >>> Py4J is the long pole rather than the capability itself. > >>> > >>> For what it is worth as an operator, the practical value of Python > >>> Processors > >>> is not just iteration speed. It is that the people writing our transforms > >>> are > >>> Python native. Removal without a replacement does not convert that work to > >>> Java, it pushes it out of NiFi entirely, to sidecars or external services, > >>> where, as Marc noted, we keep every one of the concerns you listed but > >>> lose > >>> NiFi's visibility into them. > >>> > >>> I would rather see the runtime architecture reconsidered than the > >>> capability > >>> retired. If the deciding constraint is maintainer cycles, it would be > >>> useful to > >>> know what a replacement would need in terms of effort and expertise. That > >>> is a > >>> more actionable ask of the community than a deprecation vote. > >>> > >>> Regards, > >>> Dan > >>> > >>> > >>> From: David Handermann <[email protected]> > >>> Date: Wednesday, August 12, 2026 at 9:10 AM > >>> To: [email protected] <[email protected]> > >>> Subject: Re: [DISCUSS] Future Support for Python Processors? > >>> > >>> Thanks to everyone for the replies thus far! > >>> > >>> The question about alternatives gets at the core issue, and the ideas > >>> around a more loosely coupled architecture provide some helpful > >>> possibilities. > >>> > >>> At a basic level, simple deprecation and removal would leave the > >>> current set of options, including standard Java, Groovy scripting, or > >>> externalized Python scripts executed as a stream. None of these > >>> provide the same level of features for Python itself, which prompted > >>> the original native Python Processor implementation. Without a > >>> replacement, these alternatives would remain. With the rise of > >>> AI-enabled development, it is now much easier to go from Python to > >>> Java, but work is still required. > >>> > >>> As to future strategies for Python integration, the current discussion > >>> around deprecation is more narrowly focused on the existing > >>> framework-level extension. Removal of the current implementation is > >>> not intended to halt future innovation. Although removal without an > >>> initial replacement might not be the perfect solution, it may be > >>> necessary given available maintainer cycles, and the substantive > >>> issues I described in the opening. > >>> > >>> If there is sufficient interest and effort to propose and build a > >>> different solution, that would be a great outcome of this discussion. > >>> I've thought at different points about reworking the Script Engine > >>> integration to provide a cleaner path to external extension, so there > >>> are definitely opportunities in that direction. > >>> > >>> With that, my primary concerns with the current implementation remain, > >>> but glad to consider future alternatives. > >>> > >>> Regards, > >>> David Handermann > >>> > >>> > >>> On Wed, Aug 12, 2026 at 7:52 AM Matt Burgess <[email protected]> wrote: > >>>> > >>>> I agree with Marc, the concerns of the implementation of the capability > >>>> should not warrant deprecation and future removal of the capability, but > >>>> certainly we want to ensure that anything we implement for NiFi doesn't > >>>> negatively the reputation of Apache NiFi as a secure, robust, reliable > >>>> system. > >>>> > >>>> I think we should instead consider a new architecture, one > >>>> fully extensible so if the community decides to deprecate the capability, > >>>> it could still be restored using some extension point. This kind of > >>>> generic > >>>> approach could allow other extensions not sanctioned by the Apache NiFi > >>>> community to coexist in the "NiFi+" deployment. Not to get off-topic but > >>>> it > >>>> is somewhat analogous to exposing the Spring context such that alternate > >>>> implementations of the beans could be provided. > >>>> > >>>> There are options to consider, I'm sure each with its own set of pros and > >>>> cons. Off the top of my head: > >>>> > >>>> - Sidecar server responsible for executing Python scripts with FlowFile > >>>> input(s) and returning FlowFile output(s) directly from/to processors, > >>>> like > >>>> Marc's suggestion but managed by NiFi > >>>> - Jep [1] and it's OS-independent counterpart jep-distro [2] > >>>> - Require Java bindings calling out to an embedded interpreter, such as > >>>> WrapPy4J (which uses Jep under the hood) [3] > >>>> > >>>> I am far from a Python expert and I know there are several places in the > >>>> framework where the Python stuff has landed, so I don't expect any other > >>>> implementation to be any easier or take less time than the original, > >>>> which > >>>> I'm sure took quite a lot of time and effort which is very much > >>>> appreciated. It seems that Py4J is the long pole in the tent for the > >>>> concerns, not the capability itself. > >>>> > >>>> At the end of the day I think a discussion like this clearly shows the > >>>> commitment of the whole community to ensure Apache NiFi is all that we > >>>> want > >>>> it to be and that we can introspect, improve, and collaborate to keep > >>>> NiFi > >>>> awesome :) > >>>> > >>>> Regards, > >>>> Matt > >>>> > >>>> [1] > >>>> https://urldefense.com/v3/__https://github.com/ninia/JEP?tab=readme-ov-file__;!!FtR4BK4x7WL3xYs!6mIniDSbJ62B5zII3b9g972tiJiM1K8M1E-1R8rvwlwl__KEfyNqtqWjM3xwIPbVawsv_VEsYzoNRToUxhft8Q3Rnnw$ > >>>> [2] > >>>> https://urldefense.com/v3/__https://github.com/icemachined/jep-distro?tab=readme-ov-file__;!!FtR4BK4x7WL3xYs!6mIniDSbJ62B5zII3b9g972tiJiM1K8M1E-1R8rvwlwl__KEfyNqtqWjM3xwIPbVawsv_VEsYzoNRToUxhft703BJKY$ > >>>> [3] > >>>> https://urldefense.com/v3/__https://github.com/313hemant313/wrappyj__;!!FtR4BK4x7WL3xYs!6mIniDSbJ62B5zII3b9g972tiJiM1K8M1E-1R8rvwlwl__KEfyNqtqWjM3xwIPbVawsv_VEsYzoNRToUxhftYE_fqvo$ > >>>> > >>>> On Wed, Aug 12, 2026 at 8:19 AM Marc P. <[email protected]> wrote: > >>>> > >>>>> 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 > >>>>>> http://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 > >>>>>>> > >>>>>>> > >>>>>> > >>>>> > >>> >
