NeqSim Python

Python interface to the NeqSim engine — fluid properties, process simulation, and PVT analysis from Python and Jupyter notebooks.

Quick Start · Process Simulation · PVT Simulation · Examples · Docs · Community

What is NeqSim Python?

NeqSim Python is part of the NeqSim project — a Python interface to the NeqSim Java library for estimation of fluid behavior and process design for oil and gas production. For an introduction see Introduction to Process Modelling with NeqSim in Python.

It provides Python toolboxes such as thermoTools and processTools that streamline the use of NeqSim, plus direct access to the full Java API via the jneqsim gateway.

Capability	What you get
Thermodynamics	60+ EOS models (SRK, PR, CPA, GERG-2008, …), flash calculations, phase envelopes
Physical properties	Density, viscosity, thermal conductivity, surface tension
Process simulation	33+ equipment types — separators, compressors, heat exchangers, valves, pumps, reactors
PVT simulation	CME, CVD, differential liberation, separator tests, swelling, viscosity
Pipeline & flow	Steady-state multiphase pipe flow (Beggs & Brill), pipe networks

🚀 Quick Start

Install

pip (requires Java 17+)	conda (Java included)
pip install neqsim	conda install -c conda-forge neqsim

Prerequisites: Python 3.10+ and Java 17+ (NeqSim 3.15+ requires Java 17 or higher; earlier NeqSim releases required Java 11+). The conda package automatically installs OpenJDK — no separate Java setup needed. For pip, install Java from Adoptium.

Try it now

from neqsim.thermo import fluid, TPflash, printFrame

# Create a natural gas fluid
fl = fluid('srk')
fl.addComponent('methane', 0.85)
fl.addComponent('ethane', 0.10)
fl.addComponent('propane', 0.05)
fl.setTemperature(25.0, 'C')
fl.setPressure(60.0, 'bara')
fl.setMixingRule('classic')

TPflash(fl)
printFrame(fl)

print(f"Gas density:    {fl.getPhase('gas').getDensity('kg/m3'):.2f} kg/m3")
print(f"Gas viscosity:  {fl.getPhase('gas').getViscosity('kg/msec'):.6f} kg/(m*s)")
print(f"Z-factor:       {fl.getPhase('gas').getZ():.4f}")

🔧 Process Simulation

NeqSim Python provides multiple ways to build process simulations:

1. Python Wrappers — recommended for beginners & notebooks

Simple functions with a global process — great for prototyping:

from neqsim.thermo import fluid
from neqsim.process import stream, compressor, separator, runProcess, clearProcess

clearProcess()
feed = fluid('srk')
feed.addComponent('methane', 0.9)
feed.addComponent('ethane', 0.1)
feed.setTemperature(30.0, 'C')
feed.setPressure(50.0, 'bara')
feed.setTotalFlowRate(10.0, 'MSm3/day')

inlet = stream('inlet', feed)
sep = separator('separator', inlet)
comp = compressor('compressor', sep.getGasOutStream(), pres=100.0)
runProcess()

print(f"Compressor power: {comp.getPower()/1e6:.2f} MW")

2. ProcessContext — recommended for production code

Context manager with explicit process control — supports multiple independent processes:

from neqsim.thermo import fluid
from neqsim.process import ProcessContext

feed = fluid('srk')
feed.addComponent('methane', 0.9)
feed.addComponent('ethane', 0.1)
feed.setTemperature(30.0, 'C')
feed.setPressure(50.0, 'bara')

with ProcessContext("Compression Train") as ctx:
    inlet = ctx.stream('inlet', feed)
    sep = ctx.separator('separator', inlet)
    comp = ctx.compressor('compressor', sep.getGasOutStream(), pres=100.0)
    ctx.run()
    print(f"Compressor power: {comp.getPower()/1e6:.2f} MW")

3. ProcessBuilder — fluent API for configuration-driven design

Chainable builder pattern:

from neqsim.thermo import fluid
from neqsim.process import ProcessBuilder

feed = fluid('srk')
feed.addComponent('methane', 0.9)
feed.addComponent('ethane', 0.1)
feed.setTemperature(30.0, 'C')
feed.setPressure(50.0, 'bara')

process = (ProcessBuilder("Compression Train")
    .add_stream('inlet', feed)
    .add_separator('separator', 'inlet')
    .add_compressor('compressor', 'separator', pressure=100.0)
    .run())

print(f"Compressor power: {process.get('compressor').getPower()/1e6:.2f} MW")

4. Direct Java Access — full control via jneqsim

Explicit process management using the Java API — for advanced features see the NeqSim Java repo:

from neqsim import jneqsim
from neqsim.thermo import fluid

feed = fluid('srk')
feed.addComponent('methane', 0.9)
feed.addComponent('ethane', 0.1)
feed.setTemperature(30.0, 'C')
feed.setPressure(50.0, 'bara')

# Create equipment using Java classes
inlet = jneqsim.process.equipment.stream.Stream('inlet', feed)
sep = jneqsim.process.equipment.separator.Separator('separator', inlet)
comp = jneqsim.process.equipment.compressor.Compressor('compressor', sep.getGasOutStream())
comp.setOutletPressure(100.0)

# Create and run process explicitly
process = jneqsim.process.processmodel.ProcessSystem()
process.add(inlet)
process.add(sep)
process.add(comp)
process.run()

print(f"Compressor power: {comp.getPower()/1e6:.2f} MW")

Choosing an Approach

Use Case	Recommended Approach
Learning & prototyping	Python wrappers
Jupyter notebooks	Python wrappers
Production applications	ProcessContext
Multiple parallel processes	ProcessContext
Configuration-driven design	ProcessBuilder
Advanced Java features	Direct Java access

The jneqsim gateway is the first-class path for the long tail. Only a curated subset of NeqSim's ~2500 Java classes has hand-written Python wrappers. Mechanical design, safety, field development, automation, and most specialized equipment are used directly through jneqsim — no wrapper needed.

🔎 Discovering the Full API

Direct jneqsim access is powerful but hard to explore (a JPackage has no autocomplete). The neqsim.discovery module scans the API at runtime so you can list, search, and inspect every class from Python:

from neqsim import discovery

discovery.list_equipment()                 # every process-equipment class
discovery.list_packages('process')         # sub-packages of neqsim.process
discovery.find_classes('scrubber')         # search the whole API by keyword
print(discovery.describe('Compressor'))    # constructors + methods via reflection

Compressor = discovery.get_class('Compressor')   # JClass by simple or full name

For IDE autocomplete and type checking across the entire Java API, generate type stubs (already packaged as jneqsim-stubs, regenerate with python scripts/generate_stubs.py) and point your editor at src. An offline API manifest (python scripts/generate_api_manifest.py) lets discovery list, search, and describe classes instantly and JVM-free.

Typed, validated flowsheets (optional)

With pip install "neqsim[schema]" you can build flowsheets from typed pydantic models — autocomplete and validation before the JVM runs:

from neqsim.process.schema import ProcessModel, Fluid, Unit

model = ProcessModel(
    fluid=Fluid(eos="srk", components={"methane": 0.9, "ethane": 0.1}),
    process=[
        Unit(type="Stream", name="feed",
             properties={"flowRate": [50000.0, "kg/hr"], "pressure": [50.0, "bara"]}),
        Unit(type="Separator", name="HP Sep", inlet="feed"),
    ],
)
result = model.run()           # validates, builds, and runs

Component-name helpers

from neqsim.thermo.components import find_components, suggest_component
find_components("glycol")            # search the component database
suggest_component("methan")          # ['methane', 'methanol', ...] — catch typos

Rich Jupyter display

Streams and processes render as HTML tables in notebooks automatically (just display the object) — no extra call needed.

Results to pandas

One helper turns any process into a tidy stream table (works for every equipment type, because it walks the flowsheet's streams):

from neqsim.process import stream_table, equipment_table, runProcess

runProcess()
stream_table()        # one row per stream: flow, T, P, phases, density, molar mass
equipment_table()     # one row per unit: name, type, inlet/outlet counts

stream_table(my_process)   # or pass an explicit ProcessSystem / ProcessContext

🧪 PVT Simulation

NeqSim includes a pvtsimulation package for common PVT experiments (CCE/CME, CVD, differential liberation, separator tests, swelling, viscosity, etc.) and tuning workflows.

📂 Examples

Explore ready-to-run examples in the examples folder:

Process simulation — processApproaches.py (all four approaches)
Flash calculations, phase envelopes, hydrate prediction
Compressor trains, heat exchangers, separation processes
Jupyter notebooks in examples/jupyter/
Google Colab examples

⚙️ Technical Notes

JPype bridges Python and Java. See the JPype installation guide for platform-specific details. Ensure Python and Java are both 64-bit (or both 32-bit) — mixing architectures will crash on import.

The full list of Python dependencies is on the dependencies page.

JVM Startup Control

By default, import neqsim starts the JVM immediately. This can be tuned via environment variables:

Variable	Default	Purpose
`NEQSIM_JVM_AUTOSTART`	`1`	Set to `0`/`false`/`no` to disable automatic JVM startup on import. Call `init_jvm()` explicitly before using `jneqsim`.
`NEQSIM_JVM_ARGS`	(none)	Extra JVM startup arguments (space separated), appended after the default `-Xrs`.
`NEQSIM_JVM_MAX_HEAP`	(none)	Max JVM heap size, e.g. `2g` — passed as `-Xmx2g`.

import os
os.environ["NEQSIM_JVM_AUTOSTART"] = "0"  # must be set before `import neqsim`

from neqsim.neqsimpython import init_jvm, is_jvm_started

print(is_jvm_started())        # False
init_jvm(jvm_args=["-Xrs"])     # start explicitly, e.g. with custom args
print(is_jvm_started())        # True

init_jvm() is safe to call multiple times — it is a no-op if the JVM is already running.

🏗️ Contributing

We welcome contributions — bug fixes, new examples, documentation improvements, and more.

CONTRIBUTING.md — Code of conduct and PR process
NeqSim Python Wiki — Guides and usage patterns

📚 Documentation & Resources

Resource	Link
NeqSim homepage	equinor.github.io/neqsimhome
Python wiki	neqsim-python/wiki
JavaDoc API	JavaDoc
Discussion forum	GitHub Discussions
NeqSim Java	equinor/neqsim
MATLAB binding	equinor/neqsimmatlab
Releases	GitHub Releases

Versioning

NeqSim uses SemVer for versioning.

Authors

Even Solbraa (esolbraa@gmail.com), Marlene Louise Lund

NeqSim development was initiated at NTNU. A number of master and PhD students have contributed — we greatly acknowledge their contributions.

License

Apache-2.0

Release files for neqsim 3.20.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for neqsim 3.20.0
File	Size	Uploaded
neqsim-3.20.0.tar.gz	57.9 MB	Sep 8, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for neqsim 3.20.0
File	Interpreter	ABI	Platform	Reset
neqsim-3.20.0-py3-none-any.whl 57.2 MB Sep 8, 2026	Python 3	none	any	Details

Total release size:115.1 MB

Release files / neqsim-3.20.0.tar.gz

Download URL	neqsim-3.20.0.tar.gz
Size	57.9 MB
Tags	Source
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Publishing commit: github.com/equinor/neqsim-python/tree/c286566a1dd47e4e09dc15a050b779506d63bd9e

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Publishing logs: github.com/equinor/neqsim-python/actions/runs/34255473391/attempts/1

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Release files / neqsim-3.20.0-py3-none-any.whl

Download URL	neqsim-3.20.0-py3-none-any.whl
Size	57.2 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`bc0ebda20ff25131b81024d7d66413a1f1836458563d01eed9d9d90a2819dcbb`
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Upload date	Sep 8, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/equinor/neqsim-python
Publishing commit: github.com/equinor/neqsim-python/tree/c286566a1dd47e4e09dc15a050b779506d63bd9e

Workflow

Publishing configuration: github.com/equinor/neqsim-python/blob/c286566a1dd47e4e09dc15a050b779506d63bd9e/.github/workflows/publish-to-test-pypi.yml
Publishing logs: github.com/equinor/neqsim-python/actions/runs/34255473391/attempts/1

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