Quickstart Guide

Installing cocotb


Cocotb has the following requirements:

  • Python 2.7, Python 3.5+ (recommended)

  • Python-dev packages

  • GCC 4.8.1+ and associated development packages

  • GNU Make

  • A Verilog or VHDL simulator, depending on your RTL source code

Installation via PIP

New in version 1.2.

Cocotb can be installed by running

pip3 install cocotb


pip install cocotb

For user local installation follow the pip User Guide.

To install the development version of cocotb:

git clone https://github.com/cocotb/cocotb
pip install -e ./cocotb

Native Linux Installation

The following instructions will allow building of the cocotb libraries for use with a 64-bit native simulator.

If a 32-bit simulator is being used then additional steps are needed, please see our Wiki.


sudo apt-get install git make gcc g++ swig python-dev

Red Hat-based

sudo yum install gcc gcc-c++ libstdc++-devel swig python-devel

Windows Installation

Download the MinGW installer from https://osdn.net/projects/mingw/releases/.

Run the GUI installer and specify a directory you would like the environment installed in. The installer will retrieve a list of possible packages, when this is done press “Continue”. The MinGW Installation Manager is then launched.

The following packages need selecting by checking the tick box and selecting “Mark for installation”

Basic Installation
  -- mingw-developer-tools
  -- mingw32-base
  -- mingw32-gcc-g++
  -- msys-base

From the Installation menu then select “Apply Changes”, in the next dialog select “Apply”.

When installed a shell can be opened using the msys.bat file located under the <install_dir>/msys/1.0/

Python can be downloaded from https://www.python.org/downloads/windows/. Run the installer and download to your chosen location.

It is beneficial to add the path to Python to the Windows system PATH variable so it can be used easily from inside Msys.

Once inside the Msys shell commands as given here will work as expected.

macOS Packages

You need a few packages installed to get cocotb running on macOS. Installing a package manager really helps things out here.

Brew seems to be the most popular, so we’ll assume you have that installed.

brew install python icarus-verilog gtkwave

Running your first Example

Assuming you have installed the prerequisites as above, the following lines are all you need to run a first simulation with cocotb:

git clone https://github.com/cocotb/cocotb
cd cocotb/examples/endian_swapper/tests

Selecting a different simulator is as easy as:

make SIM=vcs

Running the same example as VHDL

The endian_swapper example includes both a VHDL and a Verilog RTL implementation. The cocotb testbench can execute against either implementation using VPI for Verilog and VHPI/FLI for VHDL. To run the test suite against the VHDL implementation use the following command (a VHPI or FLI capable simulator must be used):

make SIM=ghdl TOPLEVEL_LANG=vhdl

Using cocotb

A typical cocotb testbench requires no additional HDL code (though nothing prevents you from adding testbench helper code). The Design Under Test (DUT) is instantiated as the toplevel in the simulator without any wrapper code. Cocotb drives stimulus onto the inputs to the DUT and monitors the outputs directly from Python.

Creating a Makefile

To create a cocotb test we typically have to create a Makefile. Cocotb provides rules which make it easy to get started. We simply inform cocotb of the source files we need compiling, the toplevel entity to instantiate and the Python test script to load.

VERILOG_SOURCES = $(PWD)/submodule.sv $(PWD)/my_design.sv
# TOPLEVEL is the name of the toplevel module in your Verilog or VHDL file:
# MODULE is the name of the Python test file:

include $(shell cocotb-config --makefiles)/Makefile.inc
include $(shell cocotb-config --makefiles)/Makefile.sim

We would then create a file called test_my_design.py containing our tests.

Creating a test

The test is written in Python. Cocotb wraps your top level with the handle you pass it. In this documentation, and most of the examples in the project, that handle is dut, but you can pass your own preferred name in instead. The handle is used in all Python files referencing your RTL project. Assuming we have a toplevel port called clk we could create a test file containing the following:

import cocotb
from cocotb.triggers import Timer

def my_first_test(dut):
    """Try accessing the design."""

    dut._log.info("Running test!")
    for cycle in range(10):
        dut.clk = 0
        yield Timer(1, units='ns')
        dut.clk = 1
        yield Timer(1, units='ns')
    dut._log.info("Running test!")

This will drive a square wave clock onto the clk port of the toplevel.

Accessing the design

When cocotb initializes it finds the top-level instantiation in the simulator and creates a handle called dut. Top-level signals can be accessed using the “dot” notation used for accessing object attributes in Python. The same mechanism can be used to access signals inside the design.

# Get a reference to the "clk" signal on the top-level
clk = dut.clk

# Get a reference to a register "count"
# in a sub-block "inst_sub_block"
count = dut.inst_sub_block.count

Assigning values to signals

Values can be assigned to signals using either the value property of a handle object or using direct assignment while traversing the hierarchy.

# Get a reference to the "clk" signal and assign a value
clk = dut.clk
clk.value = 1

# Direct assignment through the hierarchy
dut.input_signal <= 12

# Assign a value to a memory deep in the hierarchy
dut.sub_block.memory.array[4] <= 2

The syntax sig <= new_value is a short form of sig.value = new_value. It not only resembles HDL syntax, but also has the same semantics: writes are not applied immediately, but delayed until the next write cycle. Use sig.setimmediatevalue(new_val) to set a new value immediately (see setimmediatevalue()).

Reading values from signals

Accessing the value property of a handle object will return a BinaryValue object. Any unresolved bits are preserved and can be accessed using the binstr attribute, or a resolved integer value can be accessed using the integer attribute.

>>> # Read a value back from the DUT
>>> count = dut.counter.value
>>> print(count.binstr)
>>> # Resolve the value to an integer (X or Z treated as 0)
>>> print(count.integer)
>>> # Show number of bits in a value
>>> print(count.n_bits)

We can also cast the signal handle directly to an integer:

>>> print(int(dut.counter))

Parallel and sequential execution

A yield will run a function (that must be marked as a “coroutine”, see Coroutines) sequentially, i.e. wait for it to complete. If a coroutine should be run “in the background”, i.e. in parallel to other coroutines, the way to do this is to fork() it. The end of such a forked coroutine can be waited on by using join().

The following example shows these in action:

def reset_dut(reset_n, duration):
    reset_n <= 0
    yield Timer(duration, units='ns')
    reset_n <= 1
    reset_n._log.debug("Reset complete")

def parallel_example(dut):
    reset_n = dut.reset

    # This will call reset_dut sequentially
    # Execution will block until reset_dut has completed
    yield reset_dut(reset_n, 500)
    dut._log.debug("After reset")

    # Call reset_dut in parallel with the 250 ns timer
    reset_thread = cocotb.fork(reset_dut(reset_n, 500))

    yield Timer(250, units='ns')
    dut._log.debug("During reset (reset_n = %s)" % reset_n.value)

    # Wait for the other thread to complete
    yield reset_thread.join()
    dut._log.debug("After reset")