diff --git a/examples/notebooks/multiprocessing_zmq/README.md b/examples/notebooks/multiprocessing_zmq/README.md
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+++ b/examples/notebooks/multiprocessing_zmq/README.md
@@ -0,0 +1,3 @@
+This example shows how to use a zmq publisher-subscriber pattern to perform a computation in one process and visualize results in another process. First, run all cells in `multiprocessing_zmq_plot.ipynb`, and then run cells in `multiprocessing_zmq_compute.ipynb`. The raw bytes for the numpy array are sent using zmq in the compute notebook and received in the plot notebook and displayed.
+
+For more information on zmq see: https://zeromq.org/languages/python/
diff --git a/examples/notebooks/multiprocessing_zmq/multiprocessing_zmq_compute.ipynb b/examples/notebooks/multiprocessing_zmq/multiprocessing_zmq_compute.ipynb
new file mode 100644
index 000000000..7f24f6411
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+++ b/examples/notebooks/multiprocessing_zmq/multiprocessing_zmq_compute.ipynb
@@ -0,0 +1,73 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ca2817a3-869c-4cc6-901b-c34509518175",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import zmq"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "dd0b9780-b507-4ea2-af09-134abd76f45b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "context = zmq.Context()\n",
+ "\n",
+ "# create publisher\n",
+ "socket = context.socket(zmq.PUB)\n",
+ "socket.bind(\"tcp://127.0.0.1:5555\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "4729bfe8-3474-4bc9-a489-a57d02e5a287",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for i in range(2_000):\n",
+ " # make some data, make note of the dtype\n",
+ " data = np.random.rand(512, 512).astype(np.float32)\n",
+ "\n",
+ " # sent bytes over the socket\n",
+ " socket.send(data.tobytes())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "d47dab72-1061-439f-bf6e-a88b9ee8e5aa",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/notebooks/multiprocessing_zmq/multiprocessing_zmq_plot.ipynb b/examples/notebooks/multiprocessing_zmq/multiprocessing_zmq_plot.ipynb
new file mode 100644
index 000000000..2c6e93d8f
--- /dev/null
+++ b/examples/notebooks/multiprocessing_zmq/multiprocessing_zmq_plot.ipynb
@@ -0,0 +1,114 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "491e6050-64ae-4bfc-a480-5805cd684710",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import fastplotlib as fpl\n",
+ "import numpy as np\n",
+ "import zmq"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "97135f98-6810-49b6-a8de-d0e114720d6c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "context = zmq.Context()\n",
+ "\n",
+ "# create subscriber\n",
+ "sub = context.socket(zmq.SUB)\n",
+ "sub.setsockopt(zmq.SUBSCRIBE, b\"\")\n",
+ "\n",
+ "# keep only the most recent message\n",
+ "sub.setsockopt(zmq.CONFLATE, 1)\n",
+ "\n",
+ "# publisher address and port\n",
+ "sub.connect(\"tcp://127.0.0.1:5555\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2d4420f2-364a-445a-9658-63e9ffa586c3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_bytes():\n",
+ " \"\"\"\n",
+ " Gets the bytes from the publisher\n",
+ " \"\"\"\n",
+ " try:\n",
+ " b = sub.recv(zmq.NOBLOCK)\n",
+ " except zmq.Again:\n",
+ " pass\n",
+ " else:\n",
+ " return b\n",
+ " \n",
+ " return None"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "42d20d77-b884-4379-80e4-e08738506eeb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plot = fpl.Plot()\n",
+ "\n",
+ "# initialize some data, must be of same dtype and shape as data sent by publisher\n",
+ "data = np.random.rand(512, 512).astype(np.float32)\n",
+ "plot.add_image(data, name=\"image\")\n",
+ "\n",
+ "def update_frame(p):\n",
+ " # recieve bytes\n",
+ " b = get_bytes()\n",
+ " \n",
+ " if b is not None:\n",
+ " # numpy array from bytes, MUST specify dtype and make sure it matches what you sent\n",
+ " a = np.frombuffer(b, dtype=np.float32).reshape(512, 512)\n",
+ " \n",
+ " # set graphic data\n",
+ " p[\"image\"].data = a\n",
+ "\n",
+ "plot.add_animations(update_frame)\n",
+ "plot.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "0f8ac188-9359-4d3c-b8f1-384be84d1585",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
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