diff --git a/examples/rerun/.gitignore b/examples/rerun_example/.gitignore
similarity index 100%
rename from examples/rerun/.gitignore
rename to examples/rerun_example/.gitignore
diff --git a/examples/rerun/dna_example.py b/examples/rerun_example/dna_example.py
similarity index 100%
rename from examples/rerun/dna_example.py
rename to examples/rerun_example/dna_example.py
diff --git a/examples/rerun_example/force_driven_lockfile_graph.py b/examples/rerun_example/force_driven_lockfile_graph.py
new file mode 100644
index 000000000..a8225a8f2
--- /dev/null
+++ b/examples/rerun_example/force_driven_lockfile_graph.py
@@ -0,0 +1,108 @@
+import rerun as rr
+import networkx as nx
+import yaml
+import numpy as np
+import hashlib
+import sys
+
+# Give relative path or default to local pixi.lock
+lockfile_path = sys.argv[1] if len(sys.argv) > 1 else 'pixi.lock'
+
+with open(lockfile_path, 'r') as file:
+    lockfile_data = yaml.safe_load(file)
+
+package_data = lockfile_data['package']
+package_names = [package['name'] for package in package_data]
+
+graph = nx.DiGraph()
+for package in package_data:
+    package_name = package['name']
+    dependencies = package.get('dependencies', [])
+    graph.add_node(package_name)
+    for i, dep in enumerate(dependencies):
+        graph.add_edge(package_name, dep.split(" ")[0])
+
+rr.init("fdg", spawn=True)
+rr.connect()
+
+def hash_string_to_int(string):
+    return int(hashlib.sha256(string.encode('utf-8')).hexdigest(), 16) % (10 ** 8)
+
+
+# Memoization dictionary
+color_cache = {}
+
+
+# Function to get color
+def get_color_for_node(node):
+    if node not in color_cache:
+        np.random.seed(hash_string_to_int(node))
+        color_cache[node] = np.random.rand(3)  # Generate and store color
+    return color_cache[node]
+
+
+def apply_forces_and_log(graph, pos):
+    damping = 0.9
+    max_force = 1
+    degree_scale = 2  # Scale factor for degree-based forces
+    dist_scale = 0.5
+
+    iterations = 1000
+    repulsive_force = 0.01
+    attractive_force = 0.005
+
+    for iteration in range(iterations):
+        force = {node: np.zeros(3) for node in graph}
+
+        # Degree-based repulsive forces
+        for i, node1 in enumerate(graph):
+            for node2 in list(graph)[i + 1:]:
+                diff = pos[node1] - pos[node2]
+                dist = (np.linalg.norm(diff) + 1e-9) * dist_scale
+                degree_factor = (
+                        (graph.degree(node1) + graph.degree(node2)) * degree_scale)
+                repel = repulsive_force * degree_factor / dist ** 2
+                force_vector = repel * diff  # / dist
+                force[node1] += np.clip(force_vector, -max_force, max_force)
+                force[node2] -= np.clip(force_vector, -max_force, max_force)
+
+        # Degree-based attractive forces
+        for edge in graph.edges():
+            u, v = edge
+            diff = pos[u] - pos[v]
+            dist = dist = (np.linalg.norm(diff) + 1e-9) * dist_scale
+            if dist > 0:
+                degree_factor = (graph.degree(u) + graph.degree(v)) * degree_scale
+                attract = (attractive_force * dist ** 2) / degree_factor
+                force[u] -= attract * diff / dist
+                force[v] += attract * diff / dist
+
+        # Update positions with damping
+        for node in graph:
+            pos[node] += force[node] * damping
+            position = np.array(pos[node])
+            color = get_color_for_node(node)  # Retrieve color, memoized
+            rr.log(f"graph_nodes/{node}",
+                   rr.Points3D([position],
+                               colors=[color],
+                               radii=max(graph.degree(node) / 20, 0.5)),
+                   rr.AnyValues(node))
+
+        edges_array = np.array([[pos[u], pos[v]] for u, v in graph.edges()])
+
+        # Log the edges array
+        rr.log("graph_nodes/graph_edges",
+               rr.LineStrips3D(edges_array, radii=0.02, colors=[1, 1, 1, 0.1]))
+
+    return pos
+
+
+# Identify the node with the highest degree
+central_node = max(graph.degree, key=lambda x: x[1])[0]
+
+# Initial positions with the central node at the center
+initial_pos = nx.spring_layout(graph, dim=3)
+initial_pos[central_node] = np.array([0.5, 0.5, 0.5])  # Center position
+
+# Apply the force-directed simulation
+final_pos = apply_forces_and_log(graph, initial_pos)
diff --git a/examples/rerun/pixi.lock b/examples/rerun_example/pixi.lock
similarity index 96%
rename from examples/rerun/pixi.lock
rename to examples/rerun_example/pixi.lock
index 69bc0bdc5..8958e420d 100644
--- a/examples/rerun/pixi.lock
+++ b/examples/rerun_example/pixi.lock
@@ -1,4 +1,4 @@
-version: 2
+version: 3
 metadata:
   content_hash:
     linux-64: e90c2ee71ad70fc0a1c8302029533a7d1498f2bffcd0eaa8d2934700e775dc1d
@@ -5260,24 +5260,124 @@ package:
   license: X11 AND BSD-3-Clause
   size: 799196
   timestamp: 1686077139703
+- platform: linux-64
+  name: networkx
+  version: 3.2.1
+  category: main
+  manager: conda
+  dependencies:
+  - python >=3.9
+  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
+  hash:
+    md5: 425fce3b531bed6ec3c74fab3e5f0a1c
+    sha256: 7629aa4f9f8cdff45ea7a4701fe58dccce5bf2faa01c26eb44cbb27b7e15ca9d
+  build: pyhd8ed1ab_0
+  arch: x86_64
+  subdir: linux-64
+  build_number: 0
+  constrains:
+  - matplotlib >=3.5
+  - scipy >=1.9,!=1.11.0,!=1.11.1
+  - numpy >=1.22
+  - pandas >=1.4
+  license: BSD-3-Clause
+  license_family: BSD
+  noarch: python
+  size: 1149552
+  timestamp: 1698504905258
+- platform: osx-64
+  name: networkx
+  version: 3.2.1
+  category: main
+  manager: conda
+  dependencies:
+  - python >=3.9
+  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
+  hash:
+    md5: 425fce3b531bed6ec3c74fab3e5f0a1c
+    sha256: 7629aa4f9f8cdff45ea7a4701fe58dccce5bf2faa01c26eb44cbb27b7e15ca9d
+  build: pyhd8ed1ab_0
+  arch: x86_64
+  subdir: osx-64
+  build_number: 0
+  constrains:
+  - matplotlib >=3.5
+  - scipy >=1.9,!=1.11.0,!=1.11.1
+  - numpy >=1.22
+  - pandas >=1.4
+  license: BSD-3-Clause
+  license_family: BSD
+  noarch: python
+  size: 1149552
+  timestamp: 1698504905258
+- platform: osx-arm64
+  name: networkx
+  version: 3.2.1
+  category: main
+  manager: conda
+  dependencies:
+  - python >=3.9
+  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
+  hash:
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+    sha256: 7629aa4f9f8cdff45ea7a4701fe58dccce5bf2faa01c26eb44cbb27b7e15ca9d
+  build: pyhd8ed1ab_0
+  arch: aarch64
+  subdir: osx-arm64
+  build_number: 0
+  constrains:
+  - matplotlib >=3.5
+  - scipy >=1.9,!=1.11.0,!=1.11.1
+  - numpy >=1.22
+  - pandas >=1.4
+  license: BSD-3-Clause
+  license_family: BSD
+  noarch: python
+  size: 1149552
+  timestamp: 1698504905258
+- platform: win-64
+  name: networkx
+  version: 3.2.1
+  category: main
+  manager: conda
+  dependencies:
+  - python >=3.9
+  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
+  hash:
+    md5: 425fce3b531bed6ec3c74fab3e5f0a1c
+    sha256: 7629aa4f9f8cdff45ea7a4701fe58dccce5bf2faa01c26eb44cbb27b7e15ca9d
+  build: pyhd8ed1ab_0
+  arch: x86_64
+  subdir: win-64
+  build_number: 0
+  constrains:
+  - matplotlib >=3.5
+  - scipy >=1.9,!=1.11.0,!=1.11.1
+  - numpy >=1.22
+  - pandas >=1.4
+  license: BSD-3-Clause
+  license_family: BSD
+  noarch: python
+  size: 1149552
+  timestamp: 1698504905258
 - platform: linux-64
   name: numpy
-  version: 1.25.1
+  version: 1.26.2
   category: main
   manager: conda
   dependencies:
+  - libblas >=3.9.0,<4.0a0
   - libcblas >=3.9.0,<4.0a0
+  - libgcc-ng >=12
   - liblapack >=3.9.0,<4.0a0
   - libstdcxx-ng >=12
   - python >=3.10,<3.11.0a0
   - python_abi 3.10.* *_cp310
-  - libblas >=3.9.0,<4.0a0
-  - libgcc-ng >=12
-  url: https://conda.anaconda.org/conda-forge/linux-64/numpy-1.25.1-py310ha4c1d20_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/numpy-1.26.2-py310hb13e2d6_0.conda
   hash:
-    md5: 3810cbf2635cb1d0edb97715d4ad74e7
-    sha256: 38ec15fe0afe9fb90bd50314ccd506f0e7d1642db0c7eb2b77627d448aa9ee6c
-  build: py310ha4c1d20_0
+    md5: d3147cfbf72d6ae7bba10562208f6def
+    sha256: f5ea7769beb7827f4f5858d28bbdbc814c01649cb8cb81cccbba476ebe3798cd
+  build: py310hb13e2d6_0
   arch: x86_64
   subdir: linux-64
   build_number: 0
@@ -5285,25 +5385,26 @@ package:
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   license: BSD-3-Clause
   license_family: BSD
-  size: 6816069
-  timestamp: 1688887559516
+  size: 6922736
+  timestamp: 1700875005993
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   name: numpy
-  version: 1.25.1
+  version: 1.26.2
   category: main
   manager: conda
   dependencies:
+  - __osx >=10.9
+  - libblas >=3.9.0,<4.0a0
   - libcblas >=3.9.0,<4.0a0
-  - libcxx >=15.0.7
+  - libcxx >=16.0.6
   - liblapack >=3.9.0,<4.0a0
   - python >=3.10,<3.11.0a0
   - python_abi 3.10.* *_cp310
-  - libblas >=3.9.0,<4.0a0
-  url: https://conda.anaconda.org/conda-forge/osx-64/numpy-1.25.1-py310h7451ae0_0.conda
+  url: https://conda.anaconda.org/conda-forge/osx-64/numpy-1.26.2-py310h2a7ecf2_0.conda
   hash:
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-    sha256: 32fe99f86e998169999514fb7f96695fdec9215bd0e7061425c1b4e399ca2cae
-  build: py310h7451ae0_0
+    md5: 1ab91874430a8d4ba9b622082e08f438
+    sha256: e607a924f5fce4b17262c4e091efcf6d1ccfded59212d9ac786ecf89f4cecae4
+  build: py310h2a7ecf2_0
   arch: x86_64
   subdir: osx-64
   build_number: 0
@@ -5311,25 +5412,27 @@ package:
   - numpy-base <0a0
   license: BSD-3-Clause
   license_family: BSD
-  size: 6378643
-  timestamp: 1688887678910
+  size: 6368647
+  timestamp: 1700875132575
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   name: numpy
-  version: 1.25.1
+  version: 1.26.2
   category: main
   manager: conda
   dependencies:
+  - __osx >=10.9
+  - libblas >=3.9.0,<4.0a0
   - libcblas >=3.9.0,<4.0a0
-  - libcxx >=15.0.7
+  - libcxx >=16.0.6
   - liblapack >=3.9.0,<4.0a0
+  - python >=3.10,<3.11.0a0
   - python >=3.10,<3.11.0a0 *_cpython
   - python_abi 3.10.* *_cp310
-  - libblas >=3.9.0,<4.0a0
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/numpy-1.25.1-py310haa1e00c_0.conda
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/numpy-1.26.2-py310h30ee222_0.conda
   hash:
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-    sha256: 80a838a20e053efe45da5bdad7b21383eda398384caae77453330386c705012a
-  build: py310haa1e00c_0
+    md5: baea68ccbc288b1a8afb237ddee162c8
+    sha256: d1c03544798b3916c97571dcc3ec3cde8ad2d9afe2f7ab82277fdadef4186e46
+  build: py310h30ee222_0
   arch: aarch64
   subdir: osx-arm64
   build_number: 0
@@ -5337,27 +5440,27 @@ package:
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   license_family: BSD
-  size: 5634016
-  timestamp: 1688887693258
+  size: 5562504
+  timestamp: 1700875196095
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-  - python_abi 3.10.* *_cp310
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-  - ucrt >=10.0.20348.0
   - libcblas >=3.9.0,<4.0a0
   - liblapack >=3.9.0,<4.0a0
+  - python >=3.10,<3.11.0a0
+  - python_abi 3.10.* *_cp310
+  - ucrt >=10.0.20348.0
+  - vc >=14.2,<15
   - vc14_runtime >=14.29.30139
-  url: https://conda.anaconda.org/conda-forge/win-64/numpy-1.25.1-py310hd02465a_0.conda
+  url: https://conda.anaconda.org/conda-forge/win-64/numpy-1.26.2-py310hf667824_0.conda
   hash:
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-    sha256: 25e07d23dd78641537082fd9b0c4183784fcc1d84c65f207d6e2e7ede7702c8f
-  build: py310hd02465a_0
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+    sha256: 574818695f0d320e0bc8405dd777f154e065deecfdc3546878443ce8dfe5af35
+  build: py310hf667824_0
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@@ -5365,8 +5468,8 @@ package:
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   license: BSD-3-Clause
   license_family: BSD
-  size: 5985520
-  timestamp: 1688887651966
+  size: 6001822
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   name: openjpeg
   version: 2.5.0
@@ -6159,6 +6262,95 @@ package:
   license_family: BSD
   size: 6130
   timestamp: 1669071917673
+- platform: linux-64
+  name: pyyaml
+  version: 6.0.1
+  category: main
+  manager: conda
+  dependencies:
+  - libgcc-ng >=12
+  - python >=3.10,<3.11.0a0
+  - python_abi 3.10.* *_cp310
+  - yaml >=0.2.5,<0.3.0a0
+  url: https://conda.anaconda.org/conda-forge/linux-64/pyyaml-6.0.1-py310h2372a71_1.conda
+  hash:
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+    sha256: aa78ccddb0a75fa722f0f0eb3537c73ee1219c9dd46cea99d6b9eebfdd780f3d
+  build: py310h2372a71_1
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+  license: MIT
+  license_family: MIT
+  size: 170627
+  timestamp: 1695373587159
+- platform: osx-64
+  name: pyyaml
+  version: 6.0.1
+  category: main
+  manager: conda
+  dependencies:
+  - python >=3.10,<3.11.0a0
+  - python_abi 3.10.* *_cp310
+  - yaml >=0.2.5,<0.3.0a0
+  url: https://conda.anaconda.org/conda-forge/osx-64/pyyaml-6.0.1-py310h6729b98_1.conda
+  hash:
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+  license: MIT
+  license_family: MIT
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+  timestamp: 1695373947773
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+  name: pyyaml
+  version: 6.0.1
+  category: main
+  manager: conda
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+  - python >=3.10,<3.11.0a0
+  - python >=3.10,<3.11.0a0 *_cpython
+  - python_abi 3.10.* *_cp310
+  - yaml >=0.2.5,<0.3.0a0
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/pyyaml-6.0.1-py310h2aa6e3c_1.conda
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+  build: py310h2aa6e3c_1
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+  license: MIT
+  license_family: MIT
+  size: 158641
+  timestamp: 1695373859696
+- platform: win-64
+  name: pyyaml
+  version: 6.0.1
+  category: main
+  manager: conda
+  dependencies:
+  - python >=3.10,<3.11.0a0
+  - python_abi 3.10.* *_cp310
+  - ucrt >=10.0.20348.0
+  - vc >=14.2,<15
+  - vc14_runtime >=14.29.30139
+  - yaml >=0.2.5,<0.3.0a0
+  url: https://conda.anaconda.org/conda-forge/win-64/pyyaml-6.0.1-py310h8d17308_1.conda
+  hash:
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+  build: py310h8d17308_1
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+  license: MIT
+  license_family: MIT
+  size: 146195
+  timestamp: 1695374085323
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   version: '28.9'
@@ -7100,6 +7292,81 @@ package:
   license: LGPL-2.1 and GPL-2.0
   size: 217804
   timestamp: 1660346976440
+- platform: linux-64
+  name: yaml
+  version: 0.2.5
+  category: main
+  manager: conda
+  dependencies:
+  - libgcc-ng >=9.4.0
+  url: https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h7f98852_2.tar.bz2
+  hash:
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+  arch: x86_64
+  subdir: linux-64
+  build_number: 2
+  license: MIT
+  license_family: MIT
+  size: 89141
+  timestamp: 1641346969816
+- platform: osx-64
+  name: yaml
+  version: 0.2.5
+  category: main
+  manager: conda
+  dependencies: []
+  url: https://conda.anaconda.org/conda-forge/osx-64/yaml-0.2.5-h0d85af4_2.tar.bz2
+  hash:
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+  build: h0d85af4_2
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+  build_number: 2
+  license: MIT
+  license_family: MIT
+  size: 84237
+  timestamp: 1641347062780
+- platform: osx-arm64
+  name: yaml
+  version: 0.2.5
+  category: main
+  manager: conda
+  dependencies: []
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/yaml-0.2.5-h3422bc3_2.tar.bz2
+  hash:
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+  build_number: 2
+  license: MIT
+  license_family: MIT
+  size: 88016
+  timestamp: 1641347076660
+- platform: win-64
+  name: yaml
+  version: 0.2.5
+  category: main
+  manager: conda
+  dependencies:
+  - vc >=14.1,<15.0a0
+  - vs2015_runtime >=14.16.27012
+  url: https://conda.anaconda.org/conda-forge/win-64/yaml-0.2.5-h8ffe710_2.tar.bz2
+  hash:
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+  build: h8ffe710_2
+  arch: x86_64
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+  build_number: 2
+  license: MIT
+  license_family: MIT
+  size: 63274
+  timestamp: 1641347623319
 - platform: linux-64
   name: zstd
   version: 1.5.2
diff --git a/examples/rerun/pixi.toml b/examples/rerun_example/pixi.toml
similarity index 64%
rename from examples/rerun/pixi.toml
rename to examples/rerun_example/pixi.toml
index cdbaa1103..4f76c2daf 100644
--- a/examples/rerun/pixi.toml
+++ b/examples/rerun_example/pixi.toml
@@ -7,9 +7,11 @@ channels = ["conda-forge"]
 platforms = ["linux-64", "win-64", "osx-64", "osx-arm64"]
 
 [tasks]
-start = "python dna_example.py"
+start = "python force_driven_lockfile_graph.py"
 
 [dependencies]
-rerun-sdk = "0.10.1.*"
-numpy = "1.25.1.*"
+numpy = ">=1.26.2,<1.27"
 python = "3.10.12.*"
+rerun-sdk = ">=0.10.1,<0.11"
+networkx = ">=3.2.1,<3.3"
+pyyaml = ">=6.0.1,<6.1"