From b7f4c00d78734b7e58346685e0e2b7b8fcb80cae Mon Sep 17 00:00:00 2001
From: Matthew Iannucci <mpiannucci@gmail.com>
Date: Wed, 1 Jan 2025 12:48:12 -0500
Subject: [PATCH 1/2] Add more mrms tables

---
 .../src/templates/product/parameters/mrms.rs  | 56 +++++++++++++++++++
 gribberish/src/utils/ccsds.rs                 |  1 +
 2 files changed, 57 insertions(+)

diff --git a/gribberish/src/templates/product/parameters/mrms.rs b/gribberish/src/templates/product/parameters/mrms.rs
index 54bfe8e..2a42a15 100644
--- a/gribberish/src/templates/product/parameters/mrms.rs
+++ b/gribberish/src/templates/product/parameters/mrms.rs
@@ -128,6 +128,62 @@ pub enum MRMSPrecipitationProduct {
     #[abbrev = "RadarOnly_QPE_72H"]
     #[unit = "mm"]
     RadarPrecipSeventyTwo = 8,
+    #[description = "Multi-sensor accumulation 1-hour (1-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_01H_Pass1"]
+    #[unit = "mm"]
+    MultiSensorPrecipOnePass1 = 30,
+    #[description = "Multi-sensor accumulation 3-hour (1-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_03H_Pass1"]
+    #[unit = "mm"]
+    MultiSensorPrecipThreePass1 = 31,
+    #[description = "Multi-sensor accumulation 6-hour (1-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_06H_Pass1"]
+    #[unit = "mm"]
+    MultiSensorPrecipSixPass1 = 32,
+    #[description = "Multi-sensor accumulation 12-hour (1-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_12H_Pass1"]
+    #[unit = "mm"]
+    MultiSensorPrecipTwelvePass1 = 33,
+    #[description = "Multi-sensor accumulation 24-hour (1-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_24H_Pass1"]
+    #[unit = "mm"]
+    MultiSensorPrecipTwentyFourPass1 = 34,
+    #[description = "Multi-sensor accumulation 48-hour (1-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_48H_Pass1"]
+    #[unit = "mm"]
+    MultiSensorPrecipFortyEightPass1 = 35,
+    #[description = "Multi-sensor accumulation 72-hour (1-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_72H_Pass1"]
+    #[unit = "mm"]
+    MultiSensorPrecipSeventyTwoPass1 = 36,
+    #[description = "Multi-sensor accumulation 1-hour (2-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_01H_Pass2"]
+    #[unit = "mm"]
+    MultiSensorPrecipOnePass2 = 37,
+    #[description = "Multi-sensor accumulation 3-hour (2-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_03H_Pass2"]
+    #[unit = "mm"]
+    MultiSensorPrecipThreePass2 = 38,
+    #[description = "Multi-sensor accumulation 6-hour (2-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_06H_Pass2"]
+    #[unit = "mm"]
+    MultiSensorPrecipSixPass2 = 39,
+    #[description = "Multi-sensor accumulation 12-hour (2-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_12H_Pass2"]
+    #[unit = "mm"]
+    MultiSensorPrecipTwelvePass2 = 40,
+    #[description = "Multi-sensor accumulation 24-hour (2-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_24H_Pass2"]
+    #[unit = "mm"]
+    MultiSensorPrecipTwentyFourPass2 = 41,
+    #[description = "Multi-sensor accumulation 48-hour (2-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_48H_Pass2"]
+    #[unit = "mm"]
+    MultiSensorPrecipFortyEightPass2 = 42,
+    #[description = "Multi-sensor accumulation 72-hour (2-hour latency)"]
+    #[abbrev = "MultiSensor_QPE_72H_Pass2"]
+    #[unit = "mm"]
+    MultiSensorPrecipSeventyTwoPass2 = 43,
     #[description = "Radar precipitation accumulation 15-minute"]
     #[abbrev = "RadarOnly_QPE_15M"]
     #[unit = "mm"]
diff --git a/gribberish/src/utils/ccsds.rs b/gribberish/src/utils/ccsds.rs
index b325d0f..d150f7c 100644
--- a/gribberish/src/utils/ccsds.rs
+++ b/gribberish/src/utils/ccsds.rs
@@ -60,6 +60,7 @@ pub struct InternalState {
     pub avail_in: usize,
     pub avail_out: usize,
     pub total_in: usize,
+    #[allow(dead_code)]
     pub total_out: usize,
 
     /** First not yet flushed byte in rsi_buffer */

From bb0ef4aeef0c8ef0caca8bbc516bd90d49671d77 Mon Sep 17 00:00:00 2001
From: Matthew Iannucci <mpiannucci@gmail.com>
Date: Wed, 1 Jan 2025 12:56:50 -0500
Subject: [PATCH 2/2] Bump versions

---
 .github/workflows/python.yml     |   2 +-
 Cargo.lock                       |  10 +-
 gribberish/Cargo.toml            |   6 +-
 macros/Cargo.toml                |   4 +-
 node/Cargo.toml                  |   4 +-
 python/Cargo.toml                |   4 +-
 python/examples/read_radar.ipynb | 470 ++++---------------------------
 types/Cargo.toml                 |   2 +-
 8 files changed, 64 insertions(+), 438 deletions(-)

diff --git a/.github/workflows/python.yml b/.github/workflows/python.yml
index 0940299..a7d5cde 100644
--- a/.github/workflows/python.yml
+++ b/.github/workflows/python.yml
@@ -115,7 +115,7 @@ jobs:
     strategy:
       matrix:
         platform:
-          - runner: macos-12
+          - runner: macos-14
             target: x86_64
           - runner: macos-14
             target: aarch64
diff --git a/Cargo.lock b/Cargo.lock
index c109009..c23f927 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -277,7 +277,7 @@ dependencies = [
 
 [[package]]
 name = "gribberish"
-version = "0.21.1"
+version = "0.21.2"
 dependencies = [
  "bitflags 2.6.0",
  "bitvec",
@@ -295,7 +295,7 @@ dependencies = [
 
 [[package]]
 name = "gribberish-macros"
-version = "0.21.1"
+version = "0.21.2"
 dependencies = [
  "gribberish-types",
  "quote",
@@ -304,11 +304,11 @@ dependencies = [
 
 [[package]]
 name = "gribberish-types"
-version = "0.21.1"
+version = "0.21.2"
 
 [[package]]
 name = "gribberishjs"
-version = "0.21.1"
+version = "0.21.2"
 dependencies = [
  "chrono",
  "gribberish",
@@ -319,7 +319,7 @@ dependencies = [
 
 [[package]]
 name = "gribberishpy"
-version = "0.21.1"
+version = "0.21.2"
 dependencies = [
  "gribberish",
  "numpy",
diff --git a/gribberish/Cargo.toml b/gribberish/Cargo.toml
index 98a54bf..c12b287 100644
--- a/gribberish/Cargo.toml
+++ b/gribberish/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "gribberish"
-version = "0.21.1"
+version = "0.21.2"
 authors = ["Matthew Iannucci <mpiannucci@gmail.com>"]
 description = "Parse grib 2 files with Rust"
 edition = "2021"
@@ -10,8 +10,8 @@ keywords = ["grib", "weather", "meteorology", "climate", "oceanography"]
 categories = ["science", "encoding", "compression"]
 
 [dependencies]
-gribberish-types = { path = "../types", version = "0.21.1" }
-gribberish-macros = { path = "../macros", version = "0.21.1" }
+gribberish-types = { path = "../types", version = "0.21.2" }
+gribberish-macros = { path = "../macros", version = "0.21.2" }
 chrono = "0.4"
 openjpeg-sys = { version = "1.0.3", optional = true }
 png = { version = "0.17.2", optional = true }
diff --git a/macros/Cargo.toml b/macros/Cargo.toml
index 7013cbf..171df1e 100644
--- a/macros/Cargo.toml
+++ b/macros/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "gribberish-macros"
-version = "0.21.1"
+version = "0.21.2"
 authors = ["Matthew Iannucci <mpiannucci@gmail.com>"]
 description = "Procedural macros for the gribberish crate"
 edition = "2021"
@@ -10,7 +10,7 @@ repository = "https://github.com/mpiannucci/gribberish"
 # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
 
 [dependencies]
-gribberish-types = { path = "./../types", version = "0.21.1" }
+gribberish-types = { path = "./../types", version = "0.21.2" }
 syn = { version = "1.0", features = ["full"] }
 quote = "1.0"
 
diff --git a/node/Cargo.toml b/node/Cargo.toml
index d4731c6..8e856ad 100644
--- a/node/Cargo.toml
+++ b/node/Cargo.toml
@@ -1,7 +1,7 @@
 [package]
 edition = "2021"
 name = "gribberishjs"
-version = "0.21.1"
+version = "0.21.2"
 
 [lib]
 crate-type = ["cdylib"]
@@ -10,7 +10,7 @@ crate-type = ["cdylib"]
 # Default enable napi4 feature, see https://nodejs.org/api/n-api.html#node-api-version-matrix
 napi = { version = "2.5.0", default-features = false, features = ["chrono_date"] }
 napi-derive = "2.5.0"
-gribberish = { path = "../gribberish", version = "0.21.1" }
+gribberish = { path = "../gribberish", version = "0.21.2" }
 chrono = "0.4"
 
 [build-dependencies]
diff --git a/python/Cargo.toml b/python/Cargo.toml
index 17a0f67..3977018 100644
--- a/python/Cargo.toml
+++ b/python/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "gribberishpy"
-version = "0.21.1"
+version = "0.21.2"
 edition = "2021"
 
 # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
@@ -10,5 +10,5 @@ crate-type = ["cdylib"]
 
 [dependencies]
 pyo3 = "0.23.1"
-gribberish = { path = "../gribberish", version = "0.21.1" }
+gribberish = { path = "../gribberish", version = "0.21.2" }
 numpy = "0.23.0"
diff --git a/python/examples/read_radar.ipynb b/python/examples/read_radar.ipynb
index 7fddf27..a94c171 100644
--- a/python/examples/read_radar.ipynb
+++ b/python/examples/read_radar.ipynb
@@ -23,424 +23,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
-       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "</symbol>\n",
-       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body[data-theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-index-preview {\n",
-       "  grid-column: 2 / 5;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data,\n",
-       ".xr-index-data-in:checked ~ .xr-index-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-index-name div,\n",
-       ".xr-index-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:                        (time: 1, latitude: 3500, longitude: 7000)\n",
-       "Coordinates:\n",
-       "  * time                           (time) datetime64[ns] 2022-07-04T07:00:40\n",
-       "  * latitude                       (latitude) float64 54.99 54.98 ... 20.01 20.0\n",
-       "  * longitude                      (longitude) float64 230.0 230.0 ... 300.0\n",
-       "Data variables:\n",
-       "    mergedreflectivityqccomposite  (time, latitude, longitude) float64 ...\n",
-       "Attributes:\n",
-       "    meta:     Generated with gribberishpy</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1826b016-4904-4a64-a919-8596da1e6821' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1826b016-4904-4a64-a919-8596da1e6821' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>latitude</span>: 3500</li><li><span class='xr-has-index'>longitude</span>: 7000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ffca4081-bdf1-4d5a-9ef0-2c38eb3844a9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ffca4081-bdf1-4d5a-9ef0-2c38eb3844a9' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-07-04T07:00:40</div><input id='attrs-1a84b962-24ec-4bd2-8c11-f98069bcf0d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a84b962-24ec-4bd2-8c11-f98069bcf0d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54fcba34-d447-4523-80a3-52c5f3662df6' class='xr-var-data-in' type='checkbox'><label for='data-54fcba34-d447-4523-80a3-52c5f3662df6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>unit :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-07-04T07:00:40.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>54.99 54.98 54.97 ... 20.01 20.0</div><input id='attrs-8ecc2849-ff67-4b27-901d-b406e617efa0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ecc2849-ff67-4b27-901d-b406e617efa0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa33a358-2706-464d-af40-fa8211856169' class='xr-var-data-in' type='checkbox'><label for='data-aa33a358-2706-464d-af40-fa8211856169' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>unit :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([54.995, 54.985, 54.975, ..., 20.025, 20.015, 20.005])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>230.0 230.0 230.0 ... 300.0 300.0</div><input id='attrs-30757daf-2311-49f5-a6c7-d145d85cf18b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30757daf-2311-49f5-a6c7-d145d85cf18b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc73d8e8-7279-4fd3-b4b1-940e858e8d3a' class='xr-var-data-in' type='checkbox'><label for='data-bc73d8e8-7279-4fd3-b4b1-940e858e8d3a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>unit :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([230.005, 230.015, 230.025, ..., 299.975, 299.985, 299.995])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bf676a66-c566-4756-be82-112724a23e86' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bf676a66-c566-4756-be82-112724a23e86' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mergedreflectivityqccomposite</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cf0a47eb-fd6f-4321-8a15-b25e7a2c21f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf0a47eb-fd6f-4321-8a15-b25e7a2c21f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a74dff70-e846-409b-bd5a-989450cfba24' class='xr-var-data-in' type='checkbox'><label for='data-a74dff70-e846-409b-bd5a-989450cfba24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mergedreflectivityqccomposite</dd><dt><span>long_name :</span></dt><dd>mergedreflectivityqccomposite</dd><dt><span>unit :</span></dt><dd>dBZ</dd><dt><span>coordinates :</span></dt><dd>latitude longitude</dd><dt><span>generating_process :</span></dt><dd>observation</dd></dl></div><div class='xr-var-data'><pre>[24500000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b5a41a07-c911-41ce-bb5b-8603de1e28b7' class='xr-section-summary-in' type='checkbox'  ><label for='section-b5a41a07-c911-41ce-bb5b-8603de1e28b7' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-db11fd0a-b42a-475e-95c4-f9422c598ad5' class='xr-index-data-in' type='checkbox'/><label for='index-db11fd0a-b42a-475e-95c4-f9422c598ad5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-07-04 07:00:40&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-170c0680-7750-489e-bd87-e41e77917c6b' class='xr-index-data-in' type='checkbox'/><label for='index-170c0680-7750-489e-bd87-e41e77917c6b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([            54.995,             54.985, 54.974999999999994,\n",
-       "              54.964999999999996,             54.955,             54.945,\n",
-       "              54.934999999999995,             54.925,             54.915,\n",
-       "              54.904999999999994,\n",
-       "              ...\n",
-       "                          20.095, 20.084999999999994, 20.074999999999996,\n",
-       "              20.064999999999998,             20.055, 20.044999999999995,\n",
-       "              20.034999999999997,             20.025, 20.014999999999993,\n",
-       "              20.004999999999995],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=3500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3b2907f8-770c-43d9-a1bc-3c78ef386a8e' class='xr-index-data-in' type='checkbox'/><label for='index-3b2907f8-770c-43d9-a1bc-3c78ef386a8e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([           230.005,            230.015,            230.025,\n",
-       "                         230.035,            230.045,            230.055,\n",
-       "                         230.065,            230.075,            230.085,\n",
-       "                         230.095,\n",
-       "              ...\n",
-       "                         299.905, 299.91499999999996,            299.925,\n",
-       "                         299.935,            299.945,            299.955,\n",
-       "              299.96500000000003,            299.975,            299.985,\n",
-       "                         299.995],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=7000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7e707f30-a9ee-40a5-8390-97923d51f72e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7e707f30-a9ee-40a5-8390-97923d51f72e' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>meta :</span></dt><dd>Generated with gribberishpy</dd></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:                        (time: 1, latitude: 3500, longitude: 7000)\n",
-       "Coordinates:\n",
-       "  * time                           (time) datetime64[ns] 2022-07-04T07:00:40\n",
-       "  * latitude                       (latitude) float64 54.99 54.98 ... 20.01 20.0\n",
-       "  * longitude                      (longitude) float64 230.0 230.0 ... 300.0\n",
-       "Data variables:\n",
-       "    mergedreflectivityqccomposite  (time, latitude, longitude) float64 ...\n",
-       "Attributes:\n",
-       "    meta:     Generated with gribberishpy"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "ValueError",
+     "evalue": "No valid GRIB messages found",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[3], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m ds \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/Users/matthew/Downloads/mrms/MRMS_MultiSensor_QPE_01H_Pass2_00.00_20250101-070000.grib2\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mgribberish\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m ds\n",
+      "File \u001b[0;32m~/Developer/gribberish/python/.venv/lib/python3.11/site-packages/xarray/backends/api.py:670\u001b[0m, in \u001b[0;36mopen_dataset\u001b[0;34m(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, inline_array, chunked_array_type, from_array_kwargs, backend_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m    658\u001b[0m decoders \u001b[38;5;241m=\u001b[39m _resolve_decoders_kwargs(\n\u001b[1;32m    659\u001b[0m     decode_cf,\n\u001b[1;32m    660\u001b[0m     open_backend_dataset_parameters\u001b[38;5;241m=\u001b[39mbackend\u001b[38;5;241m.\u001b[39mopen_dataset_parameters,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    666\u001b[0m     decode_coords\u001b[38;5;241m=\u001b[39mdecode_coords,\n\u001b[1;32m    667\u001b[0m )\n\u001b[1;32m    669\u001b[0m overwrite_encoded_chunks \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moverwrite_encoded_chunks\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m--> 670\u001b[0m backend_ds \u001b[38;5;241m=\u001b[39m \u001b[43mbackend\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    671\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    672\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdrop_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    673\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdecoders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    674\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    675\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    676\u001b[0m ds \u001b[38;5;241m=\u001b[39m _dataset_from_backend_dataset(\n\u001b[1;32m    677\u001b[0m     backend_ds,\n\u001b[1;32m    678\u001b[0m     filename_or_obj,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    688\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m    689\u001b[0m )\n\u001b[1;32m    690\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ds\n",
+      "File \u001b[0;32m~/Developer/gribberish/python/gribberish/gribberish_backend.py:38\u001b[0m, in \u001b[0;36mGribberishBackend.open_dataset\u001b[0;34m(self, filename_or_obj, storage_options, drop_variables, only_variables, perserve_dims, filter_by_attrs, filter_by_variable_attrs)\u001b[0m\n\u001b[1;32m     35\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m fsspec\u001b[38;5;241m.\u001b[39mopen(filename_or_obj, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrb\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mstorage_options) \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[1;32m     36\u001b[0m     raw_data \u001b[38;5;241m=\u001b[39m f\u001b[38;5;241m.\u001b[39mread()\n\u001b[0;32m---> 38\u001b[0m     dataset \u001b[38;5;241m=\u001b[39m  \u001b[43mparse_grib_dataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     39\u001b[0m \u001b[43m        \u001b[49m\u001b[43mraw_data\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m     40\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdrop_variables\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m     41\u001b[0m \u001b[43m        \u001b[49m\u001b[43monly_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43monly_variables\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m     42\u001b[0m \u001b[43m        \u001b[49m\u001b[43mperserve_dims\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mperserve_dims\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m     43\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfilter_by_attrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilter_by_attrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m     44\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfilter_by_variable_attrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilter_by_variable_attrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     45\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     46\u001b[0m     coords \u001b[38;5;241m=\u001b[39m {k: (v[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdims\u001b[39m\u001b[38;5;124m'\u001b[39m], v[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mvalues\u001b[39m\u001b[38;5;124m'\u001b[39m], v[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mattrs\u001b[39m\u001b[38;5;124m'\u001b[39m]) \u001b[38;5;28;01mfor\u001b[39;00m (k, v) \u001b[38;5;129;01min\u001b[39;00m dataset[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcoords\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mitems()}\n\u001b[1;32m     47\u001b[0m     data_vars \u001b[38;5;241m=\u001b[39m {k: (v[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdims\u001b[39m\u001b[38;5;124m'\u001b[39m], GribberishBackendArray(filename_or_obj, storage_options\u001b[38;5;241m=\u001b[39mstorage_options, array_metadata\u001b[38;5;241m=\u001b[39mv[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mvalues\u001b[39m\u001b[38;5;124m'\u001b[39m]) , v[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mattrs\u001b[39m\u001b[38;5;124m'\u001b[39m]) \u001b[38;5;28;01mfor\u001b[39;00m (k, v) \u001b[38;5;129;01min\u001b[39;00m dataset[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata_vars\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mitems()}\n",
+      "\u001b[0;31mValueError\u001b[0m: No valid GRIB messages found"
+     ]
     }
    ],
    "source": [
-    "ds = xr.open_dataset('MRMS_MergedReflectivityQCComposite_00.50_20220704-110040.grib2', engine='gribberish')\n",
+    "ds = xr.open_dataset('/Users/matthew/Downloads/mrms/MRMS_MultiSensor_QPE_01H_Pass2_00.00_20250101-070000.grib2', engine='gribberish')\n",
     "ds"
    ]
   },
@@ -452,7 +53,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x16680d820>"
+       "<matplotlib.collections.QuadMesh at 0x1274a2150>"
       ]
      },
      "execution_count": 3,
@@ -461,7 +62,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -475,11 +76,41 @@
     "radar = radar.where(radar > -10)\n",
     "radar.plot(vmin=-10, vmax=80)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import ujson\n",
+    "from gribberish.kerchunk import scan_gribberish\n",
+    "\n",
+    "out = scan_gribberish('/Users/matthew/Downloads/mrms/MRMS_MultiSensor_QPE_01H_Pass2_00.00_20250101-060000.grib2', use_cfgrib_codec=True)\n",
+    "print(out)\n",
+    "with open('/Users/matthew/Downloads/mrms/dataset.json', 'w') as f:\n",
+    "    ujson.dump(out, f)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.9.11 64-bit ('3.9.11')",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -493,14 +124,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.11"
+   "version": "3.11.6"
   },
-  "orig_nbformat": 4,
-  "vscode": {
-   "interpreter": {
-    "hash": "f967b91afc8f880aae97afd7505e2f3f0ab4cd288ce8efac1efcdbc4f0ea20b2"
-   }
-  }
+  "orig_nbformat": 4
  },
  "nbformat": 4,
  "nbformat_minor": 2
diff --git a/types/Cargo.toml b/types/Cargo.toml
index e6214a3..f4b73ed 100644
--- a/types/Cargo.toml
+++ b/types/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "gribberish-types"
-version = "0.21.1"
+version = "0.21.2"
 authors = ["Matthew Iannucci <mpiannucci@gmail.com>"]
 description = "Common types for the gribberish crate"
 edition = "2021"