cloudnativegeo · kylebarron · Sep 1, 2023 · Aug 25, 2023 · Aug 25, 2023 · Aug 25, 2023
diff --git a/cloud-optimized-geotiffs/cogs-examples.ipynb b/cloud-optimized-geotiffs/cogs-examples.ipynb
diff --git a/cloud-optimized-geotiffs/environment.yml b/cloud-optimized-geotiffs/environment.yml
@@ -0,0 +1,11 @@
+name: coguide-cog
+channels:
+  - conda-forge
+dependencies:
+  - python=3.11
+  - earthaccess
+  - ipykernel
+  - jupyterlab
+  - matplotlib
+  - rasterio
+  - rio-cogeo
diff --git a/flatgeobuf/environment.yml b/flatgeobuf/environment.yml
@@ -0,0 +1,10 @@
+name: coguide-flatgeobuf
+channels:
+  - conda-forge
+dependencies:
+  - python=3.11
+  - geopandas==0.13.2
+  - pyogrio==0.6.0
+  - ipykernel
+  - jupyterlab
+  - pyarrow
diff --git a/flatgeobuf/flatgeobuf.ipynb b/flatgeobuf/flatgeobuf.ipynb
@@ -43,12 +43,24 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Versions\n",
+    "## Environment\n",
     "\n",
-    "The versions of `pyogrio` and `geopandas` used in this notebook are as follows:\n",
+    "The packages needed for this notebook can be installed with `conda` or `mamba`. Using the [`environment.yml` from this folder](./environment.yml) run:\n",
     "\n",
     "```bash\n",
-    "!pip install pyogrio==0.6.0 geopandas==0.13.2\n",
+    "conda create -f environment.yml\n",
+    "```\n",
+    "\n",
+    "or\n",
+    "\n",
+    "```bash\n",
+    "mamba create -f environment.yml\n",
+    "```\n",
+    "\n",
+    "Alternatively, you can install the versions of `pyogrio` and `geopandas` used in this notebook with pip:\n",
+    "\n",
+    "```bash\n",
+    "pip install pyogrio==0.6.0 geopandas==0.13.2\n",
     "```"
    ]
   },
@@ -61,7 +73,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -83,7 +95,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -108,14 +120,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "518 ms ± 6.57 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
+      "CPU times: user 565 ms, sys: 16.9 ms, total: 582 ms\n",
+      "Wall time: 685 ms\n"
      ]
     }
    ],
@@ -132,14 +145,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "28.9 ms ± 468 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
+      "CPU times: user 25.3 ms, sys: 6.84 ms, total: 32.1 ms\n",
+      "Wall time: 31.3 ms\n"
      ]
     }
    ],
@@ -156,14 +170,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "24 ms ± 351 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
+      "CPU times: user 19.7 ms, sys: 10.1 ms, total: 29.7 ms\n",
+      "Wall time: 29.1 ms\n"
      ]
     }
    ],
@@ -184,15 +199,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 354 ms, sys: 32 ms, total: 386 ms\n",
-      "Wall time: 394 ms\n"
+      "CPU times: user 362 ms, sys: 44.4 ms, total: 407 ms\n",
+      "Wall time: 418 ms\n"
      ]
     }
    ],
@@ -202,15 +217,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 61 ms, sys: 23.5 ms, total: 84.5 ms\n",
-      "Wall time: 94 ms\n"
+      "CPU times: user 60.8 ms, sys: 23.4 ms, total: 84.2 ms\n",
+      "Wall time: 83.5 ms\n"
      ]
     }
    ],
@@ -231,7 +246,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -247,7 +262,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -270,7 +285,7 @@
        " 'dataset_metadata': None}"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -294,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -312,15 +327,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 154 ms, sys: 44 ms, total: 198 ms\n",
-      "Wall time: 4.75 s\n"
+      "CPU times: user 144 ms, sys: 21.4 ms, total: 165 ms\n",
+      "Wall time: 6 s\n"
      ]
     }
    ],
@@ -337,15 +352,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 40.6 ms, sys: 16.5 ms, total: 57 ms\n",
-      "Wall time: 2 s\n"
+      "CPU times: user 26.9 ms, sys: 2.98 ms, total: 29.9 ms\n",
+      "Wall time: 490 ms\n"
      ]
     }
    ],
@@ -362,7 +377,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -511,7 +526,7 @@
        "4  MULTIPOLYGON (((4.41135 44.85476, 4.41134 44.8...  "
       ]
      },
-     "execution_count": 7,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -522,7 +537,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -531,7 +546,7 @@
        "(415, 11)"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -549,15 +564,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 29 ms, sys: 2.63 ms, total: 31.6 ms\n",
-      "Wall time: 439 ms\n"
+      "CPU times: user 25 ms, sys: 2.47 ms, total: 27.4 ms\n",
+      "Wall time: 706 ms\n"
      ]
     }
    ],
@@ -568,7 +583,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -654,7 +669,7 @@
        "4  MULTIPOLYGON (((4.41135 44.85476, 4.41134 44.8...  "
       ]
      },
-     "execution_count": 12,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }

diff --git a/geoparquet/environment.yml b/geoparquet/environment.yml
@@ -0,0 +1,18 @@
+name: coguide-geoparquet
+channels:
+  - conda-forge
+dependencies:
+  - python=3.11
+  - aiohttp
+  # TODO: how to define "fsspec[http]", so we don't have to manually install aiohttp
+  - fsspec
+  - geopandas==0.13.2
+  - ipykernel
+  - jupyterlab
+  - libgdal-arrow-parquet
+  - requests
+  # This is a hack to install pyarrow via pip because libgdal-arrow-parquet constrains libarrow to
+  # v10, which constrains pyarrow to v10, which is too old for the `filesystem` parameter at the end
+  # of the file
+  - pip:
+    - pyarrow