Migrate highlighting to CM6.

examples/example1/center.ipynb

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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "44a9ad96-674a-49e5-94ee-9d84f386ecbc",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "a = np.arange(15).reshape(3, 5)\n",
+ "b = np.arange(5)\n",
+ "c = a + b"
+ ]
+ }
+ ],
+ "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
+}

examples/example2/center.ipynb

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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "eabfe4e0-d646-4d09-95a4-09ee3d030db6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from matplotlib import pyplot as plt\n",
+ "import numpy as np\n",
+ "x = np.arange(0, 2, 0.1)\n",
+ "y1 = np.exp(x)\n",
+ "plt.plot(x, y1, 'b')"
+ ]
+ }
+ ],
+ "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
+}

examples/example2/left.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2d47bfe2-d91d-4f72-9426-1885c4edb5a9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from matplotlib import pyplot as plt\n",
+ "import numpy as np\n",
+ "x = np.linspace(0, 2, 10)\n",
+ "z = np.exp(x + 2)\n",
+ "plt.plot(x, z, 'c')\n",
+ "# this is an example"
+ ]
+ }
+ ],
+ "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
+}

examples/example2/right.ipynb

@@ -0,0 +1,42 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ff160690-22c8-48f3-9b89-d78a8997baec",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from matplotlib import pyplot as plt\n",
+ "import numpy as np\n",
+ "x = np.arange(0, 2, 0.1)\n",
+ "y2 = np.exp(x)\n",
+ "plt.plot(x, y2, 'b')\n",
+ "y1 = y2\n",
+ "plt.plot(x, y1, 'g')\n",
+ "# this is easy"
+ ]
+ }
+ ],
+ "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
+}

examples/example3/center.ipynb

@@ -0,0 +1,65 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "9e423ee0-5ba3-4792-8b16-b20fe7a775e3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd # programmers like shortening names for things, so they usually import pandas as \"pd\"\n",
+ "import altair as alt # again with the shortening of names\n",
+ "import requests # we use it for downloading the data so we don't have to save it on GitHub (too big!)\n",
+ "import zipfile # for de-compressing the files we download from the EPA"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "08e85e68-1722-4847-a13f-97c921829073",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download the data from the EPA website\n",
+ "data_file_urls = [\n",
+ " 'https://aqs.epa.gov/aqsweb/airdata/daily_88101_2020.zip',\n",
+ " 'https://aqs.epa.gov/aqsweb/airdata/daily_88101_2019.zip',\n",
+ "]\n",
+ "# copied this example from https://stackoverflow.com/questions/16694907/download-large-file-in-python-with-requests\n",
+ "for url in data_file_urls:\n",
+ " local_filename = \"data/{}\".format(url.split('/')[-1])\n",
+ " with requests.get(url, stream=True) as r:\n",
+ " r.raise_for_status()\n",
+ " with open(local_filename, 'wb') as f:\n",
+ " for chunk in r.iter_content(chunk_size=8192): \n",
+ " f.write(chunk)\n",
+ "# and unzip the files\n",
+ "files_to_unzip = [\"data/{}\".format(url.split('/')[-1]) for url in data_file_urls]\n",
+ "for f in files_to_unzip:\n",
+ " with zipfile.ZipFile(f,\"r\") as zip_ref:\n",
+ " zip_ref.extractall(\"data\")"
+ ]
+ }
+ ],
+ "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": "3.11.4"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example3/left.ipynb

@@ -0,0 +1,67 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "9e423ee0-5ba3-4792-8b16-b20fe7a775e3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd # programmers like shortening names for things, so they usually import pandas as \"pd\"\n",
+ "import altair as alt # again with the shortening of names\n",
+ "import requests # we use it for downloading the data so we don't have to save it on GitHub (too big!)\n",
+ "import zipfile # for de-compressing the files we download from the EPA\n",
+ "import numpy as np"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "08e85e68-1722-4847-a13f-97c921829073",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download the data from the EPA website\n",
+ "data_file_urls = [\n",
+ " 'https://aqs.epa.gov/aqsweb/airdata/daily_88101_2020.zip',\n",
+ " 'https://aqs.epa.gov/aqsweb/airdata/daily_88101_2019.zip',\n",
+ " 'https://aqs.epa.gov/aqsweb/airdata/daily_88101_2018.zip'\n",
+ "]\n",
+ "# copied this example from https://stackoverflow.com/questions/16694907/download-large-file-in-python-with-requests\n",
+ "for url in data_file_urls:\n",
+ " local_filename = \"data/{}\".format(url.split('/')[-1])\n",
+ " with requests.get(url, stream=True) as r:\n",
+ " r.raise_for_status()\n",
+ " with open(local_filename, 'wb') as f:\n",
+ " for chunk in r.iter_content(chunk_size=8192): \n",
+ " f.write(chunk)\n",
+ "# and unzip the files\n",
+ "files_to_unzip = [\"data/{}\".format(url.split('/')[-1]) for url in data_file_urls]\n",
+ "for f in files_to_unzip:\n",
+ " with zipfile.ZipFile(f,\"r\") as zip_ref:\n",
+ " zip_ref.extractall(\"data\")"
+ ]
+ }
+ ],
+ "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": "3.11.4"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example3/right.ipynb

@@ -0,0 +1,60 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "9e423ee0-5ba3-4792-8b16-b20fe7a775e3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd # programmers like shortening names for things, so they usually import pandas as \"pd\"\n",
+ "import superior as sup # again with the shortening of names\n",
+ "import requests # we use it for downloading the data so we don't have to save it on GitHub (too big!)\n",
+ "import tarfile # for de-compressing the files we download from the EPA"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "08e85e68-1722-4847-a13f-97c921829073",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download the data from the EPA website\n",
+ "data_file_urls = [\n",
+ " 'https://aqs.epa.gov/aqsweb/airdata/daily_88101_2017.zip',\n",
+ " 'https://aqs.epa.gov/aqsweb/airdata/daily_88101_2018.zip',\n",
+ "]\n",
+ "# copied this example from https://stackoverflow.com/questions/16694907/download-large-file-in-python-with-requests\n",
+ "for url in data_file_urls:\n",
+ " local_filename = \"data/{}\".format(url.split('/')[-1])\n",
+ " with requests.get(url, stream=True) as r:\n",
+ " r.raise_for_status()\n",
+ " with open(local_filename, 'r') as f:\n",
+ " for chunk in r.iter_content(chunk_size=8192): \n",
+ " f.write(chunk)"
+ ]
+ }
+ ],
+ "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": "3.11.4"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}