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fix: set PYTHONPATH properly
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+212
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3 files changed

+212
-3
lines changed

‎.github/workflows/ci-cd.yml

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@@ -70,7 +70,7 @@ jobs:
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- name: Test package
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env:
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# Set PYTHONPATH to include example
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PYTHONPATH: "${{ github.workspace }}/examples/src"
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PYTHONPATH: "${{ github.workspace }}/src:${{ github.workspace }}/examples/src"
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run: literary test
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publish:
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name: Publish to PyPI

‎src/literary/commands/__init__.ipynb

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{"cells": [{"cell_type": "code", "execution_count": null, "id": "68f6dc45-730c-4fa5-91bd-300fd2bba5e3", "metadata": {}, "outputs": [], "source": ["%load_ext literary.module"]}], "metadata": {"jupytext": {"cell_metadata_filter": "-all", "notebook_metadata_filter": "-all"}, "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": "3.10.4"}}, "nbformat": 4, "nbformat_minor": 5}
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "68f6dc45-730c-4fa5-91bd-300fd2bba5e3",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"%load_ext literary.module"
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]
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}
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],
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"metadata": {
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"jupytext": {
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"cell_metadata_filter": "-all",
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"notebook_metadata_filter": "-all"
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},
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎src/literary/commands/__main__.ipynb

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{"cells": [{"cell_type": "code", "execution_count": 1, "id": "spontaneous-llama", "metadata": {}, "outputs": [], "source": ["%load_ext literary.module"]}, {"cell_type": "markdown", "id": "solar-necessity", "metadata": {"tags": ["docstring"]}, "source": ["# Commandline Application"]}, {"cell_type": "code", "execution_count": 1, "id": "informed-raise", "metadata": {"execution": {"iopub.execute_input": "2022-05-12T11:23:58.033350Z", "iopub.status.busy": "2022-05-12T11:23:58.032705Z", "iopub.status.idle": "2022-05-12T11:23:58.368071Z", "shell.execute_reply": "2022-05-12T11:23:58.367446Z"}, "tags": ["export"]}, "outputs": [], "source": ["import sys\n", "\n", "from traitlets import default\n", "from traitlets.config import Application\n", "\n", "from .build import LiteraryBuildApp\n", "from .test import LiteraryTestApp"]}, {"cell_type": "code", "execution_count": 2, "id": "imported-thickness", "metadata": {"execution": {"iopub.execute_input": "2022-05-12T11:23:58.371025Z", "iopub.status.busy": "2022-05-12T11:23:58.370746Z", "iopub.status.idle": "2022-05-12T11:23:58.375871Z", "shell.execute_reply": "2022-05-12T11:23:58.375171Z"}, "tags": ["export"]}, "outputs": [], "source": ["class LiteraryLauncher(Application):\n", " description = \"Work with literate notebooks\"\n", " subcommands = {\n", " \"build\": (LiteraryBuildApp, \"Build a package from a series of notebooks\"),\n", " \"test\": (LiteraryTestApp, \"Run a series of notebook tests\"),\n", " }\n", "\n", " def start(self):\n", " \"\"\"Perform the App's actions as configured\"\"\"\n", " super().start()\n", "\n", " if self.subapp is None:\n", " sub_commands = \", \".join(sorted(self.subcommands))\n", " sys.exit(\"Please supply at least one subcommand: {}\".format(sub_commands))"]}, {"cell_type": "code", "execution_count": 3, "id": "sustainable-archive", "metadata": {"execution": {"iopub.execute_input": "2022-05-12T11:23:58.378526Z", "iopub.status.busy": "2022-05-12T11:23:58.378105Z", "iopub.status.idle": "2022-05-12T11:23:58.381525Z", "shell.execute_reply": "2022-05-12T11:23:58.381067Z"}, "tags": ["export"]}, "outputs": [], "source": ["launch_new_instance = LiteraryLauncher.launch_instance"]}, {"cell_type": "code", "execution_count": 4, "id": "7cd5310f-b1a4-4926-b909-b736e37d839c", "metadata": {"execution": {"iopub.execute_input": "2022-05-12T11:23:58.383872Z", "iopub.status.busy": "2022-05-12T11:23:58.383598Z", "iopub.status.idle": "2022-05-12T11:23:58.387073Z", "shell.execute_reply": "2022-05-12T11:23:58.386566Z"}, "tags": ["export"]}, "outputs": [], "source": ["if __name__ == \"__main__\" and not LiteraryLauncher.initialized():\n", " launch_new_instance()"]}], "metadata": {"jupytext": {"cell_metadata_filter": "-all", "main_language": "python", "notebook_metadata_filter": "-all"}, "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": "3.10.4"}}, "nbformat": 4, "nbformat_minor": 5}
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "spontaneous-llama",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"%load_ext literary.module"
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]
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},
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{
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"cell_type": "markdown",
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"id": "solar-necessity",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": [
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"docstring"
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]
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},
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"source": [
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"# Commandline Application"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "informed-raise",
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"metadata": {
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"editable": true,
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"execution": {
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"iopub.execute_input": "2022-05-12T11:23:58.033350Z",
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"iopub.status.busy": "2022-05-12T11:23:58.032705Z",
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"iopub.status.idle": "2022-05-12T11:23:58.368071Z",
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"shell.execute_reply": "2022-05-12T11:23:58.367446Z"
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},
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"slideshow": {
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"slide_type": ""
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},
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"tags": [
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"export"
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]
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},
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"outputs": [],
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"source": [
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"import sys\n",
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"\n",
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"from traitlets import default\n",
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"from traitlets.config import Application\n",
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"\n",
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"from .build import LiteraryBuildApp\n",
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"from .test import LiteraryTestApp"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "imported-thickness",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2022-05-12T11:23:58.371025Z",
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"iopub.status.busy": "2022-05-12T11:23:58.370746Z",
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"iopub.status.idle": "2022-05-12T11:23:58.375871Z",
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"shell.execute_reply": "2022-05-12T11:23:58.375171Z"
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},
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"tags": [
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"export"
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]
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},
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"outputs": [],
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"source": [
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"class LiteraryLauncher(Application):\n",
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" description = \"Work with literate notebooks\"\n",
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" subcommands = {\n",
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" \"build\": (LiteraryBuildApp, \"Build a package from a series of notebooks\"),\n",
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" \"test\": (LiteraryTestApp, \"Run a series of notebook tests\"),\n",
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" }\n",
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"\n",
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" def start(self):\n",
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" \"\"\"Perform the App's actions as configured\"\"\"\n",
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" super().start()\n",
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"\n",
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" if self.subapp is None:\n",
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" sub_commands = \", \".join(sorted(self.subcommands))\n",
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" sys.exit(\"Please supply at least one subcommand: {}\".format(sub_commands))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "sustainable-archive",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2022-05-12T11:23:58.378526Z",
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"iopub.status.busy": "2022-05-12T11:23:58.378105Z",
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"iopub.status.idle": "2022-05-12T11:23:58.381525Z",
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"shell.execute_reply": "2022-05-12T11:23:58.381067Z"
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},
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"tags": [
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"export"
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]
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},
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"outputs": [],
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"source": [
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"launch_new_instance = LiteraryLauncher.launch_instance"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "7cd5310f-b1a4-4926-b909-b736e37d839c",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2022-05-12T11:23:58.383872Z",
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"iopub.status.busy": "2022-05-12T11:23:58.383598Z",
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"iopub.status.idle": "2022-05-12T11:23:58.387073Z",
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"shell.execute_reply": "2022-05-12T11:23:58.386566Z"
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},
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"tags": [
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"export"
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]
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},
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"outputs": [],
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"source": [
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"if __name__ == \"__main__\" and not LiteraryLauncher.initialized():\n",
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" launch_new_instance()"
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]
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}
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],
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"metadata": {
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"jupytext": {
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"cell_metadata_filter": "-all",
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"main_language": "python",
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"notebook_metadata_filter": "-all"
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},
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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