notebooks/submission_endpoint_interations.ipynb
{
"metadata": {
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6-final"
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"orig_nbformat": 2,
"kernelspec": {
"name": "python_defaultSpec_1600367979214",
"display_name": "Python 3.7.6 64-bit ('ds-base': conda)"
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"nbformat": 4,
"nbformat_minor": 2,
"cells": [
{
"source": [
"# outlining the submission endpoints interactions\n",
"\n"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from requests import get, post"
]
},
{
"source": [
"## Launch the API via uvicorn using the following command:\n",
"```\n",
"export GOOGLE_CREDS=[content of service account key file]\n",
"uvicorn app.main:app --reload --workers 1 --host 0.0.0.0 --port 8000\n",
"```"
],
"cell_type": "markdown",
"metadata": {}
},
{
"source": [
"## the following cell will check if the api is runnning and accepting requests"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "200"
},
"metadata": {},
"execution_count": 3
}
],
"source": [
"server_check = get(\"http://0.0.0.0:8000\")\n",
"server_check.status_code"
]
},
{
"source": [
"## Open a local file and nest it in a files dictonary"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"tags": []
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "{'files': ('3101.jpg', <_io.BufferedReader name='3101.jpg'>)}"
},
"metadata": {},
"execution_count": 3
}
],
"source": [
"image = open('3101.jpg', 'rb')\n",
"files = {\"files\":(image.name, image)}\n",
"files"
]
},
{
"source": [
"## Make a post request to the `/submission/text` enpoint using the keyword `files` and the url argument `story_id`"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"tags": []
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": "200\n"
}
],
"source": [
"story_id = \"3101\"\n",
"args = f\"?story_id={story_id}\"\n",
"response = post(f\"http://0.0.0.0:8000/submission/text\" + args, files=files)\n",
"print(response.status_code)\n"
]
},
{
"source": [
"## Open an illustraion file"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "{'files': ('questionable.png', <_io.BufferedReader name='questionable.png'>)}"
},
"metadata": {},
"execution_count": 4
}
],
"source": [
"image = open('questionable.png', 'rb')\n",
"files = {\"files\":(image.name, image)}\n",
"files"
]
},
{
"source": [
"## post to the `/submission/illustration` enpoint and print the results"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"tags": []
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": "200\n"
}
],
"source": [
"response = post(\"http://0.0.0.0:8000/submission/illustration\", files=files)\n",
"print(response.status_code)\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "b'{\"is_flagged\":true,\"reason\":[\"adult: VERY_UNLIKELY\",\"violence: VERY_UNLIKELY\",\"racy: POSSIBLE\"]}'"
},
"metadata": {},
"execution_count": 8
}
],
"source": [
"response.content"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
]
}