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Merge pull request #2302 from jupyter-naas/2276-medium-publish-articl…
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Medium-Publish article from markdown file
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srini047 authored Oct 16, 2023
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{
"cells": [
{
"cell_type": "markdown",
"id": "b2986071-1a29-4f66-995e-72565d384ce8",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"<img width=\"10%\" alt=\"Naas\" src=\"https://landen.imgix.net/jtci2pxwjczr/assets/5ice39g4.png?w=160\"/>"
]
},
{
"cell_type": "markdown",
"id": "5d7b0c0b-5e6c-4be3-b901-704fc00b6c08",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"# Medium - Publish article from Mardown file"
]
},
{
"cell_type": "markdown",
"id": "ba4944a7-f4e5-4e89-9e3e-b4ee2e12c15f",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"**Tags:** #medium #publish #article #markdown #file #api"
]
},
{
"cell_type": "markdown",
"id": "c96fc2a3-0910-4b6d-a735-1e83cd5fa24e",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"**Author:** [SaiKiran M](www.linkedin.com/in/msaikiran9)"
]
},
{
"cell_type": "markdown",
"id": "edcf9f6c-c073-46c4-92ab-cc72866daf37",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"**Last update:** 2023-10-09 (Created: 2023-10-09)"
]
},
{
"cell_type": "markdown",
"id": "9b1586dd-d9e8-4f75-a583-c5cd5952bb05",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"**Description:** This notebook explains how to publish an article from a Markdown file via the Medium API. It is usefull for organizations that need to quickly publish content on Medium."
]
},
{
"cell_type": "markdown",
"id": "cc1d8d75-0c1f-41ad-a6b0-b0eb43fcc665",
"metadata": {
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"source": [
"**References:**\n",
"- [Programmatically Publish a Markdown File as a Medium Story with Python](https://betterprogramming.pub/programmatically-publish-a-markdown-file-as-a-medium-story-with-python-b2b072a5f968)\n",
"- [Medium API Documentation](https://github.com/Medium/medium-api-docs)"
]
},
{
"cell_type": "markdown",
"id": "32f771ab-b85d-44c2-8555-004b07b512ea",
"metadata": {
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"tags": []
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"source": [
"## Input"
]
},
{
"cell_type": "markdown",
"id": "74c2e136-cd6b-4079-9338-0b609b927692",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"### Import libraries"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e4bad8c4-13c7-4c1c-b97d-46fc1ced422c",
"metadata": {
"papermill": {},
"tags": []
},
"outputs": [],
"source": [
"try:\n",
" import naas\n",
" import json\n",
" import requests\n",
"except ImportError:\n",
" print(\"One or more modules not found. Installing necessary packages...\")\n",
" !pip install requests\n",
" import requests\n",
"#step 1 : import the necessary libraries here i.e., requests as json and naas are already present."
]
},
{
"cell_type": "markdown",
"id": "85e28cc8-0742-4aed-a9ee-c0b98cc00de4",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"### Setup variables\n",
"- `token`: Medium access token. [Instructions to get the token](https://github.com/Medium/medium-api-docs#22-authentication).\n",
"- `file_name`: Name of the Markdown file to be published."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7acc98ec-b364-4164-8524-bb0b7109d6c4",
"metadata": {
"papermill": {},
"tags": []
},
"outputs": [],
"source": [
"#step 2 : store the API token that's generated from Medium -> settings -> security and apps -> integration tokens into naas.\n",
"TOKEN = naas.secret.get(name=\"MEDIUM_TOKEN\")\n",
"file_name = \"sample.md\" #this is file to be uploaded in medium as an article ."
]
},
{
"cell_type": "markdown",
"id": "252ce263-9e42-4b03-aa2a-57efb0294c64",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"## Model"
]
},
{
"cell_type": "markdown",
"id": "20f812e5-9880-4c5e-92d8-71591450bdc1",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"### Publish article"
]
},
{
"cell_type": "markdown",
"id": "f0e2693b-779a-4c19-9c6d-e46c756e8236",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"Long description of the function without break"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "650f0106-6407-4fa8-a4e5-019762a526b1",
"metadata": {
"papermill": {},
"tags": []
},
"outputs": [],
"source": [
"#step 3 : In this step we setup publish_post fill the necessary headers & url to send the auth request.It'll send back a \n",
"#author_id user's unique identifier.And we will request to post content to the url containing the author_id at -> #1\n",
"def publish_post(title, content):\n",
" headers = {\n",
" \"Authorization\": f\"Bearer {TOKEN}\",\n",
" \"Content-Type\": \"application/json\"\n",
" }\n",
" \n",
" payload = {\n",
" \"title\": title,\n",
" \"contentFormat\": \"markdown\",\n",
" \"content\": content,\n",
" \"tags\": [\"example\", \"python\"],\n",
" \"publishStatus\": \"public\",\n",
" \"canonicalUrl\": \"http://example.com/sample\"\n",
" } \n",
" #get the author's complete api end point url.\n",
" response = requests.get(\"https://api.medium.com/v1/me\", headers=headers, params={\"Authorization\": \"Bearer {}\".format(TOKEN)})\n",
" if response.status_code == 200:\n",
" author_id = response.json()['data']['id']\n",
" url = \"https://api.medium.com/v1/users/{}/posts\".format(author_id)\n",
" else:\n",
" return\n",
" #post the data .\n",
" response = requests.post(url, headers=headers, json=payload) #1\n",
" if response.status_code == 201:\n",
" return response.json()[\"data\"][\"url\"]\n",
" else:\n",
" raise Exception(f\"Failed to publish post: {response.json()}\")\n",
"\n",
"#step 4 : Read the content of the Markdown file here let's say from \"sample.md\" file\n",
"with open(\"sample.md\", \"r\", encoding=\"utf-8\") as markdown_file:\n",
" content = markdown_file.read()\n",
"\n",
"#step 5 : Publish the post\n",
"post_url = publish_post(\"Sample Post Title\", content)\n",
"\n",
"print(\"Post published successfully!\")"
]
},
{
"cell_type": "markdown",
"id": "a4948757-3194-45e2-96f5-2e4463071eb3",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"## Output"
]
},
{
"cell_type": "markdown",
"id": "2aff52b9-5335-4240-9306-cb1238b29506",
"metadata": {
"papermill": {},
"tags": []
},
"source": [
"### Display result"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5b0af2a9-5227-45ac-9da9-d0bffabbbe0c",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"print(post_url)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.9.6"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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