I've been busy building Twitter bots again!
If you take a look at my GitHub profile, you'll see that I have quite a few repos relating to Twitter bots.
My latest project started with the decision to repurpose one of my testing repos as documentation for how to use the npm twit
package. But as I added new examples, it quickly morphed into another Twitter bot.
This bot is cobbled together from three examples we'll go over here. I'll also detail how I used Zeit's now platform to deploy the bot to a server.
Special thanks go to Tim for helping me with the now deployment. And to Hannah Davis for the egghead.io course material.
It has some pretty neat examples, which I've linked to in the relevant sections.
Getting started
This is a reference for me and anyone else that's interested in Twitter bots in JavaScript.
All of the examples here use the npm
package twit
.
We'll go through setting up a simple bot so each of these examples can be run with it.
I'm going to assume that you have nodejs
installed along with npm
and that you are comfortable with the terminal.
If you are not familiar node or do not have your environment set up to use it take a look at the README.md on my Twitter bot bootstrap repo which details getting a Twitter application set up and a development environment with c9.
A great resource is Aman Mittal's Awesome Twitter bots repo which has resources and bot examples.
A lot of this information is already out there I'm hoping this is all the information someone will need to get started with their own Twitter bot. I'm doing this for my own learning and hopefully other people will get something out of this as well.
Set up the bot
Before touching the terminal or writing any code we'll need to create a Twitter app to get our API keys, we'll need them all:
Consumer Key (API Key)
Consumer Secret (API Secret)
Access Token
Access Token Secret
Keep the keys somewhere safe so you can use them again when you need them, we're going to be using them in the .env
file we're going to create.
We're using dotenv
so that if at some point in the future we want to add our bot to GitHub the Twitter API keys are not added to GitHub for all to see.
Starting from scratch, create a new folder via the terminal and initialise the package.json
via npm
or yarn
we'll need twit
and dotenv
for all these examples.
I'll be using yarn
for all these examples, you can use npm
if you prefer.
Terminal commands:
mkdir tweebot-play
cd tweebot-play
yarn init -y
yarn add twit dotenv
touch .env .gitignore index.js
If you take a look at the package.json
that was created it should look something like this:
{
"name": "tweebot-play",
"version": "1.0.0",
"main": "index.js",
"author": "Scott Spence <spences10apps@gmail.com> (https://spences10.github.io/)",
"license": "MIT",
"dependencies": {
"dotenv": "^4.0.0",
"twit": "^2.2.5"
}
}
Add an npm
script to the package.json
to kick off the bot when we're testing and looking for output:
"scripts": {
"start": "node index.js"
},
It should look something like this now:
{
"name": "tweebot-play",
"version": "1.0.0",
"main": "index.js",
"scripts": {
"start": "node index.js"
},
"author": "Scott Spence <spences10apps@gmail.com> (https://spences10.github.io/)",
"license": "MIT",
"dependencies": {
"dotenv": "^4.0.0",
"twit": "^2.2.5"
}
}
Now we can add the following pointer to the bot in index.js
, like so:
require('./src/bot')
So when we use yarn start
to run the bot it calls the index.js
file which runs the bot.js
file from the src
folder we're going to create.
Now we add our API keys to the .env
file, it should look something like this:
CONSUMER_KEY=AmMSbxxxxxxxxxxNh4BcdMhxg
CONSUMER_SECRET=eQUfMrHbtlxxxxxxxxxxkFNNj1H107xxxxxxxxxx6CZH0fjymV
ACCESS_TOKEN=7xxxxx492-uEcacdl7HJxxxxxxxxxxecKpi90bFhdsGG2N7iII
ACCESS_TOKEN_SECRET=77vGPTt20xxxxxxxxxxxZAU8wxxxxxxxxxx0PhOo43cGO
In the .gitignore
file we need to add .env
and node_modules
# Dependency directories
node_modules
# env files
.env
Then init git:
git init
Ok, now we can start to configure the bot, we'll need a src
folder a bot.js
file and a config.js
file.
Terminal:
mkdir src
cd src
touch config.js bot.js
Then we can set up the bot config, open the config.js
file and add the following:
require('dotenv').config()
module.exports = {
consumer_key: process.env.CONSUMER_KEY,
consumer_secret: process.env.CONSUMER_SECRET,
access_token: process.env.ACCESS_TOKEN,
access_token_secret: process.env.ACCESS_TOKEN_SECRET,
}
Ok, that's the bot config done now we can set up the bot, each of the examples detailed here will have the same three lines of code:
const Twit = require('twit')
const config = require('./config')
const bot = new Twit(config)
Ok, that's it out bot is ready to go, do a test with yarn start
from the terminal, we should get this for output:
yarn start
yarn start v0.23.4
$ node index.js
Done in 0.64s.
Bot is now configured and ready to go!🚀
Post Statuses
Firstly post statuses, with .post('statuses/update'...
bot will post a hello world! status.
bot.post('statuses/update', {
status: 'hello world!'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(`${data.text} tweeted!`)
}
})
Work with users
To get a list of followers ids use .get('followers/ids'...
and include the account that you want the followers of, in this example we're using @DroidScott
, you can use any account you like. We can then log them out to the console in this example.
bot.get('followers/ids', {
screen_name: 'DroidScott',
count: 5
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(data)
}
})
You can specify with the count
parameter how many results you get up to 100 at a time.
Or to get a detailed list you can use .get('followers/list'...
Here we print off a list of user.screen_name
's up to 200 per call.
bot.get('followers/list', {
screen_name: 'DroidScott',
count:200
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
data.users.forEach(user => {
console.log(user.screen_name)
})
}
})
To follow back a follower we can use .post('friendships/create'...
here the bot is following back the user MarcGuberti
A bot should only follow users that follow the bot.
bot.post('friendships/create', {
screen_name: 'MarcGuberti'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(data)
}
})
Like with followers you can get a list of accounts that your bot is following back.
bot.get('friends/ids', {
screen_name: 'DroidScott'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(data)
}
})
And also a detailed list.
bot.get('friends/list', {
screen_name: 'DroidScott'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(data)
}
})
Get friendship status, this is useful for following new followers, this will give us the relation of a specific user. So you can run through your followers list and follow back any users that do not have the following
connection.
Lets take a look at the relation between our bot and @ScottDevTweets
bot.get('friendships/lookup', {
screen_name: 'ScottDevTweets'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(data)
}
})
If the user follows the bot, then relationship will be:
[ { name: 'Scott Spence 🌯😴💻♻',
screen_name: 'ScottDevTweets',
id: 4897735439,
id_str: '4897735439',
connections: [ 'followed_by' ] } ]
If the user and the bot are following each other, the relationship will be:
[ { name: 'Scott Spence 🌯😴💻♻',
screen_name: 'ScottDevTweets',
id: 4897735439,
id_str: '4897735439',
connections: [ 'following', 'followed_by' ] } ]
And if there is no relationship then:
[ { name: 'Scott Spence 🌯😴💻♻',
screen_name: 'ScottDevTweets',
id: 4897735439,
id_str: '4897735439',
connections: [ 'none' ] } ]
Direct Message a user with bot.post('direct_messages/new'...
A bot should only DM a user that is following the bot account
bot.post('direct_messages/new', {
screen_name: 'ScottDevTweets',
text: 'Hello from bot!'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(data)
}
})
Interact with tweets
To get a list of tweets in the bots time line use .get(statuses/home_timeline'...
bot.get('statuses/home_timeline', {
count: 1
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(data)
}
})
To be more granular you can pull out specific information on each tweet.
bot.get('statuses/home_timeline', {
count: 5
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
data.forEach(t => {
console.log(t.text)
console.log(t.user.screen_name)
console.log(t.id_str)
console.log('\n')
})
}
})
To retweet use .post('statuses/retweet/:id'...
and pass in a tweet id to retweet.
bot.post('statuses/retweet/:id', {
id: '860828247944253440'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(`${data.text} retweet success!`)
}
})
To unretweet just use .post('statuses/unretweet/:id'...
bot.post('statuses/unretweet/:id', {
id: '860828247944253440'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(`${data.text} unretweet success!`)
}
})
To like a tweet use .post('favorites/create'...
bot.post('favorites/create', {
id: '860897020726435840'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(`${data.text} tweet liked!`)
}
})
To unlike a post use .post('favorites/destroy'...
bot.post('favorites/destroy', {
id: '860897020726435840'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(`${data.text} tweet unliked!`)
}
})
To reply to a tweet is much the same a posting a tweet but you need to include the in_reply_to_status_id
parameter, but that's not enough as you will also need to put in the screen name of the person you are replying to.
bot.post('statuses/update', {
status: '@ScottDevTweets I reply to you yes!',
in_reply_to_status_id: '860900406381211649'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(`${data.text} tweeted!`)
}
})
Finally if you want to delete a tweet use .post('statuses/destroy/:id'...
passing the tweet id you want to delete.
bot.post('statuses/destroy/:id', {
id: '860900437993676801'
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(`${data.text} tweet deleted!`)
}
})
Use Twitter search
To use search use .get('search/tweets',...
there are quite a few search parameters for search.
q: ''
the Q is for query so to search for mango use q: 'mango'
we can also limit the results returned with count: n
so let's limit it the count to in the example:
bot.get('search/tweets', {
q: 'mango',
count: 5
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log(data.statuses)
}
})
Like we did with the timeline we will pull out specific items from the data.statuses
returned, like this:
bot.get('search/tweets', {
q: 'mango',
count: 5
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
data.statuses.forEach(s => {
console.log(s.text)
console.log(s.user.screen_name)
console.log('\n')
})
}
})
The search API returns for relevance and not completeness, if you want to search for an exact phrase you'll need to wrap the query in quotes "purple pancakes"
if you want to search for one of two words then use OR
like 'tabs OR spaces'
if you want to search for both use AND
like 'tabs AND spaces'
.
If you want to search for a tweet without another word use -
like donald -trump
you can use it multiple times as well, like donald -trump -duck
You can search for tweets with emoticons, like q: 'sad :('
try it!
Of course look for hashtags q: '#towie'
. Look for tweets to a user q: 'to:@stephenfry'
or from a user q: 'from:@stephenfry'
You can filter out indecent tweets with the filter:safe
parameter you can also use it to filter for media
tweets which will return tweets containing video. You can specify for images
to view tweets with images and you can specify links
for tweets with links.
If you want tweets from a certain website you can specify with the url
parameter like url:asda
bot.get('search/tweets', {
q: 'from:@dan_abramov url:facebook filter:images since:2017-01-01',
count: 5
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
data.statuses.forEach(s => {
console.log(s.text)
console.log(s.user.screen_name)
console.log('\n')
})
}
})
Last few now, there's the result_type
parameter that will return recent
, popular
or mixed
results.
The geocode
parameter that take the format latitude longitude then radius in miles '51.5033640,-0.1276250,1mi'
example:
bot.get('search/tweets', {
q: 'bacon',
geocode: '51.5033640,-0.1276250,1mi',
count: 5
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
data.statuses.forEach(s => {
console.log(s.text)
console.log(s.user.screen_name)
console.log('\n')
})
}
})
Use Twitter Stream API
There are two ways to use the Stream API first there's .stream('statuses/sample')
example:
const stream = bot.stream('statuses/sample');
stream.on('tweet', t => {
console.log(`${t.text}\n`)
})
This will give you a random sampling of tweets.
For more specific information use .stream('statuses/filter')...
then pass some parameters, use track:
to specify a search string:
var stream = bot.stream('statuses/filter', {
track: 'bot'
})
stream.on('tweet', function (t) {
console.log(t.text + '\n')
})
You can also use multiple words in the track
parameter, tis will get you results with either twitter
or bot
in them.
const stream = bot.stream('statuses/filter', {
track: 'twitter, bot'
});
stream.on('tweet', t => {
console.log(`${t.text}\n`)
})
If you want both words then remove the comma ,
you can think of spaces as AND
and commas as OR
You can also use the follow:
parameter which lets you input the ids of specific users, example:
const stream = bot.stream('statuses/filter', {
follow: '4897735439'
});
stream.on('tweet', t => {
console.log(`${t.text}\n`)
})
Tweet media files
This egghead.io video is a great resource for this section thanks to Hannah Davis for the awesome content!
This will be a request to get the NASA image of the day and tweet it.
For this we will need references to request
and fs
for working with the file system.
const Twit = require('twit')
const request = require('request')
const fs = require('fs')
const config = require('./config')
const bot = new Twit(config)
First up get the photo from the NASA api, for this we will need to create a parameter object inside our getPhoto
function that will be passed to the node HTTP client request
for the image:
function getPhoto() {
const parameters = {
url: 'https://api.nasa.gov/planetary/apod',
qs: {
api_key: process.env.NASA_KEY
},
encoding: 'binary'
};
}
The parameters
specify an api_key
for this you can apply for an API key or you can use the DEMO_KEY
this API key can be used for initially exploring APIs prior to signing up, but it has much lower rate limits, so you're encouraged to signup for your own API key.
In the example you can see that I have configured my key with the rest of my .env
variables.
CONSUMER_KEY=AmMSbxxxxxxxxxxNh4BcdMhxg
CONSUMER_SECRET=eQUfMrHbtlxxxxxxxxxxkFNNj1H107xxxxxxxxxx6CZH0fjymV
ACCESS_TOKEN=7xxxxx492-uEcacdl7HJxxxxxxxxxxecKpi90bFhdsGG2N7iII
ACCESS_TOKEN_SECRET=77vGPTt20xxxxxxxxxxxZAU8wxxxxxxxxxx0PhOo43cGO
NASA_KEY=DEMO_KEY
Now to use the request
to get the image:
function getPhoto() {
const parameters = {
url: 'https://api.nasa.gov/planetary/apod',
qs: {
api_key: process.env.NASA_KEY
},
encoding: 'binary'
};
request.get(parameters, (err, respone, body) => {
body = JSON.parse(body)
saveFile(body, 'nasa.jpg')
})
}
In the request
we pass in our parameters and parse the body as JOSN so we can save it with the saveFile
function which we'll go over now:
function saveFile(body, fileName) {
const file = fs.createWriteStream(fileName);
request(body).pipe(file).on('close', err => {
if (err) {
console.log(err)
} else {
console.log('Media saved!')
console.log(body)
}
})
}
request(body).pipe(file).on('close'...
is what saves the file from the file
variable which has the name passed to it nasa.jpg
from the getPhoto
function.
Calling getPhoto()
should now save the NASA image of the day to the root of your project.
Now we can share it on Twitter 😎
Two parts to this, first save the file.
function saveFile(body, fileName) {
const file = fs.createWriteStream(fileName);
request(body).pipe(file).on('close', err => {
if (err) {
console.log(err)
} else {
console.log('Media saved!')
const descriptionText = body.title;
uploadMedia(descriptionText, fileName)
}
})
}
Then uploadMedia
to upload media to Twitter before we can post it, this had me stumped for a bit as I have my files in a src
folder, if you have your bot files nested in folders then you will need to do the same if you are struggling with file does not exist
errors:
Add a require
to path
then use join
with the relevant relative file path.
const path = require('path')
//...
const filePath = path.join(__dirname, '../' + fileName)
Complete function here:
function uploadMedia(descriptionText, fileName) {
console.log(`uploadMedia: file PATH ${fileName}`)
bot.postMediaChunked({
file_path: fileName
}, (err, data, respone) => {
if (err) {
console.log(err)
} else {
console.log(data)
const params = {
status: descriptionText,
media_ids: data.media_id_string
}
postStatus(params)
}
})
}
Then with the params
we created in uploadMedia
we can post with a straightforward .post('statuses/update'...
function postStatus(params) {
bot.post('statuses/update', params, (err, data, respone) => {
if (err) {
console.log(err)
} else {
console.log('Status posted!')
}
})
}
Call the getPhoto()
function top post to Twitter... super straight forward, right 😀 no, I know it wasn't. Here's the complete module:
const Twit = require('twit')
const request = require('request')
const fs = require('fs')
const config = require('./config')
const path = require('path')
const bot = new Twit(config)
function getPhoto() {
const parameters = {
url: 'https://api.nasa.gov/planetary/apod',
qs: {
api_key: process.env.NASA_KEY
},
encoding: 'binary'
}
request.get(parameters, (err, respone, body) => {
body = JSON.parse(body)
saveFile(body, 'nasa.jpg')
})
}
function saveFile(body, fileName) {
const file = fs.createWriteStream(fileName)
request(body).pipe(file).on('close', err => {
if (err) {
console.log(err)
} else {
console.log('Media saved!')
const descriptionText = body.title
uploadMedia(descriptionText, fileName)
}
})
}
function uploadMedia(descriptionText, fileName) {
const filePath = path.join(__dirname, `../${fileName}`)
console.log(`file PATH ${filePath}`)
bot.postMediaChunked({
file_path: filePath
}, (err, data, respone) => {
if (err) {
console.log(err)
} else {
console.log(data)
const params = {
status: descriptionText,
media_ids: data.media_id_string
}
postStatus(params)
}
})
}
function postStatus(params) {
bot.post('statuses/update', params, (err, data, respone) => {
if (err) {
console.log(err)
} else {
console.log('Status posted!')
}
})
}
getPhoto()
Make a Markov bot
This is pretty neat, again from the egghead.io series it uses rita
natural language toolkit. It also uses csv-parse
as we're going to be reading out our Twitter archive to make the bot sound like us tweeting.
First of all, to set up the Twitter archive, you'll need to request your data from the Twitter settings page. You'll be emailed a link to download your archive, then when you have downloaded the archive extract out the tweets.csv
file, we'll then put that in it's own folder, so from the root of your project:
cd src
mkdir twitter-archive
We'll move our tweets.csv
there to be accessed by the bot we're going to go over now.
Use fs
to set up a read stream...
const filePath = path.join(__dirname, './twitter-archive/tweets.csv')
const tweetData =
fs.createReadStream(filePath)
.pipe(csvparse({
delimiter: ','
}))
.on('data', row => {
console.log(row[5])
})
When you run this from the console you should get the output from your Twitter archive.
Now clear out things like @
and RT
to help with the natural language processing we'll set up two functions cleanText
and hasNoStopWords
cleanText
will tokenize the text delimiting it on space ' '
filter out the stop words then .join(' ')
back together with a space and .trim()
any whitespace that may be at the start of the text.
function cleanText(text) {
return rita.RiTa.tokenize(text, ' ')
.filter(hasNoStopWords)
.join(' ')
.trim()
}
The tokenized text can then be fed into the hasNoStopWords
function to be sanitized for use in tweetData
function hasNoStopWords(token) {
const stopwords = ['@', 'http', 'RT'];
return stopwords.every(sw => !token.includes(sw))
}
Now that we have the data cleaned we can tweet it, so replace console.log(row[5])
with inputText = inputText + ' ' + cleanText(row[5])
then we can use rita.RiMarkov(3)
the 3 being the number of words to take into consideration. Then use markov.generateSentences(1)
with 1 being the number of sentences being generated. We'll also use .toString()
and .substring(0, 140)
to truncate the result down to 140 characters.
const tweetData =
fs.createReadStream(filePath)
.pipe(csvparse({
delimiter: ','
}))
.on('data', function (row) {
inputText = `${inputText} ${cleanText(row[5])}`
})
.on('end', function(){
const markov = new rita.RiMarkov(3)
markov.loadText(inputText)
const sentence = markov.generateSentences(1)
.toString()
.substring(0, 140)
}
Now we can tweet this with the bot using .post('statuses/update'...
passing in the sentence
variable as the status
logging out when there is a tweet.
const tweetData =
fs.createReadStream(filePath)
.pipe(csvparse({
delimiter: ','
}))
.on('data', row => {
inputText = `${inputText} ${cleanText(row[5])}`
})
.on('end', () => {
const markov = new rita.RiMarkov(3)
markov.loadText(inputText)
const sentence = markov.generateSentences(1)
.toString()
.substring(0, 140)
bot.post('statuses/update', {
status: sentence
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log('Markov status tweeted!', sentence)
}
})
})
}
If you want your sentences to be closer to the input text you can increase the words to consider in rita.RiMarkov(6)
and if you want to make it gibberish then lower the number.
Here's the completed module:
const Twit = require('twit')
const fs = require('fs')
const csvparse = require('csv-parse')
const rita = require('rita')
const config = require('./config')
const path = require('path')
let inputText = ''
const bot = new Twit(config)
const filePath = path.join(__dirname, '../twitter-archive/tweets.csv')
const tweetData =
fs.createReadStream(filePath)
.pipe(csvparse({
delimiter: ','
}))
.on('data', row => {
inputText = `${inputText} ${cleanText(row[5])}`
})
.on('end', () => {
const markov = new rita.RiMarkov(10)
markov.loadText(inputText)
const sentence = markov.generateSentences(1)
.toString()
.substring(0, 140)
bot.post('statuses/update', {
status: sentence
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log('Markov status tweeted!', sentence)
}
})
})
}
function hasNoStopWords(token) {
const stopwords = ['@', 'http', 'RT']
return stopwords.every(sw => !token.includes(sw))
}
function cleanText(text) {
return rita.RiTa.tokenize(text, ' ')
.filter(hasNoStopWords)
.join(' ')
.trim()
}
Retrieve and Tweet data from Google sheets
If you want to tweet a list of links you can use tabletop
to work though the list, in this example again from egghead.io we'll go through a list of links.
So, set up the bot and require tabletop
:
const Twit = require('twit')
const config = require('./config')
const Tabletop = require('tabletop')
const bot = new Twit(config)
On your Google spreadsheet
you'll need to have a header defined and then add your links, we'll use the following for an example:
Now from Google sheets we can select 'File'>'Publish to the web' and copy the link that is generated we can use that in table top.
Now init Table top with three parameters, key:
which is the spreadsheet URL, a callback:
function to get the data and simpleSheet:
which is true
if you only have one sheet, like in our example here:
const spreadsheetUrl = 'https://docs.google.com/spreadsheets/d/1842GC9JS9qDWHc-9leZoEn9Q_-jcPUcuDvIqd_MMPZQ/pubhtml'
Tabletop.init({
key: spreadsheetUrl,
callback(data, tabletop) {
console.log(data)
},
simpleSheet: true
})
Running the bot now should give output like this:
$ node index.js
[ { 'links': 'https://www.freecodecamp.com' },
{ 'links': 'https://github.com' },
{ 'links': 'https://www.reddit.com' },
{ 'links': 'https://twitter.com' } ]
So now we can tweet them using .post('statuses/update',...
with a forEach
on the data
that is returned in the callback:
Tabletop.init({
key: spreadsheetUrl,
callback(data, tabletop) {
data.forEach(d => {
const status = `${d.links} a link from a Google spreadsheet`;
bot.post('statuses/update', {
status
}, (err, response, data) => {
if (err) {
console.log(err)
} else {
console.log('Post success!')
}
})
})
},
simpleSheet: true
})
Note that ${d.links}
is the header name we use in the Google spreadsheet, I tried using skeleton and camel case and both returned errors so I went with a single name header on the spreadsheet.
The completed code here:
const Twit = require('twit')
const config = require('./config')
const Tabletop = require('tabletop')
const bot = new Twit(config)
const spreadsheetUrl = 'https://docs.google.com/spreadsheets/d/1842GC9JS9qDWHc-9leZoEn9Q_-jcPUcuDvIqd_MMPZQ/pubhtml'
Tabletop.init({
key: spreadsheetUrl,
callback(data, tabletop) {
data.forEach(d => {
const status = `${d.links} a link from a Google spreadsheet`
console.log(status)
bot.post('statuses/update', {
status
}, (err, response, data) => {
if (err) {
console.log(err)
} else {
console.log('Post success!')
}
})
})
},
simpleSheet: true
})
Putting it all together
Ok, so those examples were good n' all but we haven't really got a bot out of this have we? I mean you run it from the terminal and that's it done, we want to be able to kick off the bot and leave it to do its thing.
One way I have found to do this is to use setInterval
which will kick off events from the main bot.js
module, so lets try this:
Take the example we did to tweet a picture and add it to it's own module, so from the root directory of our project:
cd src
touch picture-bot.js
Take the example code from that and paste it into the new module, then we're going to make the following changes, to getPhoto
:
const getPhoto = () => {
const parameters = {
url: 'https://api.nasa.gov/planetary/apod',
qs: {
api_key: process.env.NASA_KEY
},
encoding: 'binary'
}
request.get(parameters, (err, respone, body) => {
body = JSON.parse(body)
saveFile(body, 'nasa.jpg')
})
}
Then at the bottom of the module add:
module.exports = getPhoto
So now we can call the getPhoto
function from the picture-bot.js
module in our bot.js
module, our bot.js
module should look something like this:
const picture = require('./picture-bot')
picture()
That's it, two lines of code, try running that from the terminal now:
yarn start
We should get some output like this:
yarn start v0.23.4
$ node index.js
Media saved!
file PATH C:\Users\path\to\project\tweebot-play\nasa.jpg
{ media_id: 863020197799764000,
media_id_string: '863020197799763968',
size: 371664,
expires_after_secs: 86400,
image: { image_type: 'image/jpeg', w: 954, h: 944 } }
Status posted!
Done in 9.89s.
Ok, so thats the picture of the day done, but it has run once and completed we need to put it on an interval with setInterval
which we need to pass two options to, the function it's going to call and the timeout value.
The picture updates every 24 hours so that will be how many milliseconds in 24 hours [8.64e+7] I don't even 🤷”
I work it out like this, 1000 * 60 = 1 minute, so 1000 * 60 * 60 * 24 so for now lets add that directly into the setInterval
function:
const picture = require('./picture-bot')
picture()
setInterval(picture, 1000 * 60 * 60 * 24)
Cool, that's a bot that will post the NASA image of the day every 24 hours!
Lets keep going, now lets add some randomness in with the Markov bot, like we did in the picture of the day example, lets create a new module for the Markov bot and add all the code in there from the previous example, so from the terminal:
cd src
touch markov-bot.js
Then copy pasta the markov bot example into the new module, then we're going to make the following changes:
const tweetData = () => {
fs.createReadStream(filePath)
.pipe(csvparse({
delimiter: ','
}))
.on('data', row => {
inputText = `${inputText} ${cleanText(row[5])}`
})
.on('end', () => {
const markov = new rita.RiMarkov(10)
markov.loadText(inputText)
.toString()
.substring(0, 140)
const sentence = markov.generateSentences(1)
bot.post('statuses/update', {
status: sentence
}, (err, data, response) => {
if (err) {
console.log(err)
} else {
console.log('Markov status tweeted!', sentence)
}
})
})
}
Then at the bottom of the module add:
module.exports = tweetData
Ok, same again as with the picture bot example we're going to add the tweetData
export from markov-bot.js
to our bot.js
module, which should now look something like this:
const picture = require('./picture-bot')
const markov = require('./markov-bot')
picture()
setInterval(picture, 1000 * 60 * 60 * 24)
markov()
Let's make the Markov bot tweet at random intervals between 5 minutes and 3 hours
const picture = require('./picture-bot')
const markov = require('./markov-bot')
picture()
setInterval(picture, 1000 * 60 * 60 * 24)
const markovInterval = (Math.floor(Math.random() * 180) + 1) * 1000
markov()
setInterval(markov, markovInterval)
Allrighty! Picture bot, Markov bot, done ðŸ‘
Do the same with the link bot? Ok, same as before, you get the idea now, right?
Create a new file in the src
folder for link bot:
touch link-bot.js
Copy pasta the code from the link bot example into the new module, like this:
const link = () => {
Tabletop.init({
key: spreadsheetUrl,
callback(data, tabletop) {
data.forEach(d => {
const status = `${d.links} a link from a Google spreadsheet`
console.log(status)
bot.post('statuses/update', {
status
}, (err, response, data) => {
if (err) {
console.log(err)
} else {
console.log('Post success!')
}
})
})
},
simpleSheet: true
})
}
module.exports = link
Then we can call it from the bot, so it should look something like this:
const picture = require('./picture-bot')
const markov = require('./markov-bot')
const link = require('./link-bot')
picture()
setInterval(picture, 1000 * 60 * 60 * 24)
const markovInterval = (Math.floor(Math.random() * 180) + 1) * 1000
markov()
setInterval(markov, markovInterval)
link()
setInterval(link, 1000 * 60 * 60 * 24)
Ok? Cool ðŸ‘😎
We can now leave the bot running to do its thing!!
Deploy to now
Right, we have a bot that does a few things but it's on our development environment, so it can't stay there forever, well it could but it'd be pretty impcratcical. Lets put our bot on a server somewhere to do it's thing.
To do this we're going to be using now
, now
allows for simple deployments from the CLI if you're not fimailiar with now then take a quick look at the documentation in these examples we're going to be using the now-cli
.
There's a few things we need to do in order to get our bot ready to go on now
, let's list them quickly and then go into detail.
- Signup and install
now-cli
- Add
now
settings +.npmignore
file - Add
.env
variables as secrets - Add npm
deploy
script - Re jig
picture-bot.js
Ready? Lets do this! 💪
Signup and install now-cli
Fist up lets signup for zeit â–² create an account and authenticate, then we can install the CLI.
Install now
globally on our machine so you can use it everywhere, to install the now-cli
from the terminal enter:
npm install -g now
Once it's completed login with:
now --login
The first time you run now
, it'll ask for your email address in order to identify you. Go to the email account to supplied when sigining up an click on the email sent to you from now
, and you'll be logged in automatically.
If you need to switch the account or re-authenticate, run the same command again.
You can always check out the now-cli
documentation for more information along with the your first deployment
guide.
Add now
settings
Ok, so that's signup and install sorted, we can now configure the bot for deploying to now
. First up lets add the now
settings to our package.json
file, I've put it in between my npm
scripts and the author name in my package.json
:
"scripts": {
"start": "node index.js"
},
"now": {
"alias": "my-awesome-alias",
"files": [
"src",
"index.js"
]
},
"author": "Scott Spence",
This was a source of major confusion for me so I'm hoping I can save you the pain I went through trying to configure this, all the relevant documentation is there you just need to put it all together 😎
If you find anything in here that doesn't make sense or is just outright wrong then please log an issue or create a pull request ðŸ‘
The now settings alias
is to give your deployment a shothand name over the auto generated URL that now
creates, the files
section covers what we want to include in the depoloyment to now
we'll go over the file structure shortly. Basically what is included in the files
array is all that get pused up to the now servers.
All good so for?
Ok, now we need to add a .npmignore
file in the root of the project and add the following line to it:
!tweets.csv
The tweets.csv
needs to go up to the now
server to be used by the bot, but we previously included it in our .gitignore
which is what now
uses to build your project when it's being loaded to the server. So this means that the file isn't going to get loaded unless we add the .npmignore
to not ignore the tweets.csv
😅
Add .env
variables as secrets
Ok, our super duper secret Twitter keys will need to be stored as secrets
in now
this is a pretty neat feature where you can define anything as a secret and reference it as an alias with now
.
Lets start, so the syntax is now secrets add my-secret "my value"
so for our .env
keys add them all in giving them a descriptive [but short!] name.
You will not need to wrap your "my value" in quotes but the documentation does say "when in doubt, wrap your value in quotes"
Ok, so from the terminal now secrets ls
should list out your secrets
you just created:
$ now secrets ls
> 5 secrets found under spences10 [1s]
id name created
sec_xxxxxxxxxxZpLDxxxxxxxxxx ds-twit-key 23h ago
sec_xxxxxxxxxxTE5Kxxxxxxxxxx ds-twit-secret 23h ago
sec_xxxxxxxxxxNorlxxxxxxxxxx ds-twit-access 23h ago
sec_xxxxxxxxxxMe1Cxxxxxxxxxx ds-twit-access-secret 23h ago
sec_xxxxxxxxxxMJ2jxxxxxxxxxx nasa-key 23h ago
Add npm deploy
script
Now we have out secrets defined we can create a deployment script to deploy to now
, so in our package.json
lets add an additional script:
"main": "index.js",
"scripts": {
"start": "node index.js",
"deploy": "now -e CONSUMER_KEY=@ds-twit-key -e CONSUMER_SECRET=@ds-twit-secret -e ACCESS_TOKEN=@ds-twit-access -e ACCESS_TOKEN_SECRET=@ds-twit-access-secret -e NASA_KEY=@nasa-key"
},
"now": {
Lets go over what we have added there, deploy
will run the now
command and pass it all our environment -e
variables and the associated secret
value, if we break it down into separate lines it will be a bit clearer:
now
-e CONSUMER_KEY=@ds-twit-key
-e CONSUMER_SECRET=@ds-twit-secret
-e ACCESS_TOKEN=@ds-twit-access
-e ACCESS_TOKEN_SECRET=@ds-twit-access-secret
-e NASA_KEY=@nasa-key
Re jig picture-bot.js
Ok, because now
deployments are immutable it means that there's no write access to the disk where we want to save our NASA photo of the day, so to get around that we need to use the /tmp
file location.
Shout out to @Tim from zeit
for helping me out with this!
In the picture-bot.js
module add the following two lines to the top of the module:
const os = require('os')
const tmpDir = os.tmpdir()
Those two lines give us the temp
directory of the operating system, so if like me you're on Windows it will work as well as if you are on another stsyem like a linux based system, which is what now
is. In our saveFile
function we're going to use tmpDir
to save our file.
We've taken out the nasa.jpg
from the getPhoto
function as we can define that information in the saveFile
function, the NASA potd is not just a 'jpeg
some items posted there are videos as well. We we can define the type with a ternary function off of the body
being passed in, this will send a tweet with a link to the video:
function saveFile(body) {
const fileName = body.media_type === 'image/jpeg' ? 'nasa.jpg' : 'nasa.mp4';
const filePath = path.join(tmpDir + `/${fileName}`)
console.log(`saveFile: file PATH ${filePath}`)
if (fileName === 'nasa.mp4') {
// tweet the link
const params = {
status: 'NASA video link: ' + body.url
}
postStatus(params)
return
}
const file = fs.createWriteStream(filePath)
request(body).pipe(file).on('close', err => {
if (err) {
console.log(err)
} else {
console.log('Media saved!')
const descriptionText = body.title
uploadMedia(descriptionText, filePath)
}
})
}
The completed code here:
const Twit = require('twit')
const request = require('request')
const fs = require('fs')
const config = require('./config')
const path = require('path')
const bot = new Twit(config)
const os = require('os')
const tmpDir = os.tmpdir()
const getPhoto = () => {
const parameters = {
url: 'https://api.nasa.gov/planetary/apod',
qs: {
api_key: process.env.NASA_KEY
},
encoding: 'binary'
}
request.get(parameters, (err, respone, body) => {
body = JSON.parse(body)
saveFile(body)
})
}
function saveFile(body) {
const fileName = body.media_type === 'image/jpeg' ? 'nasa.jpg' : 'nasa.mp4';
const filePath = path.join(tmpDir + `/${fileName}`)
console.log(`saveFile: file PATH ${filePath}`)
if (fileName === 'nasa.mp4') {
// tweet the link
const params = {
status: 'NASA video link: ' + body.url
}
postStatus(params)
return
}
const file = fs.createWriteStream(filePath)
request(body).pipe(file).on('close', err => {
if (err) {
console.log(err)
} else {
console.log('Media saved!')
const descriptionText = body.title
uploadMedia(descriptionText, filePath)
}
})
}
function uploadMedia(descriptionText, fileName) {
console.log(`uploadMedia: file PATH ${fileName}`)
bot.postMediaChunked({
file_path: fileName
}, (err, data, respone) => {
if (err) {
console.log(err)
} else {
console.log(data)
const params = {
status: descriptionText,
media_ids: data.media_id_string
}
postStatus(params)
}
})
}
function postStatus(params) {
bot.post('statuses/update', params, (err, data, respone) => {
if (err) {
console.log(err)
} else {
console.log('Status posted!')
}
})
}
module.exports = getPhoto
Ok, thats it! We're ready to deploy to now
!🚀
So from the terminal we call our deployment script we defined earlier:
yarn deploy
You will get some output:
λ yarn deploy
yarn deploy v0.24.4
$ now -e CONSUMER_KEY=@ds-twit-key -e CONSUMER_SECRET=@ds-twit-secret -e ACCESS_TOKEN=@ds-twit-access -e ACCESS_TOKEN_SECRET=@ds-twit-access-secret -e NASA_KEY=@nasa-key
> Deploying ~\gitrepos\tweebot-play under spences10
> Using Node.js 7.10.0 (default)
> Ready! https://twee-bot-play-rapjuiuddx.now.sh (copied to clipboard) [5s]
> Upload [====================] 100% 0.0s
> Sync complete (1.54kB) [2s]
> Initializing…
> Building
> â–² npm install
> ⧗ Installing:
> ‣ csv-parse@^1.2.0
> ‣ dotenv@^4.0.0
> ‣ rita@^1.1.63
> ‣ tabletop@^1.5.2
> ‣ twit@^2.2.5
> ✓ Installed 106 modules [3s]
> â–² npm start
> > tweet-bot-playground@1.0.0 start /home/nowuser/src
> > node index.js
> saveFile: file PATH /tmp/nasa.jpg
> Media saved!
> uploadMedia: file PATH /tmp/nasa.jpg
Woot! You have your bot deployed! 🙌
If you click on the link produced you will be able to inspect the bot as it is on now
there's also a handy logs section on the page where you can check for output. ðŸ‘
Resources
If you want to learn more about me, you can ask me anything check my Github, or tweet me @ScottDevTweets.