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slackers

A collection of Slack bots.

Getting started

  1. Create a virtual environment based on python3.
  2. Get the python requirements: pip install -r requirements.txt
  3. Create a slackers.cfg (see: slackers.cfg.example)

ec2bot

ec2bot monitors an SQS queue for ec2 events. This includes any state change notification for the ec2 instances in your account. State changes are reported to the configured channel subject to the configuration parameters described below. Slack messages will look something like this:

Image of jakebot

ec2bot uses boto3, which means that you also need to configure your shell to have access to the SQS queue. That's beyond the scope of this document, but the author uses the AWS_PROFILE environment variable to select the correct AWS credentials.

Configure & run ec2bot

  1. Create an SQS queue (called awsmonitor for this example)
  2. Create a new CloudWatch Rule with a source of aws.ec2 and a target of awsmonitor
  3. Create a Slack Bot (Workspace -> Manage Apps -> Custom Integrations -> Bots -> Add Configuration)
  4. Edit slackers.cfg with your slack token, SQS queue name, and channel name.
  5. Start up the bot! python ec2bot.py slackers.cfg

Required tags

Nag the slack channel when instances start up that are missing this list of tags. REQUIRED_TAGS should be a comma separated list of tags that should be present on every instance.

Ignored instances

Set IGNORED_INSTANCE_NAME_REGEX to a regex string to ignore certain indexes. TODO: This should be more configurable beyond a single regex and should be possible to apply to other tags and metadata. Likely this should be a more general solution that allows for json path queries.

Ignored states

Set IGNORED_STATES to a comma separated list of states to ignore. If the state matches one of these states, the event will not appear in the Slack channel.

wybott

A bunch of jank that trains a markov chain generator and imitates that user on Slack.

Once propertly trained, wybott will say things like:

Image of wybott talking

Train a model

First, get some content to train on. I did this initially by pulling everything that a particular user said publicly from our elasticsearch index and putting it into a file, one line per sentence.

Next, train a model. I used wybott-trainer.py to train the model based on the file of sentences.

Finally, run the bot with that model. python wybott.py will use slackers.cfg to find your model and connect to Slack.

About

A collection of Slack bots.

Topics

awsec2slackslackbot

Resources

Readme
Activity

Stars

3 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
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try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
slackers
A collection of Slack bots.
Getting started
  1. Create a virtual environment based on python3.
  2. Get the python requirements: pip install -r requirements.txt
  3. Create a slackers.cfg (see: slackers.cfg.example)
ec2bot
ec2bot monitors an SQS queue for ec2 events. This includes any state change notification for the ec2 instances in your account. State changes are reported to the configured channel subject to the configuration parameters described below. Slack messages will look something like this:
Image of jakebot
ec2bot uses boto3, which means that you also need to configure your shell to have access to the SQS queue. That's beyond the scope of this document, but the author uses the AWS_PROFILE environment variable to select the correct AWS credentials.
Configure & run ec2bot
  1. Create an SQS queue (called awsmonitor for this example)
  2. Create a new CloudWatch Rule with a source of aws.ec2 and a target of awsmonitor
  3. Create a Slack Bot (Workspace -> Manage Apps -> Custom Integrations -> Bots -> Add Configuration)
  4. Edit slackers.cfg with your slack token, SQS queue name, and channel name.
  5. Start up the bot! python ec2bot.py slackers.cfg
Required tags
Nag the slack channel when instances start up that are missing this list of tags. REQUIRED_TAGS should be a comma separated list of tags that should be present on every instance.
Ignored instances
Set IGNORED_INSTANCE_NAME_REGEX to a regex string to ignore certain indexes.
TODO: This should be more configurable beyond a single regex and should be possible to apply to other tags and metadata. Likely this should be a more general solution that allows for json path queries.
Ignored states
Set IGNORED_STATES to a comma separated list of states to ignore. If the state matches one of these states, the event will not appear in the Slack channel.
wybott
A bunch of jank that trains a markov chain generator and imitates that user on Slack.
Once propertly trained, wybott will say things like:
Image of wybott talking
Train a model
First, get some content to train on. I did this initially by pulling everything
that a particular user said publicly from our elasticsearch index and putting it
into a file, one line per sentence.
Next, train a model. I used wybott-trainer.py to train the model based on the file of sentences.
Finally, run the bot with that model. python wybott.py will use slackers.cfg to find your model and connect to Slack.
About
A collection of Slack bots.
Topics
awsec2slackslackbot
Resources
Readme
Activity
Stars
3 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
slackers
A collection of Slack bots.
Getting started
  1. Create a virtual environment based on python3.
  2. Get the python requirements: pip install -r requirements.txt
  3. Create a slackers.cfg (see: slackers.cfg.example)
ec2bot
ec2bot monitors an SQS queue for ec2 events. This includes any state change notification for the ec2 instances in your account. State changes are reported to the configured channel subject to the configuration parameters described below. Slack messages will look something like this:
Image of jakebot
ec2bot uses boto3, which means that you also need to configure your shell to have access to the SQS queue. That's beyond the scope of this document, but the author uses the AWS_PROFILE environment variable to select the correct AWS credentials.
Configure & run ec2bot
  1. Create an SQS queue (called awsmonitor for this example)
  2. Create a new CloudWatch Rule with a source of aws.ec2 and a target of awsmonitor
  3. Create a Slack Bot (Workspace -> Manage Apps -> Custom Integrations -> Bots -> Add Configuration)
  4. Edit slackers.cfg with your slack token, SQS queue name, and channel name.
  5. Start up the bot! python ec2bot.py slackers.cfg
Required tags
Nag the slack channel when instances start up that are missing this list of tags. REQUIRED_TAGS should be a comma separated list of tags that should be present on every instance.
Ignored instances
Set IGNORED_INSTANCE_NAME_REGEX to a regex string to ignore certain indexes.
TODO: This should be more configurable beyond a single regex and should be possible to apply to other tags and metadata. Likely this should be a more general solution that allows for json path queries.
Ignored states
Set IGNORED_STATES to a comma separated list of states to ignore. If the state matches one of these states, the event will not appear in the Slack channel.
wybott
A bunch of jank that trains a markov chain generator and imitates that user on Slack.
Once propertly trained, wybott will say things like:
Image of wybott talking
Train a model
First, get some content to train on. I did this initially by pulling everything
that a particular user said publicly from our elasticsearch index and putting it
into a file, one line per sentence.
Next, train a model. I used wybott-trainer.py to train the model based on the file of sentences.
Finally, run the bot with that model. python wybott.py will use slackers.cfg to find your model and connect to Slack.
About
A collection of Slack bots.
Topics
awsec2slackslackbot
Resources
Readme
Activity
Stars
3 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
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var ref = document.referrer;
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mutations.forEach(function(m) {
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observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
slackers
A collection of Slack bots.
Getting started
  1. Create a virtual environment based on python3.
  2. Get the python requirements: pip install -r requirements.txt
  3. Create a slackers.cfg (see: slackers.cfg.example)
ec2bot
ec2bot monitors an SQS queue for ec2 events. This includes any state change notification for the ec2 instances in your account. State changes are reported to the configured channel subject to the configuration parameters described below. Slack messages will look something like this:
Image of jakebot
ec2bot uses boto3, which means that you also need to configure your shell to have access to the SQS queue. That's beyond the scope of this document, but the author uses the AWS_PROFILE environment variable to select the correct AWS credentials.
Configure & run ec2bot
  1. Create an SQS queue (called awsmonitor for this example)
  2. Create a new CloudWatch Rule with a source of aws.ec2 and a target of awsmonitor
  3. Create a Slack Bot (Workspace -> Manage Apps -> Custom Integrations -> Bots -> Add Configuration)
  4. Edit slackers.cfg with your slack token, SQS queue name, and channel name.
  5. Start up the bot! python ec2bot.py slackers.cfg
Required tags
Nag the slack channel when instances start up that are missing this list of tags. REQUIRED_TAGS should be a comma separated list of tags that should be present on every instance.
Ignored instances
Set IGNORED_INSTANCE_NAME_REGEX to a regex string to ignore certain indexes.
TODO: This should be more configurable beyond a single regex and should be possible to apply to other tags and metadata. Likely this should be a more general solution that allows for json path queries.
Ignored states
Set IGNORED_STATES to a comma separated list of states to ignore. If the state matches one of these states, the event will not appear in the Slack channel.
wybott
A bunch of jank that trains a markov chain generator and imitates that user on Slack.
Once propertly trained, wybott will say things like:
Image of wybott talking
Train a model
First, get some content to train on. I did this initially by pulling everything
that a particular user said publicly from our elasticsearch index and putting it
into a file, one line per sentence.
Next, train a model. I used wybott-trainer.py to train the model based on the file of sentences.
Finally, run the bot with that model. python wybott.py will use slackers.cfg to find your model and connect to Slack.
About
A collection of Slack bots.
Topics
awsec2slackslackbot
Resources
Readme
Activity
Stars
3 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
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function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
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mutations.forEach(function(m) {
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} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
slackers
A collection of Slack bots.
Getting started
  1. Create a virtual environment based on python3.
  2. Get the python requirements: pip install -r requirements.txt
  3. Create a slackers.cfg (see: slackers.cfg.example)
ec2bot
ec2bot monitors an SQS queue for ec2 events. This includes any state change notification for the ec2 instances in your account. State changes are reported to the configured channel subject to the configuration parameters described below. Slack messages will look something like this:
Image of jakebot
ec2bot uses boto3, which means that you also need to configure your shell to have access to the SQS queue. That's beyond the scope of this document, but the author uses the AWS_PROFILE environment variable to select the correct AWS credentials.
Configure & run ec2bot
  1. Create an SQS queue (called awsmonitor for this example)
  2. Create a new CloudWatch Rule with a source of aws.ec2 and a target of awsmonitor
  3. Create a Slack Bot (Workspace -> Manage Apps -> Custom Integrations -> Bots -> Add Configuration)
  4. Edit slackers.cfg with your slack token, SQS queue name, and channel name.
  5. Start up the bot! python ec2bot.py slackers.cfg
Required tags
Nag the slack channel when instances start up that are missing this list of tags. REQUIRED_TAGS should be a comma separated list of tags that should be present on every instance.
Ignored instances
Set IGNORED_INSTANCE_NAME_REGEX to a regex string to ignore certain indexes.
TODO: This should be more configurable beyond a single regex and should be possible to apply to other tags and metadata. Likely this should be a more general solution that allows for json path queries.
Ignored states
Set IGNORED_STATES to a comma separated list of states to ignore. If the state matches one of these states, the event will not appear in the Slack channel.
wybott
A bunch of jank that trains a markov chain generator and imitates that user on Slack.
Once propertly trained, wybott will say things like:
Image of wybott talking
Train a model
First, get some content to train on. I did this initially by pulling everything
that a particular user said publicly from our elasticsearch index and putting it
into a file, one line per sentence.
Next, train a model. I used wybott-trainer.py to train the model based on the file of sentences.
Finally, run the bot with that model. python wybott.py will use slackers.cfg to find your model and connect to Slack.
About
A collection of Slack bots.
Topics
awsec2slackslackbot
Resources
Readme
Activity
Stars
3 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
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}
}
// Try immediately
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if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
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}, 1000);
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var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
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} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
slackers
A collection of Slack bots.
Getting started
  1. Create a virtual environment based on python3.
  2. Get the python requirements: pip install -r requirements.txt
  3. Create a slackers.cfg (see: slackers.cfg.example)
ec2bot
ec2bot monitors an SQS queue for ec2 events. This includes any state change notification for the ec2 instances in your account. State changes are reported to the configured channel subject to the configuration parameters described below. Slack messages will look something like this:
Image of jakebot
ec2bot uses boto3, which means that you also need to configure your shell to have access to the SQS queue. That's beyond the scope of this document, but the author uses the AWS_PROFILE environment variable to select the correct AWS credentials.
Configure & run ec2bot
  1. Create an SQS queue (called awsmonitor for this example)
  2. Create a new CloudWatch Rule with a source of aws.ec2 and a target of awsmonitor
  3. Create a Slack Bot (Workspace -> Manage Apps -> Custom Integrations -> Bots -> Add Configuration)
  4. Edit slackers.cfg with your slack token, SQS queue name, and channel name.
  5. Start up the bot! python ec2bot.py slackers.cfg
Required tags
Nag the slack channel when instances start up that are missing this list of tags. REQUIRED_TAGS should be a comma separated list of tags that should be present on every instance.
Ignored instances
Set IGNORED_INSTANCE_NAME_REGEX to a regex string to ignore certain indexes.
TODO: This should be more configurable beyond a single regex and should be possible to apply to other tags and metadata. Likely this should be a more general solution that allows for json path queries.
Ignored states
Set IGNORED_STATES to a comma separated list of states to ignore. If the state matches one of these states, the event will not appear in the Slack channel.
wybott
A bunch of jank that trains a markov chain generator and imitates that user on Slack.
Once propertly trained, wybott will say things like:
Image of wybott talking
Train a model
First, get some content to train on. I did this initially by pulling everything
that a particular user said publicly from our elasticsearch index and putting it
into a file, one line per sentence.
Next, train a model. I used wybott-trainer.py to train the model based on the file of sentences.
Finally, run the bot with that model. python wybott.py will use slackers.cfg to find your model and connect to Slack.
About
A collection of Slack bots.
Topics
awsec2slackslackbot
Resources
Readme
Activity
Stars
3 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
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unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
slackers
A collection of Slack bots.
Getting started
  1. Create a virtual environment based on python3.
  2. Get the python requirements: pip install -r requirements.txt
  3. Create a slackers.cfg (see: slackers.cfg.example)
ec2bot
ec2bot monitors an SQS queue for ec2 events. This includes any state change notification for the ec2 instances in your account. State changes are reported to the configured channel subject to the configuration parameters described below. Slack messages will look something like this:
Image of jakebot
ec2bot uses boto3, which means that you also need to configure your shell to have access to the SQS queue. That's beyond the scope of this document, but the author uses the AWS_PROFILE environment variable to select the correct AWS credentials.
Configure & run ec2bot
  1. Create an SQS queue (called awsmonitor for this example)
  2. Create a new CloudWatch Rule with a source of aws.ec2 and a target of awsmonitor
  3. Create a Slack Bot (Workspace -> Manage Apps -> Custom Integrations -> Bots -> Add Configuration)
  4. Edit slackers.cfg with your slack token, SQS queue name, and channel name.
  5. Start up the bot! python ec2bot.py slackers.cfg
Required tags
Nag the slack channel when instances start up that are missing this list of tags. REQUIRED_TAGS should be a comma separated list of tags that should be present on every instance.
Ignored instances
Set IGNORED_INSTANCE_NAME_REGEX to a regex string to ignore certain indexes.
TODO: This should be more configurable beyond a single regex and should be possible to apply to other tags and metadata. Likely this should be a more general solution that allows for json path queries.
Ignored states
Set IGNORED_STATES to a comma separated list of states to ignore. If the state matches one of these states, the event will not appear in the Slack channel.
wybott
A bunch of jank that trains a markov chain generator and imitates that user on Slack.
Once propertly trained, wybott will say things like:
Image of wybott talking
Train a model
First, get some content to train on. I did this initially by pulling everything
that a particular user said publicly from our elasticsearch index and putting it
into a file, one line per sentence.
Next, train a model. I used wybott-trainer.py to train the model based on the file of sentences.
Finally, run the bot with that model. python wybott.py will use slackers.cfg to find your model and connect to Slack.
About
A collection of Slack bots.
Topics
awsec2slackslackbot
Resources
Readme
Activity
Stars
3 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
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if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
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/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
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';
}
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if (style) style.remove();
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})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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slackers
A collection of Slack bots.
Getting started
  1. Create a virtual environment based on python3.
  2. Get the python requirements: pip install -r requirements.txt
  3. Create a slackers.cfg (see: slackers.cfg.example)
ec2bot
ec2bot monitors an SQS queue for ec2 events. This includes any state change notification for the ec2 instances in your account. State changes are reported to the configured channel subject to the configuration parameters described below. Slack messages will look something like this:
Image of jakebot
ec2bot uses boto3, which means that you also need to configure your shell to have access to the SQS queue. That's beyond the scope of this document, but the author uses the AWS_PROFILE environment variable to select the correct AWS credentials.
Configure & run ec2bot
  1. Create an SQS queue (called awsmonitor for this example)
  2. Create a new CloudWatch Rule with a source of aws.ec2 and a target of awsmonitor
  3. Create a Slack Bot (Workspace -> Manage Apps -> Custom Integrations -> Bots -> Add Configuration)
  4. Edit slackers.cfg with your slack token, SQS queue name, and channel name.
  5. Start up the bot! python ec2bot.py slackers.cfg
Required tags
Nag the slack channel when instances start up that are missing this list of tags. REQUIRED_TAGS should be a comma separated list of tags that should be present on every instance.
Ignored instances
Set IGNORED_INSTANCE_NAME_REGEX to a regex string to ignore certain indexes.
TODO: This should be more configurable beyond a single regex and should be possible to apply to other tags and metadata. Likely this should be a more general solution that allows for json path queries.
Ignored states
Set IGNORED_STATES to a comma separated list of states to ignore. If the state matches one of these states, the event will not appear in the Slack channel.
wybott
A bunch of jank that trains a markov chain generator and imitates that user on Slack.
Once propertly trained, wybott will say things like:
Image of wybott talking
Train a model
First, get some content to train on. I did this initially by pulling everything
that a particular user said publicly from our elasticsearch index and putting it
into a file, one line per sentence.
Next, train a model. I used wybott-trainer.py to train the model based on the file of sentences.
Finally, run the bot with that model. python wybott.py will use slackers.cfg to find your model and connect to Slack.
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A collection of Slack bots.
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