Any Python Function
Decorator-based notifications for script execution with returned output summaries.
Real-time notifications for any Python pipeline
Run anything.
Know instantly. Stay anywhere.
slackker sends real-time notifications to Slack, Telegram, Discord, or Microsoft Teams for any Python pipeline, ML training run, or automation workflow — complete with metrics, outputs, and optional plots.
from slackker.core import TelegramClient
from slackker.callbacks.simple import SimpleCallback
client = TelegramClient(token="123456:ABC-DEF...")
slackker = SimpleCallback(client)
@slackker.notifier
def train_model():
return "done"
slackker.notify(event="training_complete", status="completed")Why slackker
Stay informed without staying glued to your screen
Keras Callback
Attach to model.fit and receive metric progress during epoch training.
Lightning Callback
Track train and validation logs with monitor-based best epoch updates.
Plot Sharing
Export and send history plots so you can check model behavior quickly on mobile.
Quick start
From install to updates in five steps
- 1Install package:
pip install slackker - 2Setup either Slack, Telegram, or Teams credentials.
- 3Create a
SlackClient,TelegramClient, orTeamsClientwith your credentials. - 4Pass the client to
SimpleCallback,KerasCallback, orLightningCallback. - 5Run training and receive updates plus optional exported plots.
Client setup
Get your credentials in minutes
Pick your platform and follow the one-time steps to obtain the credentials you'll pass to the client constructor.
Telegram
Only a bot token is needed — slackker auto-discovers your chat ID from the first message you send the bot.
-
1
Find BotFather on Telegram
Open Telegram ➤ search for
@BotFather— the official bot for creating custom bots. -
2
Create your bot
Send
/newbot➤ follow the prompts to give your bot a display name and a unique username (must end inbot) -
3
Copy the bot token
BotFather replies with a token ➤ save it, this is your
tokenparameter:1234567890:AAAA_A111BBBBBCCC2DD3eEe44f5GGGgGG -
4
Send your bot a message
Open the bot's chat in Telegram ➤ send any message (e.g. "Hello!") ➤ This lets slackker auto-discover your chat ID on first
connect(), no manual lookup needed. -
5
Use the token in your code
TelegramClient(token="1234567890:AAAA_A111...")
Slack
Create a Slack App, grant it bot token scopes, install it to your workspace, then grab your token and channel ID.
-
1
Create a Slack App
Go to api.slack.com/apps ➤ Create New App ➤ From scratch. Name the app and select your workspace.
-
2
Add Bot Token Scopes
Sidebar ➤ OAuth & Permissions ➤ Bot Token Scopes ➤ add all four:
chat:writechat:write.publicfiles:readfiles:write -
3
Install the app to your workspace
Go to Basic Information ➤ Install to Workspace ➤ authorize. The app appears under Apps in Slack.
-
4
Copy your Bot User OAuth Token
Back in OAuth & Permissions, copy the token that begins with
xoxb-. This is yourtoken:xoxb-123234234235-123234234235-adedce74748c3844747aed48499bb -
5
Add the app to a channel & get the Channel ID
In Slack, open the target channel ➤ click the channel name ➤ Integrations ➤ Add an App. Then copy the Channel ID from the channel description (starts with
C):SlackClient(token="xoxb-...", channel="C04AAB77ABC")
Microsoft Teams
Register an Azure AD app (free, no admin consent), add Graph permissions, then sign in once interactively. The token is cached and refreshed silently on all future runs.
⚠️ Work account required. The Microsoft Graph Chat API requires a work or school Microsoft account. Personal Microsoft accounts (Outlook.com, Hotmail) are not supported by this API.
-
1
Register an Azure AD App
Go to Azure App Registrations ➤ New registration. Name it (e.g. slackker), set Supported account types to "Any Entra ID Tenant + Personal Microsoft accounts", click Register.
-
2
Copy Application Credentials
On the app Overview page ➤ Copy Application (client) ID — this is your
app_id➤ Copy Directory (tenant) ID — this is yourtenant_id -
3
Add delegated Microsoft Graph permissions
Sidebar ➤ API permissions ➤ Add a permission ➤ Microsoft Graph ➤ Delegated permissions. Add all four:
Chat.ReadWriteFiles.ReadWriteoffline_accessUser.ReadNo admin consent is required for these delegated scopes.
-
4
Find your Chat ID
In Microsoft Teams, open the chat you want to use ➤ right-click any message ➤ Copy link to message ➤ Extract chat ID embedded in the URL — typically starts with
19:and ends with@thread.v2. -
5
Sign in once with the device code flow
On first
connect(), slackker prints a short URL and a one-time code ➤ Visit the URL in any browser ➤ enter the code ➤ sign in with your work account ➤ The token is then cached and refreshed silently on all future runs.TeamsClient(app_id="YOUR_APP_ID", tenant_id="YOUR_TENANT_ID", chat_id="19:...")
Discord
Create a Discord bot, invite it to your server, and grab your bot token and channel ID.
-
1
Create a Discord Application
Go to the Discord Developer Portal ➤ New Application. Name your bot and create the app.
-
2
Get your Bot Token
Sidebar ➤ Bot ➤ Reset Token (or copy existing). This is your
token:MTIzNDU2Nzg5MDEyMzQ1Njc4OToxMjM0NTY3ODkwMTIzNDU2Nzg5MDEy... -
3
Invite the Bot to your Server
Sidebar ➤ OAuth2 ➤ URL Generator ➤ Select
botscope ➤ Set permissionsSend Messages&Attach Files. ➤ Visit the generated URL to invite the bot. -
4
Enable Developer Mode
Go to User Settings ➤ Developer ➤ Toggle Developer Mode to ON.
-
5
Get the Channel ID
Right-click your target channel ➤ Copy Channel ID:
DiscordClient(token="MTIz...", channel_id="123456789012345678")
Detailed callback usage
Drop-in examples for real projects
from slackker.core import TelegramClient
from slackker.callbacks.simple import SimpleCallback
client = TelegramClient(
token="123456:ABC-DEF...",
verbose=1
)
notify = SimpleCallback(client)
@notify.notifier
def run_data_pipeline(source_path: str):
rows_processed = 12500
status = "success"
return rows_processed, status
if __name__ == "__main__":
rows, status = run_data_pipeline("./data/train.csv")
notify.notify(
event="pipeline_finished",
rows_processed=rows,
status=status,
attachment="./artifacts/summary.txt"
)from slackker.core import TelegramClient
from slackker.callbacks.keras import KerasCallback
client = TelegramClient(
token="123456:ABC-DEF...",
verbose=1
)
slackker_cb = KerasCallback(
client=client,
model_name="ImageClassifierV1",
export="png",
send_plot=True,
)
history = model.fit(
x_train,
y_train,
epochs=20,
batch_size=32,
validation_data=(x_val, y_val),
callbacks=[slackker_cb]
)from lightning.pytorch import Trainer
from slackker.core import TelegramClient
from slackker.callbacks.lightning import LightningCallback
client = TelegramClient(
token="123456:ABC-DEF...",
verbose=1
)
slackker_cb = LightningCallback(
client=client,
model_name="LightningClassifier",
track_logs=["train_loss", "train_acc", "val_loss", "val_acc"],
monitor="val_loss",
export="png",
send_plot=True,
)
trainer = Trainer(max_epochs=12, callbacks=[slackker_cb])
trainer.fit(model, train_loader, val_loader)Under the hood
Three lines to stay in the loop
01
Connect
Create a SlackClient, TelegramClient, or TeamsClient with your credentials. slackker verifies connectivity and is ready to post updates.
02
Attach
Pass the client to SimpleCallback, KerasCallback, or LightningCallback. Wrap your function with @notifier or drop the callback into your trainer.
03
Receive
Get real-time updates — execution time, returned outputs, epoch metrics, best model stats, and optional training plots — delivered straight to your phone.
Your pipeline runs. Your phone notifies
Stop babysitting terminal. Slackker keeps you informed so you can stay heads-down on what actually matters.