Skip to main content

Communicate your project updates via Telegram Bot!

Project description

ChaterJee

ChaterJee

Often, we need to run computational trial and error experiments by just tweaking one or two key parameters. In machine learning, you face similar problems during hyperparameter tuning experiments.

These are probably the most boring, time-consuming, yet unavoidable phases in our day-to-day research. But what if your experiments could keep working while you're at a date XD ? What if you could kick off a hyperparameter tuning run just before bed — and wake up with results and plots waiting on your phone, like a good morning message from your research? Real-time updates, one-tap reruns, and zero late-night debugging. It’s like having a research assistant in your pocket.

Let me introduce ChaterJee to you — a playful fusion of Chater, meaning one who chats, and Jee, an honorific used in Indian culture to show respect. Think of ChaterJee as the lab assistant you always wanted — one who actually responds, never crashes your code, doesn't ask for co-authorship, and definitely doesn't need coffee all the time, unlike you.

Installation

As a prerequisite you are required to install the jq library for reading JSON files from bash script.

sudo apt update
sudo apt install jq

Now, you need two things:

  1. The ChaterJee module
  2. A telegram BOT that you own

Installing the module

I recommend to install ChaterJee module inside your project's conda environment for a seamless experience.

conda activate yourenv
pip install ChaterJee

Get your telegram BOT

To use this ChaterJee, you'll need a Telegram Bot Token and your Chat ID. Follow these simple steps:

Create a Bot and Get the Token

  • Open Telegram and search for @BotFather.
  • Start a chat and send the command /newbot.
  • Follow the prompts: choose a name and a username for your bot.
  • Once done, BotFather will give you a bot token — a long string like 123456789:ABCdefGhiJKlmNoPQRsTuvWXyz.

Get Your Chat ID

  • Open Telegram and start a chat with your newly created bot by searching its username.

  • Send Hi (any message) to your bot.

  • Open your browser and visit this URL, replacing YOUR_BOT_TOKEN with your token: https://api.telegram.org/bot{YOUR_BOT_TOKEN}/getUpdates

    with the above token, this URL becomes: https://api.telegram.org/bot123456789:ABCdefGhiJKlmNoPQRsTuvWXyz/getUpdates

  • Look for "chat":{"id":...} in the JSON response. This number is your Chat ID.

Quick Start

ChaterJee has two components.

  • NoteLogs class: This stores log files, and save project locations for parsing updates.
  • ChatLogs class: This reads log files, the last line is sent to you via the BOT. It can also share you final plots that you need for your next rerun.

The minimal example

This will register your JOB with the given JOBNAME and logfiles into a JSON file, <your home>/.data/JOB_status.json.

script.py

# This is a minimal example

# Your imports
from pathlib import Path
import ChaterJee
import json

# your code here
with open("hyperparams.json","r") as ffr:
    HYPERPARAMS = json.load(ffr)
    # get your parameters
    JOBNAME = HYPERPARAMS["JOBNAME"]
    LOGDIR = HYPERPARAMS["LOGDIR"]
    LOGFILE = HYPERPARAMS["LOGFILE"]
    LOGIMAGE = HYPERPARAMS["LOGIMAGE"]

notelogs = ChaterJee.NoteLogs()
notelogs.write(
    jobNAME=JOBNAME,
    logDIR=LOGDIR,
    logFILE=LOGFILE,
    logIMAGE=LOGIMAGE
    )

### Your code that generates logs
print(f"{logs}")

### Your code that generates plot
logPath = Path(LOGDIR)
plt.savefig(logPath / LOGIMAGE)

The hyperparams.json file should look like the following. It must contain the last 4 {key: value} pairs to let our BOT access the log results.

hyperparams.json

{
    .
    .

    "JOBNAME": "model_2.4",
    "LOGDIR": "./run_2.4",
    "LOGFILE": "outFile.log",
    "LOGIMAGE": "outImage.png"
}

Save the following script in your working directory to rerun your tuning experiments quickly.

run.sh

#!/bin/bash

# Path to hyperparameter file
hyparam_file="hyperparams.json"

# Read values from config.json using jq
stdout_log=$(jq -r '.LOGFILE' "$hyparam_file")
stdout_dir=$(jq -r '.LOGDIR' "$hyparam_file")

# Create log directory
mkdir -p "$stdout_dir"

# Backup the hyperparam file for reference
cp "$hyparam_file" "$stdout_dir/$hyparam_file"

# Run the Python script with redirected logs
nohup python script.py --hyprm "$hyparam_file" > "$stdout_dir/$stdout_log" 2> "$stdout_dir/error.log" &

# Save the PID of the background process
echo $! > "$stdout_dir/job.pid"

Also, make a kill_run.sh file to kill this job in case you need to.

kill_run.sh

#!/bin/bash
stdout_dir=$(jq -r '.LOGDIR' hyperparams.json)

# Check if the PID file exists
pid_file="$stdout_dir/job.pid"

if [ -f "$pid_file" ]; then
    pid=$(cat "$pid_file")
    echo "Killing process with PID $pid"
    kill -9 "$pid" && echo "Process killed." || echo "Failed to kill process."
else
    echo "No PID file found. Is the process running?"
fi

Next step is to receive updates on your projects.

updater.py

# Run this instance separately to parse job updates
# This is the one which actually communicates with your BOT.

import ChaterJee

if __name__ == '__main__':
    TOKEN = '123456789:ABCdefGhiJKlmNoPQRsTuvWXyz'
    CHATID = '123456789'

    cbot = ChaterJee.ChatLogs(TOKEN, CHATID)
    cbot.cmdTRIGGER()

Run the above script in a separate terminal session to start interacting with your BOT.

At your Telegram App

  • Think your inbox as the terminal.
  • cd, ls etc. works as expected. Therefore to go to parent directory, you simply type: cd .. , and to list contents type ls . You can run the run.sh executable just by typing ./run.sh .
  • texts starting with / are telegram-BOT commands.

At this stage the following 4 commands work:

  • /start : Starts the conversation with the BOT.
  • /run : Runs the job (current directory).
  • /kill : Kills the job once you allow (current directory).
  • /jobs : List the jobs as Keyboard button options.
  • /clear : Clears the chat history once you allow.
  • /edit : Let you choose and edit a JSON file (from current directory) by the webapp Editor Babu.
  • /edit file.json : Let you edit and save the JSON file (from any directory) by the webapp Editor Babu.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

chaterjee-0.9.3.tar.gz (10.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

chaterjee-0.9.3-py3-none-any.whl (10.9 kB view details)

Uploaded Python 3

File details

Details for the file chaterjee-0.9.3.tar.gz.

File metadata

  • Download URL: chaterjee-0.9.3.tar.gz
  • Upload date:
  • Size: 10.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.8.18

File hashes

Hashes for chaterjee-0.9.3.tar.gz
Algorithm Hash digest
SHA256 ab5f17acba7772facf5036d8354be572e0f8de186d0bfc2bb95e221217a89d72
MD5 5f62fc4190689ddaa1d5bec512826f76
BLAKE2b-256 9d806c135d828c21a5855e9679374dd2ace84840688c9edc142b3c08166b8978

See more details on using hashes here.

File details

Details for the file chaterjee-0.9.3-py3-none-any.whl.

File metadata

  • Download URL: chaterjee-0.9.3-py3-none-any.whl
  • Upload date:
  • Size: 10.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.8.18

File hashes

Hashes for chaterjee-0.9.3-py3-none-any.whl
Algorithm Hash digest
SHA256 3071d6e01dff70cd77560e8e166ef4c4a1a5c0b32cbf4a2fc922bc03cc631d3f
MD5 7d37c324fc91f04bad041ec5485f380c
BLAKE2b-256 825bf9345512f2551ea6ab832032cd3480db39db62418e24ed37a6fa1f6672ad

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page