How to run:

1. Create env.cfg file with your token (see env-example.cfg)
2. Use Dockerfile to build and run a Docker container

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eesteclctampere_ws_22

Base project for Great Northern Health Tracking Trek. EESTEC LC Tampere workshop November 2022

Crash course to git

• git status

  • returns status of the repository

• git add <filename>

  • stages file for commit

• git add -A

  • stages all changed files for commit

• git commit -m "Commit message"

  • commit changes to head, not yet to the remote
  • if you forget message an editor will open. propably vim, don't get scared

• git push

  • sends changes to remote

• git checkout -b <branchname>

  • creates new branch and switches to it
  • without -b handle checkout just switches from one branch to another

• git pull

  • fetch and merge changes from remote to your local directory

• check for more: https://confluence.atlassian.com/bitbucketserver/basic-git-commands-776639767.html

• actual git documentation: https://git-scm.com/docs/git

0. Installing required tools and packages

Git if you don't have already

• sudo apt install git

Package installer for Python

• sudo apt install python3-pip

Python Telegram Bot

• pip install python-telegram-bot -U --pre
  • pre-releases https://github.com/python-telegram-bot/python-telegram-bot/wiki/introduction-to-the-API
  • If you want to use older version like 13.0 the syntax is quite different.

Data is stored with sqlite3 database so let's install that

• sudo apt install sqlite3

0.1. Getting access to repository

• Log in or sign up to github.
• Now let's fork this repository: https://github.com/ahvena91/eesteclctampere_ws_22
• Forking means that you take a copy of source code and start independet development on it
• main branch has few minimal examples
• if you get stuck or want to check something there's a bit more advanced sources in other branches

1. Installing all libraries listed in requirements

• pip install -r requirements.txt

2. Talking to botfather and getting your token

• start conversation with https://t.me/botfather
• make a copy of env-example.cfg and rename it to env.cfg
• env.cfg is se to .gitignore so that we wont't publish our personal bot token by accident

3. Check echobot and conversationbot + 1_input_test

• run python3 echobot.py and python3 conversationbot.py separately
• and figure out how they work
• after this point you should at least get familiar with
  • ConversationHandler
    • https://ptb-test.readthedocs.io/en/latest/telegram.ext.conversationhandler.html
  • CommandHandler
    • https://ptb-test.readthedocs.io/en/latest/telegram.ext.commandhandler.html
  • MessageHandler
    • https://ptb-test.readthedocs.io/en/latest/telegram.ext.messagehandler.html
• In the original repository there's separate branches with more code included if you get stuck or just want to check something for reference

• You may also fork the repository again
• or just copy some of the contents

4. Plan your own features for the bot

• Minimum requirements would be that user is able to store data and plot it
• But of course this is your own design
• You may check out this features.mmd https://github.com/ahvena91/eesteclctampere_ws_22/blob/main/features.mmd
  • if you want to view it locally you need to install extension for VS Code to view it.

5. Storing data into sqlite3 database

• First make sure you have sqlite3 installed

• This should be useful for windows users: https://www.sqlitetutorial.net/download-install-sqlite/

• Check the changes in https://github.com/ahvena91/eesteclctampere_ws_22/tree/2_database_test

• There's two new files: initdatabase.py and db_handler.py

  • first one is creating the database and second one is used for implementing methods that use the db

  5.2. Testing the database

  • Database handling can be tested by running database_test.py program
  • /new command asks user a new datapoint which is now stored in the database by calling add_data method from db_handler
  • you can check that the value is indeed saved by starting sqlite3
    • sqlite3 <nameofdatabase>
    • .tables lists created data tables
    • SELECT <data> FROM <nameoftable> lists added datapoints
      • for example: SELECT datapoint FROM data_table