From easy git installation to docker startup python

What is this?

A memorandum for me who forgets to work I plan to operate git from pycharm If you do this, you will be able to work without polluting your computer.

So do it Do it anyway

Introducing git

I hope git can be used because it is convenient in many ways.

1. Installation

First, download Git from the following site

After that, if you follow the road, the installation is completed The detailed route is difficult to explain, so check it out.

2. Register user name and email address

At the console $ git config --global" username " $ git config --global" email address "` Type in to complete registration

Work on github side

Create a github account, go to the github homepage and create a repository with new repository from "+" on the upper right Decide the name by Repository name Decide whether it is public or private and click create repository

Then a meaningful url will appear on the screen, so copy it and go to the terminal

image.png (51.7 kB)

You can issue a url even from Code, so let's do it from here when cloning

Go to the directory where you want to put your git project and git clone <url> By doing this, a directory connected to git will be created, so open pycharm or anything

Create .gitignore

The directory is completed, but as it is, anything will be shared on github, so create .gitignore Create a file named .gitignore directly under the directory If you are using JetBeain series IDE, copy and paste the above source code I don't know about other IDEs

Add the path of the file you do not want to share here This will prevent git from sharing files that you don't want to share with others, such as notes.

Work on the Docker side

After finishing the work on the github side, the next work is docker


This is packed with everything from installing Docker for desktop to linking with pycharm.

Create docker-compose.yml

Create docker-conpose.yml directly under the directory and copy and paste the following


 version: '3'
    build: docker/python
    tty: true
    - ./app/:/app
    working_dir: /app

build: specifies the storage destination of dockerfile

Whether tty: will be in a standby state after startup Required because it will fall immediately if there is nothing moving with false or blank

volumes: has the role of connecting the folder of the host machine and the folder in the container. The left is the host machine, the right is inside the container If there is no folder on the host side, a new folder will be created.

working_dir: specifies the default working area

Creating dockerfile

After creating docker-compose.yml, create dockerfile in the path specified by build: If you want to run the slack bot, copy and paste the following


FROM python:latest
RUN mkdir -p /app
RUN pip install slackbot

FROM sets docker image RUN is the command to be entered after the container is created. Use it when you want to include other packages that are not included in docker image.

In the above case, after creating the container, create the app directory and install the slackbot package. You can do anything you can do mainly with a linux terminal

Creating a container

Once you get here, all you have to do is make a container In the directory where docker-compose.yml is located docker-compose up --build -d You can create a container by doing

First start docker-compose up --build -d

from next time docker-compose up -d Stop all containers docker-copose stop

Erase all containers docker-compose down

Erase containers and images together docker-compose down --rmi

Run .py

When you want to make a program and execute it Copy the name of the container you want to run with docker ps docker exec -it <name> bash You can access the terminal inside the container with After that, execute python normally with python etc.

If you want to run without accessing the terminal docker exec -it <name> <program name> Can be executed without entering the terminal with

At the end

If you have any questions or complaints, please contact Arakawa It may or may not correspond

Enjoy a comfortable python life with this!

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