I have created a docker container for my pure python program and have set python main.py to be executed when the container is run. Running the container works as expected on my local machine. However, I want to run the container on my institution's high-performance cluster. The cluster machines use Singularity, which I am using to pull my docker image hosted on Dockerhub (the repo is darshank11/ga_paci_final). However, when I try to run the Singularity container, I get the following error: python3: can't open file 'main.py': [Errno 2] No such file or directory.
I've tried to change the base image in the Dockerfile, for example from FROM python:latest to FROM ubuntu:latest. I've made sure the docker container worked on my local machine, and then got one of my co-workers to pull the container from Dockerhub and run it too. Everything works fine until I get to Singularity.
Here is my docker file:
FROM ubuntu:16.04
RUN apt-get update -y && \
apt-get install -y python3-pip python3-dev
RUN mkdir src
WORKDIR /src
COPY . /src
RUN pip3 install --upgrade pip
RUN pip3 install -r requirements.txt
CMD ["python3", "-u", "main.py"]
You're getting that error because the execution context is not what you're expecting. The run path in singularity is the current directory on the host OS (e.g., ~/ga_paci_final), which has been mounted into the singularity image.
As mentioned in the comments, one solution is to give the full path to the python file in the docker CMD statement. Another option is to modify the %runscript block of singularity definition file to something like:
%runscript
cd /src
python3 -u main.py
That way you ensure the run environment is identical between Docker and Singularity.
Related
Below my docker file,
FROM python:3.9.0
ARG WORK_DIR=/opt/quarter_1
RUN apt-get update && apt-get install cron -y && apt-get install -y default-jre
# Install python libraries
COPY requirements.txt /tmp/requirements.txt
RUN pip install --upgrade pip && pip install -r /tmp/requirements.txt
WORKDIR $WORK_DIR
EXPOSE 8888
VOLUME /home/data/quarter_1/
# Copy etl code
# copy code on container under your workdir "/opt/quarter_1"
COPY . .
I tried to connect to the server then i did the build with docker build -t my-python-app .
when i tried to run the container from a build image i got nothing and was not able to do it.
docker run -p 8888:8888 -v /home/data/quarter_1/:/opt/quarter_1 image_id
work here is opt
Update based on comments
If I understand everything you've posted correctly, my suggestion here is to use a base Docker Jupyter image, modify it to add your pip requirements, and then add your files to the work path. I've tested the following:
Start with a dockerfile like below
FROM jupyter/base-notebook:python-3.9.6
COPY requirements.txt /tmp/requirements.txt
RUN pip install --upgrade pip && pip install -r /tmp/requirements.txt
COPY ./quarter_1 /home/jovyan/quarter_1
Above assumes you are running the build from the folder containing dockerfile, "requirements.txt", and the "quarter_1" folder with your build files.
Note "home/joyvan" is the default working folder in this image.
Build the image
docker build -t biwia-jupyter:3.9.6 .
Start the container with open port to 8888. e.g.
docker run -p 8888:8888 biwia-jupyter:3.9.6
Connect to the container to access token. A few ways to do but for example:
docker exec -it CONTAINER_NAME bash
jupyter notebook list
Copy the token in the URL and connect using your server IP and port. You should be able to paste the token there, and afterwards access the folder you copied into the build, as I did below.
Jupyter screenshot
If you are deploying the image to different hosts this is probably the best way to do it using COPY/ADD etc., but otherwise look at using Docker Volumes which give you access to a folder (for example quarter_1) from the host, so you don't constantly have to rebuild during development.
Second edit for Python 3.9.0 request
Using the method above, 3.9.0 is not immediately available from DockerHub. I doubt you'll have much compatibility issues between 3.9.0 and 3.9.6, but we'll build it anyway. We can download the dockerfile folder from github, update a build argument, create our own variant with 3.9.0, and do as above.
Assuming you have git. Otherwise download the repo manually.
Download the Jupyter Docker stack repo
git clone https://github.com/jupyter/docker-stacks
change into the base-notebook directory of the cloned repo
cd ./base-notebook
Build the image with python 3.9.0 instead
docker build --build-arg PYTHON_VERSION=3.9.0 -t jupyter-base-notebook:3.9.0 .
Create the version with your copied folders and 3.9.0 version from the steps above, replacing the first line in the dockerfile instead with:
FROM jupyter-base-notebook:3.9.0
I've tested this and it works, running Python 3.9.0 without issue.
There are lots of ways to build Jupyter images, this is just one method. Check out docker hub for Jupyter to see their variants.
I'm experiencing differences with the contents of a container depending on whether I open a bash shell via docker run -i -t <container> bash or docker-compose run <container> bash and I don't know/understand how this is possible.
To aid in the explanation, please see this screenshot from my terminal. In both instances, I am running the image called blaze which has been built from the Dockerfile in my code. One of the steps during the build is to create a virutalenv called venv, however when I open a bash shell via docker-compose this virtualenv doesn't seem to exist unlike when I run docker run ....
I am relatively new to setting up my own builds with Docker, but surely if they are both referencing the same image, the output of ls within a bash shell should be the same? I would greatly appreciate any help or guidance to resources that would explain what exactly is going wrong here...
As an additional point, running docker images shows that both commands must be using the same image...
Thanks in advance!
This is my Dockerfile:
FROM blaze-base-image:latest
# add an URL that PIP automatically searches (e.g., Azure Artifact Store URL)
ARG INDEX_URL
ENV PIP_EXTRA_INDEX_URL=$INDEX_URL
# Copy source code to docker image
RUN mkdir /opt/app
COPY . /opt/app
RUN ls /opt/app
# Install Blaze pip dependencies
WORKDIR /opt/app
RUN python3.7 -m venv /opt/app/venv
RUN /opt/app/venv/bin/python -m pip install --upgrade pip
RUN /opt/app/venv/bin/python -m pip install keyring artifacts-keyring
RUN touch /opt/app/venv/pip.conf
RUN echo $'[global]\nextra-index-url=https://www.index.com' > /opt/app/venv/pip.conf
RUN /opt/app/venv/bin/python -m pip install -r /opt/app/requirements.txt
RUN /opt/app/venv/bin/python -m spacy download en_core_web_sm
# Comment
CMD ["echo", "Container build complete"]
And this is my docker-compose.yml:
version: '3'
services:
blaze:
build: .
image: blaze
volumes:
- .:/opt/app
There are two intersecting things going on here:
When you have a Compose volumes: or docker run -v option mounting host content over a container directory, the host content completely replaces what's in the image. If you don't have a ./venv directory on the host, then there won't be a /opt/app/venv directory in the container. That's why, when you docker-compose run blaze ..., the virtual environment is missing.
If you docker run a container, the only options that are considered are those in that specific docker run command. docker run doesn't know about the docker-compose.yml file and won't take options from there. That means there isn't this volume mount in the docker run case, which is why the virtual environment reappears.
Typically in Docker you don't need a virtual environment at all: the Docker image is isolated from other images and Python installations, and so it's safe and normal to install your application into the "system" Python. You also typically want your image to be self-contained and not depend on content from the host, so you wouldn't generally need the bind mount you show.
That would simplify your Dockerfile to:
FROM blaze-base-image:latest
# Any ARG will automatically appear as an environment variable to
# RUN directives; this won't be needed at run time
ARG PIP_EXTRA_INDEX_URL
# Creates the directory if it doesn't exist
WORKDIR /opt/app
# Install the Python-level dependencies
RUN pip install --upgrade pip
COPY requirements.txt .
RUN pip install -r requirements.txt
# The requirements.txt file should list every required package
# Install the rest of the application
COPY . .
# Set the main container command to run the application
CMD ["./app.py"]
The docker-compose.yml file can be similarly simplified to
version: '3.8' # '3' means '3.0'
services:
blaze:
build: .
# Compose picks its own image name
# Do not need volumes:, the image is self-contained
and then it will work consistently with either docker run or docker-compose run (or docker-compose up).
I am trying to follow the Flask/React tutorial here, on a plain Windows machine.
On Windows 10, without considering Docker, I have the tutorial working.
On Windows 10 under a docker system (ubuntu-based containers and docker-compose), I do not:
The React server works under the docker.
The Flask server won't successfully build.
The Dockerfile for the Flask server is:
FROM ubuntu:18.04
RUN apt-get update && apt-get install -y software-properties-common
RUN add-apt-repository universe
RUN apt-get update && apt-get install -y python3-pip yarn
RUN pip3 install flask
#RUN pip3 install venv
RUN mkdir -p /app
WORKDIR /app
COPY . /app
#RUN python3 -m venv venv
RUN cd api/venv/Scripts
RUN flask run --no-debugger
This fails at the very last line:
The command '/bin/sh -c flask run --no-debugger' returned a non-zero code: 1
Note that I find myself in the unenviable position of trying to use/teach myself all of Docker, venv, react, and flask at the same time. The venv commands are commented out because I'm not even sure venv makes sense in a docker (but what would I know?) and also because the pip3 install venv command halts with a non-zero code:2.
Any advice is welcome.
There are two obvious issues in the Dockerfile you show.
Each RUN command runs in a clean environment starting from the last known state of the image. Settings like the current directory (and also environment variable values) are not preserved when a RUN command exits. So RUN cd ... starts the RUN command from the old directory, changes to the new directory, and then doesn't remember that; the following RUN command starts again from the old directory. You need the WORKDIR directive to actually change directories.
The RUN commands also run during the build phase. They won't publish network ports or have access to databases; in a multi-container Compose setup they can't connect to other containers. You probably want to run the Flask app as the main container CMD.
So you can update your Dockerfile to look like:
FROM ubuntu:18.04
RUN apt-get update && apt-get install -y software-properties-common
RUN add-apt-repository universe
RUN apt-get update && apt-get install -y python3-pip yarn
WORKDIR /app # Creates the directory as well
COPY requirements.txt ./ # Includes "flask"
RUN pip install -r requirements.txt
COPY . ./
WORKDIR /app/api/venv/Scripts # Not `RUN cd ...`
CMD flask run --no-debugger # Not `RUN ...`
It is in fact common to just not use a virtual environment in Docker; the Docker image is isolated from any other Python installation and so it's safe to use the "system" Python package tree. (I am a little suspicious of the venv directory in there, since virtual environments can't be transplanted into other setups very well.)
Note that I find myself in the unenviable position of trying to use/teach myself all of Docker, venv, react, and flask at the same time.
Put Docker away for another day. It's not necessary, especially during the development phase of your application. If you read through SO questions there are a lot of questions trying to contort Docker into acting just like a local development environment, where it's really not designed for it. There's nothing wrong with locally installing the tools you need to do your job, especially when they're very routine tools like Python and Node.
I believe that flask can't find your app when you run your docker (especially as the docker build attempts to run it). If you want to use the docker only for the purpose of running your app through that docker, use CMD in the dockerfile, thus when running the docker image, it will start your flask app first thing.
I've created a docker image which runs a python script and outputs a csv file. I can "SSH" into the container and see that the csv file is there, but I want this csv file to go onto my host machine. How can I do that? I tried using this link but it does not work, the file simply never appears: Save a file generated by app running on docker to a given path in the host machine
Am I missing something? This is my dockerfile:
FROM python:3
WORKDIR /usr/src/app
COPY . /usr/src/app
RUN apt-get update && apt-get install -y vim
RUN pip install python-geoip-python3
RUN pip install pyyaml ua-parser user-agents
RUN python logParse.py
And I am running this command on my image named "parser":
docker run -d -v /Users/dppham/Desktop/logParser:/usr/src/app parser
The csv file should be in /Users/dppham/Desktop/logParser, right?
I have some files which I want to move them to a docker container.
But at the end docker can't find a file..
The folder with the files on local machine are at /home/katalonne/flask4
File Structure if it matters:
The Dockerfile:
#
# First Flask App Dockerfile
#
#
# Pull base image.
FROM centos:7.0.1406
# Build commands
RUN yum install -y python-setuptools mysql-connector mysql-devel gcc python-devel
RUN easy_install pip
RUN mkdir /opt/flask4
WORKDIR /opt/flask4
ADD requirements.txt /opt/flask4
RUN pip install -r requirements.txt
ADD . /opt/flask4
# Define deafult command.
CMD ["python","hello.py"]
# Expose ports.
EXPOSE 5000
So I built the image with this command :
docker build -t flask4 .
I ran the container with volume by :
docker run -d -p 5000:5000 -v /home/Katalonne/flask4:/opt/flask4 --name web flask4
And when I want to run the file on the container :
docker logs -f web
I get this error that it can not find my hello.py file :
python: can't open file 'hello.py': [Errno 2] No such file or directory
What is my fault?
P.S. : I'm a Docker and Linux partially-noob.
The files and directories that are located in the same location as your Dockerfile are indeed available (temporarily) to your docker build. But, after the docker build, unless you have used ADD or COPY to move those files permanently to the docker container, they will not be available to your docker container after the build is done. This file context is for the build, but you want to move them to the container.
You can add the following command:
...
ADD . /opt/flask4
ADD . .
# Define deafult command.
CMD ["python","hello.py"]
The line ADD . . should copy over all the things in your temporary build context to the container. The location that these files will go to is where your WORKDIR is pointing to (/opt/flask4).
If you only wanted to add hello.py to your container, then use
ADD hello.py hello.py
So, when you run CMD ["python","hello.py"], the pwd that you will be in is /opt/flask4, and hello.py should be in there, and running the command python hello.py in that directory should work.
HTH.