I would like to find out the missing dll needed for my exe file that is stored in the container. Found out https://stefanscherer.github.io/find-dependencies-in-windows-containers/ method but it requires installation of virtual machine. Is it possible to install dependency walker into the container using docker file to find the missing dll? I am using windowservercore as base image.
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I was wondering If any one could help me to understand the difference of python virtual environment and docker container.
So I would like to have environment for each tools isolating from each other to avoid dependency conflict for example: use of different version of same dependency causing error in one of the tool because one tool need older version and other one requires newer version.
I’m tested out python venv but not sure if it’s the right one I should use for the issue I just explained or docker is something I should be using for my situation?.
Particularly for day-to-day development, prefer a virtual environment if it's practical.
Virtual environment
Docker
Works with native tools; can just run python myscript.py
Requires Docker-specific setup
Every IDE and editor works fine with it
Requires Docker-specific IDE support
Can just open() data files with no special setup
Can't access data files without Docker-specific mount setup
Immediately re-run code after editing it
Re docker build image or use Docker-specific mount setup
Uses Python installation from host
Use any single specific version of Python
Isolated Python library tree
Isolated Python library tree
Uses host version of C library dependencies
Isolated C library dependencies
A virtual environment acts like a normal Python installation in an alternate path. You don't need to do special things to make your local code or data files available; you can just run your script directly or via your IDE. The one downside is that you're limited to what your host OS's package manager makes available for Python versions and C library dependencies.
A Docker container contains the filesystem of a complete OS, including a completely isolated Python installation. It can be a good match if you need a very specific version of Python or if you need host OS dependencies that are tricky to install. It can also be a good match if you're looking for a production-oriented deployment setup that doesn't specifically depend on installing things on to the target system. But, Docker by design makes it hard to access your host files; it is not a great match for a live development environment or especially for one-off scripts that read and write host files.
The other consideration here is, if you use the standard Python packaging tools, it's straightforward to run your program in a virtual environment, and converting that to a Docker image is almost boilerplate. Starting from Docker can make it tricky to go back the other way, and I see some setups around SO that can only be run via Docker; if they were restructured to use a standard setup.cfg/requirements.txt installation setup they would not require Docker but could still be used with it.
GitHub recently released a container registry alongside their package registry. What is the difference? When would it be better to use one or the other? Do we need both?
Packages are generally simple: they are essentially an archive (i.e. zip file) that contains contents (code libraries, application executables, etc.) and a manifest file (json document, xml file, etc) that describes those contents with a package name and version number (at a minimum).
ie:- npm,pip and composer packages.
Container images are also simple, but they're more like an archive (i.e. a zip file) than a package.
ie:- nginx, redis etc
Verdict:- if some libs repetitively used in any project then we can create package and use in project .while for all project based dependencies we need to choose container to run this. Yes we need both.
After debating this with a Docker-using friend for a while I think I've found a satisfactory explanation:
Packages are for modules of code which are compiled together into an
Application.
Containers are for Applications which are compiled together into a
Server.
This is a bit confused by the fact that a Package can contain a standalone Applications, and Containers will often use package managers like Apt to install these applications. I feel like this is an abuse of package management due to a legacy where we didn't have Containers. Eventually I would expect most Applications will be delivered in Container form.
I am trying to package an Electron app that relies on several Docker containers into a single executable. I would like to be able to convert Dockerfile's into executables runnable on Windows. Is this possible? Can I pull this off without having Docker installed on the client machine? How can I do this?
It is not possible.
Take into account, that docker images are packaged for certain architecture. Kernel must be compatible. And sure, you need docker engine to work on client machine. I think windows is not ready for this.
BRs
I'm trying to use Eclipse Che as an IDE to develop a C++ application on a remote linux machine.
Che can access the source code on the host system because of the
-v <LOCAL_PATH>:/data
part when running the docker container.
But how am I supposed to access include directories (and later libraries to link with)?
Have you tried doing this on Kubernetes? In that case, you are not just exporting the source code volume, the remote Linux machine is your workspace.
I'm afraid I'm not sure how you would do this with Che in Docker without jumping through some hoops.
I have Python 2.7 installed in "C:\Python27". Now I run 1st demo of Python4delphi with D7, which somehow uses my Py2.7 install folder. If I rename Python folder, demo can't run (without error message). I didn't change properties of a demo form.
What part/file does py4delphi use from my Python folder?
python4delphi is a loose wrapper around the Python API and as such relies on a functioning Python installation. Typically on Windows this comprises at least the following:
The main Python directory. On your system this is C:\Python27.
The Python DLL which is python27.dll and lives in your system directory.
Registry settings that indicate where your Python directory is installed.
When you rename the Python directory, the registry settings refer to a location that no longer exists. And so the failure you observe is entirely to be expected.
Perhaps you are trying to work out how to deploy your application in a self-contained way without requiring an external dependency on a Python installation. If so, then I suggest you look in to one of the portable Python distributions. You may need to adapt python4delphi a little to find the Python DLL which will be located under your application's directory. But that should be all that's needed. Take care of the licensing issues too if you do distribute Python with your application.