docker-introduction | Reproducible Computational Environments using Containers | Continuous Deployment library
kandi X-RAY | docker-introduction Summary
kandi X-RAY | docker-introduction Summary
docker-introduction is a Python library typically used in Devops, Continuous Deployment, Docker applications. docker-introduction has no bugs, it has no vulnerabilities and it has low support. However docker-introduction build file is not available and it has a Non-SPDX License. You can download it from GitHub.
Reproducible Computational Environments using Containers
Reproducible Computational Environments using Containers
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Quality
Security
License
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docker-introduction has a low active ecosystem.
It has 34 star(s) with 40 fork(s). There are 11 watchers for this library.
It had no major release in the last 6 months.
There are 31 open issues and 71 have been closed. On average issues are closed in 100 days. There are 5 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of docker-introduction is v9.5.3
Quality
docker-introduction has no bugs reported.
Security
docker-introduction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
docker-introduction has a Non-SPDX License.
Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.
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docker-introduction releases are not available. You will need to build from source code and install.
docker-introduction has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed docker-introduction and discovered the below as its top functions. This is intended to give you an instant insight into docker-introduction implemented functionality, and help decide if they suit your requirements.
- Check if the file is met
- Check if two categories are the same
- Split a metadata section into metadata and text
- Check for blank lines
- Read references from ref_path
- Require a condition
- Add a message
- Check configuration files
- Load a yaml file
- Checks the value of a field
- Return the URL for a git repository
- Determine if node matches pattern
- Check for missing labels
- Get the labels for a repository
- Read all markdown files
- Parse a Markdown file
- Pretty print the messages
- Check if condition is met
- Performs validation
- Create a checker instance
- Check metadata
- Check for missing files
- Check for source rmd files
- Parse command line arguments
- Check the files in source_dir
- Check the metadata
Get all kandi verified functions for this library.
docker-introduction Key Features
No Key Features are available at this moment for docker-introduction.
docker-introduction Examples and Code Snippets
No Code Snippets are available at this moment for docker-introduction.
Community Discussions
Trending Discussions on docker-introduction
QUESTION
Kafka: Docker container and NoBrokersAvailable error
Asked 2018-Jan-15 at 05:01
I run Kafka using:
...ANSWER
Answered 2018-Jan-15 at 05:01Instead of localhost, you have to provide the docker container IP in which Kafka server is running.
Like
producer = KafkaProducer(bootstrap_servers=':9092', value_serializer=lambda v: json.dumps(v).encode('utf-8'))
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install docker-introduction
You can download it from GitHub.
You can use docker-introduction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use docker-introduction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
We welcome all contributions to improve the lesson! Maintainers will do their best to help you if you have any questions, concerns, or experience any difficulties along the way. We'd like to ask you to familiarize yourself with our Contribution Guide and have a look at the more detailed guidelines on proper formatting, ways to render the lesson locally, and even how to write new episodes. Please see the current list of issues for ideas for contributing to this repository. For making your contribution, we use the GitHub flow, which is nicely explained in the chapter Contributing to a Project in Pro Git by Scott Chacon. Look for the tag . This indicates that the mantainers will welcome a pull request fixing this issue.
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