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Fix spelling mistakes
Signed-off-by: Christopher Hakkaart <[email protected]>
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docs/config.md

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}
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```
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The above configuration snippet sets 2 cpus for every process labeled as `hello` and 4 cpus to every process *not* label as `hello`. It also specifies the `long` queue for every process whose name does *not* start with `align`.
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The above configuration snippet sets 2 cpus for every process labeled as `hello` and 4 cpus to every process *not* labeled as `hello`. It also specifies the `long` queue for every process whose name does *not* start with `align`.
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(config-selector-priority)=
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}
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workflow.onError = {
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println "Error: something when wrong"
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println "Error: something went wrong"
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}
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```
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docs/container.md

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### Images
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Apptainer makes use of a container image file, which physically contains the container. Refer to the [Apptainer documentation](https://apptainer.org/docs) to learn how create Apptainer images.
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Apptainer makes use of a container image file, which physically contains the container. Refer to the [Apptainer documentation](https://apptainer.org/docs) to learn how to create Apptainer images.
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Apptainer allows paths that do not currently exist within the container to be created and mounted dynamically by specifying them on the command line. However this feature is only supported on hosts that support the [Overlay file system](https://en.wikipedia.org/wiki/OverlayFS) and is not enabled by default.
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nextflow run <your script> -with-apptainer [apptainer image file]
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```
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Every time your script launches a process execution, Nextflow will run it into a Apptainer container created by using the specified image. In practice Nextflow will automatically wrap your processes and launch them by running the `apptainer exec` command with the image you have provided.
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Every time your script launches a process execution, Nextflow will run it into an Apptainer container created by using the specified image. In practice Nextflow will automatically wrap your processes and launch them by running the `apptainer exec` command with the image you have provided.
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:::{note}
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A Apptainer image can contain any tool or piece of software you may need to carry out a process execution. Moreover, the container is run in such a way that the process result files are created in the host file system, thus it behaves in a completely transparent manner without requiring extra steps or affecting the flow in your pipeline.
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An Apptainer image can contain any tool or piece of software you may need to carry out a process execution. Moreover, the container is run in such a way that the process result files are created in the host file system, thus it behaves in a completely transparent manner without requiring extra steps or affecting the flow in your pipeline.
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:::
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If you want to avoid entering the Apptainer image as a command line parameter, you can define it in the Nextflow configuration file. For example you can add the following lines in the configuration file:
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Nextflow uses the library directory to determine the location of Apptainer containers. The library directory can be defined using the `apptainer.libraryDir` configuration setting or the `NXF_APPTAINER_LIBRARYDIR` environment variable. The configuration file option overrides the environment variable if both are set.
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Nextflow first checks the library directory when searching for the image. If the image is not found it then checks the cache directory. The main difference between the library directory and the cache directory is that the first is assumed to be a read-only container repository, while the latter is expected to be writable path where container images can added for caching purposes.
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Nextflow first checks the library directory when searching for the image. If the image is not found it then checks the cache directory. The main difference between the library directory and the cache directory is that the first is assumed to be a read-only container repository, while the latter is expected to be writable path where container images can be added for caching purposes.
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:::{warning}
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When using a compute cluster, the Apptainer cache directory must reside in a shared filesystem accessible to all compute nodes.
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Read the {ref}`config-page` page to learn more about the configuration file and how to use it to configure your pipeline execution.
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:::{note}
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Unlike Docker, Nextflow does not automatically mount host paths in the container when using Singularity. It expects that the paths are configure and mounted system wide by the Singularity runtime. If your Singularity installation allows user defined bind points, read the {ref}`Singularity configuration <config-singularity>` section to learn how to enable Nextflow auto mounts.
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Unlike Docker, Nextflow does not automatically mount host paths in the container when using Singularity. It expects that the paths are configured and mounted system wide by the Singularity runtime. If your Singularity installation allows user defined bind points, read the {ref}`Singularity configuration <config-singularity>` section to learn how to enable Nextflow auto mounts.
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:::
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:::{warning}
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Nextflow uses the library directory to determine the location of Singularity images. The library directory can be defined using the `singularity.libraryDir` configuration setting or the `NXF_SINGULARITY_LIBRARYDIR` environment variable. The configuration file option overrides the environment variable if both are set.
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Nextflow first checks the library directory when searching for the image. If the image is not found it then checks the cache directory. The main difference between the library directory and the cache directory is that the first is assumed to be a read-only container repository, while the latter is expected to be writable path where container images can added for caching purposes.
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Nextflow first checks the library directory when searching for the image. If the image is not found it then checks the cache directory. The main difference between the library directory and the cache directory is that the first is assumed to be a read-only container repository, while the latter is expected to be writable path where container images can be added for caching purposes.
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:::{warning}
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When using a compute cluster, the Singularity cache directory must reside in a shared filesystem accessible to all compute nodes.

docs/developer-env.md

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- {ref}`devenv-vscode`: A versatile code editor that enhances your Nextflow development with features like syntax highlighting and debugging.
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- {ref}`devenv-extensions`: The VS Code marketplace offers a variety of extensions to enhance development. The {ref}`Nextflow extension <devenv-nextflow>` is specifically designed to enhance Nextflow development with diagnostics, hover hints, code navigation, code completion, and more.
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- {ref}`devenv-docker`: A containerization platform that ensures your Nextflow workflows run consistently across different environments by packaging dependencies into isolated containers.
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- {ref}`devenv-git`: A version control system that helps manage and track changes in your Nextflow projects, making collaboration, and code management more efficient.
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- {ref}`devenv-git`: A version control system that helps manage and track changes in your Nextflow projects, making collaboration and code management more efficient.
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The sections below outline the steps for setting up these tools.
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1. Visit the [VS Code](https://code.visualstudio.com/download) website.
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1. Double-click the installer executable (`.exe`) file and follow the set up steps.
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1. Double-click the installer executable (`.exe`) file and follow the setup steps.
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```
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Git provides powerful version control that helps track code changes. Git operates locally, meaning you don't need an internet connection to track changes, but it can also be used with remote platforms like GitHub, GitLab, or Bitbucket for collaborative development.
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Nextflow seamlessly integrates with Git for source code management providers for managing pipelines as version-controlled Git repositories.
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Nextflow seamlessly integrates with Git for source code management providers to manage pipelines as version-controlled Git repositories.
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````{tabs}
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docs/executor.md

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To enable this executor, set `process.executor = 'awsbatch'` in the `nextflow.config` file.
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The pipeline can be launched either in a local computer, or an EC2 instance. EC2 is suggested for heavy or long-running workloads. Additionally, an S3 bucket must be used as the pipeline work directory.
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The pipeline can be launched either on a local computer, or an EC2 instance. EC2 is suggested for heavy or long-running workloads. Additionally, an S3 bucket must be used as the pipeline work directory.
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Resource requests and other job characteristics can be controlled via the following process directives:
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To enable this executor, set `process.executor = 'azurebatch'` in the `nextflow.config` file.
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The pipeline can be launched either in a local computer, or a cloud virtual machine. The cloud VM is suggested for heavy or long-running workloads. Additionally, an Azure Blob storage container must be used as the pipeline work directory.
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The pipeline can be launched either on a local computer, or a cloud virtual machine. The cloud VM is suggested for heavy or long-running workloads. Additionally, an Azure Blob storage container must be used as the pipeline work directory.
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[Google Cloud Batch](https://cloud.google.com/batch) is a managed computing service that allows the execution of containerized workloads in the Google Cloud Platform infrastructure.
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Nextflow provides built-in support for the Cloud Batch API, which allows the seamless deployment of a Nextflow pipeline in the cloud, offloading the process executions as pipelines.
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Nextflow provides built-in support for the Cloud Batch API, which allows the seamless deployment of Nextflow pipelines in the cloud, offloading the pipeline process executions.
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The `nsqii` executor allows you to run your pipeline script using the [NQSII](https://www.rz.uni-kiel.de/en/our-portfolio/hiperf/nec-linux-cluster) resource manager.
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The `nqsii` executor allows you to run your pipeline script using the [NQSII](https://www.rz.uni-kiel.de/en/our-portfolio/hiperf/nec-linux-cluster) resource manager.
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Nextflow manages each process as a separate job that is submitted to the cluster using the `qsub` command provided by the scheduler.
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docs/git.md

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## Git configuration
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The file `$HOME/.nextflow/scm` allows you to centralise the security credentials required to access private project repositories on Bitbucket, GitHub and GitLab source code management (SCM) platforms or to manage the configuration properties of private server installations (of the same platforms).
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The file `$HOME/.nextflow/scm` allows you to centralize the security credentials required to access private project repositories on Bitbucket, GitHub and GitLab source code management (SCM) platforms or to manage the configuration properties of private server installations (of the same platforms).
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The configuration properties for each Git provider are defined inside the `providers` section. Properties for the same provider are grouped with a common name and delimited with curly brackets. For example:
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To access your local BitBucket Server create an entry in the [SCM configuration file](#git-configuration) specifying as shown below:
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To access your local BitBucket Server create an entry in the [SCM configuration file](#git-configuration) as shown below:
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```groovy
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Nextflow has built-in support for [Azure Repos](https://azure.microsoft.com/en-us/services/devops/repos/), a Git source code management service hosted in the Azure cloud. To access your Azure Repos with Nextflow provide the repository credentials using the configuration snippet shown below:
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In the above example replace `my-repo` with your own repository. Note also that AWS CodeCommit has different URLs depending on the region in which you are working.
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