  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="docs/images/nfcore-tools_logo_dark.png">

  </picture>

[![Python tests](https://github.com/nf-core/tools/workflows/Python%20tests/badge.svg?branch=master&event=push)](https://github.com/nf-core/tools/actions?query=workflow%3A%22Python+tests%22+branch%3Amaster)
[![codecov](https://codecov.io/gh/nf-core/tools/branch/master/graph/badge.svg)](https://codecov.io/gh/nf-core/tools)
[![code style: prettier](https://img.shields.io/badge/code%20style-prettier-ff69b4.svg)](https://github.com/prettier/prettier)
[![code style: Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v1.json)](https://github.com/charliermarsh/ruff)

[![install with Bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg)](https://bioconda.github.io/recipes/nf-core/README.html)
[![install with PyPI](https://img.shields.io/badge/install%20with-PyPI-blue.svg)](https://pypi.org/project/nf-core/)
[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23tools-4A154B?logo=slack)](https://nfcore.slack.com/channels/tools)

A python package with helper tools for the nf-core community.

> **Read this documentation on the nf-core website: [https://nf-co.re/tools](https://nf-co.re/tools)**

## Table of contents

- [`nf-core` tools installation](#installation)
- [`nf-core` tools update](#update-tools)
- [`nf-core list` - List available pipelines](#listing-pipelines)
- [`nf-core launch` - Run a pipeline with interactive parameter prompts](#launch-a-pipeline)
- [`nf-core create-params-file` - Create a parameter file](#create-a-parameter-file)
- [`nf-core download` - Download a pipeline for offline use](#downloading-pipelines-for-offline-use)
- [`nf-core licences` - List software licences in a pipeline](#pipeline-software-licences)
- [`nf-core create` - Create a new pipeline with the nf-core template](#creating-a-new-pipeline)
- [`nf-core lint` - Check pipeline code against nf-core guidelines](#linting-a-workflow)
- [`nf-core schema` - Work with pipeline schema files](#pipeline-schema)
- [`nf-core bump-version` - Update nf-core pipeline version number](#bumping-a-pipeline-version-number)
- [`nf-core sync` - Synchronise pipeline TEMPLATE branches](#sync-a-pipeline-with-the-template)
- [`nf-core create-logo` - Create an nf-core pipeline logo](#create-an-nf-core-pipeline-logo)
- [`nf-core tui` - Explore the nf-core command line graphically](#tools-cli-tui)
- [`nf-core modules` - commands for dealing with DSL2 modules](#modules)

  - [`modules list` - List available modules](#list-modules)
    - [`modules list remote` - List remote modules](#list-remote-modules)
    - [`modules list local` - List installed modules](#list-installed-modules)
  - [`modules info` - Show information about a module](#show-information-about-a-module)
  - [`modules install` - Install modules in a pipeline](#install-modules-in-a-pipeline)
  - [`modules update` - Update modules in a pipeline](#update-modules-in-a-pipeline)
  - [`modules remove` - Remove a module from a pipeline](#remove-a-module-from-a-pipeline)
  - [`modules patch` - Create a patch file for a module](#create-a-patch-file-for-a-module)
  - [`modules create` - Create a module from the template](#create-a-new-module)
  - [`modules lint` - Check a module against nf-core guidelines](#check-a-module-against-nf-core-guidelines)
  - [`modules test` - Run the tests for a module](#run-the-tests-for-a-module-using-pytest)
  - [`modules bump-versions` - Bump software versions of modules](#bump-bioconda-and-container-versions-of-modules-in)

- [`nf-core subworkflows` - commands for dealing with subworkflows](#subworkflows)
  - [`subworkflows list` - List available subworkflows](#list-subworkflows)
    - [`subworkflows list remote` - List remote subworkflows](#list-remote-subworkflows)
    - [`subworkflows list local` - List installed subworkflows](#list-installed-subworkflows)
  - [`subworkflows info` - Show information about a subworkflow](#show-information-about-a-subworkflow)
  - [`subworkflows install` - Install subworkflows in a pipeline](#install-subworkflows-in-a-pipeline)
  - [`subworkflows update` - Update subworkflows in a pipeline](#update-subworkflows-in-a-pipeline)
  - [`subworkflows remove` - Remove a subworkflow from a pipeline](#remove-a-subworkflow-from-a-pipeline)
  - [`subworkflows create` - Create a subworkflow from the template](#create-a-new-subworkflow)
  - [`subworkflows lint` - Check a subworkflow against nf-core guidelines](#check-a-subworkflow-against-nf-core-guidelines)
  - [`subworkflows test` - Run the tests for a subworkflow](#run-the-tests-for-a-subworkflow-using-pytest)
- [Citation](#citation)

The nf-core tools package is written in Python and can be imported and used within other packages.
For documentation of the internal Python functions, please refer to the [Tools Python API docs](https://nf-co.re/tools/docs/).

## Installation

### Bioconda

You can install `nf-core/tools` from [bioconda](https://bioconda.github.io/recipes/nf-core/README.html).

First, install conda and configure the channels to use bioconda
(see the [bioconda documentation](https://bioconda.github.io/index.html#usage)).
Then, just run the conda installation command:

```bash
conda install nf-core
```

Alternatively, you can create a new environment with both nf-core/tools and nextflow:

```bash
conda create --name nf-core python=3.12 nf-core nextflow
conda activate nf-core
```

### Python Package Index

`nf-core/tools` can also be installed from [PyPI](https://pypi.python.org/pypi/nf-core/) using pip as follows:

```bash
pip install nf-core
```

### Docker image

There is a docker image that you can use to run `nf-core/tools` that has all of the requirements packaged (including Nextflow) and so should work out of the box. It is called [`nfcore/tools`](https://hub.docker.com/r/nfcore/tools) _**(NB: no hyphen!)**_

You can use this container on the command line as follows:

```bash
docker run -itv `pwd`:`pwd` -w `pwd` -u $(id -u):$(id -g) nfcore/tools
```

- `-i` and `-t` are needed for the interactive cli prompts to work (this tells Docker to use a pseudo-tty with stdin attached)
- The `-v` argument tells Docker to bind your current working directory (`pwd`) to the same path inside the container, so that files created there will be saved to your local file system outside of the container.
- `-w` sets the working directory in the container to this path, so that it's the same as your working directory outside of the container.
- `-u` sets your local user account as the user inside the container, so that any files created have the correct ownership permissions

After the above base command, you can use the regular command line flags that you would use with other types of installation.
For example, to launch the `viralrecon` pipeline:

```bash
docker run -itv `pwd`:`pwd` -w `pwd` -u $(id -u):$(id -g) nfcore/tools launch viralrecon -r 1.1.0
```

If you use `$NXF_SINGULARITY_CACHEDIR` for downloads, you'll also need to make this folder and environment variable available to the continer:

```bash
docker run -itv `pwd`:`pwd` -w `pwd` -u $(id -u):$(id -g) -v $NXF_SINGULARITY_CACHEDIR:$NXF_SINGULARITY_CACHEDIR -e NXF_SINGULARITY_CACHEDIR nfcore/tools launch viralrecon -r 1.1.0
```

#### Docker bash alias

The above base command is a bit of a mouthful to type, to say the least.
To make it easier to use, we highly recommend adding the following bash alias to your `~/.bashrc` file:

```bash
alias nf-core="docker run -itv `pwd`:`pwd` -w `pwd` -u $(id -u):$(id -g) nfcore/tools"
```

Once applied (you may need to reload your shell) you can just use the `nf-core` command instead:

```bash
nf-core list
```

#### Docker versions

You can use docker image tags to specify the version you would like to use. For example, `nfcore/tools:dev` for the latest development version of the code, or `nfcore/tools:1.14` for version `1.14` of tools.
If you omit this, it will default to `:latest`, which should be the latest stable release.

If you need a specific version of Nextflow inside the container, you can build an image yourself.
Clone the repo locally and check out whatever version of nf-core/tools that you need.
Then build using the `--build-arg NXF_VER` flag as follows:

```bash
docker build -t nfcore/tools:dev . --build-arg NXF_VER=20.04.0
```

### Development version

If you would like the latest development version of tools, the command is:

```bash
pip install --upgrade --force-reinstall git+https://github.com/nf-core/tools.git@dev
```

If you intend to make edits to the code, first make a fork of the repository and then clone it locally.
Go to the cloned directory and install with pip (also installs development requirements):

```bash
pip install --upgrade -r requirements-dev.txt -e .
```

### Using a specific Python interpreter

If you prefer, you can also run tools with a specific Python interpreter.
The command line usage and flags are then exactly the same as if you ran with the `nf-core` command.
Note that the module is `nf_core` with an underscore, not a hyphen like the console command.

For example:

```bash
python -m nf_core --help
python3 -m nf_core list
~/my_env/bin/python -m nf_core create --name mypipeline --description "This is a new skeleton pipeline"
```

### Using with your own Python scripts

The tools functionality is written in such a way that you can import it into your own scripts.
For example, if you would like to get a list of all available nf-core pipelines:

```python
import nf_core.list
wfs = nf_core.list.Workflows()
wfs.get_remote_workflows()
for wf in wfs.remote_workflows:
    print(wf.full_name)
```

Please see [https://nf-co.re/tools/docs/](https://nf-co.re/tools/docs/) for the function documentation.

### Automatic version check

nf-core/tools automatically checks the web to see if there is a new version of nf-core/tools available.
If you would prefer to skip this check, set the environment variable `NFCORE_NO_VERSION_CHECK`. For example:

```bash
export NFCORE_NO_VERSION_CHECK=1
```

### Update tools

It is advisable to keep nf-core/tools updated to the most recent version. The command to update depends on the system used to install it, for example if you have installed it with conda you can use:

```bash
conda update nf-core
```

if you used pip:

```bash
pip install --upgrade nf-core
```

Please refer to the respective documentation for further details to manage packages, as for example [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-pkgs.html#updating-packages) or [pip](https://packaging.python.org/en/latest/tutorials/installing-packages/#upgrading-packages).

### Activate shell completions for nf-core/tools

Auto-completion for the `nf-core` command is available for bash, zsh and fish. To activate it, add the following lines to the respective shell config files.

| shell | shell config file                         | command                                            |
| ----- | ----------------------------------------- | -------------------------------------------------- |
| bash  | `~/.bashrc`                               | `eval "$(_NF_CORE_COMPLETE=bash_source nf-core)"`  |
| zsh   | `~/.zshrc`                                | `eval "$(_NF_CORE_COMPLETE=zsh_source nf-core)"`   |
| fish  | `~/.config/fish/completions/nf-core.fish` | `eval (env _NF_CORE_COMPLETE=fish_source nf-core)` |

After a restart of the shell session you should have auto-completion for the `nf-core` command and all its sub-commands and options.

> [!NOTE]
> The added line will run the command `nf-core` (which will also slow down startup time of your shell). You should therefore either have the nf-core/tools installed globally.
> You can also wrap it inside `if type nf-core > /dev/null; then ` \<YOUR EVAL CODE LINE\> `fi` for bash and zsh or `if command -v nf-core &> /dev/null eval (env _NF_CORE_COMPLETE=fish_source nf-core) end` for fish. You need to then source the config in your environment for the completions to be activated.

> [!TIP]
> If you see the error `command not found compdef` , be sure that your config file contains the line `autoload -Uz compinit && compinit` before the eval line.

## Listing pipelines

The command `nf-core list` shows all available nf-core pipelines along with their latest version, when that was published and how recently the pipeline code was pulled to your local system (if at all).

An example of the output from the command is as follows:

![`nf-core list`](docs/images/nf-core-list.svg)

To narrow down the list, supply one or more additional keywords to filter the pipelines based on matches in titles, descriptions and topics:

![`nf-core list rna rna-seq`](docs/images/nf-core-list-rna.svg)

You can sort the results by latest release (`-s release`, default),
when you last pulled a local copy (`-s pulled`),
alphabetically (`-s name`),
or number of GitHub stars (`-s stars`).

![`nf-core list -s stars`](docs/images/nf-core-list-stars.svg)

To return results as JSON output for downstream use, use the `--json` flag.

Archived pipelines are not returned by default. To include them, use the `--show_archived` flag.

## Launch a pipeline

Some nextflow pipelines have a considerable number of command line flags that can be used.
To help with this, you can use the `nf-core launch` command.
You can choose between a web-based graphical interface or an interactive command-line wizard tool to enter the pipeline parameters for your run.
Both interfaces show documentation alongside each parameter and validate your inputs.

The tool uses the `nextflow_schema.json` file from a pipeline to give parameter descriptions, defaults and grouping.
If no file for the pipeline is found, one will be automatically generated at runtime.

Nextflow `params` variables are saved in to a JSON file called `nf-params.json` and used by nextflow with the `-params-file` flag.
This makes it easier to reuse these in the future.

The command takes one argument - either the name of an nf-core pipeline which will be pulled automatically,
or the path to a directory containing a Nextflow pipeline _(can be any pipeline, doesn't have to be nf-core)_.

![`nf-core launch rnaseq -r 3.8.1`](docs/images/nf-core-launch-rnaseq.svg)

Once complete, the wizard will ask you if you want to launch the Nextflow run.
If not, you can copy and paste the Nextflow command with the `nf-params.json` file of your inputs.

```console
INFO     [✓] Input parameters look valid
INFO     Nextflow command:
         nextflow run nf-core/rnaseq -params-file "nf-params.json"

Do you want to run this command now?  [y/n]:
```

### Launch tool options

- `-r`, `--revision`
  - Specify a pipeline release (or branch / git commit sha) of the project to run
- `-i`, `--id`
  - You can use the web GUI for nf-core pipelines by clicking _"Launch"_ on the website. Once filled in you will be given an ID to use with this command which is used to retrieve your inputs.
- `-c`, `--command-only`
  - If you prefer not to save your inputs in a JSON file and use `-params-file`, this option will specify all entered params directly in the nextflow command.
- `-p`, `--params-in PATH`
  - To use values entered in a previous pipeline run, you can supply the `nf-params.json` file previously generated.
  - This will overwrite the pipeline schema defaults before the wizard is launched.
- `-o`, `--params-out PATH`
  - Path to save parameters JSON file to. (Default: `nf-params.json`)
- `-a`, `--save-all`
  - Without this option the pipeline will ignore any values that match the pipeline schema defaults.
  - This option saves _all_ parameters found to the JSON file.
- `-h`, `--show-hidden`
  - A pipeline JSON schema can define some parameters as 'hidden' if they are rarely used or for internal pipeline use only.
  - This option forces the wizard to show all parameters, including those labelled as 'hidden'.
- `--url`
  - Change the URL used for the graphical interface, useful for development work on the website.

## Create a parameter file

Sometimes it is easier to manually edit a parameter file than to use the web interface or interactive commandline wizard
provided by `nf-core launch`, for example when running a pipeline with many options on a remote server without a graphical interface.

You can create a parameter file with all parameters of a pipeline with the `nf-core create-params-file` command.
This file can then be passed to `nextflow` with the `-params-file` flag.

This command takes one argument - either the name of a nf-core pipeline which will be pulled automatically,
or the path to a directory containing a Nextflow pipeline _(can be any pipeline, doesn't have to be nf-core)_.

The generated YAML file contains all parameters set to the pipeline default value along with their description in comments.
This template can then be used by uncommenting and modifying the value of parameters you want to pass to a pipline run.

Hidden options are not included by default, but can be included using the `-x`/`--show-hidden` flag.

## Downloading pipelines for offline use

Sometimes you may need to run an nf-core pipeline on a server or HPC system that has no internet connection.
In this case you will need to fetch the pipeline files first, then manually transfer them to your system.

To make this process easier and ensure accurate retrieval of correctly versioned code and software containers, we have written a download helper tool.

The `nf-core download` command will download both the pipeline code and the [institutional nf-core/configs](https://github.com/nf-core/configs) files. It can also optionally download any singularity image files that are required.

If run without any arguments, the download tool will interactively prompt you for the required information.
Each option has a flag, if all are supplied then it will run without any user input needed.

![`nf-core download rnaseq -r 3.8 --outdir nf-core-rnaseq -x none -s none -d`](docs/images/nf-core-download.svg)

Once downloaded, you will see something like the following file structure for the downloaded pipeline:

![`tree -L 2 nf-core-rnaseq/`](docs/images/nf-core-download-tree.svg)

You can run the pipeline by simply providing the directory path for the `workflow` folder to your `nextflow run` command:

```bash
nextflow run /path/to/download/nf-core-rnaseq-dev/workflow/ --input mydata.csv --outdir results  # usual parameters here
```

> [!NOTE]
> If you downloaded Singularity container images, you will need to use `-profile singularity` or have it enabled in your config file.

### Downloaded nf-core configs

The pipeline files are automatically updated (`params.custom_config_base` is set to `../configs`), so that the local copy of institutional configs are available when running the pipeline.
So using `-profile <NAME>` should work if available within [nf-core/configs](https://github.com/nf-core/configs).

> [!WARNING]
> This option is not available when downloading a pipeline for use with [Seqera Platform](#adapting-downloads-to-seqera-platform) because the application manages all configurations separately.

### Downloading Apptainer containers

If you're using [Singularity](https://apptainer.org) (Apptainer), the `nf-core download` command can also fetch the required container images for you.
To do this, select `singularity` in the prompt or specify `--container-system singularity` in the command.
Your archive / target output directory will then also include a separate folder `singularity-containers`.

The downloaded workflow files are again edited to add the following line to the end of the pipeline's `nextflow.config` file:

```nextflow
singularity.cacheDir = "${projectDir}/../singularity-images/"
```

This tells Nextflow to use the `singularity-containers` directory relative to the workflow for the singularity image cache directory.
All images should be downloaded there, so Nextflow will use them instead of trying to pull from the internet.

#### Singularity cache directory

We highly recommend setting the `$NXF_SINGULARITY_CACHEDIR` environment variable on your system, even if that is a different system to where you will be running Nextflow.

If found, the tool will fetch the Singularity images to this directory first before copying to the target output archive / directory.
Any images previously fetched will be found there and copied directly - this includes images that may be shared with other pipelines or previous pipeline version downloads or download attempts.

If you are running the download on the same system where you will be running the pipeline (eg. a shared filesystem where Nextflow won't have an internet connection at a later date), you can choose to _only_ use the cache via a prompt or cli options `--container-cache-utilisation amend`. This instructs `nf-core download` to fetch all Singularity images to the `$NXF_SINGULARITY_CACHEDIR` directory but does _not_ copy them to the workflow archive / directory. The workflow config file is _not_ edited. This means that when you later run the workflow, Nextflow will just use the cache folder directly.

If you are downloading a workflow for a different system, you can provide information about the contents of its image cache to `nf-core download`. To avoid unnecessary container image downloads, choose `--container-cache-utilisation remote` and provide a list of already available images as plain text file to `--container-cache-index my_list_of_remotely_available_images.txt`. To generate this list on the remote system, run `find $NXF_SINGULARITY_CACHEDIR -name "*.img" > my_list_of_remotely_available_images.txt`. The tool will then only download and copy images into your output directory, which are missing on the remote system.

#### How the Singularity image downloads work

The Singularity image download finds containers using two methods:

1. It runs `nextflow config` on the downloaded workflow to look for a `process.container` statement for the whole pipeline.
   This is the typical method used for DSL1 pipelines.
2. It scrapes any files it finds with a `.nf` file extension in the workflow `modules` directory for lines
   that look like `container = "xxx"`. This is the typical method for DSL2 pipelines, which have one container per process.

Some DSL2 modules have container addresses for docker (eg. `biocontainers/fastqc:0.11.9--0`) and also URLs for direct downloads of a Singularity container (eg. `https://depot.galaxyproject.org/singularity/fastqc:0.11.9--0`).
Where both are found, the download URL is preferred.

Once a full list of containers is found, they are processed in the following order:

1. If the target image already exists, nothing is done (eg. with `$NXF_SINGULARITY_CACHEDIR` and `--container-cache-utilisation amend` specified)
2. If found in `$NXF_SINGULARITY_CACHEDIR` and `--container-cache-utilisation copy` is specified, they are copied to the output directory
3. If they start with `http` they are downloaded directly within Python (default 4 at a time, you can customise this with `--parallel-downloads`)
4. If they look like a Docker image name, they are fetched using a `singularity pull` command. Choose the container libraries (registries) queried by providing one or multiple `--container-library` parameter(s). For example, if you call `nf-core download` with `-l quay.io -l ghcr.io -l docker.io`, every image will be pulled from `quay.io` unless an error is encountered. Subsequently, `ghcr.io` and then `docker.io` will be queried for any image that has failed before.
   - This requires Singularity/Apptainer to be installed on the system and is substantially slower

Note that compressing many GBs of binary files can be slow, so specifying `--compress none` is recommended when downloading Singularity images that are copied to the output directory.

If the download speeds are much slower than your internet connection is capable of, you can set `--parallel-downloads` to a large number to download loads of images at once.

### Adapting downloads to Seqera Platform

[Seqera Platform](https://seqera.io/platform/) (formerly _"Nextflow Tower"_) provides a graphical user interface to oversee pipeline runs, gather statistics and configure compute resources. While pipelines added to _Seqera Platform_ are preferably hosted at a Git service, providing them as disconnected, self-reliant repositories is also possible for premises with restricted network access. Choosing the `--platform` flag will download the pipeline in an appropriate form.

Subsequently, the `*.git` folder can be moved to it's final destination and linked with a pipeline in _Seqera Platform_ using the `file:/` prefix.

> [!TIP]
> Also without access to Seqera Platform, pipelines downloaded with the `--platform` flag can be run if the _absolute_ path is specified: `nextflow run -r 2.5 file:/path/to/pipelinedownload.git`. Downloads in this format allow you to include multiple revisions of a pipeline in a single file, but require that the revision (e.g. `-r 2.5`) is always explicitly specified.

Facilities and those who are setting up pipelines for others to use may find the `--tag` argument helpful. It allows customizing the downloaded pipeline with additional tags that can be used to select particular revisions in the Seqera Platform interface. For example, an accredited facility may opt to tag particular revisions according to their structured release management process: `--tag "3.12.0=testing" --tag "3.9.0=validated"` so their staff can easily ensure that the correct version of the pipeline is run in production.
The `--tag` argument must be followed by a string in a `key=value` format and can be provided multiple times. The `key` must refer to a valid branch, tag or commit SHA. The right-hand side must comply with the naming conventions for Git tags and may not yet exist in the repository.

## Pipeline software licences

Sometimes it's useful to see the software licences of the tools used in a pipeline.
You can use the `licences` subcommand to fetch and print the software licence from each conda / PyPI package used in an nf-core pipeline.

> [!WARNING]
> This command does not currently work for newer DSL2 pipelines. This will hopefully be addressed [soon](https://github.com/nf-core/tools/issues/1155).

![`nf-core licences deepvariant`](docs/images/nf-core-licences.svg)

## Creating a new pipeline

The `create` subcommand makes a new pipeline using the nf-core base template.
With a given pipeline name, description and author, it makes a starter pipeline which follows nf-core best practices.

After creating the files, the command initialises the folder as a git repository and makes an initial commit.
This first "vanilla" commit which is identical to the output from the templating tool is important, as it allows us to keep your pipeline in sync with the base template in the future.
See the [nf-core syncing docs](https://nf-co.re/developers/sync) for more information.

![` nf-core create -n nextbigthing -d "This pipeline analyses data from the next big omics technique" -a "Big Steve" --plain`](docs/images/nf-core-create.svg)

Once you have run the command, create a new empty repository on GitHub under your username (not the `nf-core` organisation, yet) and push the commits from your computer using the example commands in the above log.
You can then continue to edit, commit and push normally as you build your pipeline.

Please see the [nf-core documentation](https://nf-co.re/developers/adding_pipelines) for a full walkthrough of how to create a new nf-core workflow.

> [!TIP]
> As the log output says, remember to come and discuss your idea for a pipeline as early as possible!
> See the [documentation](https://nf-co.re/developers/adding_pipelines#join-the-community) for instructions.

Note that if the required arguments for `nf-core create` are not given, it will interactively prompt for them. If you prefer, you can supply them as command line arguments. See `nf-core create --help` for more information.

### Customizing the creation of a pipeline

The `nf-core create` command comes with a number of options that allow you to customize the creation of a pipeline if you intend to not publish it as an
nf-core pipeline. This can be done in two ways: by using interactive prompts, or by supplying a `template.yml` file using the `--template-yaml <file>` option.
Both options allow you to specify a custom pipeline prefix to use instead of the common `nf-core`, as well as selecting parts of the template to be excluded during pipeline creation.
The interactive prompts will guide you through the pipeline creation process. An example of a `template.yml` file is shown below.

```yaml
name: coolpipe
description: A cool pipeline
author: me
prefix: myorg
skip:
  - github
  - ci
  - github_badges
  - igenomes
  - nf_core_configs
```

This will create a pipeline called `coolpipe` in the directory `myorg-coolpipe` (`<prefix>-<name>`) with `me` as the author. It will exclude all possible parts of the template:

- `github`: removed all files required for GitHub hosting of the pipeline. Specifically, the `.github` folder and `.gitignore` file.
- `ci`: removes the GitHub continuous integration tests from the pipeline. Specifically, the `.github/workflows/` folder.
- `github_badges`: removes GitHub badges from the `README.md` file.
- `igenomes`: removes pipeline options related to iGenomes. Including the `conf/igenomes.config` file and all references to it.
- `nf_core_configs`: excludes `nf_core/configs` repository options, which make multiple config profiles for various institutional clusters available.

To run the pipeline creation silently (i.e. without any prompts) with the nf-core template, you can use the `--plain` option.

## Linting a workflow

The `lint` subcommand checks a given pipeline for all nf-core community guidelines.
This is the same test that is used on the automated continuous integration tests.

For example, the current version looks something like this:

![`nf-core lint`](docs/images/nf-core-lint.svg)

You can use the `-k` / `--key` flag to run only named tests for faster debugging, eg: `nf-core lint -k files_exist -k files_unchanged`. The `nf-core lint` command lints the current working directory by default, to specify another directory you can use `--dir <directory>`.

### Linting documentation

Each test result name on the left is a terminal hyperlink.
In most terminals you can ctrl + click ( cmd + click) these
links to open documentation specific to this test in your browser.

Alternatively visit <https://nf-co.re/tools/docs/latest/pipeline_lint_tests/index.html> and find your test to read more.

### Linting config

It's sometimes desirable to disable certain lint tests, especially if you're using nf-core/tools with your
own pipeline that is outside of nf-core.

To help with this, you can add a tools config file to your pipeline called `.nf-core.yml` in the pipeline root directory (previously: `.nf-core-lint.yml`).
Here you can list the names of any tests that you would like to disable and set them to `False`, for example:

```yaml
lint:
  actions_awsfulltest: False
  pipeline_todos: False
```

Some lint tests allow greater granularity, for example skipping a test only for a specific file.
This is documented in the test-specific docs but generally involves passing a list, for example:

```yaml
lint:
  files_exist:
    - CODE_OF_CONDUCT.md
  files_unchanged:
    - assets/email_template.html
    - CODE_OF_CONDUCT.md
```

Note that you have to list all configurations for the `nf-core lint` command under the `lint:` field in the `.nf-core.yml` file, as this file is also used for configuration of other commands.

### Automatically fix errors

Some lint tests can try to automatically fix any issues they find. To enable this functionality, use the `--fix` flag.
The pipeline must be a `git` repository with no uncommitted changes for this to work.
This is so that any automated changes can then be reviewed and undone (`git checkout .`) if you disagree.

### Lint results output

The output from `nf-core lint` is designed to be viewed on the command line and is deliberately succinct.
You can view all passed tests with `--show-passed` or generate JSON / markdown results with the `--json` and `--markdown` flags.

## Pipeline schema

nf-core pipelines have a `nextflow_schema.json` file in their root which describes the different parameters used by the workflow.
These files allow automated validation of inputs when running the pipeline, are used to generate command line help and can be used to build interfaces to launch pipelines.
Pipeline schema files are built according to the [JSONSchema specification](https://json-schema.org/) (Draft 7).

To help developers working with pipeline schema, nf-core tools has three `schema` sub-commands:

- `nf-core schema validate`
- `nf-core schema build`
- `nf-core schema docs`
- `nf-core schema lint`

### Validate pipeline parameters

Nextflow can take input parameters in a JSON or YAML file when running a pipeline using the `-params-file` option.
This command validates such a file against the pipeline schema.

Usage is `nf-core schema validate <pipeline> <parameter file>`. eg with the pipeline downloaded [above](#download-pipeline), you can run:

![`nf-core schema validate nf-core-rnaseq/3_8 nf-params.json`](docs/images/nf-core-schema-validate.svg)

The `pipeline` option can be a directory containing a pipeline, a path to a schema file or the name of an nf-core pipeline (which will be downloaded using `nextflow pull`).

### Build a pipeline schema

Manually building JSONSchema documents is not trivial and can be very error prone.
Instead, the `nf-core schema build` command collects your pipeline parameters and gives interactive prompts about any missing or unexpected params.
If no existing schema is found it will create one for you.

Once built, the tool can send the schema to the nf-core website so that you can use a graphical interface to organise and fill in the schema.
The tool checks the status of your schema on the website and once complete, saves your changes locally.

Usage is `nf-core schema build -d <pipeline_directory>`, eg:

![`nf-core schema build --no-prompts`](docs/images/nf-core-schema-build.svg)

There are four flags that you can use with this command:

- `--dir <pipeline_dir>`: Specify a pipeline directory other than the current working directory
- `--no-prompts`: Make changes without prompting for confirmation each time. Does not launch web tool.
- `--web-only`: Skips comparison of the schema against the pipeline parameters and only launches the web tool.
- `--url <web_address>`: Supply a custom URL for the online tool. Useful when testing locally.

### Display the documentation for a pipeline schema

To get an impression about the current pipeline schema you can display the content of the `nextflow_schema.json` with `nf-core schema docs <pipeline-schema>`. This will print the content of your schema in Markdown format to the standard output.

There are four flags that you can use with this command:

- `--output <filename>`: Output filename. Defaults to standard out.
- `--format [markdown|html]`: Format to output docs in.
- `--force`: Overwrite existing files
- `--columns <columns_list>`: CSV list of columns to include in the parameter tables

### Add new parameters to the pipeline schema

If you want to add a parameter to the schema, you first have to add the parameter and its default value to the `nextflow.config` file with the `params` scope. Afterwards, you run the command `nf-core schema build` to add the parameters to your schema and open the graphical interface to easily modify the schema.

The graphical interface is oganzised in groups and within the groups the single parameters are stored. For a better overview you can collapse all groups with the `Collapse groups` button, then your new parameters will be the only remaining one at the bottom of the page. Now you can either create a new group with the `Add group` button or drag and drop the paramters in an existing group. Therefor the group has to be expanded. The group title will be displayed, if you run your pipeline with the `--help` flag and its description apears on the parameter page of your pipeline.

Now you can start to change the parameter itself. The `ID` of a new parameter should be defined in small letters without whitespaces. The description is a short free text explanation about the parameter, that appears if you run your pipeline with the `--help` flag. By clicking on the dictionary icon you can add a longer explanation for the parameter page of your pipeline. Usually, they contain a small paragraph about the parameter settings or a used datasource, like databases or references. If you want to specify some conditions for your parameter, like the file extension, you can use the nut icon to open the settings. This menu depends on the `type` you assigned to your parameter. For integers you can define a min and max value, and for strings the file extension can be specified.

The `type` field is one of the most important points in your pipeline schema, since it defines the datatype of your input and how it will be interpreted. This allows extensive testing prior to starting the pipeline.

The basic datatypes for a pipeline schema are:

- `string`
- `number`
- `integer`
- `boolean`

For the `string` type you have three different options in the settings (nut icon): `enumerated values`, `pattern` and `format`. The first option, `enumerated values`, allows you to specify a list of specific input values. The list has to be separated with a pipe. The `pattern` and `format` settings can depend on each other. The `format` has to be either a directory or a file path. Depending on the `format` setting selected, specifying the `pattern` setting can be the most efficient and time saving option, especially for `file paths`. The `number` and `integer` types share the same settings. Similarly to `string`, there is an `enumerated values` option with the possibility of specifying a `min` and `max` value. For the `boolean` there is no further settings and the default value is usually `false`. The `boolean` value can be switched to `true` by adding the flag to the command. This parameter type is often used to skip specific sections of a pipeline.

After filling the schema, click on the `Finished` button in the top right corner, this will automatically update your `nextflow_schema.json`. If this is not working, the schema can be copied from the graphical interface and pasted in your `nextflow_schema.json` file.

### Update existing pipeline schema

It's important to change the default value of a parameter in the `nextflow.config` file first and then in the pipeline schema, because the value in the config file overwrites the value in the pipeline schema. To change any other parameter use `nf-core schema build --web-only` to open the graphical interface without rebuilding the pipeline schema. Now, the parameters can be changed as mentioned above but keep in mind that changing the parameter datatype depends on the default value specified in the `nextflow.config` file.

### Linting a pipeline schema

The pipeline schema is linted as part of the main pipeline `nf-core lint` command,
however sometimes it can be useful to quickly check the syntax of the JSONSchema without running a full lint run.

Usage is `nf-core schema lint <schema>` (defaulting to `nextflow_schema.json`), eg:

![`nf-core schema lint`](docs/images/nf-core-schema-lint.svg)

## Bumping a pipeline version number

When releasing a new version of a nf-core pipeline, version numbers have to be updated in several different places. The helper command `nf-core bump-version` automates this for you to avoid manual errors (and frustration!).

The command uses results from the linting process, so will only work with workflows that pass these tests.

Usage is `nf-core bump-version <new_version>`, eg:

![`nf-core bump-version 1.1`](docs/images/nf-core-bump-version.svg)

You can change the directory from the current working directory by specifying `--dir <pipeline_dir>`. To change the required version of Nextflow instead of the pipeline version number, use the flag `--nextflow`.

## Sync a pipeline with the template

Over time, the main nf-core pipeline template is updated. To keep all nf-core pipelines up to date,
we synchronise these updates automatically when new versions of nf-core/tools are released.
This is done by maintaining a special `TEMPLATE` branch, containing a vanilla copy of the nf-core template
with only the variables used when it first ran (name, description etc.). This branch is updated and a
pull-request can be made with just the updates from the main template code.

Note that pipeline synchronisation happens automatically each time nf-core/tools is released, creating an automated pull-request on each pipeline.
**As such, you do not normally need to run this command yourself!**

This command takes a pipeline directory and attempts to run this synchronisation.
Usage is `nf-core sync`, eg:

![`nf-core sync`](docs/images/nf-core-sync.svg)

The sync command tries to check out the `TEMPLATE` branch from the `origin` remote or an existing local branch called `TEMPLATE`.
It will fail if it cannot do either of these things.
The `nf-core create` command should make this template automatically when you first start your pipeline.
Please see the [nf-core website sync documentation](https://nf-co.re/developers/sync) if you have difficulties.

To specify a directory to sync other than the current working directory, use the `--dir <pipline_dir>`.

By default, the tool will collect workflow variables from the current branch in your pipeline directory.
You can supply the `--from-branch` flag to specific a different branch.

Finally, if you give the `--pull-request` flag, the command will push any changes to the remote and attempt to create a pull request using the GitHub API.
The GitHub username and repository name will be fetched from the remote url (see `git remote -v | grep origin`), or can be supplied with `--username` and `--github-repository`.

To create the pull request, a personal access token is required for API authentication.
These can be created at [https://github.com/settings/tokens](https://github.com/settings/tokens).
Supply this using the `--auth-token` flag.

## Create an nf-core pipeline logo

The `nf-core create-logo` command creates a logo for your pipeline based on the nf-core template and the pipeline name. You can specify the width of the logo in pixels with the `--width` flag. Additionally, you can specify the output format to be either `png` or `svg` with the `--format` flag. The default format is `png`.

Usage is `nf-core create-logo <text>`, eg:

![`nf-core create-logo nextbigthing`](docs/images/nf-core-create-logo.svg)

## Tools CLI TUI

_CLI:_ Command line interface
_TUI:_ Terminal user interface

The `nf-core` command line interface is fairly large, with a lot of commands and options.
To make it easier to explore and use, run `nf-core tui` to launch a graphical terminal interface.

This functionality works using [Textualize/trogon](https://github.com/Textualize/trogon)
and is based on the underlying CLI implementation that uses [Click](https://click.palletsprojects.com/).

## Modules

With the advent of [Nextflow DSL2](https://www.nextflow.io/docs/latest/dsl2.html), we are creating a centralised repository of modules.
These are software tool process definitions that can be imported into any pipeline.
This allows multiple pipelines to use the same code for share tools and gives a greater degree of granulairy and unit testing.

The nf-core DSL2 modules repository is at <https://github.com/nf-core/modules>

### Custom remote modules

The modules supercommand comes with two flags for specifying a custom remote:

- `--git-remote <git remote url>`: Specify the repository from which the modules should be fetched as a git URL. Defaults to the github repository of `nf-core/modules`.
- `--branch <branch name>`: Specify the branch from which the modules should be fetched. Defaults to the default branch of your repository.

For example, if you want to install the `fastqc` module from the repository `nf-core/modules-test` hosted at `gitlab.com`, you can use the following command:

```terminal
nf-core modules --git-remote git@gitlab.com:nf-core/modules-test.git install fastqc
```

Note that a custom remote must follow a similar directory structure to that of `nf-core/moduleś` for the `nf-core modules` commands to work properly.

The directory where modules are installed will be prompted or obtained from `org_path` in the `.nf-core.yml` file if available. If your modules are located at `modules/my-folder/TOOL/SUBTOOL` your `.nf-core.yml` should have:

```yaml
org_path: my-folder
```

Please avoid installing the same tools from two different remotes, as this can lead to further errors.

The modules commands will during initalisation try to pull changes from the remote repositories. If you want to disable this, for example
due to performance reason or if you want to run the commands offline, you can use the flag `--no-pull`. Note however that the commands will
still need to clone repositories that have previously not been used.

### Private remote repositories

You can use the modules command with private remote repositories. Make sure that your local `git` is correctly configured with your private remote
and then specify the remote the same way you would do with a public remote repository.

### List modules

The `nf-core modules list` command provides the subcommands `remote` and `local` for listing modules installed in a remote repository and in the local pipeline respectively. Both subcommands allow to use a pattern for filtering the modules by keywords eg: `nf-core modules list <subcommand> <keyword>`.

#### List remote modules

To list all modules available on [nf-core/modules](https://github.com/nf-core/modules), you can use
`nf-core modules list remote`, which will print all available modules to the terminal.

![`nf-core modules list remote`](docs/images/nf-core-modules-list-remote.svg)

#### List installed modules

To list modules installed in a local pipeline directory you can use `nf-core modules list local`. This will list the modules install in the current working directory by default. If you want to specify another directory, use the `--dir <pipeline_dir>` flag.

![`nf-core modules list local`](docs/images/nf-core-modules-list-local.svg)

## Show information about a module

For quick help about how a module works, use `nf-core modules info <tool>`.
This shows documentation about the module on the command line, similar to what's available on the
[nf-core website](https://nf-co.re/modules).

![`nf-core modules info abacas`](docs/images/nf-core-modules-info.svg)

### Install modules in a pipeline

You can install modules from [nf-core/modules](https://github.com/nf-core/modules) in your pipeline using `nf-core modules install`.
A module installed this way will be installed to the `./modules/nf-core/modules` directory.

![`nf-core modules install abacas`](docs/images/nf-core-modules-install.svg)

You can pass the module name as an optional argument to `nf-core modules install` instead of using the cli prompt, eg: `nf-core modules install fastqc`. You can specify a pipeline directory other than the current working directory by using the `--dir <pipeline dir>`.

There are three additional flags that you can use when installing a module:

- `--force`: Overwrite a previously installed version of the module.
- `--prompt`: Select the module version using a cli prompt.
- `--sha <commit_sha>`: Install the module at a specific commit.

### Update modules in a pipeline

You can update modules installed from a remote repository in your pipeline using `nf-core modules update`.

![`nf-core modules update --all --no-preview`](docs/images/nf-core-modules-update.svg)

You can pass the module name as an optional argument to `nf-core modules update` instead of using the cli prompt, eg: `nf-core modules update fastqc`. You can specify a pipeline directory other than the current working directory by using the `--dir <pipeline dir>`.

There are five additional flags that you can use with this command:

- `--force`: Reinstall module even if it appears to be up to date
- `--prompt`: Select the module version using a cli prompt.
- `--sha <commit_sha>`: Install the module at a specific commit from the `nf-core/modules` repository.
- `--preview/--no-preview`: Show the diff between the installed files and the new version before installing.
- `--save-diff <filename>`: Save diffs to a file instead of updating in place. The diffs can then be applied with `git apply <filename>`.
- `--all`: Use this flag to run the command on all modules in the pipeline.

If you don't want to update certain modules or want to update them to specific versions, you can make use of the `.nf-core.yml` configuration file. For example, you can prevent the `star/align` module installed from `nf-core/modules` from being updated by adding the following to the `.nf-core.yml` file:

```yaml
update:
  https://github.com/nf-core/modules.git:
    nf-core:
      star/align: False
```

If you want this module to be updated only to a specific version (or downgraded), you could instead specifiy the version:

```yaml
update:
  https://github.com/nf-core/modules.git:
    nf-core:
      star/align: "e937c7950af70930d1f34bb961403d9d2aa81c7"
```

This also works at the repository level. For example, if you want to exclude all modules installed from `nf-core/modules` from being updated you could add:

```yaml
update:
  https://github.com/nf-core/modules.git:
    nf-core: False
```

or if you want all modules in `nf-core/modules` at a specific version:

```yaml
update:
  https://github.com/nf-core/modules.git:
    nf-core: "e937c7950af70930d1f34bb961403d9d2aa81c7"
```

Note that the module versions specified in the `.nf-core.yml` file has higher precedence than versions specified with the command line flags, thus aiding you in writing reproducible pipelines.

### Remove a module from a pipeline

To delete a module from your pipeline, run `nf-core modules remove`.

![`nf-core modules remove abacas`](docs/images/nf-core-modules-remove.svg)

You can pass the module name as an optional argument to `nf-core modules remove` instead of using the cli prompt, eg: `nf-core modules remove fastqc`. To specify the pipeline directory, use `--dir <pipeline_dir>`.

### Create a patch file for a module

If you want to make a minor change to a locally installed module but still keep it up date with the remote version, you can create a patch file using `nf-core modules patch`.

![`nf-core modules patch fastqc`](docs/images/nf-core-modules-patch.svg)

The generated patches work with `nf-core modules update`: when you install a new version of the module, the command tries to apply
the patch automatically. The patch application fails if the new version of the module modifies the same lines as the patch. In this case,
the patch new version is installed but the old patch file is preserved.

When linting a patched module, the linting command will check the validity of the patch. When running other lint tests the patch is applied in reverse, and the original files are linted.

### Create a new module

This command creates a new nf-core module from the nf-core module template.
This ensures that your module follows the nf-core guidelines.
The template contains extensive `TODO` messages to walk you through the changes you need to make to the template.

You can create a new module using `nf-core modules create`.

This command can be used both when writing a module for the shared [nf-core/modules](https://github.com/nf-core/modules) repository,
and also when creating local modules for a pipeline.

Which type of repository you are working in is detected by the `repository_type` flag in a `.nf-core.yml` file in the root directory,
set to either `pipeline` or `modules`.
The command will automatically look through parent directories for this file to set the root path, so that you can run the command in a subdirectory.
It will start in the current working directory, or whatever is specified with `--dir <directory>`.

The `nf-core modules create` command will prompt you with the relevant questions in order to create all of the necessary module files.

![`cd modules && nf-core modules create fastqc --author @nf-core-bot  --label process_low --meta --force`](docs/images/nf-core-modules-create.svg)

### Check a module against nf-core guidelines

Run the `nf-core modules lint` command to check modules in the current working directory (pipeline or nf-core/modules clone) against nf-core guidelines.

Use the `--all` flag to run linting on all modules found. Use `--dir <pipeline_dir>` to specify another directory than the current working directory.

![`nf-core modules lint multiqc`](docs/images/nf-core-modules-lint.svg)

### Create a test for a module

All modules on [nf-core/modules](https://github.com/nf-core/modules) have a strict requirement of being unit tested using minimal test data. We use [nf-test](https://code.askimed.com/nf-test/) as our testing framework.
Each module comes already with a template for the test file in `test/main.nf.test`. Replace the placeholder code in that file with your specific input, output and proces. In order to generate the corresponding snapshot after writing your test, you can use the `nf-core modules test` command. This command will run `nf-test test` twice, to also check for snapshot stability, i.e. that the same snapshot is generated on multiple runs.

You can specify the module name in the form TOOL/SUBTOOL in the command or provide it later through interactive prompts.

![`nf-core modules test fastqc --no-prompts`](docs/images/nf-core-modules-test.svg)

In case you changed something in the test and want to update the snapshot, run

```bash
nf-core modules test --update
```

If you want to run the test only once without checking for snapshot stability, you can use the `--once` flag.

### Bump bioconda and container versions of modules in

If you are contributing to the `nf-core/modules` repository and want to bump bioconda and container versions of certain modules, you can use the `nf-core modules bump-versions` helper tool. This will bump the bioconda version of a single or all modules to the latest version and also fetch the correct Docker and Singularity container tags.

![`nf-core modules bump-versions fastqc`](docs/images/nf-core-modules-bump-version.svg)

If you don't want to update certain modules or want to update them to specific versions, you can make use of the `.nf-core.yml` configuration file. For example, you can prevent the `star/align` module from being updated by adding the following to the `.nf-core.yml` file:

```yaml
bump-versions:
  star/align: False
```

If you want this module to be updated only to a specific version (or downgraded), you could instead specifiy the version:

```yaml
bump-versions:
  star/align: "2.6.1d"
```

## Subworkflows

After the launch of nf-core modules, we can provide now also nf-core subworkflows to fully utilize the power of DSL2 modularization.
Subworkflows are chains of multiple module definitions that can be imported into any pipeline.
This allows multiple pipelines to use the same code for a the same tasks, and gives a greater degree of reusability and unit testing.

To allow us to test modules and subworkflows together we put the nf-core DSL2 subworkflows into the `subworkflows` directory of the modules repository is at <https://github.com/nf-core/modules>.

### Custom remote subworkflows

The subworkflows supercommand released in nf-core/tools version 2.7 comes with two flags for specifying a custom remote repository:

- `--git-remote <git remote url>`: Specify the repository from which the subworkflows should be fetched as a git URL. Defaults to the github repository of `nf-core/modules`.
- `--branch <branch name>`: Specify the branch from which the subworkflows should be fetched. Defaults to the default branch of your repository.

For example, if you want to install the `bam_stats_samtools` subworkflow from the repository `nf-core/modules-test` hosted at `gitlab.com` in the branch `subworkflows`, you can use the following command:

```bash
nf-core subworkflows --git-remote git@gitlab.com:nf-core/modules-test.git --branch subworkflows install bam_stats_samtools
```

Note that a custom remote must follow a similar directory structure to that of `nf-core/modules` for the `nf-core subworkflows` commands to work properly.

The directory where subworkflows are installed will be prompted or obtained from `org_path` in the `.nf-core.yml` file if available. If your subworkflows are located at `subworkflows/my-folder/SUBWORKFLOW_NAME` your `.nf-core.yml` file should have:

```yaml
org_path: my-folder
```

Please avoid installing the same tools from two different remotes, as this can lead to further errors.

The subworkflows commands will during initalisation try to pull changes from the remote repositories. If you want to disable this, for example due to performance reason or if you want to run the commands offline, you can use the flag `--no-pull`. Note however that the commands will still need to clone repositories that have previously not been used.

### Private remote repositories

You can use the subworkflows command with private remote repositories. Make sure that your local `git` is correctly configured with your private remote
and then specify the remote the same way you would do with a public remote repository.

### List subworkflows

The `nf-core subworkflows list` command provides the subcommands `remote` and `local` for listing subworkflows installed in a remote repository and in the local pipeline respectively. Both subcommands allow to use a pattern for filtering the subworkflows by keywords eg: `nf-core subworkflows list <subworkflow_name> <keyword>`.

#### List remote subworkflows

To list all subworkflows available on [nf-core/modules](https://github.com/nf-core/modules), you can use
`nf-core subworkflows list remote`, which will print all available subworkflows to the terminal.

![`nf-core subworkflows list remote`](docs/images/nf-core-subworkflows-list-remote.svg)

#### List installed subworkflows

To list subworkflows installed in a local pipeline directory you can use `nf-core subworkflows list local`. This will list the subworkflows install in the current working directory by default. If you want to specify another directory, use the `--dir <pipeline_dir>` flag.

![`nf-core subworkflows list local`](docs/images/nf-core-subworkflows-list-local.svg)

## Show information about a subworkflow

For quick help about how a subworkflow works, use `nf-core subworkflows info <subworkflow_name>`.
This shows documentation about the subworkflow on the command line, similar to what's available on the
[nf-core website](https://nf-co.re/subworkflows).

![`nf-core subworkflows info bam_rseqc`](docs/images/nf-core-subworkflows-info.svg)

### Install subworkflows in a pipeline

You can install subworkflows from [nf-core/modules](https://github.com/nf-core/modules) in your pipeline using `nf-core subworkflows install`.
A subworkflow installed this way will be installed to the `./subworkflows/nf-core` directory.

![`nf-core subworkflows install bam_rseqc`](docs/images/nf-core-subworkflows-install.svg)

You can pass the subworkflow name as an optional argument to `nf-core subworkflows install` like above or select it from a list of available subworkflows by only running `nf-core subworkflows install`.

There are four additional flags that you can use when installing a subworkflow:

- `--dir`: Pipeline directory, the default is the current working directory.
- `--force`: Overwrite a previously installed version of the subworkflow.
- `--prompt`: Select the subworkflow version using a cli prompt.
- `--sha <commit_sha>`: Install the subworkflow at a specific commit.

### Update subworkflows in a pipeline

You can update subworkflows installed from a remote repository in your pipeline using `nf-core subworkflows update`.

![`nf-core subworkflows update --all --no-preview`](docs/images/nf-core-subworkflows-update.svg)

You can pass the subworkflow name as an optional argument to `nf-core subworkflows update` like above or select it from the list of available subworkflows by only running `nf-core subworkflows update`.

There are six additional flags that you can use with this command:

- `--dir`: Pipeline directory, the default is the current working directory.
- `--force`: Reinstall subworkflow even if it appears to be up to date
- `--prompt`: Select the subworkflow version using a cli prompt.
- `--sha <commit_sha>`: Install the subworkflow at a specific commit from the `nf-core/modules` repository.
- `--preview/--no-preview`: Show the diff between the installed files and the new version before installing.
- `--save-diff <filename>`: Save diffs to a file instead of updating in place. The diffs can then be applied with `git apply <filename>`.
- `--all`: Use this flag to run the command on all subworkflows in the pipeline.
- `--update-deps`: Use this flag to automatically update all dependencies of a subworkflow.

If you don't want to update certain subworkflows or want to update them to specific versions, you can make use of the `.nf-core.yml` configuration file. For example, you can prevent the `bam_rseqc` subworkflow installed from `nf-core/modules` from being updated by adding the following to the `.nf-core.yml` file:

```yaml
update:
  https://github.com/nf-core/modules.git:
    nf-core:
      bam_rseqc: False
```

If you want this subworkflow to be updated only to a specific version (or downgraded), you could instead specifiy the version:

```yaml
update:
  https://github.com/nf-core/modules.git:
    nf-core:
      bam_rseqc: "36a77f7c6decf2d1fb9f639ae982bc148d6828aa"
```

This also works at the repository level. For example, if you want to exclude all modules and subworkflows installed from `nf-core/modules` from being updated you could add:

```yaml
update:
  https://github.com/nf-core/modules.git:
    nf-core: False
```

or if you want all subworkflows in `nf-core/modules` at a specific version:

```yaml
update:
  https://github.com/nf-core/modules.git:
    nf-core: "e937c7950af70930d1f34bb961403d9d2aa81c7"
```

Note that the subworkflow versions specified in the `.nf-core.yml` file has higher precedence than versions specified with the command line flags, thus aiding you in writing reproducible pipelines.

### Remove a subworkflow from a pipeline

To delete a subworkflow from your pipeline, run `nf-core subworkflows remove`.

![`nf-core subworkflows remove bam_rseqc`](docs/images/nf-core-subworkflows-remove.svg)

You can pass the subworkflow name as an optional argument to `nf-core subworkflows remove` like above or select it from the list of available subworkflows by only running `nf-core subworkflows remove`. To specify the pipeline directory, use `--dir <pipeline_dir>`.

### Create a new subworkflow

This command creates a new nf-core subworkflow from the nf-core subworkflow template.
This ensures that your subworkflow follows the nf-core guidelines.
The template contains extensive `TODO` messages to walk you through the changes you need to make to the template.
See the [subworkflow documentation](https://nf-co.re/docs/contributing/subworkflows) for more details around creating a new subworkflow, including rules about nomenclature and a step-by-step guide.

You can create a new subworkflow using `nf-core subworkflows create`.

This command can be used both when writing a subworkflow for the shared [nf-core/modules](https://github.com/nf-core/modules) repository,
and also when creating local subworkflows for a pipeline.

Which type of repository you are working in is detected by the `repository_type` flag in a `.nf-core.yml` file in the root directory,
set to either `pipeline` or `modules`.
The command will automatically look through parent directories for this file to set the root path, so that you can run the command in a subdirectory.
It will start in the current working directory, or whatever is specified with `--dir <directory>`.

The `nf-core subworkflows create` command will prompt you with the relevant questions in order to create all of the necessary subworkflow files.

![`nf-core subworkflows create bam_stats_samtools --author @nf-core-bot --force`](docs/images/nf-core-subworkflows-create.svg)

### Create a test for a subworkflow

All subworkflows on [nf-core/modules](https://github.com/nf-core/modules) have a strict requirement of being unit tested using minimal test data. We use [nf-test](https://code.askimed.com/nf-test/) as our testing framework.
Each subworkflow comes already with a template for the test file in `test/main.nf.test`. Replace the placeholder code in that file with your specific input, output and proces. In order to generate the corresponding snapshot after writing your test, you can use the `nf-core subworkflows test` command. This command will run `nf-test test` twice, to also check for snapshot stability, i.e. that the same snapshot is generated on multiple runs.

You can specify the subworkflow name in the command or provide it later through interactive prompts.

![`nf-core subworkflows test bam_rseqc --no-prompts`](docs/images/nf-core-subworkflows-test.svg)

In case you changed something in the test and want to update the snapshot, run

```bash
nf-core subworkflows test --update
```

If you want to run the test only once without checking for snapshot stability, you can use the `--once` flag.

### Check a subworkflow against nf-core guidelines

Run the `nf-core subworkflows lint` command to check subworkflows in the current working directory (a pipeline or a clone of nf-core/modules) against nf-core guidelines.

Use the `--all` flag to run linting on all subworkflows found. Use `--dir <pipeline_dir>` to specify a different directory than the current working directory.

![`nf-core subworkflows lint bam_stats_samtools`](docs/images/nf-core-subworkflows-lint.svg)

## Citation

If you use `nf-core tools` in your work, please cite the `nf-core` publication as follows:

> **The nf-core framework for community-curated bioinformatics pipelines.**
>
> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
>
> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).


# robotframework-browser

[![All Contributors](https://img.shields.io/badge/all_contributors-151-orange.svg?style=flat-square)](#contributors-)

[![Version](https://img.shields.io/pypi/v/robotframework-browser.svg)](https://pypi.python.org/pypi/robotframework-browser)
[![Actions Status](https://github.com/MarketSquare/robotframework-browser/workflows/Continuous%20integration/badge.svg)](https://github.com/MarketSquare/robotframework-browser/actions)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

----

[Robot Framework](https://robotframework.org) Browser library powered by [Playwright](https://playwright.dev/). Moving browser automation to year 2023!

Aiming for :rocket: speed, :white_check_mark: reliability and :microscope: visibility.

See [keyword documentation](https://marketsquare.github.io/robotframework-browser/Browser.html) and
[web page](https://robotframework-browser.org/) for more details.

# Installation instructions

Only Python 3.8 or newer is supported. From Node side 18 and 20 LTS versions are supported.

1. Install node.js e.g. from https://nodejs.org/en/download/
2. Update pip `pip install -U pip` to ensure latest version is used
3. Install robotframework-browser from the commandline: `pip install robotframework-browser`
4. Install the node dependencies: run `rfbrowser init` in your shell
  - if `rfbrowser` is not found, try `python -m Browser.entry init`

Please note that by default Chromium, Firefox and WebKit browser are installed, even those would be already
installed in the system. The installation size depends on the operating system, but usually is +700Mb.
It is possible to skip browser binaries installation with `rfbrowser init --skip-browsers` command, but then user
is responsible for browser binary installation. It is possible to install only selected browser binaries by adding
`chromium`, `firefox` or `webkit` as arguments to init command. Example `rfbrowser init firefox` would install
only Firefox binaries and `rfbrowser init firefox chromium` would install both Firefox and Chromium binaries.

Or use the [docker images](https://github.com/MarketSquare/robotframework-browser/pkgs/container/robotframework-browser%2Frfbrowser-stable). Documented at [docker/README.md](https://github.com/MarketSquare/robotframework-browser/blob/main/docker/README.md).

## Install with transformer

Starting from release 18.3.0 Browser library has optional dependency with
[Robotidy](https://robotidy.readthedocs.io/en/stable/). Install library with Robotidy, run install with:
`pip install robotframework-browser[tidy]`. Starting from 18.3.0 release, library will provide external
Robotidy [transformer](https://robotidy.readthedocs.io/en/stable/external_transformers.html). Transformer provided
by Browser library can be run with command: `rfbrowser transform --transformer-name /path/to/tests`. Example:
`rfbrowser transform --wait-until-network-is-idle /path/to/tests` would transform deprecated `Wait Until Network Is Idle`
keyword to `Wait For Load State` keyword. To see full list of transformers provided by Browser library, run
command: `rfbrowser transform --help`.

## Update instructions

To upgrade your already installed robotframework-browser library

1. Update from commandline: `pip install -U robotframework-browser`
2. Clean old node side dependencies and browser binaries: `rfbrowser clean-node`
3. Install the node dependencies for the newly installed version: `rfbrowser init`

## Uninstall instructions

To completely uninstall library, including the browser binaries installed by Playwright,
run following commands:
1. Clean old node side dependencies and browser binaries: `rfbrowser clean-node`
2. Uninstall with pip: `pip uninstall robotframework-browser`

# Examples

### Testing with [Robot Framework](https://robotframework.org)
```RobotFramework
*** Settings ***
Library   Browser

*** Test Cases ***
Example Test
    New Page    https://playwright.dev
    Get Text    h1    contains    Playwright
```
### and testing with [Python](https://python.org).
```python
import Browser
browser = Browser.Browser()
browser.new_page("https://playwright.dev")
assert 'Playwright' in browser.get_text("h1")
browser.close_browser()
```

### and extending with JavaScript

```JavaScript
async function myGoToKeyword(url, page, logger) {
    logger("Going to " + url)
    return await page.goto(url);
}
myGoToKeyword.rfdoc = "This is my own go to keyword";
exports.__esModule = true;
exports.myGoToKeyword = myGoToKeyword;
```

```RobotFramework
*** Settings ***
Library   Browser  jsextension=${CURDIR}/mymodule.js

*** Test Cases ***
Example Test
   New Page
   myGoToKeyword   https://www.robotframework.org
```

See [example](https://github.com/MarketSquare/robotframework-browser/tree/main/docs/examples/babelES2015).
Ready made extensions and a place to share your own at [robotframework-browser-extensions](https://github.com/MarketSquare/robotframework-browser-extensions).

### Ergonomic selector syntax, supports chaining of `text`, `css`  and `xpath` selectors

```RobotFramework
# Select element containing text "Login" with text selector strategy
# and select it's parent `input` element with xpath
Click    "Login" >> xpath=../input
# Select element with CSS strategy and select button in it with text strategy
Click    div.dialog >> "Ok"
```
### Evaluate in browser page
```RobotFramework
New Page   ${LOGIN_URL}
${ref}=    Get Element    h1
Get Property    ${ref}    innerText    ==    Login Page
Evaluate JavaScript    ${ref}    (elem) => elem.innerText = "abc"
Get Property    ${ref}    innerText    ==    abc
```
### Asynchronously waiting for HTTP requests and responses
```RobotFramework
# The button with id `delayed_request` fires a delayed request. We use a promise to capture it.
${promise}=    Promise To    Wait For Response    matcher=    timeout=3s
Click    \#delayed_request
${body}=    Wait For    ${promise}
```
### Device Descriptors
```RobotFramework
${device}=  Get Device  iPhone X
New Context  &{device}
New Page
Get Viewport Size  # returns { "width": 375, "height": 812 }
```
### Sending HTTP requests and parsing their responses
```RobotFramework
${response}=    HTTP    /api/post    POST    {"name": "John"}
Should Be Equal    ${response.status}    ${200}
```

### Parallel test execution using Pabot

You can let RF Browser spawn separate processes for every pabot process. This is very simple, just run the tests normally using pabot (see https://github.com/mkorpela/pabot#basic-use ). However if you have small tests do not use `--testlevelsplit`, it will cause lots of overhead because tests cannot share the browsers in any case.

You can share the node side RF Browser processes by using the `ROBOT_FRAMEWORK_BROWSER_NODE_PORT` environment variable, and `from Browser.utils import spawn_node_process` helper ([see the docs for the helper](https://github.com/MarketSquare/robotframework-browser/blob/a7d3e59a1e8e3e75f64b9146a088385445a5af30/Browser/utils/misc.py#L35) ). This saves some overhead based on how many splits of tests you are running. Clean up the process afterwards.

### Re-using authentication credentials

- Figure out how the page is storing authentication
- If it is localstorage or cookies `Save Storage State` should work. See usage example: https://marketsquare.github.io/robotframework-browser/Browser.html#Save%20Storage%20State

# Development

See [CONTRIBUTING.md](CONTRIBUTING.md) for development instructions.

## Core team

In order of appearance.

  * Mikko Korpela
  * Tatu Aalto
  * Janne Härkönen (Alumnus)
  * Kerkko Pelttari
  * René Rohner

## Contributors

This project is community driven and becomes a reality only through the work of all the people who contribute.
Supported by [Robocorp](https://robocorp.com/) through [Robot Framework Foundation](https://robotframework.org/foundation/).

Mikko Korpela
💻

Tatu Aalto
💻

Antti Karjalainen
🔍

Ismo Aro
🔍

Janne Härkönen
💻

Kerkko Pelttari
💻

Robocorp
💵

René
💻

Bryan Oakley
🤔

Tanakiat Srisaranyakul
🤔

Maaret Pyhäjärvi
📓

Karlo Smid
📓

Frank Schimmel
📓

Christoph
⚠

Mika Hänninen
💬

imbus
💵

Niklas
📖

gdroes
⚠

Reaktor
💵

Adrian Yorke
📖 👀

Nanakawa
⚠

Ed Manlove
📖 🐛

Brian Tsao
🐛 📓

charis
💻 🐛

s-galante
🐛

Simon Meggle
📓 🐛 ⚠ 🤔

Anna-Gunda
🐛

anton264
📓

emakaay
🐛

Nea Ohvo
🐛

Elout van Leeuwen
📖 🤔 💻

LDerikx
📖

olga-
📖 🐛

Nicholas Bollweg
📖

Ville Salonen
🐛

Jani Mikkonen
🐛 📖

Aleh Borysiewicz
🐛

Jürgen Knauth
🐛

dalaakso
🐛

msirkka
🤔

Ossi R.
💻

Adrian V.
💻 🐛 🤔

Sami Sallmén
🐛 ⚠

Pekka Klärck
💻 🐛

Jani Palsamäki
🐛

AllanMedeiros
🐛

Emmanuel Alap
🐛 💻

ankurbhalla-gmail
🤔

UliSei
🤔 🐛 💻 📓

Tomasz Pawlak
🐛

mtoskamp
🐛

zastress
🐛

Juga Paazmaya
💻

Raphael Smadja
🤔 💻 🐛

Antti Pakkanen
🐛

Luis A Gomez-Tinoco
🐛 💡 💻

ePlanLori
🐛

laguna357
🐛

Gavin Rodgers
🐛

pokaalinkanssayohon
🤔

Ryan Sandbach
🐛 💻

Niko Kahilainen
🐛

Guillaume Gautier
📖

Robin Matz
🤔

Stavros Ntentos
📖

Massukio
🐛 🤔

Atihinen
🐛

gvrkumar
🤔

Lauri Helkkula
🐛

rlall07
🐛 🤔

Eldad Uzman
🤔

mgarcibu
🐛

DominikG
🤔

jokinr
⚠ 🐛

Jier Chen
💻

IDvoe
🐛

Cosmin Poieana
🐛

Shenthil
🐛

Marduk Bolaños
🐛 🤔

amodzelewski
🐛

TimDicos
🐛

vinismarques
🐛

nizwiz
🐛

Reddriver
🤔

Seppo
🐛

rousku
🐛

tomaspekarovic
🤔

Robin Mackaij
🐛

nixuewei
🤔

Slava
🤔 🐛 💻

Kari Harju
🐛

you
🐛

axiom41
🐛

amankul
🐛

jcb-entrnce
🐛

Remppa
🐛

Tomasz Pawlak
🐛

Timo Stordell
🐛

Marcin Gmurczyk
💻

Daniel Biehl
🐛 🤔

rarajabs
🐛

Sandeep Vaidya
🤔

falk
📖

ciadoh
🐛

Johan van Iperen
💻

Fabio Zadrozny
🐛

BCGST
📖

Wilfried van Asten
🐛 💻

Mikal H Henriksen
🐛

alexinoDr
🐛

trybuskrzysztof
🐛

Aino1980
🐛

BjornAhmark
🐛

Mezohren
🐛

Zoupers Zou
🤔

lasselindqvist
🐛

David Nieto Sanz
🐛

Gil Forcada Codinachs
📖 🐛

Nathan Hannig
🐛

Martin Kjellstrand
🐛

Anton Medvedev
💻

martamedovova-ext91522
🐛 🤔

Dr. Dirk Richter
🤔

RatexMak
🤔

horzuff
💻

naibra
🐛

Antti Pekka Vilkko
🐛

Serafín Martín
🐛

JoostW21111
🐛

Camatius
🐛

terckert
🐛

Maksim Bondarew
🐛

HenrikSchuette
🐛

Gurunatharudh Bhandarkavathe(Infosys)
🐛

alpip1997
🐛

terolindfors
🐛

Thisara Wijesundera
🤔

masudparvez
🤔

gitkatsi
🐛 💻

Many Kasiriha
🐛

Thulasi Raju
📖

Giancarlo Soverini
🤔

lennartq
💻

Lukas Boekenoogen
📖

anacomparada
🐛 📖

siongwai
🤔

nfaustin
🐛

Guido Schmitz
💻

Chris Nesbitt-Smith
💻

vmmattila
🐛

Andre-A-AtGithub
🐛


[![PyPi version](https://img.shields.io/pypi/v/sPyNNaker.svg?style=flat)](https://pypi.org/project/sPyNNaker/)
[![Python Build Status](https://github.com/SpiNNakerManchester/sPyNNaker/workflows/Python%20Actions/badge.svg?branch=master)](https://github.com/SpiNNakerManchester/sPyNNaker/actions?query=workflow%3A%22Python+Actions%22+branch%3Amaster)
[![C Build Status](https://github.com/SpiNNakerManchester/sPyNNaker/workflows/C%20Actions/badge.svg?branch=master)](https://github.com/SpiNNakerManchester/sPyNNaker/actions?query=workflow%3A%22C+Actions%22+branch%3Amaster)
[![Documentation Status](https://readthedocs.org/projects/spynnaker/badge/?version=master)](https://spynnaker.readthedocs.io/en/master/?badge=master)
[![Coverage Status](https://coveralls.io/repos/github/SpiNNakerManchester/sPyNNaker/badge.svg?branch=master)](https://coveralls.io/github/SpiNNakerManchester/sPyNNaker?branch=master)

sPyNNaker - PyNN Simulations on SpiNNaker Hardware
==================================================
This package provides common code for PyNN implementations for SpiNNaker.

We have [user installation instructions](http://spinnakermanchester.github.io/)
which describe in detail more about what is going on.

Developer Installation
----------------------
If you want to be able to edit the source code, but still have it referenced
from other Python modules, you can set the install to be a
[developer install](http://spinnakermanchester.github.io/development/devenv.html)
which describes the process of installing the other modules which these
depend upon for a complete editable install.

Documentation
-------------
[sPyNNaker Python documentation](https://spynnaker.readthedocs.io/)
<br>
[sPyNNaker C documentation](http://spinnakermanchester.github.io/sPyNNaker/c/)

[Combined PyNN8 python documentation](http://spinnakermanchester.readthedocs.io)


mflowgen
==========================================================================
[![Documentation Status](https://readthedocs.org/projects/mflowgen/badge/?version=latest)](https://mflowgen.readthedocs.io/en/latest) [![mflowgen pytest CI](https://github.com/mflowgen/mflowgen/actions/workflows/pytest-ci.yml/badge.svg)](https://github.com/mflowgen/mflowgen/actions/workflows/pytest-ci.yml) [![pypi](https://img.shields.io/pypi/v/mflowgen)](https://pypi.org/project/mflowgen)

<!-- **Author**: Christopher Torng (ctorng@stanford.edu) -->

mflowgen is a modular flow specification and build-system
generator for ASIC and FPGA design-space exploration built around
sandboxed and modular nodes.

mflowgen allows you to programmatically define and parameterize a graph
of nodes (i.e., sandboxes that run anything you like) with
well-defined inputs and outputs. Build system files (e.g., make,
ninja) are then generated which shuttle files between nodes before
running them.

<img width='350px' src='docs/_static/images/example-graph.jpg'>

Key features and design philosophies:

- **Process and technology independence** -- Process technology
  libraries and variables can be abstracted and separated from
  physical design scripts. Specifically, a single node called the
  ASIC design kit (ADK) captures this material in one place for
  better maintainability and access control.

- **Sandboxed and modular nodes** -- Traditional ASIC flows are
  composed of many steps executing with fixed path dependencies. The
  resulting flows have low reusability across designs and technology
  nodes and can be confusing and monolithic. In contrast,
  _modularity_ encourages reuse of the same scripts across many
  projects, while _sandboxing_ makes each node self-contained and
  also makes the role of each node easy to understand (i.e., take
  these inputs and generate those outputs).

- **Programmatically defined build-system generator**: A
  Python-based scripting interface and a simple graph API allows
  flexible connection and disconnection of edges, insertion and
  removal of nodes, and parameter space expansions. A simple graph
  can be specified for a quick synthesis and place-and-route spin,
  or a more complex graph can be built for a more aggressive chip
  tapeout (reusing many of the same nodes from before).

- **Run-time assertions** -- Assertions can be built into each
  modular node and checked at run-time. Preconditions and
  postconditions are simply Python snippets that run before and
  after a node to catch unexpected situations that arise at build
  time. Assertions are collected and run with pytest. The mflowgen
  graph-building DSL can also extend a node with _design-specific_
  assertions by extending Python lists.

- **A focus on hardware design-space exploration** -- Parameter
  expansion can be applied to nodes to quickly spin out parallel
  builds for design-space exploration at both smaller scales with a
  single parameter (e.g., sweeping clock targets) as well as at
  larger scales with multiple parameters (e.g., to characterize the
  area-energy tradeoff space of a new architectural widget with
  different knobs). Dependent files are shuttled to each sandbox
  as needed.

- **Complete freedom in defining what nodes do** -- Aside from
  exposing precisely what the inputs and outputs are, no other
  restrictions are placed on what nodes do. A node may conduct an
  analysis pass and report a gate count. A node can also apply a
  transform pass to a netlist before passing it to other tools. In
  addition, a node can even instantiate a subgraph to implement a
  hierarchical flow.

mflowgen ships with a limited set of ASIC flow scripts for both
open-source and commercial tools including synthesis (e.g., Synopsys
DC, yosys), place and route (e.g., Cadence Innovus Foundation Flow,
RePlAce, graywolf, qrouter), and signoff (e.g., Synopsys PTPX,
Mentor Calibre). In addition, we include an open-source 45nm ASIC design
kit (ADK) assembled from FreePDK45 version 1.4 and the NanGate Open
Cell Library.

More info can be found in the
[documentation](https://mflowgen.readthedocs.io/en/latest).

--------------------------------------------------------------------------
License
--------------------------------------------------------------------------

mflowgen is offered under the terms of the Open Source Initiative BSD
3-Clause License. More information about this license can be found
here:

- http://choosealicense.com/licenses/bsd-3-clause
- http://opensource.org/licenses/BSD-3-Clause


# IMPROVER

[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
[![Tests](https://github.com/metoppv/improver/actions/workflows/scheduled.yml/badge.svg)](https://github.com/metoppv/improver/actions/workflows/scheduled.yml)
[![Codacy Badge](https://api.codacy.com/project/badge/Grade/f7dcb46e8e1b4110b3d194dba03fe526)](https://www.codacy.com/app/metoppv_tech/improver?utm_source=github.com&utm_medium=referral&utm_content=metoppv/improver&utm_campaign=Badge_Grade)
[![Codacy Badge](https://api.codacy.com/project/badge/Coverage/f7dcb46e8e1b4110b3d194dba03fe526)](https://www.codacy.com/app/metoppv_tech/improver?utm_source=github.com&utm_medium=referral&utm_content=metoppv/improver&utm_campaign=Badge_Coverage)
[![codecov](https://codecov.io/gh/metoppv/improver/branch/master/graph/badge.svg)](https://codecov.io/gh/metoppv/improver)
[![Documentation Status](https://readthedocs.org/projects/improver/badge/?version=latest)](http://improver.readthedocs.io/en/latest/?badge=latest)
[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)
[![Python 3.7](https://img.shields.io/badge/python-3.7-blue.svg)](https://www.python.org/downloads/release/python-370/)
[![DOI](https://zenodo.org/badge/85334761.svg)](https://zenodo.org/badge/latestdoi/85334761)

IMPROVER is a library of algorithms for meteorological post-processing and verification.

## Installing improver

### Conda installation

Here we demonstrate the installation of improver via conda with aid of the [mamba](https://mamba.readthedocs.io/en/latest/index.html) package manager to speedup the process.

install a mamba environment
```
conda create -c conda-forge --override-channels mamba -n mamba
```

activate this mamba environment
```
conda activate mamba
```

install the improver environment using mamba
```
mamba create -c conda-forge python=3.7 improver -n improver
```

deactivate your mamba environment
```
conda deactivate
```

activate your new improver environment
```
conda activate improver
```


# PyCon Italia website

> The monorepo for the new PyCon Italia website, based on Django, Strawberry,
> Next.js and React.

## How to setup

Use our local docker-compose setup to start all services you need.

After cloning the project, you can run:

```
docker-compose up
```

to start the services.

You will find the services at the following ports:

| Service name         | Address               |
| -------------------- | --------------------- |
| Backend              | http://localhost:8000/admin - http://localhost:8000/cms-admin |
| Frontend             | http://localhost:3000 |

Everything you need to get started is already configured
and will work out of the box.

If you need to work with our Stripe or Pretix integration, you will have to ask
on Slack which secret key you need and why you need it.

Once given, create a `.env` file at the project root with inside:

```text
STRIPE_PUBLIC_KEY=
PRETIX_API_TOKEN=
STRIPE_WEBHOOK_SIGNATURE_SECRET=
STRIPE_SECRET_API_KEY=
```

Adding the secret keys after the `=` symbol.

## External repos

Repos used by this project are in separate repositories.

| Name          | Description                                             | Link                                                   |
| ------------- | ------------------------------------------------------- | ------------------------------------------------------ |
| Toolkit (Deprecated)       | Backend Toolkit used to share code between all services | https://github.com/pythonitalia/pythonit-toolkit       |
| Pretix Extended API | Pretix plugin to expose more APIs                   | https://github.com/pythonitalia/pretix-plugin-extended-api |
| Pretix Attendance certificate | Pretix plugin to generate and send Attendance certificates | https://github.com/pythonitalia/pretix-plugin-attendance-certificate |

[](https://vercel.com?utm_source=python-italia&utm_campaign=oss)


# CI Statuses

Check | Status
---|---
Documentation|[![Documentation Status](https://readthedocs.org/projects/dexterous-hand/badge/?version=latest)](https://dexterous-hand.readthedocs.io/en/latest/?badge=latest)|
Build|[](https://eu-west-2.console.aws.amazon.com/codesuite/codebuild/projects/auto_sr_interface_noetic-devel_install_check/)
Style|[](https://eu-west-2.console.aws.amazon.com/codesuite/codebuild/projects/auto_sr_interface_noetic-devel_style_check/)
Code Coverage|[](https://eu-west-2.console.aws.amazon.com/codesuite/codebuild/projects/auto_sr_interface_noetic-devel_code_coverage/)

# Shadow Robot Interface packages
This repository contains the high level interface and its dependencies for interacting simply with our robots.


Kivy
====

[Kivy](https://www.kivy.org) is an open-source [Python](https://python.org) framework
for developing GUI apps that work cross-platform, including desktop, mobile and
embedded platforms.

The aim is to allow for quick and easy interaction design and rapid prototyping
whilst making your code reusable and deployable: Innovative user interfaces made
easy.

Kivy is written in Python and [Cython](https://cython.org/) and is built on
[OpenGL ES 2.0](https://www.khronos.org/opengles/). It supports various input
devices and has an extensive (and extensible) widget library. With the
same codebase, you can target Windows, macOS, Linux (including Raspberry Pi OS),
Android, and iOS. All Kivy widgets are built with multitouch support.

Kivy is [MIT licensed](LICENSE), actively developed by a great community and is
supported by many projects managed by the
[Kivy Organization](https://www.kivy.org/about.html).

[![Backers on Open Collective](https://opencollective.com/kivy/backers/badge.svg)](#backers)
[![Sponsors on Open Collective](https://opencollective.com/kivy/sponsors/badge.svg)](#sponsors)
[![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg)](CODE_OF_CONDUCT.md)
[![GitHub contributors](https://img.shields.io/github/contributors-anon/kivy/kivy)](https://github.com/kivy/kivy/graphs/contributors)

![PyPI - Version](https://img.shields.io/pypi/v/kivy)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/kivy)

[![Windows Unittests Status](https://github.com/kivy/kivy/workflows/Windows%20Unittests/badge.svg)](https://github.com/kivy/kivy/actions?query=workflow%3A%22Windows+Unittests%22)
[![Ubuntu Unittests Status](https://github.com/kivy/kivy/workflows/Ubuntu%20Unittests/badge.svg)](https://github.com/kivy/kivy/actions?query=workflow%3A%22Ubuntu+Unittests%22)
[![OSX Unittests Status](https://github.com/kivy/kivy/workflows/OSX%20Unittests/badge.svg)](https://github.com/kivy/kivy/actions?query=workflow%3A%22OSX+Unittests%22)
[![Coverage Status](https://coveralls.io/repos/kivy/kivy/badge.svg?branch=master)](https://coveralls.io/r/kivy/kivy?branch=master)

[![Windows wheels Status](https://github.com/kivy/kivy/workflows/Windows%20wheels/badge.svg)](https://github.com/kivy/kivy/actions?query=workflow%3A%22Windows+wheels%22)
[![Manylinux wheels Status](https://github.com/kivy/kivy/workflows/Manylinux%20wheels/badge.svg)](https://github.com/kivy/kivy/actions?query=workflow%3A%22Manylinux+wheels%22)
[![Raspberry Pi wheels Status](https://github.com/kivy/kivy/workflows/RPi%20wheels/badge.svg)](https://github.com/kivy/kivy/actions?query=workflow%3A%22RPi+wheels%22)
[![OSX wheels Status](https://github.com/kivy/kivy/workflows/OSX%20wheels%2Fapp/badge.svg)](https://github.com/kivy/kivy/actions?query=workflow%3A%22OSX+wheels%2Fapp%22)

Installation, Documentation and Examples
----------------------------------------

Extensive installation instructions as well as tutorials and general
documentation, including an API reference, can be found at https://www.kivy.org/docs.
A [PDF version](https://media.readthedocs.org/pdf/kivy/latest/kivy.pdf) is also available.

Kivy ships with many examples which can be found in the `examples` folder.

Support
-------

Are you having trouble using the Kivy framework, or any of its related projects?
Is there an error you don’t understand? Are you trying to figure out how to use
it? We have volunteers who can help!

The best channels to contact us for support are listed in the latest
[Contact Us](CONTACT.md) document.

Contributing
------------

We love pull requests and discussing novel ideas. Check out our
[latest contribution guide](CONTRIBUTING.md) and
feel free to improve Kivy.

It gives details of the best places online to discuss the development with the
core developers and other enthusiasts.

Sibling projects
----------------

The Kivy team manager a number of additional projects that support the Kivy
eco-system.

- [Buildozer](https://github.com/kivy/buildozer):  a development tool for turning Python applications into binary packages ready for installation on
  any of a number of platforms, including mobile devices.
- [Plyer](https://github.com/kivy/plyer): a platform-independent Python API for accessing hardware features of various platforms (Android, iOS,
  macOS, Linux and Windows).
- [PyJNIus](https://github.com/kivy/pyjnius): a Python library for accessing Java classes using the Java Native Interface (JNI).
- [Pyobjus](https://github.com/kivy/pyobjus): Python module for accessing Objective-C classes as Python classes using
  Objective-C runtime reflection.
- [Python for Android](https://github.com/kivy/python-for-android): a development tool that packages Python apps into binaries that can run on Android devices.
- [Kivy iOS](https://github.com/kivy/kivy-ios): a toolchain to compile the necessary libraries for iOS to run Kivy applications, and manage the
  creation of Xcode projects.
- [Audiostream](https://github.com/kivy/audiostream): library for direct access
  to the microphone and speaker.
- [KivEnt](https://github.com/kivy/kivent): entity-based game engine for Kivy.
- [Oscpy](https://github.com/kivy/oscpy/): a Python implementation of Open Sound Control (OSC) network protocol.
- [Garden](https://github.com/kivy-garden): widgets and libraries created and
  maintained by users.

Licenses
--------

- Kivy is released under the terms of the MIT License. Please refer to the
  [LICENSE](LICENSE) file.
- The provided fonts Roboto and Roboto Mono are licensed and
  distributed under the terms of the
  [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
  The DejaVuSans (used for the virtual keyboard) license can be viewed
  [here](https://github.com/dejavu-fonts/dejavu-fonts/blob/master/LICENSE).
- The current UI design has been adapted from Moblintouch theme's SVGs
  and is licensed under the terms of the
  [LGPLv2.1](https://www.gnu.org/licenses/old-licenses/lgpl-2.1).

## Code of Conduct

In the interest of fostering an open and welcoming community, we as
contributors and maintainers need to ensure participation in our project and
our sister projects is a harassment-free and positive experience for everyone.
It is vital that all interaction is conducted in a manner conveying respect,
open-mindedness and gratitude.

Please consult the [latest Code of Conduct](https://github.com/kivy/kivy/blob/master/CODE_OF_CONDUCT.md).

## Contributors

This project exists thanks to
[all the people who contribute](https://github.com/kivy/kivy/graphs/contributors).
[[Become a contributor](CONTRIBUTING.md)].

## Backers

Thank you to [all of our backers](https://opencollective.com/kivy)!
🙏 [[Become a backer](https://opencollective.com/kivy#backer)]

## Sponsors

Special thanks to
[all of our sponsors, past and present](https://opencollective.com/kivy).
Support this project by
[[becoming a sponsor](https://opencollective.com/kivy#sponsor)].

Here are our top current sponsors. Please click through to see their websites,
and support them as they support us.