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This is a NOMAD parser for [NWChem](https://nwchemgit.github.io/). It will read NWChem input and
output files and provide all information in NOMAD's unified Metainfo based Archive format.
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## Preparing code input and output file for uploading to NOMAD

NOMAD accepts `.zip` and `.tar.gz` archives as uploads. Each upload can contain arbitrary
files and directories. NOMAD will automatically try to choose the right parser for you files.
For each parser (i.e. for each supported code) there is one type of file that the respective
parser can recognize. We call these files `mainfiles` as they typically are the main
output file a code. For each `mainfile` that NOMAD discovers it will create an entry
in the database that users can search, view, and download. NOMAD will associate all files
in the same directory as files that also belong to that entry. Parsers
might also read information from these auxillary files. This way you can add more files
to an entry, even if the respective parser/code might not directly support it.

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For NWChem please provide at least the files from this table if applicable to your
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calculations (remember that you can provide more files if you want):
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To create an upload with all calculations in a directory structure:

```
zip -r <upload-file>.zip <directory>/*
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```

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Go to the [NOMAD upload page](https://nomad-lab.eu/prod/rae/gui/uploads) to upload files
or find instructions about how to upload files from the command line.

## Using the parser
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You can use NOMAD's parsers and normalizers locally on your computer. You need to install
NOMAD's pypi package:

```
pip install nomad-lab
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```

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To parse code input/output from the command line, you can use NOMAD's command line
interface (CLI) and print the processing results output to stdout:
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```
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nomad parse --show-archive <path-to-file>
```

To parse a file in Python, you can program something like this:
```python
import sys
from nomad.cli.parse import parse, normalize_all
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# match and run the parser
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archive = parse(sys.argv[1])
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# run all normalizers
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normalize_all(archive)
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# get the 'main section' section_run as a metainfo object
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section_run = archive.section_run[0]
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# get the same data as JSON serializable Python dict
python_dict = section_run.m_to_dict()
```

## Developing the parser

Also install NOMAD's pypi package:

```
pip install nomad-lab
```

Clone the parser project and install it in development mode:

```
git clone https://gitlab.mpcdf.mpg.de/nomad-lab/parser-nwchem parser-nwchem
pip install -e parser-nwchem
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```
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Running the parser now, will use the parser's Python code from the clone project.
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