path: root/python-cow-csvw.spec

%global _empty_manifest_terminate_build 0
Name:		python-cow-csvw
Version:	1.21
Release:	1
Summary:	Integrated CSV to RDF converter, using CSVW and nanopublications
License:	MIT
URL:		https://github.com/CLARIAH/COW
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/8d/c4/96a4c09c6fef23cf46ea16f38ce46ef72831685140950207e4006e43828b/cow_csvw-1.21.tar.gz
BuildArch:	noarch


%description
## CoW: Integrated CSV to RDF Converter

> CoW (Csv on the Web) is an integrated CSV to RDF converter that uses the W3C standard [CSVW](https://www.w3.org/TR/tabular-data-primer/) for rich semantic table specificatons, and [nanopublications](http://nanopub.org/) as an output RDF model



### What is CoW

CoW is a command-line utility to convert any CSV file into an RDF dataset. Its distinctive features are:

- Expressive CSVW-compatible schemas based on the [Jinja](https://github.com/pallets/jinja) template enginge
- Highly efficient implementation leveraging multithreaded and multicore architectures
- Available as a pythonic [CLI tool](#cli), [library](#library), and [web service](#web-service)
- Supports Python 3

### Documentation and support
For user documentation see the basic introduction video https://t.co/SDWC3NhWZf and [wiki](https://github.com/clariah/cow/wiki/). Technical details are provided below. If you encounter an issue then please [report](https://github.com/CLARIAH/COW/issues/new/choose) it. Also feel free to create pull requests!

### Install (requires Python to be installed)

`pip3` is the recommended method of installing COW in your system:

```
pip3 install cow-csvw
```

You can upgrade your currently installed version with:

```
pip3 install cow-csvw --upgrade
```

Possible issues:

- Permission issues. You can get around them by installing CoW in user space: `pip3 install cow-csvw --user`. Make sure your binary user directory (typically something like `/Users/user/Library/Python/3.7/bin` in MacOS or `/home/user/.local/bin` in Linux) is in your PATH (in MacOS: `/etc/paths`. For Windows/MacOS we recommend to install Python via the [official distribution page](https://www.python.org/downloads/). You can also use [virtualenv](https://virtualenv.pypa.io/en/latest/) to avoid conflicts with your system libraries
- Please [report your unlisted issue](https://github.com/CLARIAH/CoW/issues/new)

If you can't/don't want to deal with installing CoW, you can use the [cattle](http://cattle.datalegend.net/) [web service version](#web-service) (deprecated).

### Usage

#### CLI

The CLI (command line interface) is the recommended way of using CoW for most users. The straightforward CSV to RDF conversion is done in two steps. First:

```
cow_tool build myfile.csv
```

This will create a file named `myfile.csv-metadata.json` (from now on: JSON schema file or just JSF). You don't need to worry about this file if you only want a syntactic conversion. Then:

```
cow_tool convert myfile.csv
```

Will output a `myfile.csv.nq` RDF file (nquads by default; you can control the output RDF serialization with e.g. ``--format turtle``). That's it!

If you want to control the base URI namespace, URIs used in predicates, virtual columns, and the many other features of CoW, you'll need to edit the `myfile.csv-metadata.json` JSF and/or use CoW arguments. Have a look at the [CLI options](#options) below, the examples in the [wiki](https://github.com/CLARIAH/CoW/wiki), and the [technical documentation](http://csvw-converter.readthedocs.io/en/latest/).

##### Options

Check the ``--help`` for a complete list of options:

```
usage: cow_tool [-h] [--dataset DATASET] [--delimiter DELIMITER]
                [--quotechar QUOTECHAR] [--encoding ENCODING] [--processes PROCESSES]
                [--chunksize CHUNKSIZE] [--base BASE]
                [--format [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}]]
				[--gzip] [--version]
                {convert,build} file [file ...]

Not nearly CSVW compliant schema builder and RDF converter

positional arguments:
  {convert,build}       Use the schema of the `file` specified to convert it
                        to RDF, or build a schema from scratch.
  file                  Path(s) of the file(s) that should be used for
                        building or converting. Must be a CSV file.

optional arguments:
  -h, --help            show this help message and exit
  --dataset DATASET     A short name (slug) for the name of the dataset (will
                        use input file name if not specified)
  --delimiter DELIMITER
                        The delimiter used in the CSV file(s)
  --quotechar QUOTECHAR
                        The character used as quotation character in the CSV
                        file(s)
  --encoding ENCODING   The character encoding used in the CSV file(s)

  --processes PROCESSES
                        The number of processes the converter should use
  --chunksize CHUNKSIZE
                        The number of rows processed at each time
  --base BASE           The base for URIs generated with the schema (only
                        relevant when `build`ing a schema)
  --gzip 				Compress the output file using gzip
  --format [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}], -f [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}]
                        RDF serialization format
  --version             show program's version number and exit
```

#### Web service

There is web service and interface running CoW, called [cattle](http://cattle.datalegend.net/). Two public instances are running at:

- http://cattle.datalegend.net/ - runs CoW in Python3
- http://legacy.cattle.datalegend.net/ - runs CoW in Python2 for legacy reasons

Beware of the web service limitations:

- There's a limit to the size of the CSVs you can upload
- It's a public instance, so your conversion could take longer
- Cattle is no longer being maintained and these public instances will eventually be taken offline

#### Library

Once installed, CoW can be used as a library as follows:

```
from cow_csvw.csvw_tool import COW
import os

COW(mode='build', files=[os.path.join(path, filename)], dataset='My dataset', delimiter=';', quotechar='\"')

COW(mode='convert', files=[os.path.join(path, filename)], dataset='My dataset', delimiter=';', quotechar='\"', processes=4, chunksize=100, base='http://example.org/my-dataset', format='turtle', gzipped=False)
```

### Technical documentation

Technical documentation for CoW are maintained in this GitHub repository (under <docs>), and published through [Read the Docs](http://readthedocs.org) at <http://csvw-converter.readthedocs.io/en/latest/>.

To build the documentation from source, change into the `docs` directory, and run `make html`. This should produce an HTML version of the documentation in the `_build/html` directory.

### Examples

The [wiki](https://github.com/CLARIAH/COW/wiki) provides more hands-on examples of transposing CSVs into Linked Data

### License

MIT License (see [license.txt](license.txt))

### Acknowledgements

**Authors:**    Albert Meroño-Peñuela, Roderick van der Weerdt, Rinke Hoekstra, Kathrin Dentler, Auke Rijpma, Richard Zijdeman, Melvin Roest, Xander Wilcke

**Copyright:**  Vrije Universiteit Amsterdam, Utrecht University, International Institute of Social History


CoW is developed and maintained by the CLARIAH project and funded by NWO.


%package -n python3-cow-csvw
Summary:	Integrated CSV to RDF converter, using CSVW and nanopublications
Provides:	python-cow-csvw
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-cow-csvw
## CoW: Integrated CSV to RDF Converter

> CoW (Csv on the Web) is an integrated CSV to RDF converter that uses the W3C standard [CSVW](https://www.w3.org/TR/tabular-data-primer/) for rich semantic table specificatons, and [nanopublications](http://nanopub.org/) as an output RDF model



### What is CoW

CoW is a command-line utility to convert any CSV file into an RDF dataset. Its distinctive features are:

- Expressive CSVW-compatible schemas based on the [Jinja](https://github.com/pallets/jinja) template enginge
- Highly efficient implementation leveraging multithreaded and multicore architectures
- Available as a pythonic [CLI tool](#cli), [library](#library), and [web service](#web-service)
- Supports Python 3

### Documentation and support
For user documentation see the basic introduction video https://t.co/SDWC3NhWZf and [wiki](https://github.com/clariah/cow/wiki/). Technical details are provided below. If you encounter an issue then please [report](https://github.com/CLARIAH/COW/issues/new/choose) it. Also feel free to create pull requests!

### Install (requires Python to be installed)

`pip3` is the recommended method of installing COW in your system:

```
pip3 install cow-csvw
```

You can upgrade your currently installed version with:

```
pip3 install cow-csvw --upgrade
```

Possible issues:

- Permission issues. You can get around them by installing CoW in user space: `pip3 install cow-csvw --user`. Make sure your binary user directory (typically something like `/Users/user/Library/Python/3.7/bin` in MacOS or `/home/user/.local/bin` in Linux) is in your PATH (in MacOS: `/etc/paths`. For Windows/MacOS we recommend to install Python via the [official distribution page](https://www.python.org/downloads/). You can also use [virtualenv](https://virtualenv.pypa.io/en/latest/) to avoid conflicts with your system libraries
- Please [report your unlisted issue](https://github.com/CLARIAH/CoW/issues/new)

If you can't/don't want to deal with installing CoW, you can use the [cattle](http://cattle.datalegend.net/) [web service version](#web-service) (deprecated).

### Usage

#### CLI

The CLI (command line interface) is the recommended way of using CoW for most users. The straightforward CSV to RDF conversion is done in two steps. First:

```
cow_tool build myfile.csv
```

This will create a file named `myfile.csv-metadata.json` (from now on: JSON schema file or just JSF). You don't need to worry about this file if you only want a syntactic conversion. Then:

```
cow_tool convert myfile.csv
```

Will output a `myfile.csv.nq` RDF file (nquads by default; you can control the output RDF serialization with e.g. ``--format turtle``). That's it!

If you want to control the base URI namespace, URIs used in predicates, virtual columns, and the many other features of CoW, you'll need to edit the `myfile.csv-metadata.json` JSF and/or use CoW arguments. Have a look at the [CLI options](#options) below, the examples in the [wiki](https://github.com/CLARIAH/CoW/wiki), and the [technical documentation](http://csvw-converter.readthedocs.io/en/latest/).

##### Options

Check the ``--help`` for a complete list of options:

```
usage: cow_tool [-h] [--dataset DATASET] [--delimiter DELIMITER]
                [--quotechar QUOTECHAR] [--encoding ENCODING] [--processes PROCESSES]
                [--chunksize CHUNKSIZE] [--base BASE]
                [--format [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}]]
				[--gzip] [--version]
                {convert,build} file [file ...]

Not nearly CSVW compliant schema builder and RDF converter

positional arguments:
  {convert,build}       Use the schema of the `file` specified to convert it
                        to RDF, or build a schema from scratch.
  file                  Path(s) of the file(s) that should be used for
                        building or converting. Must be a CSV file.

optional arguments:
  -h, --help            show this help message and exit
  --dataset DATASET     A short name (slug) for the name of the dataset (will
                        use input file name if not specified)
  --delimiter DELIMITER
                        The delimiter used in the CSV file(s)
  --quotechar QUOTECHAR
                        The character used as quotation character in the CSV
                        file(s)
  --encoding ENCODING   The character encoding used in the CSV file(s)

  --processes PROCESSES
                        The number of processes the converter should use
  --chunksize CHUNKSIZE
                        The number of rows processed at each time
  --base BASE           The base for URIs generated with the schema (only
                        relevant when `build`ing a schema)
  --gzip 				Compress the output file using gzip
  --format [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}], -f [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}]
                        RDF serialization format
  --version             show program's version number and exit
```

#### Web service

There is web service and interface running CoW, called [cattle](http://cattle.datalegend.net/). Two public instances are running at:

- http://cattle.datalegend.net/ - runs CoW in Python3
- http://legacy.cattle.datalegend.net/ - runs CoW in Python2 for legacy reasons

Beware of the web service limitations:

- There's a limit to the size of the CSVs you can upload
- It's a public instance, so your conversion could take longer
- Cattle is no longer being maintained and these public instances will eventually be taken offline

#### Library

Once installed, CoW can be used as a library as follows:

```
from cow_csvw.csvw_tool import COW
import os

COW(mode='build', files=[os.path.join(path, filename)], dataset='My dataset', delimiter=';', quotechar='\"')

COW(mode='convert', files=[os.path.join(path, filename)], dataset='My dataset', delimiter=';', quotechar='\"', processes=4, chunksize=100, base='http://example.org/my-dataset', format='turtle', gzipped=False)
```

### Technical documentation

Technical documentation for CoW are maintained in this GitHub repository (under <docs>), and published through [Read the Docs](http://readthedocs.org) at <http://csvw-converter.readthedocs.io/en/latest/>.

To build the documentation from source, change into the `docs` directory, and run `make html`. This should produce an HTML version of the documentation in the `_build/html` directory.

### Examples

The [wiki](https://github.com/CLARIAH/COW/wiki) provides more hands-on examples of transposing CSVs into Linked Data

### License

MIT License (see [license.txt](license.txt))

### Acknowledgements

**Authors:**    Albert Meroño-Peñuela, Roderick van der Weerdt, Rinke Hoekstra, Kathrin Dentler, Auke Rijpma, Richard Zijdeman, Melvin Roest, Xander Wilcke

**Copyright:**  Vrije Universiteit Amsterdam, Utrecht University, International Institute of Social History


CoW is developed and maintained by the CLARIAH project and funded by NWO.


%package help
Summary:	Development documents and examples for cow-csvw
Provides:	python3-cow-csvw-doc
%description help
## CoW: Integrated CSV to RDF Converter

> CoW (Csv on the Web) is an integrated CSV to RDF converter that uses the W3C standard [CSVW](https://www.w3.org/TR/tabular-data-primer/) for rich semantic table specificatons, and [nanopublications](http://nanopub.org/) as an output RDF model



### What is CoW

CoW is a command-line utility to convert any CSV file into an RDF dataset. Its distinctive features are:

- Expressive CSVW-compatible schemas based on the [Jinja](https://github.com/pallets/jinja) template enginge
- Highly efficient implementation leveraging multithreaded and multicore architectures
- Available as a pythonic [CLI tool](#cli), [library](#library), and [web service](#web-service)
- Supports Python 3

### Documentation and support
For user documentation see the basic introduction video https://t.co/SDWC3NhWZf and [wiki](https://github.com/clariah/cow/wiki/). Technical details are provided below. If you encounter an issue then please [report](https://github.com/CLARIAH/COW/issues/new/choose) it. Also feel free to create pull requests!

### Install (requires Python to be installed)

`pip3` is the recommended method of installing COW in your system:

```
pip3 install cow-csvw
```

You can upgrade your currently installed version with:

```
pip3 install cow-csvw --upgrade
```

Possible issues:

- Permission issues. You can get around them by installing CoW in user space: `pip3 install cow-csvw --user`. Make sure your binary user directory (typically something like `/Users/user/Library/Python/3.7/bin` in MacOS or `/home/user/.local/bin` in Linux) is in your PATH (in MacOS: `/etc/paths`. For Windows/MacOS we recommend to install Python via the [official distribution page](https://www.python.org/downloads/). You can also use [virtualenv](https://virtualenv.pypa.io/en/latest/) to avoid conflicts with your system libraries
- Please [report your unlisted issue](https://github.com/CLARIAH/CoW/issues/new)

If you can't/don't want to deal with installing CoW, you can use the [cattle](http://cattle.datalegend.net/) [web service version](#web-service) (deprecated).

### Usage

#### CLI

The CLI (command line interface) is the recommended way of using CoW for most users. The straightforward CSV to RDF conversion is done in two steps. First:

```
cow_tool build myfile.csv
```

This will create a file named `myfile.csv-metadata.json` (from now on: JSON schema file or just JSF). You don't need to worry about this file if you only want a syntactic conversion. Then:

```
cow_tool convert myfile.csv
```

Will output a `myfile.csv.nq` RDF file (nquads by default; you can control the output RDF serialization with e.g. ``--format turtle``). That's it!

If you want to control the base URI namespace, URIs used in predicates, virtual columns, and the many other features of CoW, you'll need to edit the `myfile.csv-metadata.json` JSF and/or use CoW arguments. Have a look at the [CLI options](#options) below, the examples in the [wiki](https://github.com/CLARIAH/CoW/wiki), and the [technical documentation](http://csvw-converter.readthedocs.io/en/latest/).

##### Options

Check the ``--help`` for a complete list of options:

```
usage: cow_tool [-h] [--dataset DATASET] [--delimiter DELIMITER]
                [--quotechar QUOTECHAR] [--encoding ENCODING] [--processes PROCESSES]
                [--chunksize CHUNKSIZE] [--base BASE]
                [--format [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}]]
				[--gzip] [--version]
                {convert,build} file [file ...]

Not nearly CSVW compliant schema builder and RDF converter

positional arguments:
  {convert,build}       Use the schema of the `file` specified to convert it
                        to RDF, or build a schema from scratch.
  file                  Path(s) of the file(s) that should be used for
                        building or converting. Must be a CSV file.

optional arguments:
  -h, --help            show this help message and exit
  --dataset DATASET     A short name (slug) for the name of the dataset (will
                        use input file name if not specified)
  --delimiter DELIMITER
                        The delimiter used in the CSV file(s)
  --quotechar QUOTECHAR
                        The character used as quotation character in the CSV
                        file(s)
  --encoding ENCODING   The character encoding used in the CSV file(s)

  --processes PROCESSES
                        The number of processes the converter should use
  --chunksize CHUNKSIZE
                        The number of rows processed at each time
  --base BASE           The base for URIs generated with the schema (only
                        relevant when `build`ing a schema)
  --gzip 				Compress the output file using gzip
  --format [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}], -f [{xml,n3,turtle,nt,pretty-xml,trix,trig,nquads}]
                        RDF serialization format
  --version             show program's version number and exit
```

#### Web service

There is web service and interface running CoW, called [cattle](http://cattle.datalegend.net/). Two public instances are running at:

- http://cattle.datalegend.net/ - runs CoW in Python3
- http://legacy.cattle.datalegend.net/ - runs CoW in Python2 for legacy reasons

Beware of the web service limitations:

- There's a limit to the size of the CSVs you can upload
- It's a public instance, so your conversion could take longer
- Cattle is no longer being maintained and these public instances will eventually be taken offline

#### Library

Once installed, CoW can be used as a library as follows:

```
from cow_csvw.csvw_tool import COW
import os

COW(mode='build', files=[os.path.join(path, filename)], dataset='My dataset', delimiter=';', quotechar='\"')

COW(mode='convert', files=[os.path.join(path, filename)], dataset='My dataset', delimiter=';', quotechar='\"', processes=4, chunksize=100, base='http://example.org/my-dataset', format='turtle', gzipped=False)
```

### Technical documentation

Technical documentation for CoW are maintained in this GitHub repository (under <docs>), and published through [Read the Docs](http://readthedocs.org) at <http://csvw-converter.readthedocs.io/en/latest/>.

To build the documentation from source, change into the `docs` directory, and run `make html`. This should produce an HTML version of the documentation in the `_build/html` directory.

### Examples

The [wiki](https://github.com/CLARIAH/COW/wiki) provides more hands-on examples of transposing CSVs into Linked Data

### License

MIT License (see [license.txt](license.txt))

### Acknowledgements

**Authors:**    Albert Meroño-Peñuela, Roderick van der Weerdt, Rinke Hoekstra, Kathrin Dentler, Auke Rijpma, Richard Zijdeman, Melvin Roest, Xander Wilcke

**Copyright:**  Vrije Universiteit Amsterdam, Utrecht University, International Institute of Social History


CoW is developed and maintained by the CLARIAH project and funded by NWO.


%prep
%autosetup -n cow-csvw-1.21

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-cow-csvw -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri Apr 21 2023 Python_Bot <Python_Bot@openeuler.org> - 1.21-1
- Package Spec generated