%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 ), and published through [Read the Docs](http://readthedocs.org) at . 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 ), and published through [Read the Docs](http://readthedocs.org) at . 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 ), and published through [Read the Docs](http://readthedocs.org) at . 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 - 1.21-1 - Package Spec generated