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%global _empty_manifest_terminate_build 0
Name:		python-csvw
Version:	3.1.3
Release:	1
Summary:	Python library to work with CSVW described tabular data
License:	Apache 2.0
URL:		https://github.com/cldf/csvw
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/c1/b2/bbd8d72578de1778f39d7ed43f899b7f9ff261fe41738a02acb97660bf4d/csvw-3.1.3.tar.gz
BuildArch:	noarch

Requires:	python3-attrs
Requires:	python3-babel
Requires:	python3-colorama
Requires:	python3-isodate
Requires:	python3-jsonschema
Requires:	python3-language-tags
Requires:	python3-dateutil
Requires:	python3-rdflib
Requires:	python3-requests
Requires:	python3-rfc3986
Requires:	python3-uritemplate
Requires:	python3-build
Requires:	python3-flake8
Requires:	python3-twine
Requires:	python3-wheel
Requires:	python3-sphinx
Requires:	python3-sphinx-autodoc-typehints
Requires:	python3-sphinx-rtd-theme
Requires:	python3-frictionless
Requires:	python3-pytest-cov
Requires:	python3-pytest-mock
Requires:	python3-pytest
Requires:	python3-requests-mock

%description
# csvw

[![Build Status](https://github.com/cldf/csvw/workflows/tests/badge.svg)](https://github.com/cldf/csvw/actions?query=workflow%3Atests)
[![PyPI](https://img.shields.io/pypi/v/csvw.svg)](https://pypi.org/project/csvw)
[![Documentation Status](https://readthedocs.org/projects/csvw/badge/?version=latest)](https://csvw.readthedocs.io/en/latest/?badge=latest)


This package provides
- a Python API to read and write relational, tabular data according to the [CSV on the Web](https://csvw.org/) specification and 
- commandline tools for reading and validating CSVW data.


## Links

- GitHub: https://github.com/cldf/csvw
- PyPI: https://pypi.org/project/csvw
- Issue Tracker: https://github.com/cldf/csvw/issues


## Installation

This package runs under Python >=3.7, use pip to install:

```bash
$ pip install csvw
```


## CLI

### `csvw2json`

Converting CSVW data [to JSON](https://www.w3.org/TR/csv2json/)

```shell
$ csvw2json tests/fixtures/zipped-metadata.json 
{
    "tables": [
        {
            "url": "tests/fixtures/zipped.csv",
            "row": [
                {
                    "url": "tests/fixtures/zipped.csv#row=2",
                    "rownum": 1,
                    "describes": [
                        {
                            "ID": "abc",
                            "Value": "the value"
                        }
                    ]
                },
                {
                    "url": "tests/fixtures/zipped.csv#row=3",
                    "rownum": 2,
                    "describes": [
                        {
                            "ID": "cde",
                            "Value": "another one"
                        }
                    ]
                }
            ]
        }
    ]
}
```

### `csvwvalidate`

Validating CSVW data

```shell
$ csvwvalidate tests/fixtures/zipped-metadata.json 
OK
```

### `csvwdescribe`

Describing tabular-data files with CSVW metadata

```shell
$ csvwdescribe --delimiter "|" tests/fixtures/frictionless-data.csv
{
    "@context": "http://www.w3.org/ns/csvw",
    "dc:conformsTo": "data-package",
    "tables": [
        {
            "dialect": {
                "delimiter": "|"
            },
            "tableSchema": {
                "columns": [
                    {
                        "datatype": "string",
                        "name": "FK"
                    },
                    {
                        "datatype": "integer",
                        "name": "Year"
                    },
                    {
                        "datatype": "string",
                        "name": "Location name"
                    },
                    {
                        "datatype": "string",
                        "name": "Value"
                    },
                    {
                        "datatype": "string",
                        "name": "binary"
                    },
                    {
                        "datatype": "string",
                        "name": "anyURI"
                    },
                    {
                        "datatype": "string",
                        "name": "email"
                    },
                    {
                        "datatype": "string",
                        "name": "boolean"
                    },
                    {
                        "datatype": {
                            "dc:format": "application/json",
                            "base": "json"
                        },
                        "name": "array"
                    },
                    {
                        "datatype": {
                            "dc:format": "application/json",
                            "base": "json"
                        },
                        "name": "geojson"
                    }
                ]
            },
            "url": "tests/fixtures/frictionless-data.csv"
        }
    ]
}
```


## Python API

Find the Python API documentation at [csvw.readthedocs.io](https://csvw.readthedocs.io/en/latest/).

A quick example for using `csvw` from Python code:

```python
import json
from csvw import CSVW
data = CSVW('https://raw.githubusercontent.com/cldf/csvw/master/tests/fixtures/test.tsv')
print(json.dumps(data.to_json(minimal=True), indent=4))
[
    {
        "province": "Hello",
        "territory": "world",
        "precinct": "1"
    }
]
```


## Known limitations

- We read **all** data which is specified as UTF-8 encoded using the 
  [`utf-8-sig` codecs](https://docs.python.org/3/library/codecs.html#module-encodings.utf_8_sig).
  Thus, if such data starts with `U+FEFF` this will be interpreted as [BOM](https://en.wikipedia.org/wiki/Byte_order_mark)
  and skipped.
- Low level CSV parsing is delegated to the `csv` module in Python's standard library. Thus, if a `commentPrefix`
  is specified in a `Dialect` instance, this will lead to skipping rows where the first value starts
  with `commentPrefix`, **even if the value was quoted**.
- Also, cell content containing `escapechar` may not be round-tripped as expected (when specifying
  `escapechar` or a `csvw.Dialect` with `quoteChar` but `doubleQuote==False`),
  when minimal quoting is specified. This is due to inconsistent `csv` behaviour
  across Python versions (see https://bugs.python.org/issue44861).


## CSVW conformance

While we use the CSVW specification as guideline, this package does not (and 
probably never will) implement the full extent of this spec.

- When CSV files with a header are read, columns are not matched in order with
  column descriptions in the `tableSchema`, but instead are matched based on the
  CSV column header and the column descriptions' `name` and `titles` atributes.
  This allows for more flexibility, because columns in the CSV file may be
  re-ordered without invalidating the metadata. A stricter matching can be forced
  by specifying `"header": false` and `"skipRows": 1` in the table's dialect
  description.

However, `csvw.CSVW` works correctly for
- 269 out of 270 [JSON tests](https://w3c.github.io/csvw/tests/#manifest-json),
- 280 out of 282 [validation tests](https://w3c.github.io/csvw/tests/#manifest-validation),
- 10 out of 18 [non-normative tests](https://w3c.github.io/csvw/tests/#manifest-nonnorm)

from the [CSVW Test suites](https://w3c.github.io/csvw/tests/).


## Compatibility with [Frictionless Data Specs](https://specs.frictionlessdata.io/)

A CSVW-described dataset is basically equivalent to a Frictionless DataPackage where all 
[Data Resources](https://specs.frictionlessdata.io/data-resource/) are [Tabular Data](https://specs.frictionlessdata.io/tabular-data-resource/).
Thus, the `csvw` package provides some conversion functionality. To
"read CSVW data from a Data Package", there's the `csvw.TableGroup.from_frictionless_datapackage` method:
```python
from csvw import TableGroup
tg = TableGroup.from_frictionless_datapackage('PATH/TO/datapackage.json')
```
To convert the metadata, the `TableGroup` can then be serialzed:
```python
tg.to_file('csvw-metadata.json')
```

Note that the CSVW metadata file must be written to the Data Package's directory
to make sure relative paths to data resources work.

This functionality - together with the schema inference capabilities
of [`frictionless describe`](https://framework.frictionlessdata.io/docs/guides/describing-data/) - provides
a convenient way to bootstrap CSVW metadata for a set of "raw" CSV
files, implemented in the [`csvwdescribe` command described above](#csvwdescribe).


## See also

- https://www.w3.org/2013/csvw/wiki/Main_Page
- https://csvw.org
- https://github.com/CLARIAH/COW
- https://github.com/CLARIAH/ruminator
- https://github.com/bloomberg/pycsvw
- https://specs.frictionlessdata.io/table-schema/
- https://github.com/theodi/csvlint.rb
- https://github.com/ruby-rdf/rdf-tabular
- https://github.com/rdf-ext/rdf-parser-csvw
- https://github.com/Robsteranium/csvwr


## License

This package is distributed under the [Apache 2.0 license](https://opensource.org/licenses/Apache-2.0).




%package -n python3-csvw
Summary:	Python library to work with CSVW described tabular data
Provides:	python-csvw
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-csvw
# csvw

[![Build Status](https://github.com/cldf/csvw/workflows/tests/badge.svg)](https://github.com/cldf/csvw/actions?query=workflow%3Atests)
[![PyPI](https://img.shields.io/pypi/v/csvw.svg)](https://pypi.org/project/csvw)
[![Documentation Status](https://readthedocs.org/projects/csvw/badge/?version=latest)](https://csvw.readthedocs.io/en/latest/?badge=latest)


This package provides
- a Python API to read and write relational, tabular data according to the [CSV on the Web](https://csvw.org/) specification and 
- commandline tools for reading and validating CSVW data.


## Links

- GitHub: https://github.com/cldf/csvw
- PyPI: https://pypi.org/project/csvw
- Issue Tracker: https://github.com/cldf/csvw/issues


## Installation

This package runs under Python >=3.7, use pip to install:

```bash
$ pip install csvw
```


## CLI

### `csvw2json`

Converting CSVW data [to JSON](https://www.w3.org/TR/csv2json/)

```shell
$ csvw2json tests/fixtures/zipped-metadata.json 
{
    "tables": [
        {
            "url": "tests/fixtures/zipped.csv",
            "row": [
                {
                    "url": "tests/fixtures/zipped.csv#row=2",
                    "rownum": 1,
                    "describes": [
                        {
                            "ID": "abc",
                            "Value": "the value"
                        }
                    ]
                },
                {
                    "url": "tests/fixtures/zipped.csv#row=3",
                    "rownum": 2,
                    "describes": [
                        {
                            "ID": "cde",
                            "Value": "another one"
                        }
                    ]
                }
            ]
        }
    ]
}
```

### `csvwvalidate`

Validating CSVW data

```shell
$ csvwvalidate tests/fixtures/zipped-metadata.json 
OK
```

### `csvwdescribe`

Describing tabular-data files with CSVW metadata

```shell
$ csvwdescribe --delimiter "|" tests/fixtures/frictionless-data.csv
{
    "@context": "http://www.w3.org/ns/csvw",
    "dc:conformsTo": "data-package",
    "tables": [
        {
            "dialect": {
                "delimiter": "|"
            },
            "tableSchema": {
                "columns": [
                    {
                        "datatype": "string",
                        "name": "FK"
                    },
                    {
                        "datatype": "integer",
                        "name": "Year"
                    },
                    {
                        "datatype": "string",
                        "name": "Location name"
                    },
                    {
                        "datatype": "string",
                        "name": "Value"
                    },
                    {
                        "datatype": "string",
                        "name": "binary"
                    },
                    {
                        "datatype": "string",
                        "name": "anyURI"
                    },
                    {
                        "datatype": "string",
                        "name": "email"
                    },
                    {
                        "datatype": "string",
                        "name": "boolean"
                    },
                    {
                        "datatype": {
                            "dc:format": "application/json",
                            "base": "json"
                        },
                        "name": "array"
                    },
                    {
                        "datatype": {
                            "dc:format": "application/json",
                            "base": "json"
                        },
                        "name": "geojson"
                    }
                ]
            },
            "url": "tests/fixtures/frictionless-data.csv"
        }
    ]
}
```


## Python API

Find the Python API documentation at [csvw.readthedocs.io](https://csvw.readthedocs.io/en/latest/).

A quick example for using `csvw` from Python code:

```python
import json
from csvw import CSVW
data = CSVW('https://raw.githubusercontent.com/cldf/csvw/master/tests/fixtures/test.tsv')
print(json.dumps(data.to_json(minimal=True), indent=4))
[
    {
        "province": "Hello",
        "territory": "world",
        "precinct": "1"
    }
]
```


## Known limitations

- We read **all** data which is specified as UTF-8 encoded using the 
  [`utf-8-sig` codecs](https://docs.python.org/3/library/codecs.html#module-encodings.utf_8_sig).
  Thus, if such data starts with `U+FEFF` this will be interpreted as [BOM](https://en.wikipedia.org/wiki/Byte_order_mark)
  and skipped.
- Low level CSV parsing is delegated to the `csv` module in Python's standard library. Thus, if a `commentPrefix`
  is specified in a `Dialect` instance, this will lead to skipping rows where the first value starts
  with `commentPrefix`, **even if the value was quoted**.
- Also, cell content containing `escapechar` may not be round-tripped as expected (when specifying
  `escapechar` or a `csvw.Dialect` with `quoteChar` but `doubleQuote==False`),
  when minimal quoting is specified. This is due to inconsistent `csv` behaviour
  across Python versions (see https://bugs.python.org/issue44861).


## CSVW conformance

While we use the CSVW specification as guideline, this package does not (and 
probably never will) implement the full extent of this spec.

- When CSV files with a header are read, columns are not matched in order with
  column descriptions in the `tableSchema`, but instead are matched based on the
  CSV column header and the column descriptions' `name` and `titles` atributes.
  This allows for more flexibility, because columns in the CSV file may be
  re-ordered without invalidating the metadata. A stricter matching can be forced
  by specifying `"header": false` and `"skipRows": 1` in the table's dialect
  description.

However, `csvw.CSVW` works correctly for
- 269 out of 270 [JSON tests](https://w3c.github.io/csvw/tests/#manifest-json),
- 280 out of 282 [validation tests](https://w3c.github.io/csvw/tests/#manifest-validation),
- 10 out of 18 [non-normative tests](https://w3c.github.io/csvw/tests/#manifest-nonnorm)

from the [CSVW Test suites](https://w3c.github.io/csvw/tests/).


## Compatibility with [Frictionless Data Specs](https://specs.frictionlessdata.io/)

A CSVW-described dataset is basically equivalent to a Frictionless DataPackage where all 
[Data Resources](https://specs.frictionlessdata.io/data-resource/) are [Tabular Data](https://specs.frictionlessdata.io/tabular-data-resource/).
Thus, the `csvw` package provides some conversion functionality. To
"read CSVW data from a Data Package", there's the `csvw.TableGroup.from_frictionless_datapackage` method:
```python
from csvw import TableGroup
tg = TableGroup.from_frictionless_datapackage('PATH/TO/datapackage.json')
```
To convert the metadata, the `TableGroup` can then be serialzed:
```python
tg.to_file('csvw-metadata.json')
```

Note that the CSVW metadata file must be written to the Data Package's directory
to make sure relative paths to data resources work.

This functionality - together with the schema inference capabilities
of [`frictionless describe`](https://framework.frictionlessdata.io/docs/guides/describing-data/) - provides
a convenient way to bootstrap CSVW metadata for a set of "raw" CSV
files, implemented in the [`csvwdescribe` command described above](#csvwdescribe).


## See also

- https://www.w3.org/2013/csvw/wiki/Main_Page
- https://csvw.org
- https://github.com/CLARIAH/COW
- https://github.com/CLARIAH/ruminator
- https://github.com/bloomberg/pycsvw
- https://specs.frictionlessdata.io/table-schema/
- https://github.com/theodi/csvlint.rb
- https://github.com/ruby-rdf/rdf-tabular
- https://github.com/rdf-ext/rdf-parser-csvw
- https://github.com/Robsteranium/csvwr


## License

This package is distributed under the [Apache 2.0 license](https://opensource.org/licenses/Apache-2.0).




%package help
Summary:	Development documents and examples for csvw
Provides:	python3-csvw-doc
%description help
# csvw

[![Build Status](https://github.com/cldf/csvw/workflows/tests/badge.svg)](https://github.com/cldf/csvw/actions?query=workflow%3Atests)
[![PyPI](https://img.shields.io/pypi/v/csvw.svg)](https://pypi.org/project/csvw)
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This package provides
- a Python API to read and write relational, tabular data according to the [CSV on the Web](https://csvw.org/) specification and 
- commandline tools for reading and validating CSVW data.


## Links

- GitHub: https://github.com/cldf/csvw
- PyPI: https://pypi.org/project/csvw
- Issue Tracker: https://github.com/cldf/csvw/issues


## Installation

This package runs under Python >=3.7, use pip to install:

```bash
$ pip install csvw
```


## CLI

### `csvw2json`

Converting CSVW data [to JSON](https://www.w3.org/TR/csv2json/)

```shell
$ csvw2json tests/fixtures/zipped-metadata.json 
{
    "tables": [
        {
            "url": "tests/fixtures/zipped.csv",
            "row": [
                {
                    "url": "tests/fixtures/zipped.csv#row=2",
                    "rownum": 1,
                    "describes": [
                        {
                            "ID": "abc",
                            "Value": "the value"
                        }
                    ]
                },
                {
                    "url": "tests/fixtures/zipped.csv#row=3",
                    "rownum": 2,
                    "describes": [
                        {
                            "ID": "cde",
                            "Value": "another one"
                        }
                    ]
                }
            ]
        }
    ]
}
```

### `csvwvalidate`

Validating CSVW data

```shell
$ csvwvalidate tests/fixtures/zipped-metadata.json 
OK
```

### `csvwdescribe`

Describing tabular-data files with CSVW metadata

```shell
$ csvwdescribe --delimiter "|" tests/fixtures/frictionless-data.csv
{
    "@context": "http://www.w3.org/ns/csvw",
    "dc:conformsTo": "data-package",
    "tables": [
        {
            "dialect": {
                "delimiter": "|"
            },
            "tableSchema": {
                "columns": [
                    {
                        "datatype": "string",
                        "name": "FK"
                    },
                    {
                        "datatype": "integer",
                        "name": "Year"
                    },
                    {
                        "datatype": "string",
                        "name": "Location name"
                    },
                    {
                        "datatype": "string",
                        "name": "Value"
                    },
                    {
                        "datatype": "string",
                        "name": "binary"
                    },
                    {
                        "datatype": "string",
                        "name": "anyURI"
                    },
                    {
                        "datatype": "string",
                        "name": "email"
                    },
                    {
                        "datatype": "string",
                        "name": "boolean"
                    },
                    {
                        "datatype": {
                            "dc:format": "application/json",
                            "base": "json"
                        },
                        "name": "array"
                    },
                    {
                        "datatype": {
                            "dc:format": "application/json",
                            "base": "json"
                        },
                        "name": "geojson"
                    }
                ]
            },
            "url": "tests/fixtures/frictionless-data.csv"
        }
    ]
}
```


## Python API

Find the Python API documentation at [csvw.readthedocs.io](https://csvw.readthedocs.io/en/latest/).

A quick example for using `csvw` from Python code:

```python
import json
from csvw import CSVW
data = CSVW('https://raw.githubusercontent.com/cldf/csvw/master/tests/fixtures/test.tsv')
print(json.dumps(data.to_json(minimal=True), indent=4))
[
    {
        "province": "Hello",
        "territory": "world",
        "precinct": "1"
    }
]
```


## Known limitations

- We read **all** data which is specified as UTF-8 encoded using the 
  [`utf-8-sig` codecs](https://docs.python.org/3/library/codecs.html#module-encodings.utf_8_sig).
  Thus, if such data starts with `U+FEFF` this will be interpreted as [BOM](https://en.wikipedia.org/wiki/Byte_order_mark)
  and skipped.
- Low level CSV parsing is delegated to the `csv` module in Python's standard library. Thus, if a `commentPrefix`
  is specified in a `Dialect` instance, this will lead to skipping rows where the first value starts
  with `commentPrefix`, **even if the value was quoted**.
- Also, cell content containing `escapechar` may not be round-tripped as expected (when specifying
  `escapechar` or a `csvw.Dialect` with `quoteChar` but `doubleQuote==False`),
  when minimal quoting is specified. This is due to inconsistent `csv` behaviour
  across Python versions (see https://bugs.python.org/issue44861).


## CSVW conformance

While we use the CSVW specification as guideline, this package does not (and 
probably never will) implement the full extent of this spec.

- When CSV files with a header are read, columns are not matched in order with
  column descriptions in the `tableSchema`, but instead are matched based on the
  CSV column header and the column descriptions' `name` and `titles` atributes.
  This allows for more flexibility, because columns in the CSV file may be
  re-ordered without invalidating the metadata. A stricter matching can be forced
  by specifying `"header": false` and `"skipRows": 1` in the table's dialect
  description.

However, `csvw.CSVW` works correctly for
- 269 out of 270 [JSON tests](https://w3c.github.io/csvw/tests/#manifest-json),
- 280 out of 282 [validation tests](https://w3c.github.io/csvw/tests/#manifest-validation),
- 10 out of 18 [non-normative tests](https://w3c.github.io/csvw/tests/#manifest-nonnorm)

from the [CSVW Test suites](https://w3c.github.io/csvw/tests/).


## Compatibility with [Frictionless Data Specs](https://specs.frictionlessdata.io/)

A CSVW-described dataset is basically equivalent to a Frictionless DataPackage where all 
[Data Resources](https://specs.frictionlessdata.io/data-resource/) are [Tabular Data](https://specs.frictionlessdata.io/tabular-data-resource/).
Thus, the `csvw` package provides some conversion functionality. To
"read CSVW data from a Data Package", there's the `csvw.TableGroup.from_frictionless_datapackage` method:
```python
from csvw import TableGroup
tg = TableGroup.from_frictionless_datapackage('PATH/TO/datapackage.json')
```
To convert the metadata, the `TableGroup` can then be serialzed:
```python
tg.to_file('csvw-metadata.json')
```

Note that the CSVW metadata file must be written to the Data Package's directory
to make sure relative paths to data resources work.

This functionality - together with the schema inference capabilities
of [`frictionless describe`](https://framework.frictionlessdata.io/docs/guides/describing-data/) - provides
a convenient way to bootstrap CSVW metadata for a set of "raw" CSV
files, implemented in the [`csvwdescribe` command described above](#csvwdescribe).


## See also

- https://www.w3.org/2013/csvw/wiki/Main_Page
- https://csvw.org
- https://github.com/CLARIAH/COW
- https://github.com/CLARIAH/ruminator
- https://github.com/bloomberg/pycsvw
- https://specs.frictionlessdata.io/table-schema/
- https://github.com/theodi/csvlint.rb
- https://github.com/ruby-rdf/rdf-tabular
- https://github.com/rdf-ext/rdf-parser-csvw
- https://github.com/Robsteranium/csvwr


## License

This package is distributed under the [Apache 2.0 license](https://opensource.org/licenses/Apache-2.0).




%prep
%autosetup -n csvw-3.1.3

%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-csvw -f filelist.lst
%dir %{python3_sitelib}/*

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

%changelog
* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 3.1.3-1
- Package Spec generated