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@@ -0,0 +1 @@ +/dbt2looker-0.11.0.tar.gz diff --git a/python-dbt2looker.spec b/python-dbt2looker.spec new file mode 100644 index 0000000..4261679 --- /dev/null +++ b/python-dbt2looker.spec @@ -0,0 +1,332 @@ +%global _empty_manifest_terminate_build 0 +Name: python-dbt2looker +Version: 0.11.0 +Release: 1 +Summary: Generate lookml view files from dbt models +License: MIT +URL: https://github.com/hubble-data/dbt2looker +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/9e/e9/30e36510fc149b5b92d44809e80f33fbdfebe2742ecd1b3ad839c4f7b48d/dbt2looker-0.11.0.tar.gz +BuildArch: noarch + +Requires: python3-lkml +Requires: python3-pydantic +Requires: python3-PyYAML +Requires: python3-typing-extensions +Requires: python3-importlib-metadata + +%description +# dbt2looker + +Use `dbt2looker` to generate Looker view files automatically from dbt models. + +Want a deeper integration between dbt and your BI tool? You should also checkout [Lightdash - the open source alternative to Looker](https://github.com/lightdash/lightdash) + +**Features** + +* **Column descriptions** synced to looker +* **Dimension** for each column in dbt model +* **Dimension groups** for datetime/timestamp/date columns +* **Measures** defined through dbt column `metadata` [see below](#defining-measures) +* Looker types +* Warehouses: BigQuery, Snowflake, Redshift (postgres to come) + +[](https://asciinema.org/a/407407) + +## Quickstart + +Run `dbt2looker` in the root of your dbt project *after compiling looker docs*. + +**Generate Looker view files for all models:** +```shell +dbt docs generate +dbt2looker +``` + +**Generate Looker view files for all models tagged `prod`** +```shell +dbt2looker --tag prod +``` + +## Install + +**Install from PyPi repository** + +Install from pypi into a fresh virtual environment. + +``` +# Create virtual env +python3.7 -m venv dbt2looker-venv +source dbt2looker-venv/bin/activate + +# Install +pip install dbt2looker + +# Run +dbt2looker +``` + +**Build from source** + +Requires [poetry](https://python-poetry.org/docs/) and python >=3.7 + +For development, it is recommended to use python 3.7: + +``` +# Ensure you're using 3.7 +poetry env use 3.7 +# alternative: poetry env use /usr/local/opt/python@3.7/bin/python3 + +# Install dependencies and main package +poetry install + +# Run dbtlooker in poetry environment +poetry run dbt2looker +``` + +## Defining measures + +You can define looker measures in your dbt `schema.yml` files. For example: + +```yaml +models: + - name: pages + columns: + - name: url + description: "Page url" + - name: event_id + description: unique event id for page view + meta: + measures: + page_views: + type: count +``` + + +%package -n python3-dbt2looker +Summary: Generate lookml view files from dbt models +Provides: python-dbt2looker +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-dbt2looker +# dbt2looker + +Use `dbt2looker` to generate Looker view files automatically from dbt models. + +Want a deeper integration between dbt and your BI tool? You should also checkout [Lightdash - the open source alternative to Looker](https://github.com/lightdash/lightdash) + +**Features** + +* **Column descriptions** synced to looker +* **Dimension** for each column in dbt model +* **Dimension groups** for datetime/timestamp/date columns +* **Measures** defined through dbt column `metadata` [see below](#defining-measures) +* Looker types +* Warehouses: BigQuery, Snowflake, Redshift (postgres to come) + +[](https://asciinema.org/a/407407) + +## Quickstart + +Run `dbt2looker` in the root of your dbt project *after compiling looker docs*. + +**Generate Looker view files for all models:** +```shell +dbt docs generate +dbt2looker +``` + +**Generate Looker view files for all models tagged `prod`** +```shell +dbt2looker --tag prod +``` + +## Install + +**Install from PyPi repository** + +Install from pypi into a fresh virtual environment. + +``` +# Create virtual env +python3.7 -m venv dbt2looker-venv +source dbt2looker-venv/bin/activate + +# Install +pip install dbt2looker + +# Run +dbt2looker +``` + +**Build from source** + +Requires [poetry](https://python-poetry.org/docs/) and python >=3.7 + +For development, it is recommended to use python 3.7: + +``` +# Ensure you're using 3.7 +poetry env use 3.7 +# alternative: poetry env use /usr/local/opt/python@3.7/bin/python3 + +# Install dependencies and main package +poetry install + +# Run dbtlooker in poetry environment +poetry run dbt2looker +``` + +## Defining measures + +You can define looker measures in your dbt `schema.yml` files. For example: + +```yaml +models: + - name: pages + columns: + - name: url + description: "Page url" + - name: event_id + description: unique event id for page view + meta: + measures: + page_views: + type: count +``` + + +%package help +Summary: Development documents and examples for dbt2looker +Provides: python3-dbt2looker-doc +%description help +# dbt2looker + +Use `dbt2looker` to generate Looker view files automatically from dbt models. + +Want a deeper integration between dbt and your BI tool? You should also checkout [Lightdash - the open source alternative to Looker](https://github.com/lightdash/lightdash) + +**Features** + +* **Column descriptions** synced to looker +* **Dimension** for each column in dbt model +* **Dimension groups** for datetime/timestamp/date columns +* **Measures** defined through dbt column `metadata` [see below](#defining-measures) +* Looker types +* Warehouses: BigQuery, Snowflake, Redshift (postgres to come) + +[](https://asciinema.org/a/407407) + +## Quickstart + +Run `dbt2looker` in the root of your dbt project *after compiling looker docs*. + +**Generate Looker view files for all models:** +```shell +dbt docs generate +dbt2looker +``` + +**Generate Looker view files for all models tagged `prod`** +```shell +dbt2looker --tag prod +``` + +## Install + +**Install from PyPi repository** + +Install from pypi into a fresh virtual environment. + +``` +# Create virtual env +python3.7 -m venv dbt2looker-venv +source dbt2looker-venv/bin/activate + +# Install +pip install dbt2looker + +# Run +dbt2looker +``` + +**Build from source** + +Requires [poetry](https://python-poetry.org/docs/) and python >=3.7 + +For development, it is recommended to use python 3.7: + +``` +# Ensure you're using 3.7 +poetry env use 3.7 +# alternative: poetry env use /usr/local/opt/python@3.7/bin/python3 + +# Install dependencies and main package +poetry install + +# Run dbtlooker in poetry environment +poetry run dbt2looker +``` + +## Defining measures + +You can define looker measures in your dbt `schema.yml` files. For example: + +```yaml +models: + - name: pages + columns: + - name: url + description: "Page url" + - name: event_id + description: unique event id for page view + meta: + measures: + page_views: + type: count +``` + + +%prep +%autosetup -n dbt2looker-0.11.0 + +%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-dbt2looker -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.11.0-1 +- Package Spec generated @@ -0,0 +1 @@ +1edfcdda0a01b80a66839005fea358af dbt2looker-0.11.0.tar.gz |