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|
%global _empty_manifest_terminate_build 0
Name: python-curvenote
Version: 0.7.2
Release: 1
Summary: Helper library from Curvenote for data science in Jupyter notebooks
License: MIT License
URL: http://curvenote.com
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/71/f0/9cee6deca808eb3f38bda6d5d8c4e6c9bfc0eca8aabf0440ff8cc63a8b33/curvenote-0.7.2.tar.gz
BuildArch: noarch
Requires: python3-ipython
Requires: python3-pandas
Requires: python3-traitlets
Requires: python3-ipywidgets
%description
# curvenote
The Curvenote helper library for working in Jupyter Notebooks with Python kernels
## Installation
```bash
~$ python -m pip install curvenote
```
## Summary
- `stash` save a dict or pandas dataframe in a cell output without diaplying the data
```python
from curvenote import stash
stash('myvars', myvars)
```
- `AppState` a traitlet based class to help manage state in ipywidgets ui's
```python
from curvenote import AppState, with_state
state = AppState()
# register a widget in state
wave_1_amp = FloatSlider(1.0, min=0.1, max=5.0, step=0.1, description="1 - Amp")
state.register_stateful_widget(wave_1_amp, "wave_1_amp", Float(1.0))
# register any trailet as a propery
state.register_stateful_property("my_dict", Dict(dict(A="hello", B="world", C=1)))
# observe the entire state
def my_update_fn(state):
some_calc_function(state.wave_1_amp, state.my_dict)
state.observe(with_state(my_update_fn))
# observe a single registered widget
def wave_1_observer(evt):
pass
state.register_widget_observer("wave_1_amp", wave_1_observer)
# observe a single trait
def trait_observer(evt):
pass
state.register_widget_observer("my_dict", trait_observer)
# display state changes for debugging
from IPython.display import display
display(state.outlet)
```
%package -n python3-curvenote
Summary: Helper library from Curvenote for data science in Jupyter notebooks
Provides: python-curvenote
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-curvenote
# curvenote
The Curvenote helper library for working in Jupyter Notebooks with Python kernels
## Installation
```bash
~$ python -m pip install curvenote
```
## Summary
- `stash` save a dict or pandas dataframe in a cell output without diaplying the data
```python
from curvenote import stash
stash('myvars', myvars)
```
- `AppState` a traitlet based class to help manage state in ipywidgets ui's
```python
from curvenote import AppState, with_state
state = AppState()
# register a widget in state
wave_1_amp = FloatSlider(1.0, min=0.1, max=5.0, step=0.1, description="1 - Amp")
state.register_stateful_widget(wave_1_amp, "wave_1_amp", Float(1.0))
# register any trailet as a propery
state.register_stateful_property("my_dict", Dict(dict(A="hello", B="world", C=1)))
# observe the entire state
def my_update_fn(state):
some_calc_function(state.wave_1_amp, state.my_dict)
state.observe(with_state(my_update_fn))
# observe a single registered widget
def wave_1_observer(evt):
pass
state.register_widget_observer("wave_1_amp", wave_1_observer)
# observe a single trait
def trait_observer(evt):
pass
state.register_widget_observer("my_dict", trait_observer)
# display state changes for debugging
from IPython.display import display
display(state.outlet)
```
%package help
Summary: Development documents and examples for curvenote
Provides: python3-curvenote-doc
%description help
# curvenote
The Curvenote helper library for working in Jupyter Notebooks with Python kernels
## Installation
```bash
~$ python -m pip install curvenote
```
## Summary
- `stash` save a dict or pandas dataframe in a cell output without diaplying the data
```python
from curvenote import stash
stash('myvars', myvars)
```
- `AppState` a traitlet based class to help manage state in ipywidgets ui's
```python
from curvenote import AppState, with_state
state = AppState()
# register a widget in state
wave_1_amp = FloatSlider(1.0, min=0.1, max=5.0, step=0.1, description="1 - Amp")
state.register_stateful_widget(wave_1_amp, "wave_1_amp", Float(1.0))
# register any trailet as a propery
state.register_stateful_property("my_dict", Dict(dict(A="hello", B="world", C=1)))
# observe the entire state
def my_update_fn(state):
some_calc_function(state.wave_1_amp, state.my_dict)
state.observe(with_state(my_update_fn))
# observe a single registered widget
def wave_1_observer(evt):
pass
state.register_widget_observer("wave_1_amp", wave_1_observer)
# observe a single trait
def trait_observer(evt):
pass
state.register_widget_observer("my_dict", trait_observer)
# display state changes for debugging
from IPython.display import display
display(state.outlet)
```
%prep
%autosetup -n curvenote-0.7.2
%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-curvenote -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.2-1
- Package Spec generated
|
