automatic import of python-alfabetopeneuler20.03

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+/alfabet-0.4.1.tar.gz
diff --git a/python-alfabet.spec b/python-alfabet.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-alfabet
+Version:	0.4.1
+Release:	1
+Summary:	A library to estimate bond dissociation energies (BDEs) of organic molecules
+License:	MIT License
+URL:		https://github.com/NREL/alfabet
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/f0/51/0fac2d12ff586c42deea6785fdb7161a0f0ffdaee9c676a8699da25a8462/alfabet-0.4.1.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-pandas
+Requires:	python3-nfp
+Requires:	python3-tqdm
+Requires:	python3-pooch
+Requires:	python3-joblib
+Requires:	python3-scikit-learn
+
+%description
+![ALFABET logo](/docs/logo.svg)
+
+[![PyPI version](https://badge.fury.io/py/alfabet.svg)](https://badge.fury.io/py/alfabet)
+[![Build Status](https://travis-ci.com/NREL/alfabet.svg?branch=master)](https://travis-ci.com/NREL/alfabet)
+
+# A machine-Learning derived, Fast, Accurate Bond dissociation Enthalpy Tool (ALFABET)
+
+This library contains the trained graph neural network model for the prediction of homolytic bond dissociation energies (BDEs) of organic molecules with C, H, N, and O atoms. This package offers a command-line interface to the web-based model predictions at [bde.ml.nrel.gov](https://bde.ml.nrel.gov/).
+
+The basic interface works as follows, where `predict` expects a list of SMILES strings of the target molecules
+```python
+>>> from alfabet import model
+>>> model.predict(['CC', 'NCCO'])
+```
+```
+  molecule  bond_index bond_type fragment1 fragment2  ...    bde_pred  is_valid
+0       CC           0       C-C     [CH3]     [CH3]  ...   90.278282      True
+1       CC           1       C-H       [H]    [CH2]C  ...   99.346184      True
+2     NCCO           0       C-N   [CH2]CO     [NH2]  ...   89.988495      True
+3     NCCO           1       C-C    [CH2]O    [CH2]N  ...   82.122429      True
+4     NCCO           2       C-O   [CH2]CN      [OH]  ...   98.250961      True
+5     NCCO           3       H-N       [H]   [NH]CCO  ...   99.134750      True
+6     NCCO           5       C-H       [H]   N[CH]CO  ...   92.216087      True
+7     NCCO           7       C-H       [H]   NC[CH]O  ...   92.562988      True
+8     NCCO           9       H-O       [H]    NCC[O]  ...  105.120598      True
+```
+
+The model breaks all single, non-cyclic bonds in the input molecules and calculates their bond dissociation energies. Typical prediction errors are less than 1 kcal/mol. 
+The model is based on Tensorflow (2.x), and makes heavy use of the [neural fingerprint](github.com/NREL/nfp) library (0.1.x).
+
+For additional details, see the publication:
+St. John, P. C., Guan, Y., Kim, Y., Kim, S., & Paton, R. S. (2020). Prediction of organic homolytic bond dissociation enthalpies at near chemical accuracy with sub-second computational cost. Nature Communications, 11(1). doi:10.1038/s41467-020-16201-z
+
+*Note:* For the exact model described in the text, install `alfabet` version 0.0.x. Versions >0.1 have been updated for tensorflow 2.
+
+## Installation
+Installation with `conda` is recommended, as [`rdkit`](https://github.com/rdkit/rdkit) can otherwise be difficult to install
+
+```bash
+$ conda create -n alfabet -c conda-forge python=3.7 rdkit
+$ source activate alfabet
+$ pip install alfabet
+``
+
+
+%package -n python3-alfabet
+Summary:	A library to estimate bond dissociation energies (BDEs) of organic molecules
+Provides:	python-alfabet
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-alfabet
+![ALFABET logo](/docs/logo.svg)
+
+[![PyPI version](https://badge.fury.io/py/alfabet.svg)](https://badge.fury.io/py/alfabet)
+[![Build Status](https://travis-ci.com/NREL/alfabet.svg?branch=master)](https://travis-ci.com/NREL/alfabet)
+
+# A machine-Learning derived, Fast, Accurate Bond dissociation Enthalpy Tool (ALFABET)
+
+This library contains the trained graph neural network model for the prediction of homolytic bond dissociation energies (BDEs) of organic molecules with C, H, N, and O atoms. This package offers a command-line interface to the web-based model predictions at [bde.ml.nrel.gov](https://bde.ml.nrel.gov/).
+
+The basic interface works as follows, where `predict` expects a list of SMILES strings of the target molecules
+```python
+>>> from alfabet import model
+>>> model.predict(['CC', 'NCCO'])
+```
+```
+  molecule  bond_index bond_type fragment1 fragment2  ...    bde_pred  is_valid
+0       CC           0       C-C     [CH3]     [CH3]  ...   90.278282      True
+1       CC           1       C-H       [H]    [CH2]C  ...   99.346184      True
+2     NCCO           0       C-N   [CH2]CO     [NH2]  ...   89.988495      True
+3     NCCO           1       C-C    [CH2]O    [CH2]N  ...   82.122429      True
+4     NCCO           2       C-O   [CH2]CN      [OH]  ...   98.250961      True
+5     NCCO           3       H-N       [H]   [NH]CCO  ...   99.134750      True
+6     NCCO           5       C-H       [H]   N[CH]CO  ...   92.216087      True
+7     NCCO           7       C-H       [H]   NC[CH]O  ...   92.562988      True
+8     NCCO           9       H-O       [H]    NCC[O]  ...  105.120598      True
+```
+
+The model breaks all single, non-cyclic bonds in the input molecules and calculates their bond dissociation energies. Typical prediction errors are less than 1 kcal/mol. 
+The model is based on Tensorflow (2.x), and makes heavy use of the [neural fingerprint](github.com/NREL/nfp) library (0.1.x).
+
+For additional details, see the publication:
+St. John, P. C., Guan, Y., Kim, Y., Kim, S., & Paton, R. S. (2020). Prediction of organic homolytic bond dissociation enthalpies at near chemical accuracy with sub-second computational cost. Nature Communications, 11(1). doi:10.1038/s41467-020-16201-z
+
+*Note:* For the exact model described in the text, install `alfabet` version 0.0.x. Versions >0.1 have been updated for tensorflow 2.
+
+## Installation
+Installation with `conda` is recommended, as [`rdkit`](https://github.com/rdkit/rdkit) can otherwise be difficult to install
+
+```bash
+$ conda create -n alfabet -c conda-forge python=3.7 rdkit
+$ source activate alfabet
+$ pip install alfabet
+``
+
+
+%package help
+Summary:	Development documents and examples for alfabet
+Provides:	python3-alfabet-doc
+%description help
+![ALFABET logo](/docs/logo.svg)
+
+[![PyPI version](https://badge.fury.io/py/alfabet.svg)](https://badge.fury.io/py/alfabet)
+[![Build Status](https://travis-ci.com/NREL/alfabet.svg?branch=master)](https://travis-ci.com/NREL/alfabet)
+
+# A machine-Learning derived, Fast, Accurate Bond dissociation Enthalpy Tool (ALFABET)
+
+This library contains the trained graph neural network model for the prediction of homolytic bond dissociation energies (BDEs) of organic molecules with C, H, N, and O atoms. This package offers a command-line interface to the web-based model predictions at [bde.ml.nrel.gov](https://bde.ml.nrel.gov/).
+
+The basic interface works as follows, where `predict` expects a list of SMILES strings of the target molecules
+```python
+>>> from alfabet import model
+>>> model.predict(['CC', 'NCCO'])
+```
+```
+  molecule  bond_index bond_type fragment1 fragment2  ...    bde_pred  is_valid
+0       CC           0       C-C     [CH3]     [CH3]  ...   90.278282      True
+1       CC           1       C-H       [H]    [CH2]C  ...   99.346184      True
+2     NCCO           0       C-N   [CH2]CO     [NH2]  ...   89.988495      True
+3     NCCO           1       C-C    [CH2]O    [CH2]N  ...   82.122429      True
+4     NCCO           2       C-O   [CH2]CN      [OH]  ...   98.250961      True
+5     NCCO           3       H-N       [H]   [NH]CCO  ...   99.134750      True
+6     NCCO           5       C-H       [H]   N[CH]CO  ...   92.216087      True
+7     NCCO           7       C-H       [H]   NC[CH]O  ...   92.562988      True
+8     NCCO           9       H-O       [H]    NCC[O]  ...  105.120598      True
+```
+
+The model breaks all single, non-cyclic bonds in the input molecules and calculates their bond dissociation energies. Typical prediction errors are less than 1 kcal/mol. 
+The model is based on Tensorflow (2.x), and makes heavy use of the [neural fingerprint](github.com/NREL/nfp) library (0.1.x).
+
+For additional details, see the publication:
+St. John, P. C., Guan, Y., Kim, Y., Kim, S., & Paton, R. S. (2020). Prediction of organic homolytic bond dissociation enthalpies at near chemical accuracy with sub-second computational cost. Nature Communications, 11(1). doi:10.1038/s41467-020-16201-z
+
+*Note:* For the exact model described in the text, install `alfabet` version 0.0.x. Versions >0.1 have been updated for tensorflow 2.
+
+## Installation
+Installation with `conda` is recommended, as [`rdkit`](https://github.com/rdkit/rdkit) can otherwise be difficult to install
+
+```bash
+$ conda create -n alfabet -c conda-forge python=3.7 rdkit
+$ source activate alfabet
+$ pip install alfabet
+``
+
+
+%prep
+%autosetup -n alfabet-0.4.1
+
+%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-alfabet -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.1-1
+- Package Spec generated
diff --git a/sources b/sources
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+++ b/sources
@@ -0,0 +1 @@
+e4818146a2a9293d0597cd289d44a40c  alfabet-0.4.1.tar.gz