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|
%global _empty_manifest_terminate_build 0
Name: python-iops
Version: 0.5.1
Release: 1
Summary: Open-source Python release of the IO-PS package
License: MIT License
URL: https://github.com/WoutersResearchGroup/py-IO-PS
Source0: https://mirrors.aliyun.com/pypi/web/packages/3b/07/05bbfac58aa25ef5e35c281cef8fb0bd3689a8f6abeff19bd2e682b93b49/iops-0.5.1.tar.gz
BuildArch: noarch
%description
# py-IO-PS
Public repository of developmental Python code related to research on the input-output product space (IO-PS)
[Described in Bam, W., & De Bruyne, K. (2019). Improving Industrial Policy Intervention: The Case of Steel in South Africa. The Journal of Development Studies, 55(11), 2460–2475. https://doi.org/10.1080/00220388.2018.1528354]
## Package
### Installation
The package is available from the Python Package Index: https://pypi.org/project/iops/
```text
pip install iops
pip install ecomplexity
```
### Usage
CEPII-BACI trade data is a required input (.csv). The BACI data is available at: http://www.cepii.fr/CEPII/fr/bdd_modele/presentation.asp?id=37
Full IO-PS analysis requires a value chain input (.csv). Three columns are required: 'Tier', 'Category' and 'HS Trade Code'.
```python
import pandas as pd
from iops import main
tradedata_df = pd.read_csv('BACI_HSXX_YXXXX_V202001.csv')
valuechain_df = pd.read_csv('X_Value_Chain.csv')
main.iops(tradedata_df,valuechain_df)
```
### Value Chain Output
Results are generated at tier, category and product level. Results are written to an Excel spreadsheet and headless CSV for each.
```text
Tier_Results.csv
Tier_Results.xlsx
Product_Category_Results.csv
Product_Category_Results.xlsx
Product_Results.csv
Product_Results.xlsx
```
### Function
```Python
def iops(tradedata, valuechain=None, countrycode=710, tradedigit=6, statanorm=False):
""" IO-PS calculation function that writes the results to .xls and .csv
Arguments:
tradedata: pandas dataframe containing raw CEPII-BACI trade data.
valuechain: .csv of the value chain the IO-PS will map.
columns - 'Tier', 'Category', 'HS Trade Code'
default - None
countrycode: integer indicating which country the IO-PS will map.
default - 710
tradedigit: Integer of 6 or 4 to indicate the raw trade digit summation level.
default - 6
statanorm: Boolean indicator of literature based or CID-Harvard STATA normalization.
default - False
"""
```
## Future Considerations
* User error warnings
* Investigate use of ecomplexity package fork
* Additional IO-PS metrics
* ECI and distance alignment
## References
### IO-PS
* Bam, W., & De Bruyne, K. (2017). Location policy and downstream mineral processing: A research agenda. Extractive Industries and Society, 4(3), 443–447. https://doi.org/10.1016/j.exis.2017.06.009
* Marais, M., & Bam, W. (2019). Developmental potential of the aerospace industry: the case of South Africa. In 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1–9). IEEE. https://doi.org/10.1109/ICE.2019.8792812
### Economic Complexity and Product Complexity
This packages uses a modified copy of the Growth Lab at Harvard's Center for International Development py-ecomplexity package. The ecomplexity package is used to calculate economic complexity indices: https://github.com/cid-harvard/py-ecomplexity
%package -n python3-iops
Summary: Open-source Python release of the IO-PS package
Provides: python-iops
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-iops
# py-IO-PS
Public repository of developmental Python code related to research on the input-output product space (IO-PS)
[Described in Bam, W., & De Bruyne, K. (2019). Improving Industrial Policy Intervention: The Case of Steel in South Africa. The Journal of Development Studies, 55(11), 2460–2475. https://doi.org/10.1080/00220388.2018.1528354]
## Package
### Installation
The package is available from the Python Package Index: https://pypi.org/project/iops/
```text
pip install iops
pip install ecomplexity
```
### Usage
CEPII-BACI trade data is a required input (.csv). The BACI data is available at: http://www.cepii.fr/CEPII/fr/bdd_modele/presentation.asp?id=37
Full IO-PS analysis requires a value chain input (.csv). Three columns are required: 'Tier', 'Category' and 'HS Trade Code'.
```python
import pandas as pd
from iops import main
tradedata_df = pd.read_csv('BACI_HSXX_YXXXX_V202001.csv')
valuechain_df = pd.read_csv('X_Value_Chain.csv')
main.iops(tradedata_df,valuechain_df)
```
### Value Chain Output
Results are generated at tier, category and product level. Results are written to an Excel spreadsheet and headless CSV for each.
```text
Tier_Results.csv
Tier_Results.xlsx
Product_Category_Results.csv
Product_Category_Results.xlsx
Product_Results.csv
Product_Results.xlsx
```
### Function
```Python
def iops(tradedata, valuechain=None, countrycode=710, tradedigit=6, statanorm=False):
""" IO-PS calculation function that writes the results to .xls and .csv
Arguments:
tradedata: pandas dataframe containing raw CEPII-BACI trade data.
valuechain: .csv of the value chain the IO-PS will map.
columns - 'Tier', 'Category', 'HS Trade Code'
default - None
countrycode: integer indicating which country the IO-PS will map.
default - 710
tradedigit: Integer of 6 or 4 to indicate the raw trade digit summation level.
default - 6
statanorm: Boolean indicator of literature based or CID-Harvard STATA normalization.
default - False
"""
```
## Future Considerations
* User error warnings
* Investigate use of ecomplexity package fork
* Additional IO-PS metrics
* ECI and distance alignment
## References
### IO-PS
* Bam, W., & De Bruyne, K. (2017). Location policy and downstream mineral processing: A research agenda. Extractive Industries and Society, 4(3), 443–447. https://doi.org/10.1016/j.exis.2017.06.009
* Marais, M., & Bam, W. (2019). Developmental potential of the aerospace industry: the case of South Africa. In 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1–9). IEEE. https://doi.org/10.1109/ICE.2019.8792812
### Economic Complexity and Product Complexity
This packages uses a modified copy of the Growth Lab at Harvard's Center for International Development py-ecomplexity package. The ecomplexity package is used to calculate economic complexity indices: https://github.com/cid-harvard/py-ecomplexity
%package help
Summary: Development documents and examples for iops
Provides: python3-iops-doc
%description help
# py-IO-PS
Public repository of developmental Python code related to research on the input-output product space (IO-PS)
[Described in Bam, W., & De Bruyne, K. (2019). Improving Industrial Policy Intervention: The Case of Steel in South Africa. The Journal of Development Studies, 55(11), 2460–2475. https://doi.org/10.1080/00220388.2018.1528354]
## Package
### Installation
The package is available from the Python Package Index: https://pypi.org/project/iops/
```text
pip install iops
pip install ecomplexity
```
### Usage
CEPII-BACI trade data is a required input (.csv). The BACI data is available at: http://www.cepii.fr/CEPII/fr/bdd_modele/presentation.asp?id=37
Full IO-PS analysis requires a value chain input (.csv). Three columns are required: 'Tier', 'Category' and 'HS Trade Code'.
```python
import pandas as pd
from iops import main
tradedata_df = pd.read_csv('BACI_HSXX_YXXXX_V202001.csv')
valuechain_df = pd.read_csv('X_Value_Chain.csv')
main.iops(tradedata_df,valuechain_df)
```
### Value Chain Output
Results are generated at tier, category and product level. Results are written to an Excel spreadsheet and headless CSV for each.
```text
Tier_Results.csv
Tier_Results.xlsx
Product_Category_Results.csv
Product_Category_Results.xlsx
Product_Results.csv
Product_Results.xlsx
```
### Function
```Python
def iops(tradedata, valuechain=None, countrycode=710, tradedigit=6, statanorm=False):
""" IO-PS calculation function that writes the results to .xls and .csv
Arguments:
tradedata: pandas dataframe containing raw CEPII-BACI trade data.
valuechain: .csv of the value chain the IO-PS will map.
columns - 'Tier', 'Category', 'HS Trade Code'
default - None
countrycode: integer indicating which country the IO-PS will map.
default - 710
tradedigit: Integer of 6 or 4 to indicate the raw trade digit summation level.
default - 6
statanorm: Boolean indicator of literature based or CID-Harvard STATA normalization.
default - False
"""
```
## Future Considerations
* User error warnings
* Investigate use of ecomplexity package fork
* Additional IO-PS metrics
* ECI and distance alignment
## References
### IO-PS
* Bam, W., & De Bruyne, K. (2017). Location policy and downstream mineral processing: A research agenda. Extractive Industries and Society, 4(3), 443–447. https://doi.org/10.1016/j.exis.2017.06.009
* Marais, M., & Bam, W. (2019). Developmental potential of the aerospace industry: the case of South Africa. In 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1–9). IEEE. https://doi.org/10.1109/ICE.2019.8792812
### Economic Complexity and Product Complexity
This packages uses a modified copy of the Growth Lab at Harvard's Center for International Development py-ecomplexity package. The ecomplexity package is used to calculate economic complexity indices: https://github.com/cid-harvard/py-ecomplexity
%prep
%autosetup -n iops-0.5.1
%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-iops -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri Jun 09 2023 Python_Bot <Python_Bot@openeuler.org> - 0.5.1-1
- Package Spec generated
|
