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diff --git a/python-rediz.spec b/python-rediz.spec new file mode 100644 index 0000000..cb659cb --- /dev/null +++ b/python-rediz.spec @@ -0,0 +1,227 @@ +%global _empty_manifest_terminate_build 0 +Name: python-rediz +Version: 1.0.12 +Release: 1 +Summary: Powering community nowcasts at www.microprediction.org +License: MIT +URL: https://github.com/microprediction/rediz +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/9f/41/0cbf558ccc0842b6884857697ffe7b6751df3b5f57b6de2e578f04e0b86e/rediz-1.0.12.tar.gz +BuildArch: noarch + +Requires: python3-microconventions +Requires: python3-fakeredis +Requires: python3-getjson +Requires: python3-redis +Requires: python3-sortedcontainers +Requires: python3-numpy +Requires: python3-pymorton +Requires: python3-scipy + +%description + + +# Rediz + +Server code for open community microprediction at www.microprediction.org. + +### Microprediction.Org + + + +### Overview + +The python packages called "microprediction" (user client library) and "rediz" (system implementation using redis as transport) are demonstrated at www.microprediction.org, where they +make it easy for anyone who needs a live source of data predicted to receive help from clever humans and self-navigating time series algorithms. They do this by: + + - Obtaining a write_key with microconventions.create_key(difficulty=12), which takes several hours + - Using the write_key to update a live quantity, such as https://www.microprediction.org/live/cop.json + - Repeating often. + +They can then access history (e.g. https://www.microprediction.org/live/lagged::cop.json) and predictions (e.g. https://www.microprediction.org/cdf/cop.json). This is an easy way to +normalize data and perform anomaly detection. Over time it may garner other insights such as assessment of the predictive value of the data stream the identities of streams that +might be causally related. + +This setup is especially well suited to collective prediction of civic data streams such as transport, water, electricity, public supply chain indicators or the spread of infectious diseases. The client +library +https://github.com/microprediction/rediz/blob/master/README.md and site www.microprediction.org provide more information. + +### Related packages and dependencies + + muid getjson + | | + microconventions + | | + rediz microprediction + + +- Conventions https://github.com/microprediction/microconventions/blob/master/README.md +- Microprediction https://github.com/microprediction/rediz/blob/master/README.md + +### Rediz details + +This may be a little stale. + + - https://github.com/microprediction/rediz/blob/master/README_REDIZ.md + - https://github.com/microprediction/rediz/blob/master/README_REDIZ_DETAILS.md + + + + + + +%package -n python3-rediz +Summary: Powering community nowcasts at www.microprediction.org +Provides: python-rediz +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-rediz + + +# Rediz + +Server code for open community microprediction at www.microprediction.org. + +### Microprediction.Org + + + +### Overview + +The python packages called "microprediction" (user client library) and "rediz" (system implementation using redis as transport) are demonstrated at www.microprediction.org, where they +make it easy for anyone who needs a live source of data predicted to receive help from clever humans and self-navigating time series algorithms. They do this by: + + - Obtaining a write_key with microconventions.create_key(difficulty=12), which takes several hours + - Using the write_key to update a live quantity, such as https://www.microprediction.org/live/cop.json + - Repeating often. + +They can then access history (e.g. https://www.microprediction.org/live/lagged::cop.json) and predictions (e.g. https://www.microprediction.org/cdf/cop.json). This is an easy way to +normalize data and perform anomaly detection. Over time it may garner other insights such as assessment of the predictive value of the data stream the identities of streams that +might be causally related. + +This setup is especially well suited to collective prediction of civic data streams such as transport, water, electricity, public supply chain indicators or the spread of infectious diseases. The client +library +https://github.com/microprediction/rediz/blob/master/README.md and site www.microprediction.org provide more information. + +### Related packages and dependencies + + muid getjson + | | + microconventions + | | + rediz microprediction + + +- Conventions https://github.com/microprediction/microconventions/blob/master/README.md +- Microprediction https://github.com/microprediction/rediz/blob/master/README.md + +### Rediz details + +This may be a little stale. + + - https://github.com/microprediction/rediz/blob/master/README_REDIZ.md + - https://github.com/microprediction/rediz/blob/master/README_REDIZ_DETAILS.md + + + + + + +%package help +Summary: Development documents and examples for rediz +Provides: python3-rediz-doc +%description help + + +# Rediz + +Server code for open community microprediction at www.microprediction.org. + +### Microprediction.Org + + + +### Overview + +The python packages called "microprediction" (user client library) and "rediz" (system implementation using redis as transport) are demonstrated at www.microprediction.org, where they +make it easy for anyone who needs a live source of data predicted to receive help from clever humans and self-navigating time series algorithms. They do this by: + + - Obtaining a write_key with microconventions.create_key(difficulty=12), which takes several hours + - Using the write_key to update a live quantity, such as https://www.microprediction.org/live/cop.json + - Repeating often. + +They can then access history (e.g. https://www.microprediction.org/live/lagged::cop.json) and predictions (e.g. https://www.microprediction.org/cdf/cop.json). This is an easy way to +normalize data and perform anomaly detection. Over time it may garner other insights such as assessment of the predictive value of the data stream the identities of streams that +might be causally related. + +This setup is especially well suited to collective prediction of civic data streams such as transport, water, electricity, public supply chain indicators or the spread of infectious diseases. The client +library +https://github.com/microprediction/rediz/blob/master/README.md and site www.microprediction.org provide more information. + +### Related packages and dependencies + + muid getjson + | | + microconventions + | | + rediz microprediction + + +- Conventions https://github.com/microprediction/microconventions/blob/master/README.md +- Microprediction https://github.com/microprediction/rediz/blob/master/README.md + +### Rediz details + +This may be a little stale. + + - https://github.com/microprediction/rediz/blob/master/README_REDIZ.md + - https://github.com/microprediction/rediz/blob/master/README_REDIZ_DETAILS.md + + + + + + +%prep +%autosetup -n rediz-1.0.12 + +%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-rediz -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.12-1 +- Package Spec generated |