%global _empty_manifest_terminate_build 0 Name: python-foxrelax Version: 0.4.3 Release: 1 Summary: foxrelax License: BSD License URL: https://github.com/relaxdl/foxrelax Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a8/34/7b226da3d952768a620355fcf41d2de97bd0cd3a19ae28fe12f574a19d7b/foxrelax-0.4.3.tar.gz BuildArch: noarch Requires: python3-pandas Requires: python3-numpy Requires: python3-cython Requires: python3-requests Requires: python3-enum34 %description # foxrelax ## Project description * it’s easy to use because most of the data returned are pandas DataFrame objects * we have our own data server, efficient and stable operation * free stock market data * friendly to machine learning and data mining ## Target Users * learners of financial data analysis with pandas/NumPy * financial market analyst * financial data analysis enthusiasts * quanters who are interested in stock market ## Installation ```bash pip install foxrelax ``` ## Upgrade ```bash pip install foxrelax –upgrade ``` ## Quick Start ```python import foxrelax as relax resp = relax.stock_daily(symbol='000049.SZ', start_date='2018-01-01', end_date='2019-11-28') print('code={0} message={1}'.format(resp.code, resp.message)) print(resp.result) ``` return: ```text code=0 message=success symbol trade_date open high low close pre_close \ 0 000049.SZ 2018-01-02 39.91 40.18 39.22 39.78 39.59 1 000049.SZ 2018-01-03 39.90 40.59 39.71 40.56 39.78 2 000049.SZ 2018-01-04 41.61 43.18 41.61 42.65 40.56 3 000049.SZ 2018-01-05 42.00 42.45 41.51 42.07 42.65 4 000049.SZ 2018-01-08 42.08 42.38 41.32 41.49 42.07 5 000049.SZ 2018-01-09 41.50 41.60 40.60 40.80 41.49 ... 458 000049.SZ 2019-11-21 36.53 36.77 36.00 36.50 36.81 459 000049.SZ 2019-11-22 36.44 37.80 36.30 36.68 36.50 460 000049.SZ 2019-11-25 36.30 36.48 34.93 35.16 36.68 461 000049.SZ 2019-11-26 35.28 35.89 35.00 35.76 35.16 462 000049.SZ 2019-11-27 35.69 37.27 35.40 36.72 35.76 463 000049.SZ 2019-11-28 36.72 38.48 36.50 37.49 36.72 price_change pct_change volume money 0 0.19 0.4800 3197416 126769960 1 0.78 1.9600 3913276 157416236 2 2.09 5.1500 8300770 352188889 3 -0.58 -1.3600 4260338 178822929 4 -0.58 -1.3800 3569519 148331795 5 -0.69 -1.6600 3138719 128433609 ... 458 -0.31 -0.8422 4079903 148147523 459 0.18 0.4932 8250452 306343236 460 -1.52 -4.1439 6989292 247534854 461 0.60 1.7065 4304988 153468524 462 0.96 2.6846 7701535 281834519 463 0.77 2.0969 10463935 394639040 ``` %package -n python3-foxrelax Summary: foxrelax Provides: python-foxrelax BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-foxrelax # foxrelax ## Project description * it’s easy to use because most of the data returned are pandas DataFrame objects * we have our own data server, efficient and stable operation * free stock market data * friendly to machine learning and data mining ## Target Users * learners of financial data analysis with pandas/NumPy * financial market analyst * financial data analysis enthusiasts * quanters who are interested in stock market ## Installation ```bash pip install foxrelax ``` ## Upgrade ```bash pip install foxrelax –upgrade ``` ## Quick Start ```python import foxrelax as relax resp = relax.stock_daily(symbol='000049.SZ', start_date='2018-01-01', end_date='2019-11-28') print('code={0} message={1}'.format(resp.code, resp.message)) print(resp.result) ``` return: ```text code=0 message=success symbol trade_date open high low close pre_close \ 0 000049.SZ 2018-01-02 39.91 40.18 39.22 39.78 39.59 1 000049.SZ 2018-01-03 39.90 40.59 39.71 40.56 39.78 2 000049.SZ 2018-01-04 41.61 43.18 41.61 42.65 40.56 3 000049.SZ 2018-01-05 42.00 42.45 41.51 42.07 42.65 4 000049.SZ 2018-01-08 42.08 42.38 41.32 41.49 42.07 5 000049.SZ 2018-01-09 41.50 41.60 40.60 40.80 41.49 ... 458 000049.SZ 2019-11-21 36.53 36.77 36.00 36.50 36.81 459 000049.SZ 2019-11-22 36.44 37.80 36.30 36.68 36.50 460 000049.SZ 2019-11-25 36.30 36.48 34.93 35.16 36.68 461 000049.SZ 2019-11-26 35.28 35.89 35.00 35.76 35.16 462 000049.SZ 2019-11-27 35.69 37.27 35.40 36.72 35.76 463 000049.SZ 2019-11-28 36.72 38.48 36.50 37.49 36.72 price_change pct_change volume money 0 0.19 0.4800 3197416 126769960 1 0.78 1.9600 3913276 157416236 2 2.09 5.1500 8300770 352188889 3 -0.58 -1.3600 4260338 178822929 4 -0.58 -1.3800 3569519 148331795 5 -0.69 -1.6600 3138719 128433609 ... 458 -0.31 -0.8422 4079903 148147523 459 0.18 0.4932 8250452 306343236 460 -1.52 -4.1439 6989292 247534854 461 0.60 1.7065 4304988 153468524 462 0.96 2.6846 7701535 281834519 463 0.77 2.0969 10463935 394639040 ``` %package help Summary: Development documents and examples for foxrelax Provides: python3-foxrelax-doc %description help # foxrelax ## Project description * it’s easy to use because most of the data returned are pandas DataFrame objects * we have our own data server, efficient and stable operation * free stock market data * friendly to machine learning and data mining ## Target Users * learners of financial data analysis with pandas/NumPy * financial market analyst * financial data analysis enthusiasts * quanters who are interested in stock market ## Installation ```bash pip install foxrelax ``` ## Upgrade ```bash pip install foxrelax –upgrade ``` ## Quick Start ```python import foxrelax as relax resp = relax.stock_daily(symbol='000049.SZ', start_date='2018-01-01', end_date='2019-11-28') print('code={0} message={1}'.format(resp.code, resp.message)) print(resp.result) ``` return: ```text code=0 message=success symbol trade_date open high low close pre_close \ 0 000049.SZ 2018-01-02 39.91 40.18 39.22 39.78 39.59 1 000049.SZ 2018-01-03 39.90 40.59 39.71 40.56 39.78 2 000049.SZ 2018-01-04 41.61 43.18 41.61 42.65 40.56 3 000049.SZ 2018-01-05 42.00 42.45 41.51 42.07 42.65 4 000049.SZ 2018-01-08 42.08 42.38 41.32 41.49 42.07 5 000049.SZ 2018-01-09 41.50 41.60 40.60 40.80 41.49 ... 458 000049.SZ 2019-11-21 36.53 36.77 36.00 36.50 36.81 459 000049.SZ 2019-11-22 36.44 37.80 36.30 36.68 36.50 460 000049.SZ 2019-11-25 36.30 36.48 34.93 35.16 36.68 461 000049.SZ 2019-11-26 35.28 35.89 35.00 35.76 35.16 462 000049.SZ 2019-11-27 35.69 37.27 35.40 36.72 35.76 463 000049.SZ 2019-11-28 36.72 38.48 36.50 37.49 36.72 price_change pct_change volume money 0 0.19 0.4800 3197416 126769960 1 0.78 1.9600 3913276 157416236 2 2.09 5.1500 8300770 352188889 3 -0.58 -1.3600 4260338 178822929 4 -0.58 -1.3800 3569519 148331795 5 -0.69 -1.6600 3138719 128433609 ... 458 -0.31 -0.8422 4079903 148147523 459 0.18 0.4932 8250452 306343236 460 -1.52 -4.1439 6989292 247534854 461 0.60 1.7065 4304988 153468524 462 0.96 2.6846 7701535 281834519 463 0.77 2.0969 10463935 394639040 ``` %prep %autosetup -n foxrelax-0.4.3 %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-foxrelax -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri May 05 2023 Python_Bot - 0.4.3-1 - Package Spec generated