%global _empty_manifest_terminate_build 0 Name: python-quiverquant Version: 0.1.57 Release: 1 Summary: Quiver Quantitative Alternative Data License: MIT License URL: https://github.com/Quiver-Quantitative/python-api Source0: https://mirrors.nju.edu.cn/pypi/web/packages/45/7d/7b3fd786ec0f3cb09a5c86cd38bd3b44c900e31c889d2b2a49a3c37b5c61/quiverquant-0.1.57.tar.gz BuildArch: noarch Requires: python3-pandas Requires: python3-requests %description # Quiver Quantitative Alternative Data This package allows you to access several alternative data sources which are updated daily and mapped to tickers. These include: - Trading by US congressmen - Corporate Lobbying - Government Contracts - Patents - Off-exchange short volume - Companies' Wikipedia page views - Discussion on Reddit's r/wallstreetbets - Discussion on Reddit's r/SPACs - Companies' Twitter followings - Flights by corporate private jets - Political Beta - Insider Transactions This data can be used for backtesting and implementing trading strategies. ### Receiving API Token You can sign up for a Quiver API token [here](https://api.quiverquant.com). The pricing starts at $10/month, please [e-mail me](mailto:chris@quiverquant.com) if that is an issue and I may be able to help cover. ## Getting Started #### Prerequisites - Python version 3 installed locally - Pip installed locally #### Installation The package can easily be installed in your terminal by entering ```python pip install quiverquant ``` ### Usage ```python #Import the package import quiverquant #Connect to the API using your token #Replace with your token quiver = quiverquant.quiver("") #Get data on WallStreetBets discussion dfWSB = quiver.wallstreetbets() #Get data on WallStreetBets discussion of GameStop dfWSB_GameStop = quiver.wallstreetbets("GME") #Get recent trades by members of U.S. Congress dfCongress = quiver.congress_trading() #Get trades of a Tesla by members of congress dfCongress_Tesla = quiver.congress_trading("TSLA") #Get trades made by U.S. Senator Richard Burr dfCongress_Burr = quiver.congress_trading("Richard Burr", politician=True) #Get recent corporate lobbying dfLobbying = quiver.lobbying() #Get corporate lobbying by Apple dfLobbying_Apple = quiver.lobbying("AAPL") #Get data on government contracts dfContracts = quiver.gov_contracts() #Get data on government contracts to Lockheed Martin dfContracts_Lockheed = quiver.gov_contracts("LMT") #Get data on off-exchange short volume dfOTC = quiver.offexchange() #Get data on off-exchange short volume for AMC dfOTC_AMC = quiver.offexchange("AMC") #Get data on Wikipedia page views dfWiki = quiver.wikipedia() #Get data on Wikipedia page views of Microsoft dfWiki_Microsoft = quiver.wikipedia("MSFT") #Get data on companies' Twitter following dfTwitter = quiver.twitter() #Get data on GE's Twitter following dfTwitter_GE = quiver.twitter("GE") #Get data on r/SPACs discussion dfSPACs = quiver.spacs() #Get data on r/SPACs discussion of CCIV dfSPACs_CCIV = quiver.spacs("CCIV") #Get data on recent corporate private jet flights dfFlights = quiver.flights() #Get data on private jet flights by Target dfFlights_Target = quiver.flights("TGT") #Get data on patents by Apple dfPatents_Apple = quiver.patents("AAPL") #Get data on recent insider transactions dfInsiders = quiver.insiders() #Get data on recent insider transactions by Tesla insiders dfInsiders_Tesla = quiver.insiders("TSLA") ``` %package -n python3-quiverquant Summary: Quiver Quantitative Alternative Data Provides: python-quiverquant BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-quiverquant # Quiver Quantitative Alternative Data This package allows you to access several alternative data sources which are updated daily and mapped to tickers. These include: - Trading by US congressmen - Corporate Lobbying - Government Contracts - Patents - Off-exchange short volume - Companies' Wikipedia page views - Discussion on Reddit's r/wallstreetbets - Discussion on Reddit's r/SPACs - Companies' Twitter followings - Flights by corporate private jets - Political Beta - Insider Transactions This data can be used for backtesting and implementing trading strategies. ### Receiving API Token You can sign up for a Quiver API token [here](https://api.quiverquant.com). The pricing starts at $10/month, please [e-mail me](mailto:chris@quiverquant.com) if that is an issue and I may be able to help cover. ## Getting Started #### Prerequisites - Python version 3 installed locally - Pip installed locally #### Installation The package can easily be installed in your terminal by entering ```python pip install quiverquant ``` ### Usage ```python #Import the package import quiverquant #Connect to the API using your token #Replace with your token quiver = quiverquant.quiver("") #Get data on WallStreetBets discussion dfWSB = quiver.wallstreetbets() #Get data on WallStreetBets discussion of GameStop dfWSB_GameStop = quiver.wallstreetbets("GME") #Get recent trades by members of U.S. Congress dfCongress = quiver.congress_trading() #Get trades of a Tesla by members of congress dfCongress_Tesla = quiver.congress_trading("TSLA") #Get trades made by U.S. Senator Richard Burr dfCongress_Burr = quiver.congress_trading("Richard Burr", politician=True) #Get recent corporate lobbying dfLobbying = quiver.lobbying() #Get corporate lobbying by Apple dfLobbying_Apple = quiver.lobbying("AAPL") #Get data on government contracts dfContracts = quiver.gov_contracts() #Get data on government contracts to Lockheed Martin dfContracts_Lockheed = quiver.gov_contracts("LMT") #Get data on off-exchange short volume dfOTC = quiver.offexchange() #Get data on off-exchange short volume for AMC dfOTC_AMC = quiver.offexchange("AMC") #Get data on Wikipedia page views dfWiki = quiver.wikipedia() #Get data on Wikipedia page views of Microsoft dfWiki_Microsoft = quiver.wikipedia("MSFT") #Get data on companies' Twitter following dfTwitter = quiver.twitter() #Get data on GE's Twitter following dfTwitter_GE = quiver.twitter("GE") #Get data on r/SPACs discussion dfSPACs = quiver.spacs() #Get data on r/SPACs discussion of CCIV dfSPACs_CCIV = quiver.spacs("CCIV") #Get data on recent corporate private jet flights dfFlights = quiver.flights() #Get data on private jet flights by Target dfFlights_Target = quiver.flights("TGT") #Get data on patents by Apple dfPatents_Apple = quiver.patents("AAPL") #Get data on recent insider transactions dfInsiders = quiver.insiders() #Get data on recent insider transactions by Tesla insiders dfInsiders_Tesla = quiver.insiders("TSLA") ``` %package help Summary: Development documents and examples for quiverquant Provides: python3-quiverquant-doc %description help # Quiver Quantitative Alternative Data This package allows you to access several alternative data sources which are updated daily and mapped to tickers. These include: - Trading by US congressmen - Corporate Lobbying - Government Contracts - Patents - Off-exchange short volume - Companies' Wikipedia page views - Discussion on Reddit's r/wallstreetbets - Discussion on Reddit's r/SPACs - Companies' Twitter followings - Flights by corporate private jets - Political Beta - Insider Transactions This data can be used for backtesting and implementing trading strategies. ### Receiving API Token You can sign up for a Quiver API token [here](https://api.quiverquant.com). The pricing starts at $10/month, please [e-mail me](mailto:chris@quiverquant.com) if that is an issue and I may be able to help cover. ## Getting Started #### Prerequisites - Python version 3 installed locally - Pip installed locally #### Installation The package can easily be installed in your terminal by entering ```python pip install quiverquant ``` ### Usage ```python #Import the package import quiverquant #Connect to the API using your token #Replace with your token quiver = quiverquant.quiver("") #Get data on WallStreetBets discussion dfWSB = quiver.wallstreetbets() #Get data on WallStreetBets discussion of GameStop dfWSB_GameStop = quiver.wallstreetbets("GME") #Get recent trades by members of U.S. Congress dfCongress = quiver.congress_trading() #Get trades of a Tesla by members of congress dfCongress_Tesla = quiver.congress_trading("TSLA") #Get trades made by U.S. Senator Richard Burr dfCongress_Burr = quiver.congress_trading("Richard Burr", politician=True) #Get recent corporate lobbying dfLobbying = quiver.lobbying() #Get corporate lobbying by Apple dfLobbying_Apple = quiver.lobbying("AAPL") #Get data on government contracts dfContracts = quiver.gov_contracts() #Get data on government contracts to Lockheed Martin dfContracts_Lockheed = quiver.gov_contracts("LMT") #Get data on off-exchange short volume dfOTC = quiver.offexchange() #Get data on off-exchange short volume for AMC dfOTC_AMC = quiver.offexchange("AMC") #Get data on Wikipedia page views dfWiki = quiver.wikipedia() #Get data on Wikipedia page views of Microsoft dfWiki_Microsoft = quiver.wikipedia("MSFT") #Get data on companies' Twitter following dfTwitter = quiver.twitter() #Get data on GE's Twitter following dfTwitter_GE = quiver.twitter("GE") #Get data on r/SPACs discussion dfSPACs = quiver.spacs() #Get data on r/SPACs discussion of CCIV dfSPACs_CCIV = quiver.spacs("CCIV") #Get data on recent corporate private jet flights dfFlights = quiver.flights() #Get data on private jet flights by Target dfFlights_Target = quiver.flights("TGT") #Get data on patents by Apple dfPatents_Apple = quiver.patents("AAPL") #Get data on recent insider transactions dfInsiders = quiver.insiders() #Get data on recent insider transactions by Tesla insiders dfInsiders_Tesla = quiver.insiders("TSLA") ``` %prep %autosetup -n quiverquant-0.1.57 %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-quiverquant -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue May 30 2023 Python_Bot - 0.1.57-1 - Package Spec generated