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|
%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.aliyun.com/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 <TOKEN> with your token
quiver = quiverquant.quiver("<TOKEN>")
#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 <TOKEN> with your token
quiver = quiverquant.quiver("<TOKEN>")
#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 <TOKEN> with your token
quiver = quiverquant.quiver("<TOKEN>")
#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
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.57-1
- Package Spec generated
|
