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
- 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
This data can be used for backtesting and implementing trading strategies.
Receiving API Token
You can sign up for a Quiver API token here.
The pricing starts at $10/month, please e-mail me 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
pip install quiverquant
Usage
#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 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 data on WallStreetBets discussion of GameStop
dfWSB_GameStop = quiver.wallstreetbets("GME")
#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 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")
Metadata
Release files for quiverquant 0.1.27
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| quiverquant-0.1.27.tar.gz | 3.3 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| quiverquant-0.1.27-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.6 kB
Release files / quiverquant-0.1.27.tar.gz
| Download URL | quiverquant-0.1.27.tar.gz |
|---|---|
| Size | 3.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
eca1510377da85a8a07dbbe7cc67987d4bc7130c222cd758eb0e1e9d0b296359
|
|
BLAKE2b-256 checksum How to use checksums |
afe8864f7728042e0dfba401498b8c1403d2e11b2c2b18ded84baf3286ff217a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6
|
Release files / quiverquant-0.1.27-py3-none-any.whl
| Download URL | quiverquant-0.1.27-py3-none-any.whl |
|---|---|
| Size | 4.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
5341be9e554512364be32fbf812943d9cd4dbed799639ac3ad6f8456f0c1f65f
|
|
BLAKE2b-256 checksum How to use checksums |
718783cca5b00bdc4355a45d621d2990888976cc0defa6e91dbbcee012be80ba
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6
|
Security for quiverquant 0.1.27
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.