prophet
Prophet is a Python microframework for financial markets. Prophet strives to let the programmer focus on modeling financial strategies, portfolio management, and analyzing backtests. It achieves this by having few functions to learn to hit the ground running, yet being flexible enough to accomodate sophistication.
build status
See the documentation for more details.
Join the mailing list here or join by email.
Quickstart
from datetime import datetime
from prophet import Prophet
from prophet.data import YahooCloseData
from prophet.analyze import default_analyzers
from prophet.orders import Orders
class OrderGenerator(object):
def __init__(self):
super(OrderGenerator, self).__init__()
self._data = dict()
def run(self, prices, timestamp, cash, **kwargs):
symbol = "AAPL"
orders = Orders()
if (prices.loc[timestamp, symbol] * 100) < cash:
orders.add_order(symbol, 100)
return orders
prophet = Prophet()
prophet.set_universe(['AAPL', 'XOM'])
prophet.register_data_generators(YahooCloseData())
prophet.set_order_generator(OrderGenerator())
backtest = prophet.run_backtest(start=datetime(2010, 1, 1))
prophet.register_portfolio_analyzers(default_analyzers)
analysis = prophet.analyze_backtest(backtest)
print analysis
# +--------------------------------------+
# | sharpe | 1.09754359611 |
# | average_return | 0.00105478425027 |
# | cumulative_return | 2.168833 |
# | volatility | 0.0152560508189 |
# +--------------------------------------+
# Generate orders for you to execute today
# Using Nov, 10 2014 as the date because there might be no data for today's
# date (Market might not be open) and we don't want examples to fail.
today = datetime(2014, 11, 10)
print prophet.generate_orders(today)
# Orders[Order(symbol='AAPL', shares=100)]Contribute
Run the following to your development environment setup:
git clone git@github.com:Emsu/prophet.git
cd prophet
virtualenv env
pip install dev-requirements.txt
python setup.py developCredits
Prophet wouldn’t be possible without the wonderful pandas library and is inspired by QSTK and Zipline.
The trading calendar util in Prophet is from Zipline which is under the Apache 2.0 License.
3 maintainers
Metadata
3 maintainers
Release files for prophet 0.1.1.post1
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 | |
|---|---|---|---|---|
| prophet-0.1.1.post1.tar.gz | 90.7 kB | Without provenance | Details |
Release files / prophet-0.1.1.post1.tar.gz
| Download URL | prophet-0.1.1.post1.tar.gz |
|---|---|
| Size | 90.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ab70aa92d19037b54970b44699a483edf450e0e1bdc9f38edf3ad14ee1cabf54
|
|
BLAKE2b-256 checksum How to use checksums |
918d2ed577196f58f9d7a93958ec650ffee35d42e81f430b1a44f0963eb83ce0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/45.1.0 requests-toolbelt/0.8.0 tqdm/4.42.0 CPython/3.7.6
|
Security for prophet 0.1.1.post1
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.
