.circleci/config.yml

@@ -12,12 +12,18 @@ jobs:
             python3 -m venv venv
             . venv/bin/activate
             pip3 install setuptools --upgrade
+            pip install numpy==1.19.4
             python3 setup.py develop
       - save_cache:
           key: deps-{{ checksum "setup.py" }}
           paths:
             - venv
-      - run: python3 setup.py flake8 test
+      - run:
+          command: |
+            . venv/bin/activate
+            pip install -r requirements/requirements_test.txt
+            flake8 ./pylivetrader && echo "Flake8 passed"
+            pytest
 
   build-python37:
     docker:
@@ -36,10 +42,15 @@ jobs:
           key: deps-{{ checksum "setup.py" }}
           paths:
             - venv
-      - run: python3 setup.py flake8 test
+      - run:
+          command: |
+            . venv/bin/activate
+            pip install -r requirements/requirements_test.txt
+            flake8 ./pylivetrader && echo "Flake8 passed"
+            pytest
 
 workflows:
   version: 2
   build:
     jobs:
-      - build-python36
+      - build-python36

.pyup.yml

@@ -0,0 +1,35 @@
+# configure updates globally
+# default: all
+# allowed: all, insecure, False
+update: all
+
+# configure dependency pinning globally
+# default: True
+# allowed: True, False
+pin: True
+
+# set the default branch
+# default: empty, the default branch on GitHub
+branch: master
+
+# update schedule
+# default: empty
+# allowed: "every day", "every week", ..
+schedule: "every week"
+
+# search for requirement files
+# default: True
+# allowed: True, False
+search: True
+
+# Specify requirement files by hand, default is empty
+# default: empty
+# allowed: list
+requirements:
+  - requirements/requirements.txt:
+      # update all dependencies and pin them
+      update: all
+      pin: True
+  - requirements/requirements_test.txt:
+      # don't update dependencies, use global 'pin' default
+      update: False

README.md

@@ -1,5 +1,7 @@
 [![PyPI version](https://badge.fury.io/py/pylivetrader.svg)](https://badge.fury.io/py/pylivetrader)
 [![CircleCI](https://circleci.com/gh/alpacahq/pylivetrader.svg?style=shield)](https://circleci.com/gh/alpacahq/pylivetrader)
+[![Updates](https://pyup.io/repos/github/alpacahq/pylivetrader/shield.svg)](https://pyup.io/repos/github/alpacahq/pylivetrader/)
+[![Python 3](https://pyup.io/repos/github/alpacahq/pylivetrader/python-3-shield.svg)](https://pyup.io/repos/github/alpacahq/pylivetrader/)
 
 # pylivetrader
 
@@ -8,9 +10,22 @@ The main purpose is to run algorithms developed in the Quantopian platform in
 live trading via broker API. In order to convert your algorithm for pylivetrader,
 please read the [migration document](./migration.md).
 
+## example code
+check out the [examples](https://github.com/alpacahq/pylivetrader/tree/master/examples) 
+folder. you will find there the following examples:
+* simple MACD "momentum" trading
+* using pipeline-live to screen top stocks every day
+* a potfolio optimizer (used to optimize an existing porfolio. not to buy new
+ stocks)
+
+each sample code contains a readme file and a smoke runner (read further to
+  understand what smoke is)
+
 ## Simple Usage
 
-Here is the example dual moving average algorithm (by [quantopian/zipline](https://github.com/quantopian/zipline/blob/master/zipline/examples/dual_moving_average.py)). We provide mostly the same API interfaces with zipline.
+Here is the example dual moving average algorithm (by 
+[quantopian/zipline](https://github.com/quantopian/zipline/blob/master/zipline/examples/dual_moving_average.py)).
+ We provide mostly the same API interfaces with zipline.
 
 ```py
 from pylivetrader.api import order_target, symbol
@@ -49,8 +64,9 @@ Config file is just simple yaml or json format.
 $ cat config.yaml
 key_id: BROKER_API_KEY
 secret: BROKER_SECRET
+base_url: https://paper-api.alpaca.markets
+feed: iex  # <== change to pro if you have a paid account
 ```
-
 ### Usage with redis
 
 If you are running pylivetrader in an environment with an ephemeral file store and need your context
@@ -73,10 +89,12 @@ Assuming you have redis running, this will now serialize your context object to
 
 ## Installation
 
-Install with pip. **pylivetrader currently supports Python 3.5, 3.6 and 3.7+**
+Install with pip. **pylivetrader currently supports only Python 3.6.
 
 ```
-$ pip install pylivetrader
+$ python3.6 -m venv venv
+$ source venv/bin/activate
+(venv)$ pip install pylivetrader
 ```
 
 Additionally, pylivetrader works well with [pipeline-live](https://github.com/alpacahq/pipeline-live).
@@ -92,7 +110,7 @@ before the session starts) or if it starts after that. Once the session
 starts, it calls the `handle_data()` function every minute until the
 session ends, or any functions that are registered by `schedule_function` API.
 
-The options are as follows.
+The options are as follows
 
 - `-f` or `--file`: the file path to the algorithm source
 - `-b` or `--backend`: the name of backend to use
@@ -107,15 +125,45 @@ The options are as follows.
 `pylivetrader shell` goes into the IPython interactive shell mode as if you are
 in the algorithm script namespace. It means, you can call Algorithm API
 such as `symbol()` and `data.history()` so you can check the behavior
-of each operation. At the start of shell, nothing has been called, so you
-may want to initialize the context by `initialize(context)` which would
-execute your `initialize()` function.
+of each operation.
 
 ```
 $ pylivetrader shell algo.py
 ```
 
-The options are the same as `run`.
+
+The options are as follows
+
+- `-f` or `--file`: the file path to the algorithm source
+- `-b` or `--backend`: the name of backend to use
+- `--backend-config`: the yaml file for backend parameters
+
+#### things you could do with the shell
+* get asset price data. e.g: data.history(symbol("AAPL"), "close", 10, "1d")
+* check if you can trade a certain asset. e.g: data.can_trade(symbol("AAPL"))
+* get your account information: context.account
+* get your portfolio information: context.account.portfolio
+* get all opened orders: context.get_open_orders()
+* get all orders: context.get_all_orders()
+* get a list of all available assets. eg: context._backend._api.list_assets(asset_class='us_equity')
+
+### migrate
+
+`pylivetrader migrate` allows you to easily migrate your quantopian/zipline code to pylivetrader compatible code.<br>
+how to run:
+```sh
+pylivetrader migrate -i zipline_code.py -o pylivetrader_compatible.py
+```
+now you could execute it with the `run` command
+<br>note: we do not support the optimize api by quantopian since it is not a part of zipline
+
+## Working with Pipline-live
+You can see an example usage under the examples folder.<br>
+To work with pipeline-live you need to do the following steps:
+* Create the pipeline (usually you will create it in a method, convention name is `make_pipeline()`. Inside you will define your universe and add factors and filters.
+* DO NOT store the pipe in the context object. We cannot store it to the statefile and you don't need to do it. we store it for you.
+* attach the pipeline to the Algortihm instance. do it like this: `context.attach_pipeline(pipe, "my_pipe")`. this should be done in the `intialize()` or `before_trading_start()` methods.
+* Now, to get the output of the pipeline, you do this: `context.pipeline_output('my_pipe')`. you should call it in `handle_data()` or any other method you use the scheduler for.
 
 ## State Management
 
@@ -131,7 +179,7 @@ restored on the next startup.
 Second, because the context properties are restored, you may need to
 take care of the extra steps. Often an algorithm is written under
 the assumption that `initialize()` is called only once and
-`before_start_trading()` is called once every morning. If you are
+`before_trading_start()` is called once every morning. If you are
 to restart the program in the middle of day, these functions are
 called again, with the restored context object. Therefore, you
 might need to check if the fields are from the other session
@@ -168,16 +216,20 @@ try our [docker image `alpacamarkets/pylivetrader`](https://hub.docker.com/r/alp
 This has installed pylivetrader so you can start right away without
 worrying about your python environment.  See more details in the
 `dockerfiles` directory.
-
-If your algorithm file is called `algo.py`, this could be it.
+<br>If your algorithm file is called `algo.py`, this could be all you need to run it.
 
 ```sh
 docker run -v $PWD:/work -w /work alpacamarkets/pylivetrader pylivetrader run -f algo.py
 ```
 
-Make sure you set up environment variables for the  backend
+Make sure you set up environment variables for the backend
 (use `-e KEY=VAL` for docker command).
 
+
+you could also build the docker image from source like this:<br>
+`docker build -t alpaca/pylivetrader-dev -f dockerfiles/Dockerfile-dev .`<br>
+it gives you the power to run it locally and edit or debug the code if you desire.
+
 ## Smoke Test
 
 pylivetrader provides a facility for smoke testing. This helps catch
@@ -243,3 +295,13 @@ Again, the purpose of this smoke testing is to actually exercise various
 code paths to make sure there are no easy mistakes. This code works well
 with standard test frameworks such as `pytest` and you can easily report
 line coverage using those frameworks too.
+
+## Running Multiple Strategies
+There's a way to execute more than one algorithm at once.<br>
+The websocket connection is limited to 1 connection per account. <br>
+For that exact purpose this ![project](https://github.com/shlomikushchi/alpaca-proxy-agent)  was created<br>
+The steps to execute this are:
+* Run the Alpaca Proxy Agent as described in the project's README
+* Define this env variable: `DATA_PROXY_WS` to be the address of the proxy agent. (e.g: `DATA_PROXY_WS=ws://127.0.0.1:8765`)
+* execute your algorithm. it will connect to the servers through the proxy agent allowing you to execute multiple strategies
+

dockerfiles/Dockerfile

@@ -9,9 +9,4 @@ RUN wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz && \
   make install
 RUN rm -R ta-lib ta-lib-0.4.0-src.tar.gz
 
-RUN pip install pipenv
-
-ADD Pipfile Pipfile.lock /tmp/
-ADD Pipfile Pipfile.lock /
-
-RUN pipenv install --system --dev
+RUN pip install pylivetrader==0.5.5

dockerfiles/Dockerfile-dev

@@ -0,0 +1,15 @@
+FROM python:3.6-stretch
+
+# Install talib
+RUN wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz && \
+  tar -xvzf ta-lib-0.4.0-src.tar.gz && \
+  cd ta-lib/ && \
+  ./configure --prefix=/usr && \
+  make && \
+  make install
+RUN rm -R ta-lib ta-lib-0.4.0-src.tar.gz
+
+
+ADD . /opt/project
+WORKDIR /opt/project
+RUN pip install -e .