Example PyData app on Cloud Foundry using Spyre (https://github.com/adamhajari/spyre) and the Python conda buildpack (https://github.com/ihuston/python-conda-buildpack)

conda_requirements.txt

numpy
scipy
pandas
matplotlib

manifest.yml

---
applications:
- name: ih-spyre-test
  memory: 1GB
  buildpack: git://github.com/ihuston/python-conda-buildpack.git
  timeout: 180
  command: .conda/bin/python stocks.py

requirements.txt

cherrypy
dataspyre==0.1.0

simple_sine_example.py

"""Example Spyre app from https://github.com/adamhajari/spyre"""
import matplotlib
# Needed to use headless
matplotlib.use('Agg')

from spyre import server

import os


import matplotlib.pyplot as plt
import numpy as np

class SimpleSineApp(server.App):
    title = "Simple Sine App"
    inputs = [{ "input_type":"text",
                "variable_name":"freq",
                "value":5,
                "action_id":"sine_wave_plot"}]

    outputs = [{"output_type":"plot",
                "output_id":"sine_wave_plot",
                "on_page_load":True }]

    def getPlot(self, params):
        f = float(params['freq'])
        print f
        x = np.arange(0,2*np.pi,np.pi/150)
        y = np.sin(f*x)
        fig = plt.figure()
        splt1 = fig.add_subplot(1,1,1)
        splt1.plot(x,y)
        return fig

port = int(os.getenv("VCAP_APP_PORT"))

app = SimpleSineApp()
app.launch(port=port, host='0.0.0.0')

Spyre app on Cloud Foundry

## PyData stack on Cloud Foundry
The current Python buildpack uses `pip` to install dependencies. Anyone who has tried to install NumPy or SciPy using `pip` knows that the process can be lengthy and painful often requiring manual intervention to correct library paths and install Fortran compilers.

Fortunately [Continuum Analytics'](http://continuum.io/) [conda package manager](conda.pydata.org) was created to solve these problems by packaging and distributing the standard tools of the Python data stack in compiled binaries.

I wanted to build web apps on Cloud Foundry using the PyData stack so with help from [a colleague](https://github.com/nebhale) I have written a [Cloud Foundry buildpack](https://github.com/ihuston/python-conda-buildpack) which uses both conda and pip to install required packages.

You can specify packages to be installed by `conda` in the `conda_requirements.txt` file and these will be installed first, followed by packages in the `requirements.txt` which will be installed as usual by `pip`.

This web app uses [Spyre](https://github.com/adamhajari/spyre) by Adam Hajari which is available on PyPI as `dataspyre`.

stocks.py

"""Example Spyre app from https://github.com/adamhajari/spyre"""
import matplotlib
# Needed to use headless
matplotlib.use('Agg')

import os
from spyre import server

import pandas as pd
import urllib2
import json

class StockExample(server.App):
    title = "Historical Stock Prices"

    inputs = [{     "input_type":'dropdown',
                    "label": 'Company',
                    "options" : [ {"label": "Google", "value":"GOOG"},
                                  {"label": "Yahoo", "value":"YHOO"},
                                  {"label": "Apple", "value":"AAPL"}],
                    "variable_name": 'ticker',
                    "action_id": "update_data" }]

    controls = [{   "control_type" : "hidden",
                    "label" : "get historical stock prices",
                    "control_id" : "update_data"}]

    tabs = ["Plot", "Table"]

    outputs = [{    "output_type" : "plot",
                    "output_id" : "plot",
                    "control_id" : "update_data",
                    "tab" : "Plot",
                    "on_page_load" : True },
                {   "output_type" : "table",
                    "output_id" : "table_id",
                    "control_id" : "update_data",
                    "tab" : "Table",
                    "on_page_load" : True }]

    def getData(self, params):
        ticker = params['ticker']
        # make call to yahoo finance api to get historical stock data
        api_url = 'https://chartapi.finance.yahoo.com/instrument/1.0/{}/chartdata;type=quote;range=3m/json'.format(ticker)
        result = urllib2.urlopen(api_url).read()
        data = json.loads(result.replace('finance_charts_json_callback( ','')[:-1])  # strip away the javascript and load json
        self.company_name = data['meta']['Company-Name']
        df = pd.DataFrame.from_records(data['series'])
        df['Date'] = pd.to_datetime(df['Date'],format='%Y%m%d')
        return df

    def getPlot(self, params):
        df = self.getData(params)
        plt_obj = df.set_index('Date').drop(['volume'],axis=1).plot()
        plt_obj.set_ylabel("Price")
        plt_obj.set_title(self.company_name)
        fig = plt_obj.get_figure()
        return fig

port = int(os.getenv("VCAP_APP_PORT"))
app = StockExample()
app.launch(port=port, host='0.0.0.0')

Hi, I tried to reproduce what you did, but there might be a problem to install matplotlib
I got this error when I push the app
ERR grep: ./app/.conda/pkgs/matplotlib-1.4.2-np19py27_0/lib/libtcl.so: No such file or directory
any ideas?