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    "info": {
        "author": "Goutham Balaraman",
        "author_email": "gouthaman.balaraman@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "Intended Audience :: End Users/Desktop",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# Quant Python ToolKit\r\n\r\nThis package is intended to be a layer above QuantLib Python and a few other quantitative libraries \r\nto be more accessible for quantitative finance calculations.\r\n\r\n## Minimal Example\r\nHere is a minimal example for valuing a bond using a provided zero rates.\r\n\r\n    from qtk import Controller, Field as F, Template as T\r\n\r\n    data = [{\r\n              'Compounding': 'Compounded',\r\n              'CompoundingFrequency': 'Annual',\r\n              'Currency': 'USD',\r\n              'DiscountBasis': '30/360',\r\n              'DiscountCalendar': 'UnitedStates',\r\n              'ListOfDate': ['1/15/2015', '7/15/2015', '1/15/2016'],\r\n              'ListOfZeroRate': [0.0, 0.005, 0.007],\r\n              'ObjectId': 'USD.Zero.Curve',\r\n              'Template': 'TermStructure.Yield.ZeroCurve'},\r\n             {\r\n              'DiscountCurve': '->USD.Zero.Curve',\r\n              'ObjectId': 'BondEngine',\r\n              'Template': 'Engine.Bond.Discounting'},\r\n             {\r\n              'AccrualCalendar': 'UnitedStates',\r\n              'AccrualDayConvention': 'Unadjusted',\r\n              'AsOfDate': '2016-01-15',\r\n              'Coupon': 0.06,\r\n              'CouponFrequency': 'Semiannual',\r\n              'Currency': 'USD',\r\n              'DateGeneration': 'Backward',\r\n              'EndOfMonth': False,\r\n              'IssueDate': '2015-01-15',\r\n              'MaturityDate': '2016-01-15',\r\n              'ObjectId': 'USD.TBond',\r\n              'PaymentBasis': '30/360',\r\n              'PricingEngine': '->BondEngine',\r\n              'Template': 'Instrument.Bond.TreasuryBond'}]\r\n\r\n    res = Controller(data)\r\n    asof_date = \"1/15/2015\"\r\n\r\n    ret = res.process(asof_date)\r\n    tbond = res.object(\"USD.TBond\")\r\n    print tbond.NPV()\r\n\r\n\r\nThe basic idea here is that once you have the data prepared, the `Controller` can be invoked to do the calculations. \r\nA few points that are worth noting here. \r\n\r\n- All the data is textual and rather intuitive. For instance, the coupon\r\n  frequency is just stated as `Annual` or `Semiannual`. The same is true for a lot of other fields. For dates,\r\n  the `dateutil` package is used to parse and covers a wide variety of formats. \r\n\r\n- The `data` is essentially a `list` of `dict` with each `dict` corresponding to a specific `object` as determined\r\n  by the value to the key `Template` in each `dict`. Each `object` here has a name as specified by the value of the \r\n  key `ObjectId`\r\n  \r\n- One of the values can refer to another object described by a `dict` by using the `reference` syntax. For instance,\r\n  the first `dict` in the `data` list (with `ObjectId` given as *USD.Zero.Curve* ) variable refers to an interest \r\n  rate term structure of zero rates. The next object is a discounting bond engine, and require an yield curve as \r\n  input for the discount curve. Here the yield curve is refered by using the prefix `->` along with the name of the\r\n  object we are referring to.\r\n  \r\n- Here, the `Controller` parses the data, and figures out the dependency and processes the object in the correct order\r\n  and fulfills the dependencies behind the scenes. \r\n  \r\n## Introspection\r\n  \r\nThere are a few convenience methods that provide help on how to construct the data packet. For example,\r\nthe `help` method in the template prints out the summary and list of fields on how to construct\r\nthe data packet for the template.\r\n\r\n    > T.TS_YIELD_BOND.help()\r\n    \r\n**Description**\r\n\r\nA template for creating yield curve by stripping bond quotes.\r\n\r\n**Required Fields**\r\n\r\n - `Template` [*Template*]: 'TermStructure.Yield.BondCurve'\r\n - `InstrumentCollection` [*List*]: Collection of instruments\r\n - `AsOfDate` [*Date*]: Reference date or as of date\r\n - `Country` [*String*]: Country\r\n - `Currency` [*String*]: Currency\r\n\r\n**Optional Fields**\r\n\r\n - `ObjectId` [*String*]: A unique name or identifier to refer to this dictionary data\r\n - `InterpolationMethod` [*String*]: The interpolation method can be one of the following choices: LinearZero, CubicZero, FlatForward, LinearForward,LogCubicDiscount.\r\n - `DiscountBasis` [*DayCount*]: Discount Basis\r\n - `SettlementDays` [*Integer*]: Settlement days\r\n - `DiscountCalendar` [*Calendar*]: Discount Calendar\r\n\r\nThe `help` method prints the description in `info` method in Markdown format. While using IPython/Jupyter notebooks, the description\r\nprints in a nice looking format. One can start with a sample data packet to fill out the input fields using the `sample_data` method.\r\n\r\n    > T.TS_YIELD_BOND.sample_data()\r\n    \r\n    {'AsOfDate': 'Required (Date)',\r\n     'Country': 'Required (String)',\r\n     'Currency': 'Required (String)',\r\n     'DiscountBasis': 'Optional (DayCount)',\r\n     'DiscountCalendar': 'Optional (Calendar)',\r\n     'InstrumentCollection': 'Required (List)',\r\n     'InterpolationMethod': 'Optional (String)',\r\n     'ObjectId': 'Optional (String)',\r\n     'SettlementDays': 'Optional (Integer)',\r\n     'Template': 'TermStructure.Yield.BondCurve'}\r\n \r\n  \r\n## Installation\r\n\r\nYou can install qtk using `pip` or `easy_install`\r\n\r\n    pip install qtk\r\n    \r\nor\r\n\r\n    easy_install qtk\r\n    \r\n`qtk` has a dependency on `QuantLib-Python` which needs to be installed as well.\r\n\r\n\r\n  ",
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