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    "info": {
        "author": "Jonathan Ferretti",
        "author_email": "jon@jonathanferretti.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Natural Language :: English",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4"
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        "description": "Sourcerer\r\n=========\r\n\r\n![image](https://img.shields.io/pypi/v/sourcerer.svg)\r\n\r\nProgramatically generate PEP8 python source code\r\n\r\n### Running examples\r\n\r\n```bash\r\nshark@tack ~/sourcerer/examples $ python swagger_to_flask.py ../sample_data/uber.yaml\r\nshark@tack ~/sourcerer/examples $ python call_example.py\r\n```\r\n\r\n### Generate code from code\r\n\r\nLet\u2019s start with the absolute basics\r\n\r\n```python\r\nfrom sourcerer import Document, Statement\r\n\r\n# The most important class in Sourcerer is the statement. Just about everything is a statement.\r\n# Statements hold source code, and have a child scope. They can hold other statements.\r\n# Even a document is just a special kind of Statement.\r\n# A Document job is to hold statements and then output its contents.\r\ndoc = Document()\r\n\r\n# Now we make a generic statement to assign 1 to x\r\ns = Statement(\"x = 1\")\r\n\r\n# Add it to the  document.\r\n# add_child() is a member function of Statement. It will append to a Statements child scope.\r\ndoc.add_child(s)\r\n\r\n# Now output the current document\r\n# output() without an output_file_name will output to standard out.\r\n\r\ndoc.output()\r\n```\r\n\r\n**Output**:\r\n\r\n```python\r\nx = 1\r\n```\r\n\r\nLet\u2019s use some of the purpose built tools in Sourcerer to make this easier to generate.\r\n\r\n```python\r\nfrom sourcerer import Document, Name\r\n\r\ndoc = Document()\r\n\r\n# Names are variable/function/class/etc... names\r\n# We'll use a good name\r\ngood_name = Name(\"descriptive_name\")\r\n\r\n# and a bad name\r\nbad_name = Name(\"1@*plz_help\")\r\n\r\n# Add both the children at once\r\n\r\ndoc.add_children([good_name, bad_name])\r\n\r\ndoc.output()\r\n```\r\n\r\n**Output**:\r\n\r\n```python\r\ndescriptive_name\r\nplz_help\r\n```\r\n\r\nNotice the bad name has been transformed into a valid python name, this behavior can be turned off by setting validate=False\r\n\r\nLet\u2019s get back to that naive assignment we first made. We can improve it using Name and Assignment. We\u2019ll also use Num just for good practice.\r\n\r\n```python\r\nfrom sourcerer import Document, Name, Assignment, Num\r\n\r\ndoc = Document()\r\n\r\n# We'll wrap this up in one line because it's not that long.\r\n# Num can take a string, int, long, float, etc...\r\na = Assignment(Name(\"x\"), Num(\"1\"))\r\n\r\ndoc.add_child(a)\r\n\r\ndoc.output()\r\n```\r\n\r\n**Output**:\r\n\r\n```python\r\nx = 1\r\n```\r\n\r\nNow that we\u2019re warmed up, let\u2019s do something more interesting. How about some functions?\r\n\r\n```python\r\nfrom sourcerer import Document, FunctionDef, Return, Str, Num, Name, Assignment, DecoratorDef, Call\r\n\r\ndoc = Document()\r\n\r\n# A function that returns 0\r\nfunc_a = FunctionDef(name=Name(\"get_a_zero\"))\r\nret_a = Return(Num(\"0\"))\r\n\r\nfunc_a.add_child(ret_a)\r\ndoc.add_child(func_a)\r\n\r\n# A function that passes. We'll put it in an list for easier consumption later\r\nfunc_b = [FunctionDef(name=Name(\"just_pass\")),\r\n          Return(_type=\"pass\")\r\n]\r\n\r\n# Cascade the list of statements\r\ndoc.create_lineage(func_b)\r\n\r\n# A function with args, and a *arg\r\nfunc_c = [FunctionDef(name=Name(\"so_many_args\"), arg_names=[\"a1\", Name(\"a2\")], varargs=\"args\"),\r\n          Return(Str(\"Not enough time\"))\r\n]\r\n\r\ndoc.create_lineage(func_c)\r\n\r\n# A function with kwargs, and a **\r\nfunc_d = [FunctionDef(name=Name(\"so_many_kwargs\"), kwarg_pairs={Name(\"a1\"):\"val\"}, keywords=\"kwargs\"),\r\n          Return()\r\n]\r\n\r\ndoc.create_lineage(func_d)\r\n\r\n# A function decorated function. Philosophy: If things get complicated, just make them a list.\r\nfunc_e = [DecoratorDef(name=Name(\"fancy\")),\r\n          FunctionDef(name=Name(\"pants\")),\r\n          Return(Str(\"Hello World!\"))\r\n]\r\n\r\ndoc.create_lineage(func_e)\r\n\r\ndoc.output()\r\n```\r\n\r\n**Output**:\r\n\r\n```python\r\ndef get_a_zero():\r\n    return 0\r\n\r\n\r\ndef just_pass():\r\n    pass\r\n\r\n\r\ndef so_many_args(a1, a2, *args):\r\n    return \"Not enough time\"\r\n\r\n\r\ndef so_many_kwargs(a1=val, **kwargs):\r\n    return\r\n\r\n\r\n@fancy()\r\ndef pants():\r\n    return \"Hello World!\"\r\n```\r\n\r\nHere is an example that generates an extremely rough flask Blueprint from a swagger (<http://swagger.io/>) yml doc\r\n\r\n``` python\r\nfrom yaml import load\r\nfrom sourcerer import Document, FunctionDef, DecoratorDef, Return, Str, Name, Call, Assignment, Attribute\r\nfrom sys import argv\r\n\r\n# Create a document to put our code in\r\ndoc = Document()\r\n\r\n# Open our yml file and read it in\r\napi = load(open(argv[1], 'r').read())\r\n\r\nblueprint = Name(api['basePath'])\r\n\r\nbp = Assignment(blueprint,\r\n                Call(name=\"Blueprint\",\r\n                     arg_names=[Str(blueprint), '__name__'],\r\n                     kwarg_pairs={'template_folder': Str('templates')}))\r\n\r\ndoc.add_child(bp)\r\n\r\nfor path in api['paths']:\r\n    route = [DecoratorDef(name=Attribute(caller_list=[blueprint], name=Name('route')),\r\n                          arg_names=[Str(path)]), # A decorator: @routename(\"mypath\")\r\n             FunctionDef(name=Name(path)), # A function: def routename():\r\n             Return()] # A return statement: return\r\n\r\n    doc.create_lineage(route) # Cascade these objects into the main document scope\r\n                              # ...\r\n                              # @routename(\"mypath\")\r\n                              # def routename():\r\n                              #     return\r\n                              # ...\r\n\r\ndoc.output() # Send output to standard out (output to file optional)\r\n\r\n####################\r\n# Without inline comments:\r\n##\r\n\r\nfrom yaml import load\r\nfrom sourcerer import Document, FunctionDef, DecoratorDef, Return, Str, Name, Call, Assignment, Attribute\r\nfrom sys import argv\r\n\r\ndoc = Document()\r\n\r\napi = load(open(argv[1], 'r').read())\r\n\r\nblueprint = Name(api['basePath'])\r\n\r\nbp = Assignment(blueprint,\r\n                Call(name=\"Blueprint\",\r\n                     arg_names=[Str(blueprint), '__name__'],\r\n                     kwarg_pairs={'template_folder': Str('templates')}))\r\ndoc.add_child(bp)\r\n\r\nfor path in api['paths']:\r\n    route = [DecoratorDef(name=Attribute(caller_list=[blueprint], name=Name('route')),\r\n                          arg_names=[Str(path)]),\r\n             FunctionDef(name=Name(path)),\r\n             Return()]\r\n    doc.create_lineage(route)\r\n\r\ndoc.output()\r\n```\r\n\r\n**Output:**\r\n\r\n```python\r\nv1 = Blueprint(\"v1\", __name__, template_folder=\"templates\")\r\n\r\n\r\n@v1.route(\"/products\")\r\ndef products():\r\n    return\r\n\r\n\r\n@v1.route(\"/estimates/price\")\r\ndef estimatesprice():\r\n    return\r\n\r\n\r\n@v1.route(\"/history\")\r\ndef history():\r\n    return\r\n\r\n\r\n@v1.route(\"/me\")\r\ndef me():\r\n    return\r\n\r\n\r\n@v1.route(\"/estimates/time\")\r\ndef estimatestime():\r\n    return\r\n```\r\n\r\n## Technologies\r\n\r\n* YAPF formatted output to produce pep8 compliant code\r\n\r\n\r\n## Upcoming Features\r\n\r\n### Generate code from Spellbooks\r\n\r\nSource code can also be generated by ingesting and parsing a config document (ex. yaml, json, xml\u2026), known as a Spellbook. Spellbooks can be parsed into source code be defining a schema, called a Syntax Map.\r\n\r\n#### Example Spellbook (YAML):\r\n\r\n```YAML\r\nfunctions:\r\n    func1:\r\n        args: ['thing1', 'thing2']\r\n        kwargs: {\"key1\": \"val1\"}\r\n        varargs: false\r\n        keywords: false\r\n        ret:\r\n            value:\r\n                true\r\n```\r\n\r\n#### Example Syntax Map to parse this Spellbook:\r\n\r\n\r\n```python\r\n# Without inline comments\r\n{\"functions\": {'type': FunctionDef,\r\n               'key': 'name',\r\n               'value_map': {'args': 'arg_names',\r\n                             'kwargs': 'kwarg_pairs',\r\n                             'varargs': 'varargs',\r\n                             'keywords': 'keywords'},\r\n               'children':{'ret':'return'}},\r\n \"return\": {'type': Return,\r\n             'value_map': {'value':'val'}}\r\n}\r\n\r\n# With inline comments\r\n{\"functions\": {'type': FunctionDef, # Each top level entry under functions is a FunctionDef\r\n               'key': 'name', # The functions key (func1) is the value to the name argument for the FunctionDef\r\n               'value_map': {'args': 'arg_names',  # Define what args are called in the markups schema\r\n                             'kwargs': 'kwarg_pairs',\r\n                             'varargs': 'varargs',\r\n                             'keywords': 'keywords'},\r\n               'children':{'ret':'return'}}, # When top-level objects are seen their values will be\r\n                                             # pared as well, building a new object from the mapping\r\n                                             # they specify and then appended to this object\r\n \"return\": {'type': Return,\r\n             'value_map': {'value':'val'}}\r\n}\r\n```\r\n\r\n#### Building a Syntax Map for a Spellbook:\r\n\r\nYour Syntax Maps top-level keys define what your Spellbook top-level sections are containing. The values of your Syntax Map top-level keys are dictionaries defining how to handle the contents of your Spellbook sections.\r\n\r\nIn the given example, the only top-level Spellbook section is \u2018functions\u2019. In the Syntax Map, the \u2018functions\u2019 key\u2019s value says several things:\r\n\r\n1.  For each child node encountered, create a new FunctionObj (defined by \u2018type\u2019)\r\n2.  The key defining each child node is the \u2018name\u2019 argument for the FunctionObj\r\n3.  The sub-keys of the child node are properties of the FunctionObj. The values of those sub-keys are can be one of two things:\r\n    -   If the value is in the value map, it is an argument to FunctionObj\r\n    -   If the value is in the children map, it should be placed into the scope of the FunctionObj. The value will be looked up in the Syntax Map top-level to see if it can be be instantiated into a new sourcerer object.\r\n\r\n#### The Syntax Map schema should consist of:\r\n\r\n-   type (required): The class name to instantiate\r\n-   key (required): what the key for the node represents\r\n-   value\\_map (required): map properties to arguments to the class\r\n-   children: values that should be instantiated and placed into the current nodes child scope\r\n\r\n#### Using a Syntax Map and Spellbook to generate your source:\r\n\r\nBased on the example Syntax Map and the Example YAML, the following will write the resulting source code to stardard out\r\n\r\n```python\r\nfrom sourcerer import YAMLProcessor\r\n\r\ngen = YAMLProcessor()\r\ngen.load('sample_data/sample.yml')\r\ngen.output()\r\n```\r\n\r\n\r\n\r\n\r\nHistory\r\n-------\r\n\r\n0.0.3 (2015-04-15)\r\n---------------------",
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