calmjs.parse 1.3.2

Manual installation and packaging requirements

This section is for developers and advanced users; contains important information for package maintainers for OS distributions (e.g. Linux) that will prevent less than ideal experiences for downstream users.

Development is still ongoing with calmjs.parse, for the latest features and bug fixes, the development version may be installed through git like so:

$ pip install ply setuptools  # this MUST be done first; see below for reason
$ pip install -e git+https://github.com/calmjs/calmjs.parse.git#egg=calmjs.parse

Note that all dependencies MUST be pre-installed setup.py build step to run, otherwise the build step required to create the pre-generated modules will result in failure.

If ply isn’t installed:

$ python -m pip install -e .
...
running egg_info
...
WARNING: cannot find distribution for 'ply'; using default value,
assuming 'ply==3.11' for pre-generated modules
ERROR: cannot find pre-generated modules for the assumed 'ply'
version from above and/or cannot `import ply` to build generated
modules, aborting build; please either ensure that the source
archive containing the pre-generate modules is being used, or that
the python package 'ply' is installed and available for import
before attempting to use the setup.py to build this package; please
refer to the top level README for further details

If setuptools isn’t installed:

$ python -m pip install -e .
...
running egg_info
...
Traceback (most recent call last):
  ...
ModuleNotFoundError: No module named 'pkg_resources'

Naturally, the git repository can be cloned directly and execute python setup.py develop while inside the root of the source directory; again, both ply AND setuptools MUST already have be available for import.

As the git repository does NOT contain any pre-generated modules or code, the above message is likely to be seen by developers or distro maintainers who are on their first try at interacting with this software. However, the zip archives released on PyPI starting from version 1.3.0 do contain these modules fully pre-generated, thus they may be used as part of a standard installation step, i.e. without requiring ply be available for import before usage of the setup.py for any purpose. While the same warning message about ply being missing may be shown, the pre-generated modules will allow the build step to proceed as normal.

Manual optimization

As lex and yacc require the generation of symbol tables, a way to optimize the performance is to cache the results. For ply, this is done using an auto-generated module. However, the generated file is marked with a version number, as the results may be specific to the installed version of ply. In calmjs.parse this is handled by giving them a name specific to the version of ply and the major Python version, as both together does result in subtle differences in the outputs and expectations of the auto-generated modules.

Typically, the process for this optimization is automatic and a correct symbol table will be generated, however there are cases where this will fail, so for this reason calmjs.parse provide a helper module and executable that can be optionally invoked to ensure that the correct encoding be used to generate that file. Other reasons where this may be necessary is to allow system administrators to do so for their end users, as they may not have write privileges at that level.

To execute the optimizer from the shell, the provided helper script may be used like so:

$ python -m calmjs.parse.parsers.optimize

If warnings appear that warn that tokens are defined but not used, they may be safely ignored.

This step is generally optionally for users who installed this package from PyPI via a Python wheel, provided the caveats as outlined in the installation section are addressed.

Testing the installation

To ensure that the calmjs.parse installation is functioning correctly, the built-in testsuite can be executed by the following:

$ python -m unittest calmjs.parse.tests.make_suite

If there are failures, please file an issue on the issue tracker with the full traceback, and/or the method of installation. Please also include applicable information about the environment, such as the version of this software, Python version, operating system environments, the version of ply that was installed, plus other information related to the issue at hand.

Pretty/minified printing

There is also a set of pretty printing helpers for turning the AST back into a string. These are available as functions or class constructors, and are produced by composing various lower level classes available in the calmjs.parse.unparsers and related modules.

There is a default short-hand helper for turning the previously produced AST back into a string, which can be manually invoked with certain parameters, such as what characters to use for indentation: (note that the __str__ call implicitly invoked through print shown previously is implemented through this).

>>> from calmjs.parse.unparsers.es5 import pretty_print
>>> print(pretty_print(program, indent_str='    '))
var main = function(greet) {
    var hello = "hello " + greet;
    return hello;
};
console.log(main('world'));

>>>

There is also one for printing without any unneeded whitespaces, works as a source minifier:

>>> from calmjs.parse.unparsers.es5 import minify_print
>>> print(minify_print(program))
var main=function(greet){var hello="hello "+greet;return hello;};...
>>> print(minify_print(program, obfuscate=True, obfuscate_globals=True))
var a=function(b){var a="hello "+b;return a;};console.log(a('world'));

Note that in the second example, the obfuscate_globals option was only enabled to demonstrate the source obfuscation on the global scope, and this is generally not an option that should be enabled on production library code that is meant to be reused by other packages (other sources referencing the original unobfuscated names will be unable to do so).

Alternatively, direct invocation on a raw string can be done using the attributes provided under the same name as the above base objects that were imported initially. Relevant keyword arguments would be diverted to the appropriate underlying functions, for example:

>>> # pretty print without comments being parsed
>>> print(es5.pretty_print(program_source))
var main = function(greet) {
  var hello = "hello " + greet;
  return hello;
};
console.log(main('world'));

>>> # pretty print with comments parsed
>>> print(es5.pretty_print(program_source, with_comments=True))
// simple program
var main = function(greet) {
  var hello = "hello " + greet;
  return hello;
};
console.log(main('world'));

>>> # minify print
>>> print(es5.minify_print(program_source, obfuscate=True))
var main=function(b){var a="hello "+b;return a;};console.log(main('world'));

Source map generation

For the generation of source maps, a lower level unparser instance can be constructed through one of the printer factory functions. Passing in an AST node will produce a generator which produces tuples containing the yielded text fragment, plus other information which will aid in the generation of source maps. There are helper functions from the calmjs.parse.sourcemap module can be used like so to write the regenerated source code to some stream, along with processing the results into a sourcemap file. An example:

>>> import json
>>> from io import StringIO
>>> from calmjs.parse.unparsers.es5 import pretty_printer
>>> from calmjs.parse.sourcemap import encode_sourcemap, write
>>> stream_p = StringIO()
>>> print_p = pretty_printer()
>>> rawmap_p, _, names_p = write(print_p(program), stream_p)
>>> sourcemap_p = encode_sourcemap(
...     'demo.min.js', rawmap_p, ['custom_name.js'], names_p)
>>> print(json.dumps(sourcemap_p, indent=2, sort_keys=True))
{
  "file": "demo.min.js",
  "mappings": "AAEA;IACI;IACA;AACJ;AACA;",
  "names": [],
  "sources": [
    "custom_name.js"
  ],
  "version": 3
}
>>> print(stream_p.getvalue())
var main = function(greet) {
...

Likewise, this works similarly for the minify printer, which provides the ability to create out a minified output with unneeded whitespaces removed and identifiers obfuscated with the shortest possible value.

Note that in previous example, the second return value in the write method was not used and that a custom value was passed in. This is simply due to how the program was generated from a string and thus the sourcepath attribute was not assigned with a usable value for populating the "sources" list in the resulting source map. For the following example, assign a value to that attribute on the program directly.

>>> from calmjs.parse.unparsers.es5 import minify_printer
>>> program.sourcepath = 'demo.js'  # say this was opened there
>>> stream_m = StringIO()
>>> print_m = minify_printer(obfuscate=True, obfuscate_globals=True)
>>> sourcemap_m = encode_sourcemap(
...     'demo.min.js', *write(print_m(program), stream_m))
>>> print(json.dumps(sourcemap_m, indent=2, sort_keys=True))
{
  "file": "demo.min.js",
  "mappings": "AAEA,IAAIA,CAAK,CAAE,SAASC,CAAK,CAAE,CACvB,...,YAAYF,CAAI",
  "names": [
    "main",
    "greet",
    "hello"
  ],
  "sources": [
    "demo.js"
  ],
  "version": 3
}
>>> print(stream_m.getvalue())
var a=function(b){var a="hello "+b;return a;};console.log(a('world'));

A high level API for working with named streams (i.e. opened files, or stream objects like io.StringIO assigned with a name attribute) is provided by the read and write functions from io module. The following example shows how to use the function to read from a stream and write out the relevant items back out to the write only streams:

>>> from calmjs.parse import io
>>> h4_program_src = open('/tmp/html4.js')
>>> h4_program_min = open('/tmp/html4.min.js', 'w+')
>>> h4_program_map = open('/tmp/html4.min.js.map', 'w+')
>>> h4_program = io.read(es5, h4_program_src)
>>> print(h4_program)
var bold = function(s) {
  return '<b>' + s + '</b>';
};
var italics = function(s) {
  return '<i>' + s + '</i>';
};
>>> io.write(print_m, h4_program, h4_program_min, h4_program_map)
>>> pos = h4_program_map.seek(0)
>>> print(h4_program_map.read())
{"file": "html4.min.js", "mappings": ..., "version": 3}
>>> pos = h4_program_min.seek(0)
>>> print(h4_program_min.read())
var b=function(a){return'<b>'+a+'</b>';};var a=function(a){...};
//# sourceMappingURL=html4.min.js.map

For a simple concatenation of multiple sources into one file, along with inline source map (i.e. where the sourceMappingURL is a data: URL of the base64 encoding of the JSON string), the following may be done:

>>> files = [open('/tmp/html4.js'), open('/tmp/legacy.js')]
>>> combined = open('/tmp/combined.js', 'w+')
>>> io.write(print_p, (io.read(es5, f) for f in files), combined, combined)
>>> pos = combined.seek(0)
>>> print(combined.read())
var bold = function(s) {
    return '<b>' + s + '</b>';
};
var italics = function(s) {
    return '<i>' + s + '</i>';
};
var marquee = function(s) {
    return '<marquee>' + s + '</marquee>';
};
var blink = function(s) {
    return '<blink>' + s + '</blink>';
};
//# sourceMappingURL=data:application/json;base64;...

In this example, the io.write function was provided with the pretty unparser, an generator expression that will produce the two ASTs from the two source files, and then both the target and sourcemap argument are identical, which forces the source map generator to generate the base64 encoding.

Do note that if multiple ASTs were supplied to a minifying printer with globals being obfuscated, the resulting script will have the earlier obfuscated global names mangled by later ones, as the unparsing is done separately by the io.write function.

Extract an AST to a dict

To assist with extracting values from an ast into a dict, the calmjs.parse.unparsers.extractor module provides an ast_to_dict helper function to aid with that. This function will accept any valid ast that was parsed as the argument,

>>> from calmjs.parse.unparsers.extractor import ast_to_dict
>>> configuration = es5('''
... var config = module.exports = {};
...
... var name = "Morgan"
... msg = "Hello, " + name + "! " + "Welcome to the host.";
...
... config.server = {
...   host: '0.0.0.0',
...   port: process.env.PORT || 8000,
...   threads: 4 + 4,
...   columns: ['id', 'name', 'description'],
...   memory: 1 << 15,
...   msg: msg
... };
...
... // default proxy stub
... config.proxy = {
...   host: 'localhost',
...   port: 8080,
...   options: {
...     "https": !1,
...     "threshold": -100
...   }
... };
... ''')
>>> baseconf = ast_to_dict(configuration)

Accessing the values is simply done as a mapping:

>>> print(baseconf['name'])
Morgan

Assignments are bound to the entire expression, i.e. not interpreted down to individual existing assignments.

>>> baseconf['config']
{}
>>> baseconf['config.server']['columns']
['id', 'name', 'description']
>>> baseconf['config.server']['msg']
'msg'
>>> baseconf['config.proxy']['options']['threshold']
-100

Note that the -100 value involves folding the unary expression with the - operator, and by default all other expressions of this type are simply written back out as is.

>>> baseconf['config.proxy']['options']['https']
'!1'
>>> baseconf['msg']
'"Hello, " + name + "! " + "Welcome to the host."'
>>> baseconf['config.server']['threads']
'4 + 4'

To assist with a more generalized usage, the ast_to_dict provides an additional fold_ops argument. When set to True, operator folding will be enabled on supported types; for example, constants will be attempted to be folded into a single value as per how operators are handled in the ECMAScript specification. This is often useful for ensuring concatenated strings are merged, and normalizing short-hand definition of boolean values via !0 or !1, among other commonly seen expressions.

>>> foldedconf = ast_to_dict(configuration, fold_ops=True)
>>> foldedconf['config.server']['threads']
8
>>> foldedconf['config.server']['memory']
32768
>>> foldedconf['config.server']['port']
8000
>>> foldedconf['config.proxy']['options']['https']
False
>>> # variables will remain as is
>>> foldedconf['config.server']['msg']
'msg'
>>> # however, in the context of a concatenated string, it will form
>>> # a format string instead.
>>> foldedconf['msg']
'Hello, {name}! Welcome to the host.'

As noted, any valid AST may serve as the input argument, with any dangling expressions (i.e. those that are not assigned or bound to a name) simply be appened to a list keyed under of its outermost asttype.

>>> from calmjs.parse.asttypes import (
...     Identifier, FuncExpr, UnaryExpr)
>>> dict_of_ast = ast_to_dict(es5(u"""
... var i;
... i;
... !'ok';
... function foo(bar) {
...     baz = true;
... }
... (function(y) {
...     x = 1;
... });
... """), fold_ops=True)
>>> dict_of_ast['i']
>>> dict_of_ast[Identifier]
['i']
>>> dict_of_ast[UnaryExpr]  # not simply string or boolean
[False]
>>> dict_of_ast['foo']  # named function resolved
[['bar'], {'baz': True}]
>>> dict_of_ast[FuncExpr]
[[['y'], {'x': 1}]]

Lower level unparsing API

Naturally, the printers demonstrated previously are constructed using the underlying Unparser class, which in turn bridges together the walk function and the Dispatcher class found in the walker module. The walk function walks through the AST node with an instance of the Dispatcher class, which provides a description of all node types for the particular type of AST node provided, along with the relevant handlers. These handlers can be set up using existing rule provider functions. For instance, a printer for obfuscating identifier names while maintaining indentation for the output of an ES5 AST can be constructed like so:

>>> from calmjs.parse.unparsers.es5 import Unparser
>>> from calmjs.parse.rules import indent
>>> from calmjs.parse.rules import obfuscate
>>> pretty_obfuscate = Unparser(rules=(
...     # note that indent must come after, so that the whitespace
...     # handling rules by indent will shadow over the minimum set
...     # provided by obfuscate.
...     obfuscate(obfuscate_globals=False),
...     indent(indent_str='    '),
... ))
>>> math_module = es5('''
... (function(root) {
...   var fibonacci = function(count) {
...     if (count < 2)
...       return count;
...     else
...       return fibonacci(count - 1) + fibonacci(count - 2);
...   };
...
...   var factorial = function(n) {
...     if (n < 1)
...       throw new Error('factorial where n < 1 not supported');
...     else if (n == 1)
...       return 1;
...     else
...       return n * factorial(n - 1);
...   }
...
...   root.fibonacci = fibonacci;
...   root.factorial = factorial;
... })(window);
...
... var value = window.factorial(5) / window.fibonacci(5);
... console.log('the value is ' + value);
... ''')
>>> print(''.join(c.text for c in pretty_obfuscate(math_module)))
(function(b) {
    var a = function(b) {
        if (b < 2) return b;
        else return a(b - 1) + a(b - 2);
    };
    var c = function(a) {
        if (a < 1) throw new Error('factorial where n < 1 not supported');
        else if (a == 1) return 1;
        else return a * c(a - 1);
    };
    b.fibonacci = a;
    b.factorial = c;
})(window);
var value = window.factorial(5) / window.fibonacci(5);
console.log('the value is ' + value);

Each of the rules (functions) have specific options that are set using specific keyword arguments, details are documented in their respective docstrings.

At an even lower level, the ruletypes submodule contains the primitives that form the underlying definitions that each Dispatcher implementations currently available. For an example on how this might be extended beyond simply unparsing back to text, see the source for the extractor unparser module.

Tree walking

AST (Abstract Syntax Tree) generic walker classes are defined under the appropriate named modules calmjs.parse.walkers. Two default walker classes are supplied. One of them is the ReprWalker class which was previously demonstrated. The other is the Walker class, which supplies a collection of generic tree walking methods for a tree of AST nodes. The following is an example usage on how one might extract all Object assignments from a given script file:

>>> from calmjs.parse import es5
>>> from calmjs.parse.asttypes import Object, VarDecl, FunctionCall
>>> from calmjs.parse.walkers import Walker
>>> walker = Walker()
>>> declarations = es5('''
... var i = 1;
... var s = {
...     a: "test",
...     o: {
...         v: "value"
...     }
... };
... foo({foo: "bar"});
... function bar() {
...     var t = {
...         foo: "bar",
...     };
...     return t;
... }
... foo.bar = bar;
... foo.bar();
... ''')
>>> # print out the object nodes that were part of some assignments
>>> for node in walker.filter(declarations, lambda node: (
...         isinstance(node, VarDecl) and
...         isinstance(node.initializer, Object))):
...     print(node.initializer)
...
{
  a: "test",
  o: {
    v: "value"
  }
}
{
  foo: "bar"
}
>>> # print out all function calls
>>> for node in walker.filter(declarations, lambda node: (
...         isinstance(node, FunctionCall))):
...     print(node.identifier)
...
foo
foo.bar

Further details and example usage can be consulted from the various docstrings found within the module.

Instantiation of parser classes fails with UnicodeEncodeError

For platforms or systems that do not have utf8 configured as the default encoding, the automatic table generation may fail when constructing a parser instance. An example:

>>> from calmjs.parse.parsers import es5
>>> parser = es5.Parser()
Traceback (most recent call last):
  ...
  File "c:\python35\....\ply\lex.py", line 1043, in lex
    lexobj.writetab(lextab, outputdir)
  File "c:\python35\....\ply\lex.py", line 195, in writetab
    tf.write('_lexstatere   = %s\n' % repr(tabre))
  File "c:\python35\lib\encodings\cp1252.py", line 19, in encode
    return codecs.charmap_encode(input,self.errors,encoding_table)[0]
UnicodeEncodeError: 'charmap' codec can't encode character '\u02c1' ...

A workaround helper script is provided, it may be executed like so:

$ python -m calmjs.parse.parsers.optimize

Further details on this topic may be found in the manual optimization section of this document.

WARNING: There are unused tokens on import

This indicates that the installation method or source for this package being imported isn’t optimized. A quick workaround is to follow the instructions at the manual optimization section of this document to ensure these messages are no longer generated (and if this warning happens every time the module is imported, it means the symbol tables are regenerated every time that happens and this extra computational overhead should be corrected through the generation of that optimization module).

The optimization modules are included with the wheel release and the source release on PyPI, but it is not part of the source repository as generated code are never committed. Should a binary release made by a third-party results in this warning upon import, their release should be corrected to include the optimization module.

Moreover, there are safeguards in place that prevent this warning from being generated for releases made for releases from 1.3.1 onwards by a more heavy handed enforcement of this optimization step at build time, but persistent (or careless) actors may circumvent this during the build process, but official releases made through PyPI should include the required optimization for all supported ply versions (which are versions 3.6 to 3.11, inclusive).

Alternatively, this issue may also occur via usage of pyinstaller if the package metadata is not copied for ply in versions prior to calmjs.parse-1.3.1 and will always occur if the hidden imports are not declared for those optimization modules. The following hook should may be used to ensure calmjs.parse functions correctly in the compiled binary:

from PyInstaller.utils.hooks import collect_data_files, copy_metadata
from calmjs.parse.utils import generate_tab_names

datas = []
datas.extend(collect_data_files("ply"))
datas.extend(copy_metadata("ply"))
datas.extend(collect_data_files("calmjs.parse"))
datas.extend(copy_metadata("calmjs.parse"))

hiddenimports = []
hiddenimports.extend(generate_tab_names('calmjs.parse.parsers.es5'))

# if running under Python 3 with ply-3.11, above is equivalent to
# hiddenimports = [
#     "calmjs.parse.parsers.lextab_es5_py3_ply3_11",
#     "calmjs.parse.parsers.yacctab_es5_py3_ply3_11",
# ]

Slow performance

As this program is basically fully decomposed into very small functions, this result in massive performance penalties as compared to other implementations due to function calls being one of the most expensive operations in Python. It may be possible to further optimize the definitions within the description in the Dispatcher by combining all the resolved generator functions for each asttype Node type, however this will may require both the token and layout functions not having arguments with name collisions, and the new function will take in all of those arguments in one go.

ERROR message about import error when trying to install

As noted in the error message, the ply and setuptools package must be installed before attempting to install build the package in the situation where the pre-generated modules are missing. This situation may be caused by building directly using the source provided by the source code repository, or where there is no matching pre-generated module matching with the installed version of ply. Please ensure that ply is installed and available first before installing from source if this error message is sighted.