""" ast ~~~ The `ast` module helps Python applications to process trees of the Python abstract syntax grammar. The abstract syntax itself might change with each Python release; this module helps to find out programmatically what the current grammar looks like and allows modifications of it. An abstract syntax tree can be generated by passing `ast.PyCF_ONLY_AST` as a flag to the `compile()` builtin function or by using the `parse()` function from this module. The result will be a tree of objects whose classes all inherit from `ast.AST`. A modified abstract syntax tree can be compiled into a Python code object using the built-in `compile()` function. Additionally various helper functions are provided that make working with the trees simpler. The main intention of the helper functions and this module in general is to provide an easy to use interface for libraries that work tightly with the python syntax (template engines for example). :copyright: Copyright 2008 by Armin Ronacher. :license: Python License. """ from _ast import * def parse(source, filename='<unknown>', mode='exec'): """ Parse the source into an AST node. Equivalent to compile(source, filename, mode, PyCF_ONLY_AST). """ return compile(source, filename, mode, PyCF_ONLY_AST) def literal_eval(node_or_string): """ Safely evaluate an expression node or a string containing a Python expression. The string or node provided may only consist of the following Python literal structures: strings, bytes, numbers, tuples, lists, dicts, sets, booleans, and None. """ if isinstance(node_or_string, str): node_or_string = parse(node_or_string, mode='eval') if isinstance(node_or_string, Expression): node_or_string = node_or_string.body def _convert(node): if isinstance(node, (Str, Bytes)): return node.s elif isinstance(node, Num): return node.n elif isinstance(node, Tuple): return tuple(map(_convert, node.elts)) elif isinstance(node, List): return list(map(_convert, node.elts)) elif isinstance(node, Set): return set(map(_convert, node.elts)) elif isinstance(node, Dict): return dict((_convert(k), _convert(v)) for k, v in zip(node.keys, node.values)) elif isinstance(node, NameConstant): return node.value elif isinstance(node, UnaryOp) and \ isinstance(node.op, (UAdd, USub)) and \ isinstance(node.operand, (Num, UnaryOp, BinOp)): operand = _convert(node.operand) if isinstance(node.op, UAdd): return + operand else: return - operand elif isinstance(node, BinOp) and \ isinstance(node.op, (Add, Sub)) and \ isinstance(node.right, (Num, UnaryOp, BinOp)) and \ isinstance(node.left, (Num, UnaryOp, BinOp)): left = _convert(node.left) right = _convert(node.right) if isinstance(node.op, Add): return left + right else: return left - right raise ValueError('malformed node or string: ' + repr(node)) return _convert(node_or_string) def dump(node, annotate_fields=True, include_attributes=False): """ Return a formatted dump of the tree in *node*. This is mainly useful for debugging purposes. The returned string will show the names and the values for fields. This makes the code impossible to evaluate, so if evaluation is wanted *annotate_fields* must be set to False. Attributes such as line numbers and column offsets are not dumped by default. If this is wanted, *include_attributes* can be set to True. """ def _format(node): if isinstance(node, AST): fields = [(a, _format(b)) for a, b in iter_fields(node)] rv = '%s(%s' % (node.__class__.__name__, ', '.join( ('%s=%s' % field for field in fields) if annotate_fields else (b for a, b in fields) )) if include_attributes and node._attributes: rv += fields and ', ' or ' ' rv += ', '.join('%s=%s' % (a, _format(getattr(node, a))) for a in node._attributes) return rv + ')' elif isinstance(node, list): return '[%s]' % ', '.join(_format(x) for x in node) return repr(node) if not isinstance(node, AST): raise TypeError('expected AST, got %r' % node.__class__.__name__) return _format(node) def copy_location(new_node, old_node): """ Copy source location (`lineno` and `col_offset` attributes) from *old_node* to *new_node* if possible, and return *new_node*. """ for attr in 'lineno', 'col_offset': if attr in old_node._attributes and attr in new_node._attributes \ and hasattr(old_node, attr): setattr(new_node, attr, getattr(old_node, attr)) return new_node def fix_missing_locations(node): """ When you compile a node tree with compile(), the compiler expects lineno and col_offset attributes for every node that supports them. This is rather tedious to fill in for generated nodes, so this helper adds these attributes recursively where not already set, by setting them to the values of the parent node. It works recursively starting at *node*. """ def _fix(node, lineno, col_offset): if 'lineno' in node._attributes: if not hasattr(node, 'lineno'): node.lineno = lineno else: lineno = node.lineno if 'col_offset' in node._attributes: if not hasattr(node, 'col_offset'): node.col_offset = col_offset else: col_offset = node.col_offset for child in iter_child_nodes(node): _fix(child, lineno, col_offset) _fix(node, 1, 0) return node def increment_lineno(node, n=1): """ Increment the line number of each node in the tree starting at *node* by *n*. This is useful to "move code" to a different location in a file. """ for child in walk(node): if 'lineno' in child._attributes: child.lineno = getattr(child, 'lineno', 0) + n return node def iter_fields(node): """ Yield a tuple of ``(fieldname, value)`` for each field in ``node._fields`` that is present on *node*. """ for field in node._fields: try: yield field, getattr(node, field) except AttributeError: pass def iter_child_nodes(node): """ Yield all direct child nodes of *node*, that is, all fields that are nodes and all items of fields that are lists of nodes. """ for name, field in iter_fields(node): if isinstance(field, AST): yield field elif isinstance(field, list): for item in field: if isinstance(item, AST): yield item def get_docstring(node, clean=True): """ Return the docstring for the given node or None if no docstring can be found. If the node provided does not have docstrings a TypeError will be raised. """ if not isinstance(node, (AsyncFunctionDef, FunctionDef, ClassDef, Module)): raise TypeError("%r can't have docstrings" % node.__class__.__name__) if node.body and isinstance(node.body[0], Expr) and \ isinstance(node.body[0].value, Str): if clean: import inspect return inspect.cleandoc(node.body[0].value.s) return node.body[0].value.s def walk(node): """ Recursively yield all descendant nodes in the tree starting at *node* (including *node* itself), in no specified order. This is useful if you only want to modify nodes in place and don't care about the context. """ from collections import deque todo = deque([node]) while todo: node = todo.popleft() todo.extend(iter_child_nodes(node)) yield node class NodeVisitor(object): """ A node visitor base class that walks the abstract syntax tree and calls a visitor function for every node found. This function may return a value which is forwarded by the `visit` method. This class is meant to be subclassed, with the subclass adding visitor methods. Per default the visitor functions for the nodes are ``'visit_'`` + class name of the node. So a `TryFinally` node visit function would be `visit_TryFinally`. This behavior can be changed by overriding the `visit` method. If no visitor function exists for a node (return value `None`) the `generic_visit` visitor is used instead. Don't use the `NodeVisitor` if you want to apply changes to nodes during traversing. For this a special visitor exists (`NodeTransformer`) that allows modifications. """ def visit(self, node): """Visit a node.""" method = 'visit_' + node.__class__.__name__ visitor = getattr(self, method, self.generic_visit) return visitor(node) def generic_visit(self, node): """Called if no explicit visitor function exists for a node.""" for field, value in iter_fields(node): if isinstance(value, list): for item in value: if isinstance(item, AST): self.visit(item) elif isinstance(value, AST): self.visit(value) class NodeTransformer(NodeVisitor): """ A :class:`NodeVisitor` subclass that walks the abstract syntax tree and allows modification of nodes. The `NodeTransformer` will walk the AST and use the return value of the visitor methods to replace or remove the old node. If the return value of the visitor method is ``None``, the node will be removed from its location, otherwise it is replaced with the return value. The return value may be the original node in which case no replacement takes place. Here is an example transformer that rewrites all occurrences of name lookups (``foo``) to ``data['foo']``:: class RewriteName(NodeTransformer): def visit_Name(self, node): return copy_location(Subscript( value=Name(id='data', ctx=Load()), slice=Index(value=Str(s=node.id)), ctx=node.ctx ), node) Keep in mind that if the node you're operating on has child nodes you must either transform the child nodes yourself or call the :meth:`generic_visit` method for the node first. For nodes that were part of a collection of statements (that applies to all statement nodes), the visitor may also return a list of nodes rather than just a single node. Usually you use the transformer like this:: node = YourTransformer().visit(node) """ def generic_visit(self, node): for field, old_value in iter_fields(node): if isinstance(old_value, list): new_values = [] for value in old_value: if isinstance(value, AST): value = self.visit(value) if value is None: continue elif not isinstance(value, AST): new_values.extend(value) continue new_values.append(value) old_value[:] = new_values elif isinstance(old_value, AST): new_node = self.visit(old_value) if new_node is None: delattr(node, field) else: setattr(node, field, new_node) return node

RE-INVENTING THE TELEVISION NEWS BUSINESS*

A revolution in video storytelling

Creating entirely new & cost-effective production methods

From the world leaders in video production training and the creators of Character Driven Storytelling™

*and every other business that uses video

WHAT WE DO

Over the past 35 years, we have designed, built or restructured some of the most powerful news and journalism companies in the world.

We replace the traditional TV news ‘crew’ with one highly trained journalist, working alone with nothing but an iPhone.

No more TV news ‘crews’, no editors and no field producers.

This is television news done the way newspaper journalism is done – one reporter with their electronic pad and pencil.

In doing this, we can cut the cost of production by as much as 75% while increasing ratings and audience engagement.

In the place of conventional TV news ‘packages’ – ie, reporter stand up, interview, b-roll, man on the street, we marry great journalism with Netflix and Hollywood storytelling.

It’s a combination that works.

We have taken most of our clients to #1 in their respective markets.

And it’s not just for news. Any company, any profit, any NGO and anyone else who is online needs to tell their story in compelling yet cost-effective video. We can teach you to do that. Either in person or virtually.

EXAMPLES OF WHAT WE CAN TEACH YOUR STAFF TO PRODUCE

ITAY HOD

Itay Hod, MMJ with KPIX/CBS in San Francisco, took the 5-Day Intensive Video Storytelling Bootcamp in 2018.

Because he works alone, with only an iPhone, he was able to embed himself with a homeless family.

Here’s the story he produced in a one-day turn.

KIET DO

Kiet Do, an MMJ with KPIX/CBS in San Francisco, took the 5-Day Intensive Video Storytelling Bootcamp in 2021.

Here is a story he produced, all on his own, with only an iPhone and in a one-day turn.

TAYLOR SCHAUB

Taylor Schaub, an MMJ with Spectrum News 1 in LA, took the 5-Day Intensive Video Storytelling Bootcamp in 2023.

Here is a story he turned in only one day, using only an iPhone. It was the first video story he ever did and it was nominated for an Emmy.

THE BOOTCAMP

How do we convert stations and whole networks to working in this way?

Since 1988, we have run intensive 5-Day Video Storytelling Bootcamps

We have done these all over the world.

These are hands-on bootcamps, and participants learn an entirely new way of creating TV news stories.

-We shoot at a 3:1 ratio or lower, so turnaround times are fast.

-We go directly from camera to timelilne and edit – no written scripts. We work in the medium of pictures and sound.

-We are entirely character-driven.

-We are driven by pictures and real events.

-We are focused almost entirely on ’the viewer experience’.

Since 1988, more than 70,000 journalists around the world have taken our bootcamps, either in person on virtualy.

Case Studies

CBS News

We have started to work with CBS News, bringing our ideas of character-driven storytelling to one of the most successful and biggest networks in the United States. Since beginning to work with them ratings have climbed and more importantly, audience engagement is through the ceiling.

Learn More

New York Times Television

We started New York Times Television in 1990 and it was the first paper to be brought into the world of TV. It quickly became one of the most successful non-fiction production companies in the United States. The series and documentaries we produced won many awards including multiple Emmys.

Learn More

The BBC

We have been working with the BBC since the year 2000 helping to convert their national news network to our visual storytelling technique. Most recently we have trained teams from their sports, documentaries, and comedy divisions to make character-driven stories using only smartphones.

Learn More

Spectrum News

For the past five years we have worked with Spectrum News to introduce and train their journalists on visual, character driven storytelling using smartphones helping to create a different kind of local news for their network of 24-Hour News Stations across the United States.

Learn More

The United Nations

In 2006, we were approached by the United Nations. Rather than rely on news outlets, it would be much easier to train the field operatives to produce their own stories. We spent two years working with the UN, training more than 100 of their staff in bootcamps in Geneva and Nairobi.

Learn More

The Newark Star-Ledger

We trained 50 print reporters at the paper to shoot and tell their own stories, in conjunction with their print work. We built a TV newsroom in their existing print newsroom – you could not ask for a better set and they began to live stream their stories in conjunction with their print work.

Learn More

Mcgraw Hill

We spent two years with McGraw Hill, training more than 150 of their staffers, making them completely video literate. McGraw/Hill media properties we transit included Business Week, Aviation Week, (what was the name of the architecture magazine), and JD Power and Associates.

Learn More

Voice of America

In 1990, we were approached by The Voice of America, the official broadcasting agency for the United States Government. When we met with VOA, they were only a short wave radio broadcaster, but working with them, we took them into television, launching VOA-TV.

Learn More

Oyster Yachts

British based Oyster Yachts makes some of the finest yachts in the world. Like every other company, they had to find a way to feed the never-ending video demands of social media – sites like Instagram and TikTok. We trained the Oyster staff to tell their own stories, using only iPhones.

Learn More

Scottish Environmental Protection Agency

We were approached by SEPA, the Scottish Environmental Protection Agency because they had to continually find a way to ‘feed the media beast’. The result was that SEPA was able to tell their own stories, whenever they wanted, and at almost no additional cost.

Learn More

Michael on Media

Michael Rosenblum has been writing about the media since 1988. His work and ideas have appeared in The Guardian, The Huffington Post, Ilkeston Life and many other publications.

He has been blogging regularly for the past 35 years on this subject. Having taught media studies at Columbia University, NYU and now the University of Oxford, he is considered an expert on this subject.

Continue reading this post or look back at previous posts.

Do You Have Questions About Learning Video Skills?

If you would like to know more about our courses contact us and one of our training advisors will be happy to call you.

Your IP : 216.73.216.224

RE-INVENTING THE TELEVISION NEWS BUSINESS*

A revolution in video storytelling

Creating entirely new & cost-effective production methods

From the world leaders in video production training and the creators of Character Driven Storytelling™

*and every other business that uses video

WHAT WE DO

Over the past 35 years, we have designed, built or restructured some of the most powerful news and journalism companies in the world.

We replace the traditional TV news ‘crew’ with one highly trained journalist, working alone with nothing but an iPhone.

No more TV news ‘crews’, no editors and no field producers.

This is television news done the way newspaper journalism is done – one reporter with their electronic pad and pencil.

In doing this, we can cut the cost of production by as much as 75% while increasing ratings and audience engagement.

In the place of conventional TV news ‘packages’ – ie, reporter stand up, interview, b-roll, man on the street, we marry great journalism with Netflix and Hollywood storytelling.

It’s a combination that works.

We have taken most of our clients to #1 in their respective markets.

And it’s not just for news. Any company, any profit, any NGO and anyone else who is online needs to tell their story in compelling yet cost-effective video. We can teach you to do that. Either in person or virtually.

EXAMPLES OF WHAT WE CAN TEACH YOUR STAFF TO PRODUCE

ITAY HOD

Itay Hod, MMJ with KPIX/CBS in San Francisco, took the 5-Day Intensive Video Storytelling Bootcamp in 2018.

Because he works alone, with only an iPhone, he was able to embed himself with a homeless family.

Here’s the story he produced in a one-day turn.

KIET DO

Kiet Do, an MMJ with KPIX/CBS in San Francisco, took the 5-Day Intensive Video Storytelling Bootcamp in 2021.

Here is a story he produced, all on his own, with only an iPhone and in a one-day turn.

TAYLOR SCHAUB

Taylor Schaub, an MMJ with Spectrum News 1 in LA, took the 5-Day Intensive Video Storytelling Bootcamp in 2023.

Here is a story he turned in only one day, using only an iPhone. It was the first video story he ever did and it was nominated for an Emmy.

THE BOOTCAMP

How do we convert stations and whole networks to working in this way?

Since 1988, we have run intensive 5-Day Video Storytelling Bootcamps

We have done these all over the world.

These are hands-on bootcamps, and participants learn an entirely new way of creating TV news stories.

-We shoot at a 3:1 ratio or lower, so turnaround times are fast.

-We go directly from camera to timelilne and edit – no written scripts. We work in the medium of pictures and sound.

-We are entirely character-driven.

-We are driven by pictures and real events.

-We are focused almost entirely on ’the viewer experience’.

Since 1988, more than 70,000 journalists around the world have taken our bootcamps, either in person on virtualy.

Case Studies

CBS News

New York Times Television

The BBC

Spectrum News

The United Nations

The Newark Star-Ledger

Mcgraw Hill

Voice of America

Oyster Yachts

Scottish Environmental Protection Agency

Michael on Media