"""Implementation of JSONEncoder """ import re try: from _json import encode_basestring_ascii as c_encode_basestring_ascii except ImportError: c_encode_basestring_ascii = None try: from _json import encode_basestring as c_encode_basestring except ImportError: c_encode_basestring = None try: from _json import make_encoder as c_make_encoder except ImportError: c_make_encoder = None ESCAPE = re.compile(r'[\x00-\x1f\\"\b\f\n\r\t]') ESCAPE_ASCII = re.compile(r'([\\"]|[^\ -~])') HAS_UTF8 = re.compile(b'[\x80-\xff]') ESCAPE_DCT = { '\\': '\\\\', '"': '\\"', '\b': '\\b', '\f': '\\f', '\n': '\\n', '\r': '\\r', '\t': '\\t', } for i in range(0x20): ESCAPE_DCT.setdefault(chr(i), '\\u{0:04x}'.format(i)) #ESCAPE_DCT.setdefault(chr(i), '\\u%04x' % (i,)) INFINITY = float('inf') FLOAT_REPR = repr def py_encode_basestring(s): """Return a JSON representation of a Python string """ def replace(match): return ESCAPE_DCT[match.group(0)] return '"' + ESCAPE.sub(replace, s) + '"' encode_basestring = (c_encode_basestring or py_encode_basestring) def py_encode_basestring_ascii(s): """Return an ASCII-only JSON representation of a Python string """ def replace(match): s = match.group(0) try: return ESCAPE_DCT[s] except KeyError: n = ord(s) if n < 0x10000: return '\\u{0:04x}'.format(n) #return '\\u%04x' % (n,) else: # surrogate pair n -= 0x10000 s1 = 0xd800 | ((n >> 10) & 0x3ff) s2 = 0xdc00 | (n & 0x3ff) return '\\u{0:04x}\\u{1:04x}'.format(s1, s2) return '"' + ESCAPE_ASCII.sub(replace, s) + '"' encode_basestring_ascii = ( c_encode_basestring_ascii or py_encode_basestring_ascii) class JSONEncoder(object): """Extensible JSON <http://json.org> encoder for Python data structures. Supports the following objects and types by default: +-------------------+---------------+ | Python | JSON | +===================+===============+ | dict | object | +-------------------+---------------+ | list, tuple | array | +-------------------+---------------+ | str | string | +-------------------+---------------+ | int, float | number | +-------------------+---------------+ | True | true | +-------------------+---------------+ | False | false | +-------------------+---------------+ | None | null | +-------------------+---------------+ To extend this to recognize other objects, subclass and implement a ``.default()`` method with another method that returns a serializable object for ``o`` if possible, otherwise it should call the superclass implementation (to raise ``TypeError``). """ item_separator = ', ' key_separator = ': ' def __init__(self, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None): """Constructor for JSONEncoder, with sensible defaults. If skipkeys is false, then it is a TypeError to attempt encoding of keys that are not str, int, float or None. If skipkeys is True, such items are simply skipped. If ensure_ascii is true, the output is guaranteed to be str objects with all incoming non-ASCII characters escaped. If ensure_ascii is false, the output can contain non-ASCII characters. If check_circular is true, then lists, dicts, and custom encoded objects will be checked for circular references during encoding to prevent an infinite recursion (which would cause an OverflowError). Otherwise, no such check takes place. If allow_nan is true, then NaN, Infinity, and -Infinity will be encoded as such. This behavior is not JSON specification compliant, but is consistent with most JavaScript based encoders and decoders. Otherwise, it will be a ValueError to encode such floats. If sort_keys is true, then the output of dictionaries will be sorted by key; this is useful for regression tests to ensure that JSON serializations can be compared on a day-to-day basis. If indent is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines. None is the most compact representation. If specified, separators should be an (item_separator, key_separator) tuple. The default is (', ', ': ') if *indent* is ``None`` and (',', ': ') otherwise. To get the most compact JSON representation, you should specify (',', ':') to eliminate whitespace. If specified, default is a function that gets called for objects that can't otherwise be serialized. It should return a JSON encodable version of the object or raise a ``TypeError``. """ self.skipkeys = skipkeys self.ensure_ascii = ensure_ascii self.check_circular = check_circular self.allow_nan = allow_nan self.sort_keys = sort_keys self.indent = indent if separators is not None: self.item_separator, self.key_separator = separators elif indent is not None: self.item_separator = ',' if default is not None: self.default = default def default(self, o): """Implement this method in a subclass such that it returns a serializable object for ``o``, or calls the base implementation (to raise a ``TypeError``). For example, to support arbitrary iterators, you could implement default like this:: def default(self, o): try: iterable = iter(o) except TypeError: pass else: return list(iterable) # Let the base class default method raise the TypeError return JSONEncoder.default(self, o) """ raise TypeError(repr(o) + " is not JSON serializable") def encode(self, o): """Return a JSON string representation of a Python data structure. >>> from json.encoder import JSONEncoder >>> JSONEncoder().encode({"foo": ["bar", "baz"]}) '{"foo": ["bar", "baz"]}' """ # This is for extremely simple cases and benchmarks. if isinstance(o, str): if self.ensure_ascii: return encode_basestring_ascii(o) else: return encode_basestring(o) # This doesn't pass the iterator directly to ''.join() because the # exceptions aren't as detailed. The list call should be roughly # equivalent to the PySequence_Fast that ''.join() would do. chunks = self.iterencode(o, _one_shot=True) if not isinstance(chunks, (list, tuple)): chunks = list(chunks) return ''.join(chunks) def iterencode(self, o, _one_shot=False): """Encode the given object and yield each string representation as available. For example:: for chunk in JSONEncoder().iterencode(bigobject): mysocket.write(chunk) """ if self.check_circular: markers = {} else: markers = None if self.ensure_ascii: _encoder = encode_basestring_ascii else: _encoder = encode_basestring def floatstr(o, allow_nan=self.allow_nan, _repr=FLOAT_REPR, _inf=INFINITY, _neginf=-INFINITY): # Check for specials. Note that this type of test is processor # and/or platform-specific, so do tests which don't depend on the # internals. if o != o: text = 'NaN' elif o == _inf: text = 'Infinity' elif o == _neginf: text = '-Infinity' else: return _repr(o) if not allow_nan: raise ValueError( "Out of range float values are not JSON compliant: " + repr(o)) return text if (_one_shot and c_make_encoder is not None and self.indent is None): _iterencode = c_make_encoder( markers, self.default, _encoder, self.indent, self.key_separator, self.item_separator, self.sort_keys, self.skipkeys, self.allow_nan) else: _iterencode = _make_iterencode( markers, self.default, _encoder, self.indent, floatstr, self.key_separator, self.item_separator, self.sort_keys, self.skipkeys, _one_shot) return _iterencode(o, 0) def _make_iterencode(markers, _default, _encoder, _indent, _floatstr, _key_separator, _item_separator, _sort_keys, _skipkeys, _one_shot, ## HACK: hand-optimized bytecode; turn globals into locals ValueError=ValueError, dict=dict, float=float, id=id, int=int, isinstance=isinstance, list=list, str=str, tuple=tuple, ): if _indent is not None and not isinstance(_indent, str): _indent = ' ' * _indent def _iterencode_list(lst, _current_indent_level): if not lst: yield '[]' return if markers is not None: markerid = id(lst) if markerid in markers: raise ValueError("Circular reference detected") markers[markerid] = lst buf = '[' if _indent is not None: _current_indent_level += 1 newline_indent = '\n' + _indent * _current_indent_level separator = _item_separator + newline_indent buf += newline_indent else: newline_indent = None separator = _item_separator first = True for value in lst: if first: first = False else: buf = separator if isinstance(value, str): yield buf + _encoder(value) elif value is None: yield buf + 'null' elif value is True: yield buf + 'true' elif value is False: yield buf + 'false' elif isinstance(value, int): # Subclasses of int/float may override __str__, but we still # want to encode them as integers/floats in JSON. One example # within the standard library is IntEnum. yield buf + str(int(value)) elif isinstance(value, float): # see comment above for int yield buf + _floatstr(float(value)) else: yield buf if isinstance(value, (list, tuple)): chunks = _iterencode_list(value, _current_indent_level) elif isinstance(value, dict): chunks = _iterencode_dict(value, _current_indent_level) else: chunks = _iterencode(value, _current_indent_level) yield from chunks if newline_indent is not None: _current_indent_level -= 1 yield '\n' + _indent * _current_indent_level yield ']' if markers is not None: del markers[markerid] def _iterencode_dict(dct, _current_indent_level): if not dct: yield '{}' return if markers is not None: markerid = id(dct) if markerid in markers: raise ValueError("Circular reference detected") markers[markerid] = dct yield '{' if _indent is not None: _current_indent_level += 1 newline_indent = '\n' + _indent * _current_indent_level item_separator = _item_separator + newline_indent yield newline_indent else: newline_indent = None item_separator = _item_separator first = True if _sort_keys: items = sorted(dct.items(), key=lambda kv: kv[0]) else: items = dct.items() for key, value in items: if isinstance(key, str): pass # JavaScript is weakly typed for these, so it makes sense to # also allow them. Many encoders seem to do something like this. elif isinstance(key, float): # see comment for int/float in _make_iterencode key = _floatstr(float(key)) elif key is True: key = 'true' elif key is False: key = 'false' elif key is None: key = 'null' elif isinstance(key, int): # see comment for int/float in _make_iterencode key = str(int(key)) elif _skipkeys: continue else: raise TypeError("key " + repr(key) + " is not a string") if first: first = False else: yield item_separator yield _encoder(key) yield _key_separator if isinstance(value, str): yield _encoder(value) elif value is None: yield 'null' elif value is True: yield 'true' elif value is False: yield 'false' elif isinstance(value, int): # see comment for int/float in _make_iterencode yield str(int(value)) elif isinstance(value, float): # see comment for int/float in _make_iterencode yield _floatstr(float(value)) else: if isinstance(value, (list, tuple)): chunks = _iterencode_list(value, _current_indent_level) elif isinstance(value, dict): chunks = _iterencode_dict(value, _current_indent_level) else: chunks = _iterencode(value, _current_indent_level) yield from chunks if newline_indent is not None: _current_indent_level -= 1 yield '\n' + _indent * _current_indent_level yield '}' if markers is not None: del markers[markerid] def _iterencode(o, _current_indent_level): if isinstance(o, str): yield _encoder(o) elif o is None: yield 'null' elif o is True: yield 'true' elif o is False: yield 'false' elif isinstance(o, int): # see comment for int/float in _make_iterencode yield str(int(o)) elif isinstance(o, float): # see comment for int/float in _make_iterencode yield _floatstr(float(o)) elif isinstance(o, (list, tuple)): yield from _iterencode_list(o, _current_indent_level) elif isinstance(o, dict): yield from _iterencode_dict(o, _current_indent_level) else: if markers is not None: markerid = id(o) if markerid in markers: raise ValueError("Circular reference detected") markers[markerid] = o o = _default(o) yield from _iterencode(o, _current_indent_level) if markers is not None: del markers[markerid] return _iterencode

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 : 216.73.216.134

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