"""Utilities for comparing files and directories. Classes: dircmp Functions: cmp(f1, f2, shallow=True) -> int cmpfiles(a, b, common) -> ([], [], []) clear_cache() """ import os import stat from itertools import filterfalse __all__ = ['clear_cache', 'cmp', 'dircmp', 'cmpfiles', 'DEFAULT_IGNORES'] _cache = {} BUFSIZE = 8*1024 DEFAULT_IGNORES = [ 'RCS', 'CVS', 'tags', '.git', '.hg', '.bzr', '_darcs', '__pycache__'] def clear_cache(): """Clear the filecmp cache.""" _cache.clear() def cmp(f1, f2, shallow=True): """Compare two files. Arguments: f1 -- First file name f2 -- Second file name shallow -- Just check stat signature (do not read the files). defaults to True. Return value: True if the files are the same, False otherwise. This function uses a cache for past comparisons and the results, with cache entries invalidated if their stat information changes. The cache may be cleared by calling clear_cache(). """ s1 = _sig(os.stat(f1)) s2 = _sig(os.stat(f2)) if s1[0] != stat.S_IFREG or s2[0] != stat.S_IFREG: return False if shallow and s1 == s2: return True if s1[1] != s2[1]: return False outcome = _cache.get((f1, f2, s1, s2)) if outcome is None: outcome = _do_cmp(f1, f2) if len(_cache) > 100: # limit the maximum size of the cache clear_cache() _cache[f1, f2, s1, s2] = outcome return outcome def _sig(st): return (stat.S_IFMT(st.st_mode), st.st_size, st.st_mtime) def _do_cmp(f1, f2): bufsize = BUFSIZE with open(f1, 'rb') as fp1, open(f2, 'rb') as fp2: while True: b1 = fp1.read(bufsize) b2 = fp2.read(bufsize) if b1 != b2: return False if not b1: return True # Directory comparison class. # class dircmp: """A class that manages the comparison of 2 directories. dircmp(a, b, ignore=None, hide=None) A and B are directories. IGNORE is a list of names to ignore, defaults to DEFAULT_IGNORES. HIDE is a list of names to hide, defaults to [os.curdir, os.pardir]. High level usage: x = dircmp(dir1, dir2) x.report() -> prints a report on the differences between dir1 and dir2 or x.report_partial_closure() -> prints report on differences between dir1 and dir2, and reports on common immediate subdirectories. x.report_full_closure() -> like report_partial_closure, but fully recursive. Attributes: left_list, right_list: The files in dir1 and dir2, filtered by hide and ignore. common: a list of names in both dir1 and dir2. left_only, right_only: names only in dir1, dir2. common_dirs: subdirectories in both dir1 and dir2. common_files: files in both dir1 and dir2. common_funny: names in both dir1 and dir2 where the type differs between dir1 and dir2, or the name is not stat-able. same_files: list of identical files. diff_files: list of filenames which differ. funny_files: list of files which could not be compared. subdirs: a dictionary of dircmp objects, keyed by names in common_dirs. """ def __init__(self, a, b, ignore=None, hide=None): # Initialize self.left = a self.right = b if hide is None: self.hide = [os.curdir, os.pardir] # Names never to be shown else: self.hide = hide if ignore is None: self.ignore = DEFAULT_IGNORES else: self.ignore = ignore def phase0(self): # Compare everything except common subdirectories self.left_list = _filter(os.listdir(self.left), self.hide+self.ignore) self.right_list = _filter(os.listdir(self.right), self.hide+self.ignore) self.left_list.sort() self.right_list.sort() def phase1(self): # Compute common names a = dict(zip(map(os.path.normcase, self.left_list), self.left_list)) b = dict(zip(map(os.path.normcase, self.right_list), self.right_list)) self.common = list(map(a.__getitem__, filter(b.__contains__, a))) self.left_only = list(map(a.__getitem__, filterfalse(b.__contains__, a))) self.right_only = list(map(b.__getitem__, filterfalse(a.__contains__, b))) def phase2(self): # Distinguish files, directories, funnies self.common_dirs = [] self.common_files = [] self.common_funny = [] for x in self.common: a_path = os.path.join(self.left, x) b_path = os.path.join(self.right, x) ok = 1 try: a_stat = os.stat(a_path) except OSError as why: # print('Can\'t stat', a_path, ':', why.args[1]) ok = 0 try: b_stat = os.stat(b_path) except OSError as why: # print('Can\'t stat', b_path, ':', why.args[1]) ok = 0 if ok: a_type = stat.S_IFMT(a_stat.st_mode) b_type = stat.S_IFMT(b_stat.st_mode) if a_type != b_type: self.common_funny.append(x) elif stat.S_ISDIR(a_type): self.common_dirs.append(x) elif stat.S_ISREG(a_type): self.common_files.append(x) else: self.common_funny.append(x) else: self.common_funny.append(x) def phase3(self): # Find out differences between common files xx = cmpfiles(self.left, self.right, self.common_files) self.same_files, self.diff_files, self.funny_files = xx def phase4(self): # Find out differences between common subdirectories # A new dircmp object is created for each common subdirectory, # these are stored in a dictionary indexed by filename. # The hide and ignore properties are inherited from the parent self.subdirs = {} for x in self.common_dirs: a_x = os.path.join(self.left, x) b_x = os.path.join(self.right, x) self.subdirs[x] = dircmp(a_x, b_x, self.ignore, self.hide) def phase4_closure(self): # Recursively call phase4() on subdirectories self.phase4() for sd in self.subdirs.values(): sd.phase4_closure() def report(self): # Print a report on the differences between a and b # Output format is purposely lousy print('diff', self.left, self.right) if self.left_only: self.left_only.sort() print('Only in', self.left, ':', self.left_only) if self.right_only: self.right_only.sort() print('Only in', self.right, ':', self.right_only) if self.same_files: self.same_files.sort() print('Identical files :', self.same_files) if self.diff_files: self.diff_files.sort() print('Differing files :', self.diff_files) if self.funny_files: self.funny_files.sort() print('Trouble with common files :', self.funny_files) if self.common_dirs: self.common_dirs.sort() print('Common subdirectories :', self.common_dirs) if self.common_funny: self.common_funny.sort() print('Common funny cases :', self.common_funny) def report_partial_closure(self): # Print reports on self and on subdirs self.report() for sd in self.subdirs.values(): print() sd.report() def report_full_closure(self): # Report on self and subdirs recursively self.report() for sd in self.subdirs.values(): print() sd.report_full_closure() methodmap = dict(subdirs=phase4, same_files=phase3, diff_files=phase3, funny_files=phase3, common_dirs = phase2, common_files=phase2, common_funny=phase2, common=phase1, left_only=phase1, right_only=phase1, left_list=phase0, right_list=phase0) def __getattr__(self, attr): if attr not in self.methodmap: raise AttributeError(attr) self.methodmap[attr](self) return getattr(self, attr) def cmpfiles(a, b, common, shallow=True): """Compare common files in two directories. a, b -- directory names common -- list of file names found in both directories shallow -- if true, do comparison based solely on stat() information Returns a tuple of three lists: files that compare equal files that are different filenames that aren't regular files. """ res = ([], [], []) for x in common: ax = os.path.join(a, x) bx = os.path.join(b, x) res[_cmp(ax, bx, shallow)].append(x) return res # Compare two files. # Return: # 0 for equal # 1 for different # 2 for funny cases (can't stat, etc.) # def _cmp(a, b, sh, abs=abs, cmp=cmp): try: return not abs(cmp(a, b, sh)) except OSError: return 2 # Return a copy with items that occur in skip removed. # def _filter(flist, skip): return list(filterfalse(skip.__contains__, flist)) # Demonstration and testing. # def demo(): import sys import getopt options, args = getopt.getopt(sys.argv[1:], 'r') if len(args) != 2: raise getopt.GetoptError('need exactly two args', None) dd = dircmp(args[0], args[1]) if ('-r', '') in options: dd.report_full_closure() else: dd.report() if __name__ == '__main__': demo()

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