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BlendedSiteGenerator/Blended
blended/functions.py
getunzipped
def getunzipped(username, repo, thedir): """Downloads and unzips a zip file""" theurl = "https://github.com/" + username + "/" + repo + "/archive/master.zip" name = os.path.join(thedir, 'temp.zip') try: name = urllib.urlretrieve(theurl, name) name = os.path.join(thedir, 'temp.zip') except IOError as e: print("Can't retrieve %r to %r: %s" % (theurl, thedir, e)) return try: z = zipfile.ZipFile(name) except zipfile.error as e: print("Bad zipfile (from %r): %s" % (theurl, e)) return z.extractall(thedir) z.close() os.remove(name) copy_tree(os.path.join(thedir, repo + "-master"), thedir) shutil.rmtree(os.path.join(thedir, repo + "-master"))
python
def getunzipped(username, repo, thedir): """Downloads and unzips a zip file""" theurl = "https://github.com/" + username + "/" + repo + "/archive/master.zip" name = os.path.join(thedir, 'temp.zip') try: name = urllib.urlretrieve(theurl, name) name = os.path.join(thedir, 'temp.zip') except IOError as e: print("Can't retrieve %r to %r: %s" % (theurl, thedir, e)) return try: z = zipfile.ZipFile(name) except zipfile.error as e: print("Bad zipfile (from %r): %s" % (theurl, e)) return z.extractall(thedir) z.close() os.remove(name) copy_tree(os.path.join(thedir, repo + "-master"), thedir) shutil.rmtree(os.path.join(thedir, repo + "-master"))
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Downloads and unzips a zip file
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train
https://github.com/BlendedSiteGenerator/Blended/blob/e5865a8633e461a22c86ef6ee98cdd7051c412ac/blended/functions.py#L72-L92
BlendedSiteGenerator/Blended
blended/functions.py
checkConfig
def checkConfig(): """If the config.py file exists, back it up""" config_file_dir = os.path.join(cwd, "config.py") if os.path.exists(config_file_dir): print("Making a backup of your config file!") config_file_dir2 = os.path.join(cwd, "config.py.oldbak") copyfile(config_file_dir, config_file_dir2)
python
def checkConfig(): """If the config.py file exists, back it up""" config_file_dir = os.path.join(cwd, "config.py") if os.path.exists(config_file_dir): print("Making a backup of your config file!") config_file_dir2 = os.path.join(cwd, "config.py.oldbak") copyfile(config_file_dir, config_file_dir2)
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If the config.py file exists, back it up
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train
https://github.com/BlendedSiteGenerator/Blended/blob/e5865a8633e461a22c86ef6ee98cdd7051c412ac/blended/functions.py#L95-L101
BlendedSiteGenerator/Blended
blended/functions.py
createConfig
def createConfig(app_version=5.0, wname="", wdesc="", wdescl="", wlic="", wlan="", wurl="", aname="", abio=""): """Generates a config file from the information""" config_file_dir = os.path.join(cwd, "config.py") config_file = open(config_file_dir, "w") config_file.write('blended_version = ' + app_version + '\n') config_file.write('\n') config_file.write( '# Configuration is automatically generated by Blended (http://jmroper.com/blended), feel free to edit any values below') config_file.write('\n') config_file.write('website_name = "' + wname + '"\n') config_file.write('website_description = "' + wdesc + '"\n') config_file.write( 'website_description_long = "' + wdescl + '"\n') config_file.write('website_license = "' + wlic + '"\n') config_file.write('website_language = "' + wlan + '"\n') config_file.write('website_url = "' + wurl + '"\n') config_file.write('\n') config_file.write('author_name = "' + aname + '"\n') config_file.write('author_bio = "' + abio + '"\n') config_file.write('\n') config_file.write('home_page_list = True\n') config_file.write('\n') config_file.write('plugins = [] # Place all needed plugins in here\n') config_file.write( 'custom_variables = {} # Place all custom variables in here\n') config_file.write('\n') config_file.write('minify_css = False\n') config_file.write('minify_js = False\n') config_file.write('\n') config_file.write('# The following values are used for FTP uploads') config_file.write('\n') config_file.write('ftp_server = "localhost"\n') config_file.write('ftp_username = "user"\n') config_file.write('ftp_password = "pass"\n') config_file.write('ftp_port = 21\n') config_file.write('ftp_upload_path = "public_html/myWebsite"\n') config_file.close()
python
def createConfig(app_version=5.0, wname="", wdesc="", wdescl="", wlic="", wlan="", wurl="", aname="", abio=""): """Generates a config file from the information""" config_file_dir = os.path.join(cwd, "config.py") config_file = open(config_file_dir, "w") config_file.write('blended_version = ' + app_version + '\n') config_file.write('\n') config_file.write( '# Configuration is automatically generated by Blended (http://jmroper.com/blended), feel free to edit any values below') config_file.write('\n') config_file.write('website_name = "' + wname + '"\n') config_file.write('website_description = "' + wdesc + '"\n') config_file.write( 'website_description_long = "' + wdescl + '"\n') config_file.write('website_license = "' + wlic + '"\n') config_file.write('website_language = "' + wlan + '"\n') config_file.write('website_url = "' + wurl + '"\n') config_file.write('\n') config_file.write('author_name = "' + aname + '"\n') config_file.write('author_bio = "' + abio + '"\n') config_file.write('\n') config_file.write('home_page_list = True\n') config_file.write('\n') config_file.write('plugins = [] # Place all needed plugins in here\n') config_file.write( 'custom_variables = {} # Place all custom variables in here\n') config_file.write('\n') config_file.write('minify_css = False\n') config_file.write('minify_js = False\n') config_file.write('\n') config_file.write('# The following values are used for FTP uploads') config_file.write('\n') config_file.write('ftp_server = "localhost"\n') config_file.write('ftp_username = "user"\n') config_file.write('ftp_password = "pass"\n') config_file.write('ftp_port = 21\n') config_file.write('ftp_upload_path = "public_html/myWebsite"\n') config_file.close()
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Generates a config file from the information
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train
https://github.com/BlendedSiteGenerator/Blended/blob/e5865a8633e461a22c86ef6ee98cdd7051c412ac/blended/functions.py#L104-L141
BlendedSiteGenerator/Blended
blended/functions.py
createBlendedFolders
def createBlendedFolders(): """Creates the standard folders for a Blended website""" # Create the templates folder create_folder(os.path.join(cwd, "templates")) # Create the templates/assets folder create_folder(os.path.join(cwd, "templates", "assets")) # Create the templates/assets/css folder create_folder(os.path.join(cwd, "templates", "assets", "css")) # Create the templates/assets/js folder create_folder(os.path.join(cwd, "templates", "assets", "js")) # Create the templates/assets/img folder create_folder(os.path.join(cwd, "templates", "assets", "img")) # Create the content folder create_folder(os.path.join(cwd, "content"))
python
def createBlendedFolders(): """Creates the standard folders for a Blended website""" # Create the templates folder create_folder(os.path.join(cwd, "templates")) # Create the templates/assets folder create_folder(os.path.join(cwd, "templates", "assets")) # Create the templates/assets/css folder create_folder(os.path.join(cwd, "templates", "assets", "css")) # Create the templates/assets/js folder create_folder(os.path.join(cwd, "templates", "assets", "js")) # Create the templates/assets/img folder create_folder(os.path.join(cwd, "templates", "assets", "img")) # Create the content folder create_folder(os.path.join(cwd, "content"))
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Creates the standard folders for a Blended website
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https://github.com/BlendedSiteGenerator/Blended/blob/e5865a8633e461a22c86ef6ee98cdd7051c412ac/blended/functions.py#L144-L162
tkf/rash
rash/record.py
get_environ
def get_environ(keys): """ Get environment variables from :data:`os.environ`. :type keys: [str] :rtype: dict Some additional features. * If 'HOST' is not in :data:`os.environ`, this function automatically fetch it using :meth:`platform.node`. * If 'TTY' is not in :data:`os.environ`, this function automatically fetch it using :meth:`os.ttyname`. * Set 'RASH_SPENV_TERMINAL' if needed. """ items = ((k, os.environ.get(k)) for k in keys) subenv = dict((k, v) for (k, v) in items if v is not None) needset = lambda k: k in keys and not subenv.get(k) def setifnonempty(key, value): if value: subenv[key] = value if needset('HOST'): import platform subenv['HOST'] = platform.node() if needset('TTY'): setifnonempty('TTY', get_tty()) if needset('RASH_SPENV_TERMINAL'): from .utils.termdetection import detect_terminal setifnonempty('RASH_SPENV_TERMINAL', detect_terminal()) return subenv
python
def get_environ(keys): """ Get environment variables from :data:`os.environ`. :type keys: [str] :rtype: dict Some additional features. * If 'HOST' is not in :data:`os.environ`, this function automatically fetch it using :meth:`platform.node`. * If 'TTY' is not in :data:`os.environ`, this function automatically fetch it using :meth:`os.ttyname`. * Set 'RASH_SPENV_TERMINAL' if needed. """ items = ((k, os.environ.get(k)) for k in keys) subenv = dict((k, v) for (k, v) in items if v is not None) needset = lambda k: k in keys and not subenv.get(k) def setifnonempty(key, value): if value: subenv[key] = value if needset('HOST'): import platform subenv['HOST'] = platform.node() if needset('TTY'): setifnonempty('TTY', get_tty()) if needset('RASH_SPENV_TERMINAL'): from .utils.termdetection import detect_terminal setifnonempty('RASH_SPENV_TERMINAL', detect_terminal()) return subenv
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/record.py#L51-L83
tkf/rash
rash/record.py
generate_session_id
def generate_session_id(data): """ Generate session ID based on HOST, TTY, PID [#]_ and start time. :type data: dict :rtype: str .. [#] PID of the shell, i.e., PPID of this Python process. """ host = data['environ']['HOST'] tty = data['environ'].get('TTY') or 'NO_TTY' return ':'.join(map(str, [ host, tty, os.getppid(), data['start']]))
python
def generate_session_id(data): """ Generate session ID based on HOST, TTY, PID [#]_ and start time. :type data: dict :rtype: str .. [#] PID of the shell, i.e., PPID of this Python process. """ host = data['environ']['HOST'] tty = data['environ'].get('TTY') or 'NO_TTY' return ':'.join(map(str, [ host, tty, os.getppid(), data['start']]))
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/record.py#L86-L99
tkf/rash
rash/record.py
record_run
def record_run(record_type, print_session_id, **kwds): """ Record shell history. """ if print_session_id and record_type != 'init': raise RuntimeError( '--print-session-id should be used with --record-type=init') cfstore = ConfigStore() # SOMEDAY: Pass a list of environment variables to shell by "rash # init" and don't read configuration in "rash record" command. It # is faster. config = cfstore.get_config() envkeys = config.record.environ[record_type] json_path = os.path.join(cfstore.record_path, record_type, time.strftime('%Y-%m-%d-%H%M%S.json')) mkdirp(os.path.dirname(json_path)) # Command line options directly map to record keys data = dict((k, v) for (k, v) in kwds.items() if v is not None) data.update( environ=get_environ(envkeys), ) # Automatically set some missing variables: data.setdefault('cwd', getcwd()) if record_type in ['command', 'exit']: data.setdefault('stop', int(time.time())) elif record_type in ['init']: data.setdefault('start', int(time.time())) if print_session_id: data['session_id'] = generate_session_id(data) print(data['session_id']) with open(json_path, 'w') as fp: json.dump(data, fp)
python
def record_run(record_type, print_session_id, **kwds): """ Record shell history. """ if print_session_id and record_type != 'init': raise RuntimeError( '--print-session-id should be used with --record-type=init') cfstore = ConfigStore() # SOMEDAY: Pass a list of environment variables to shell by "rash # init" and don't read configuration in "rash record" command. It # is faster. config = cfstore.get_config() envkeys = config.record.environ[record_type] json_path = os.path.join(cfstore.record_path, record_type, time.strftime('%Y-%m-%d-%H%M%S.json')) mkdirp(os.path.dirname(json_path)) # Command line options directly map to record keys data = dict((k, v) for (k, v) in kwds.items() if v is not None) data.update( environ=get_environ(envkeys), ) # Automatically set some missing variables: data.setdefault('cwd', getcwd()) if record_type in ['command', 'exit']: data.setdefault('stop', int(time.time())) elif record_type in ['init']: data.setdefault('start', int(time.time())) if print_session_id: data['session_id'] = generate_session_id(data) print(data['session_id']) with open(json_path, 'w') as fp: json.dump(data, fp)
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Record shell history.
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/record.py#L102-L139
staticdev/django-sorting-bootstrap
sorting_bootstrap/compat.py
format_html
def format_html(format_string, *args, **kwargs): """ Similar to str.format, but passes all arguments through conditional_escape, and calls 'mark_safe' on the result. This function should be used instead of str.format or % interpolation to build up small HTML fragments. """ args_safe = map(conditional_escape, args) kwargs_safe = dict([(k, conditional_escape(v)) for (k, v) in six.iteritems(kwargs)]) return mark_safe(format_string.format(*args_safe, **kwargs_safe))
python
def format_html(format_string, *args, **kwargs): """ Similar to str.format, but passes all arguments through conditional_escape, and calls 'mark_safe' on the result. This function should be used instead of str.format or % interpolation to build up small HTML fragments. """ args_safe = map(conditional_escape, args) kwargs_safe = dict([(k, conditional_escape(v)) for (k, v) in six.iteritems(kwargs)]) return mark_safe(format_string.format(*args_safe, **kwargs_safe))
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tkf/rash
rash/database.py
normalize_directory
def normalize_directory(path): """ Append "/" to `path` if needed. """ if path is None: return None if path.endswith(os.path.sep): return path else: return path + os.path.sep
python
def normalize_directory(path): """ Append "/" to `path` if needed. """ if path is None: return None if path.endswith(os.path.sep): return path else: return path + os.path.sep
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L52-L61
tkf/rash
rash/database.py
sql_program_name_func
def sql_program_name_func(command): """ Extract program name from `command`. >>> sql_program_name_func('ls') 'ls' >>> sql_program_name_func('git status') 'git' >>> sql_program_name_func('EMACS=emacs make') 'make' :type command: str """ args = command.split(' ') for prog in args: if '=' not in prog: return prog return args[0]
python
def sql_program_name_func(command): """ Extract program name from `command`. >>> sql_program_name_func('ls') 'ls' >>> sql_program_name_func('git status') 'git' >>> sql_program_name_func('EMACS=emacs make') 'make' :type command: str """ args = command.split(' ') for prog in args: if '=' not in prog: return prog return args[0]
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Extract program name from `command`. >>> sql_program_name_func('ls') 'ls' >>> sql_program_name_func('git status') 'git' >>> sql_program_name_func('EMACS=emacs make') 'make' :type command: str
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L68-L86
tkf/rash
rash/database.py
sql_pathdist_func
def sql_pathdist_func(path1, path2, sep=os.path.sep): """ Return a distance between `path1` and `path2`. >>> sql_pathdist_func('a/b/', 'a/b/', sep='/') 0 >>> sql_pathdist_func('a/', 'a/b/', sep='/') 1 >>> sql_pathdist_func('a', 'a/', sep='/') 0 """ seq1 = path1.rstrip(sep).split(sep) seq2 = path2.rstrip(sep).split(sep) return sum(1 for (p1, p2) in zip_longest(seq1, seq2) if p1 != p2)
python
def sql_pathdist_func(path1, path2, sep=os.path.sep): """ Return a distance between `path1` and `path2`. >>> sql_pathdist_func('a/b/', 'a/b/', sep='/') 0 >>> sql_pathdist_func('a/', 'a/b/', sep='/') 1 >>> sql_pathdist_func('a', 'a/', sep='/') 0 """ seq1 = path1.rstrip(sep).split(sep) seq2 = path2.rstrip(sep).split(sep) return sum(1 for (p1, p2) in zip_longest(seq1, seq2) if p1 != p2)
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Return a distance between `path1` and `path2`. >>> sql_pathdist_func('a/b/', 'a/b/', sep='/') 0 >>> sql_pathdist_func('a/', 'a/b/', sep='/') 1 >>> sql_pathdist_func('a', 'a/', sep='/') 0
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L89-L103
tkf/rash
rash/database.py
DataBase._init_db
def _init_db(self): """Creates the database tables.""" with self._get_db() as db: with open(self.schemapath) as f: db.cursor().executescript(f.read()) db.commit()
python
def _init_db(self): """Creates the database tables.""" with self._get_db() as db: with open(self.schemapath) as f: db.cursor().executescript(f.read()) db.commit()
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Creates the database tables.
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L121-L126
tkf/rash
rash/database.py
DataBase.connection
def connection(self, commit=False): """ Context manager to keep around DB connection. :rtype: sqlite3.Connection SOMEDAY: Get rid of this function. Keeping connection around as an argument to the method using this context manager is probably better as it is more explicit. Also, holding "global state" as instance attribute is bad for supporting threaded search, which is required for more fluent percol integration. """ if commit: self._need_commit = True if self._db: yield self._db else: try: with self._get_db() as db: self._db = db db.create_function("REGEXP", 2, sql_regexp_func) db.create_function("PROGRAM_NAME", 1, sql_program_name_func) db.create_function("PATHDIST", 2, sql_pathdist_func) yield self._db if self._need_commit: db.commit() finally: self._db = None self._need_commit = False
python
def connection(self, commit=False): """ Context manager to keep around DB connection. :rtype: sqlite3.Connection SOMEDAY: Get rid of this function. Keeping connection around as an argument to the method using this context manager is probably better as it is more explicit. Also, holding "global state" as instance attribute is bad for supporting threaded search, which is required for more fluent percol integration. """ if commit: self._need_commit = True if self._db: yield self._db else: try: with self._get_db() as db: self._db = db db.create_function("REGEXP", 2, sql_regexp_func) db.create_function("PROGRAM_NAME", 1, sql_program_name_func) db.create_function("PATHDIST", 2, sql_pathdist_func) yield self._db if self._need_commit: db.commit() finally: self._db = None self._need_commit = False
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L129-L160
tkf/rash
rash/database.py
DataBase.close_connection
def close_connection(self): """ Close connection kept by :meth:`connection`. If commit is needed, :meth:`sqlite3.Connection.commit` is called first and then :meth:`sqlite3.Connection.interrupt` is called. A few methods/generators support :meth:`close_connection`: - :meth:`search_command_record` - :meth:`select_by_command_record` """ if self._db: db = self._db try: if self._need_commit: db.commit() finally: db.interrupt() self._db = None self._need_commit = False
python
def close_connection(self): """ Close connection kept by :meth:`connection`. If commit is needed, :meth:`sqlite3.Connection.commit` is called first and then :meth:`sqlite3.Connection.interrupt` is called. A few methods/generators support :meth:`close_connection`: - :meth:`search_command_record` - :meth:`select_by_command_record` """ if self._db: db = self._db try: if self._need_commit: db.commit() finally: db.interrupt() self._db = None self._need_commit = False
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L164-L186
tkf/rash
rash/database.py
DataBase._executing
def _executing(self, sql, params=[]): """ Execute and yield rows in a way to support :meth:`close_connection`. """ with self.connection() as connection: for row in connection.execute(sql, params): yield row if not self._db: return
python
def _executing(self, sql, params=[]): """ Execute and yield rows in a way to support :meth:`close_connection`. """ with self.connection() as connection: for row in connection.execute(sql, params): yield row if not self._db: return
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L188-L196
tkf/rash
rash/database.py
DataBase.get_version_records
def get_version_records(self): """ Yield RASH version information stored in DB. Latest first. :rtype: [VersionRecord] """ keys = ['id', 'rash_version', 'schema_version', 'updated'] sql = """ SELECT id, rash_version, schema_version, updated FROM rash_info ORDER BY id DESC """ with self.connection() as connection: for row in connection.execute(sql): yield VersionRecord(**dict(zip(keys, row)))
python
def get_version_records(self): """ Yield RASH version information stored in DB. Latest first. :rtype: [VersionRecord] """ keys = ['id', 'rash_version', 'schema_version', 'updated'] sql = """ SELECT id, rash_version, schema_version, updated FROM rash_info ORDER BY id DESC """ with self.connection() as connection: for row in connection.execute(sql): yield VersionRecord(**dict(zip(keys, row)))
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https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L202-L217
tkf/rash
rash/database.py
DataBase.update_version_records
def update_version_records(self): """ Update rash_info table if necessary. """ from .__init__ import __version__ as version with self.connection(commit=True) as connection: for vrec in self.get_version_records(): if (vrec.rash_version == version and vrec.schema_version == schema_version): return # no need to insert the new one! connection.execute( 'INSERT INTO rash_info (rash_version, schema_version) ' 'VALUES (?, ?)', [version, schema_version])
python
def update_version_records(self): """ Update rash_info table if necessary. """ from .__init__ import __version__ as version with self.connection(commit=True) as connection: for vrec in self.get_version_records(): if (vrec.rash_version == version and vrec.schema_version == schema_version): return # no need to insert the new one! connection.execute( 'INSERT INTO rash_info (rash_version, schema_version) ' 'VALUES (?, ?)', [version, schema_version])
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L219-L232
tkf/rash
rash/database.py
DataBase.select_by_command_record
def select_by_command_record(self, crec): """ Yield records that matches to `crec`. All attributes of `crec` except for `environ` are concerned. """ keys = ['command_history_id', 'command', 'session_history_id', 'cwd', 'terminal', 'start', 'stop', 'exit_code'] sql = """ SELECT command_history.id, CL.command, session_id, DL.directory, TL.terminal, start_time, stop_time, exit_code FROM command_history LEFT JOIN command_list AS CL ON command_id = CL.id LEFT JOIN directory_list AS DL ON directory_id = DL.id LEFT JOIN terminal_list AS TL ON terminal_id = TL.id WHERE (CL.command = ? OR (CL.command IS NULL AND ? IS NULL)) AND (DL.directory = ? OR (DL.directory IS NULL AND ? IS NULL)) AND (TL.terminal = ? OR (TL.terminal IS NULL AND ? IS NULL)) AND (start_time = ? OR (start_time IS NULL AND ? IS NULL)) AND (stop_time = ? OR (stop_time IS NULL AND ? IS NULL)) AND (exit_code = ? OR (exit_code IS NULL AND ? IS NULL)) """ desired_row = [ crec.command, normalize_directory(crec.cwd), crec.terminal, convert_ts(crec.start), convert_ts(crec.stop), crec.exit_code] params = list(itertools.chain(*zip(desired_row, desired_row))) return self._select_rows(CommandRecord, keys, sql, params)
python
def select_by_command_record(self, crec): """ Yield records that matches to `crec`. All attributes of `crec` except for `environ` are concerned. """ keys = ['command_history_id', 'command', 'session_history_id', 'cwd', 'terminal', 'start', 'stop', 'exit_code'] sql = """ SELECT command_history.id, CL.command, session_id, DL.directory, TL.terminal, start_time, stop_time, exit_code FROM command_history LEFT JOIN command_list AS CL ON command_id = CL.id LEFT JOIN directory_list AS DL ON directory_id = DL.id LEFT JOIN terminal_list AS TL ON terminal_id = TL.id WHERE (CL.command = ? OR (CL.command IS NULL AND ? IS NULL)) AND (DL.directory = ? OR (DL.directory IS NULL AND ? IS NULL)) AND (TL.terminal = ? OR (TL.terminal IS NULL AND ? IS NULL)) AND (start_time = ? OR (start_time IS NULL AND ? IS NULL)) AND (stop_time = ? OR (stop_time IS NULL AND ? IS NULL)) AND (exit_code = ? OR (exit_code IS NULL AND ? IS NULL)) """ desired_row = [ crec.command, normalize_directory(crec.cwd), crec.terminal, convert_ts(crec.start), convert_ts(crec.stop), crec.exit_code] params = list(itertools.chain(*zip(desired_row, desired_row))) return self._select_rows(CommandRecord, keys, sql, params)
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L346-L377
tkf/rash
rash/database.py
DataBase.search_command_record
def search_command_record( self, after_context, before_context, context, context_type, **kwds): """ Search command history. :rtype: [CommandRecord] """ if after_context or before_context or context: kwds['condition_as_column'] = True limit = kwds['limit'] kwds['limit'] = -1 kwds['unique'] = False kwds['sort_by'] = { 'session': ['session_start_time', 'start_time'], 'time': ['start_time'], }[context_type] if not kwds['reverse']: # Default (reverse=False) means latest history comes first. after_context, before_context = before_context, after_context (sql, params, keys) = self._compile_sql_search_command_record(**kwds) records = self._select_rows(CommandRecord, keys, sql, params) # SOMEDAY: optimize context search; do not create CommandRecord # object for all (including non-matching) records. predicate = lambda r: r.condition if context: records = include_context(predicate, context, records) elif before_context: records = include_before(predicate, before_context, records) elif after_context: records = include_after(predicate, after_context, records) if after_context or before_context or context and limit >= 0: records = itertools.islice(records, limit) # NOTE: as SQLite does not support row_number function, let's # do the filtering at Python side when context modifier # is given. This is *very* inefficient but at least it # works.. return records
python
def search_command_record( self, after_context, before_context, context, context_type, **kwds): """ Search command history. :rtype: [CommandRecord] """ if after_context or before_context or context: kwds['condition_as_column'] = True limit = kwds['limit'] kwds['limit'] = -1 kwds['unique'] = False kwds['sort_by'] = { 'session': ['session_start_time', 'start_time'], 'time': ['start_time'], }[context_type] if not kwds['reverse']: # Default (reverse=False) means latest history comes first. after_context, before_context = before_context, after_context (sql, params, keys) = self._compile_sql_search_command_record(**kwds) records = self._select_rows(CommandRecord, keys, sql, params) # SOMEDAY: optimize context search; do not create CommandRecord # object for all (including non-matching) records. predicate = lambda r: r.condition if context: records = include_context(predicate, context, records) elif before_context: records = include_before(predicate, before_context, records) elif after_context: records = include_after(predicate, after_context, records) if after_context or before_context or context and limit >= 0: records = itertools.islice(records, limit) # NOTE: as SQLite does not support row_number function, let's # do the filtering at Python side when context modifier # is given. This is *very* inefficient but at least it # works.. return records
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L379-L421
tkf/rash
rash/database.py
DataBase.get_full_command_record
def get_full_command_record(self, command_history_id, merge_session_environ=True): """ Get fully retrieved :class:`CommandRecord` instance by ID. By "fully", it means that complex slots such as `environ` and `pipestatus` are available. :type command_history_id: int :type merge_session_environ: bool """ with self.connection() as db: crec = self._select_command_record(db, command_history_id) crec.pipestatus = self._get_pipestatus(db, command_history_id) # Set environment variables cenv = self._select_environ(db, 'command', command_history_id) crec.environ.update(cenv) if merge_session_environ: senv = self._select_environ( db, 'session', crec.session_history_id) crec.environ.update(senv) return crec
python
def get_full_command_record(self, command_history_id, merge_session_environ=True): """ Get fully retrieved :class:`CommandRecord` instance by ID. By "fully", it means that complex slots such as `environ` and `pipestatus` are available. :type command_history_id: int :type merge_session_environ: bool """ with self.connection() as db: crec = self._select_command_record(db, command_history_id) crec.pipestatus = self._get_pipestatus(db, command_history_id) # Set environment variables cenv = self._select_environ(db, 'command', command_history_id) crec.environ.update(cenv) if merge_session_environ: senv = self._select_environ( db, 'session', crec.session_history_id) crec.environ.update(senv) return crec
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L742-L764
mathiasertl/xmpp-backends
xmpp_backends/dummy.py
DummyBackend.start_user_session
def start_user_session(self, username, domain, resource, **kwargs): """Method to add a user session for debugging. Accepted parameters are the same as to the constructor of :py:class:`~xmpp_backends.base.UserSession`. """ kwargs.setdefault('uptime', pytz.utc.localize(datetime.utcnow())) kwargs.setdefault('priority', 0) kwargs.setdefault('status', 'online') kwargs.setdefault('status_text', '') kwargs.setdefault('connection_type', CONNECTION_XMPP) kwargs.setdefault('encrypted', True) kwargs.setdefault('compressed', False) kwargs.setdefault('ip_address', '127.0.0.1') if six.PY2 and isinstance(kwargs['ip_address'], str): # ipaddress constructor does not eat str in py2 :-/ kwargs['ip_address'] = kwargs['ip_address'].decode('utf-8') if isinstance(kwargs['ip_address'], six.string_types): kwargs['ip_address'] = ipaddress.ip_address(kwargs['ip_address']) user = '%s@%s' % (username, domain) session = UserSession(self, username, domain, resource, **kwargs) data = self.module.get(user) if data is None: raise UserNotFound(username, domain, resource) data.setdefault('sessions', set()) if isinstance(data['sessions'], list): # Cast old data to set data['sessions'] = set(data['sessions']) data['sessions'].add(session) self.module.set(user, data) all_sessions = self.module.get('all_sessions', set()) all_sessions.add(session) self.module.set('all_sessions', all_sessions)
python
def start_user_session(self, username, domain, resource, **kwargs): """Method to add a user session for debugging. Accepted parameters are the same as to the constructor of :py:class:`~xmpp_backends.base.UserSession`. """ kwargs.setdefault('uptime', pytz.utc.localize(datetime.utcnow())) kwargs.setdefault('priority', 0) kwargs.setdefault('status', 'online') kwargs.setdefault('status_text', '') kwargs.setdefault('connection_type', CONNECTION_XMPP) kwargs.setdefault('encrypted', True) kwargs.setdefault('compressed', False) kwargs.setdefault('ip_address', '127.0.0.1') if six.PY2 and isinstance(kwargs['ip_address'], str): # ipaddress constructor does not eat str in py2 :-/ kwargs['ip_address'] = kwargs['ip_address'].decode('utf-8') if isinstance(kwargs['ip_address'], six.string_types): kwargs['ip_address'] = ipaddress.ip_address(kwargs['ip_address']) user = '%s@%s' % (username, domain) session = UserSession(self, username, domain, resource, **kwargs) data = self.module.get(user) if data is None: raise UserNotFound(username, domain, resource) data.setdefault('sessions', set()) if isinstance(data['sessions'], list): # Cast old data to set data['sessions'] = set(data['sessions']) data['sessions'].add(session) self.module.set(user, data) all_sessions = self.module.get('all_sessions', set()) all_sessions.add(session) self.module.set('all_sessions', all_sessions)
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train
https://github.com/mathiasertl/xmpp-backends/blob/214ef0664dbf90fa300c2483b9b3416559e5d171/xmpp_backends/dummy.py#L66-L103
INM-6/hybridLFPy
examples/example_microcircuit.py
merge_gdf
def merge_gdf(model_params, raw_label='spikes_', file_type='gdf', fileprefix='spikes'): ''' NEST produces one file per virtual process containing recorder output. This function gathers and combines them into one single file per network population. Parameters ---------- model_params : object network parameters object Returns ------- None ''' def get_raw_gids(model_params): ''' Reads text file containing gids of neuron populations as created within the NEST simulation. These gids are not continuous as in the simulation devices get created in between. Parameters ---------- model_params : object network parameters object Returns ------- gids : list list of neuron ids and value (spike time, voltage etc.) ''' gidfile = open(os.path.join(model_params.raw_nest_output_path, model_params.GID_filename),'r') gids = [] for l in gidfile : a = l.split() gids.append([int(a[0]),int(a[1])]) return gids #some preprocessing raw_gids = get_raw_gids(model_params) pop_sizes = [raw_gids[i][1]-raw_gids[i][0]+1 for i in np.arange(model_params.Npops)] raw_first_gids = [raw_gids[i][0] for i in np.arange(model_params.Npops)] converted_first_gids = [int(1 + np.sum(pop_sizes[:i])) for i in np.arange(model_params.Npops)] for pop_idx in np.arange(model_params.Npops): if pop_idx % SIZE == RANK: files = glob(os.path.join(model_params.raw_nest_output_path, raw_label + str(pop_idx) + '*.' + file_type)) gdf = [] # init for f in files: new_gdf = helpers.read_gdf(f) for line in new_gdf: line[0] = line[0] - raw_first_gids[pop_idx] + \ converted_first_gids[pop_idx] gdf.append(line) print 'writing: %s' % os.path.join(model_params.spike_output_path, fileprefix + '_%s.gdf' % model_params.X[pop_idx]) helpers.write_gdf(gdf, os.path.join(model_params.spike_output_path, fileprefix + '_%s.gdf' % model_params.X[pop_idx])) COMM.Barrier() return
python
def merge_gdf(model_params, raw_label='spikes_', file_type='gdf', fileprefix='spikes'): ''' NEST produces one file per virtual process containing recorder output. This function gathers and combines them into one single file per network population. Parameters ---------- model_params : object network parameters object Returns ------- None ''' def get_raw_gids(model_params): ''' Reads text file containing gids of neuron populations as created within the NEST simulation. These gids are not continuous as in the simulation devices get created in between. Parameters ---------- model_params : object network parameters object Returns ------- gids : list list of neuron ids and value (spike time, voltage etc.) ''' gidfile = open(os.path.join(model_params.raw_nest_output_path, model_params.GID_filename),'r') gids = [] for l in gidfile : a = l.split() gids.append([int(a[0]),int(a[1])]) return gids #some preprocessing raw_gids = get_raw_gids(model_params) pop_sizes = [raw_gids[i][1]-raw_gids[i][0]+1 for i in np.arange(model_params.Npops)] raw_first_gids = [raw_gids[i][0] for i in np.arange(model_params.Npops)] converted_first_gids = [int(1 + np.sum(pop_sizes[:i])) for i in np.arange(model_params.Npops)] for pop_idx in np.arange(model_params.Npops): if pop_idx % SIZE == RANK: files = glob(os.path.join(model_params.raw_nest_output_path, raw_label + str(pop_idx) + '*.' + file_type)) gdf = [] # init for f in files: new_gdf = helpers.read_gdf(f) for line in new_gdf: line[0] = line[0] - raw_first_gids[pop_idx] + \ converted_first_gids[pop_idx] gdf.append(line) print 'writing: %s' % os.path.join(model_params.spike_output_path, fileprefix + '_%s.gdf' % model_params.X[pop_idx]) helpers.write_gdf(gdf, os.path.join(model_params.spike_output_path, fileprefix + '_%s.gdf' % model_params.X[pop_idx])) COMM.Barrier() return
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train
https://github.com/INM-6/hybridLFPy/blob/c38bdf38982c4624c2f70caeb50c40f1d5980abd/examples/example_microcircuit.py#L86-L159
INM-6/hybridLFPy
examples/example_microcircuit.py
dict_of_numpyarray_to_dict_of_list
def dict_of_numpyarray_to_dict_of_list(d): ''' Convert dictionary containing numpy arrays to dictionary containing lists Parameters ---------- d : dict sli parameter name and value as dictionary key and value pairs Returns ------- d : dict modified dictionary ''' for key,value in d.iteritems(): if isinstance(value,dict): # if value == dict # recurse d[key] = dict_of_numpyarray_to_dict_of_list(value) elif isinstance(value,np.ndarray): # or isinstance(value,list) : d[key] = value.tolist() return d
python
def dict_of_numpyarray_to_dict_of_list(d): ''' Convert dictionary containing numpy arrays to dictionary containing lists Parameters ---------- d : dict sli parameter name and value as dictionary key and value pairs Returns ------- d : dict modified dictionary ''' for key,value in d.iteritems(): if isinstance(value,dict): # if value == dict # recurse d[key] = dict_of_numpyarray_to_dict_of_list(value) elif isinstance(value,np.ndarray): # or isinstance(value,list) : d[key] = value.tolist() return d
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INM-6/hybridLFPy
examples/example_microcircuit.py
send_nest_params_to_sli
def send_nest_params_to_sli(p): ''' Read parameters and send them to SLI Parameters ---------- p : dict sli parameter name and value as dictionary key and value pairs Returns ------- None ''' for name in p.keys(): value = p[name] if type(value) == np.ndarray: value = value.tolist() if type(value) == dict: value = dict_of_numpyarray_to_dict_of_list(value) if name == 'neuron_model': # special case as neuron_model is a # NEST model and not a string try: nest.sli_run('/'+name) nest.sli_push(value) nest.sli_run('eval') nest.sli_run('def') except: print 'Could not put variable %s on SLI stack' % (name) print type(value) else: try: nest.sli_run('/'+name) nest.sli_push(value) nest.sli_run('def') except: print 'Could not put variable %s on SLI stack' % (name) print type(value) return
python
def send_nest_params_to_sli(p): ''' Read parameters and send them to SLI Parameters ---------- p : dict sli parameter name and value as dictionary key and value pairs Returns ------- None ''' for name in p.keys(): value = p[name] if type(value) == np.ndarray: value = value.tolist() if type(value) == dict: value = dict_of_numpyarray_to_dict_of_list(value) if name == 'neuron_model': # special case as neuron_model is a # NEST model and not a string try: nest.sli_run('/'+name) nest.sli_push(value) nest.sli_run('eval') nest.sli_run('def') except: print 'Could not put variable %s on SLI stack' % (name) print type(value) else: try: nest.sli_run('/'+name) nest.sli_push(value) nest.sli_run('def') except: print 'Could not put variable %s on SLI stack' % (name) print type(value) return
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staticdev/django-sorting-bootstrap
sorting_bootstrap/util.py
label_for_field
def label_for_field(name, model, return_attr=False): """ Returns a sensible label for a field name. The name can be a callable, property (but not created with @property decorator) or the name of an object's attribute, as well as a genuine fields. If return_attr is True, the resolved attribute (which could be a callable) is also returned. This will be None if (and only if) the name refers to a field. """ attr = None try: field = model._meta.get_field_by_name(name)[0] if isinstance(field, RelatedObject): label = field.opts.verbose_name else: label = field.verbose_name except models.FieldDoesNotExist: if name == "__unicode__": label = force_text(model._meta.verbose_name) attr = six.text_type elif name == "__str__": label = force_str(model._meta.verbose_name) attr = bytes else: if callable(name): attr = name elif hasattr(model, name): attr = getattr(model, name) else: message = "Unable to lookup '%s' on %s" % (name, model._meta.object_name) raise AttributeError(message) if hasattr(attr, "short_description"): label = attr.short_description elif (isinstance(attr, property) and hasattr(attr, "fget") and hasattr(attr.fget, "short_description")): label = attr.fget.short_description elif callable(attr): if attr.__name__ == "<lambda>": label = "--" else: label = pretty_name(attr.__name__) else: label = pretty_name(name) if return_attr: return (label, attr) else: return label
python
def label_for_field(name, model, return_attr=False): """ Returns a sensible label for a field name. The name can be a callable, property (but not created with @property decorator) or the name of an object's attribute, as well as a genuine fields. If return_attr is True, the resolved attribute (which could be a callable) is also returned. This will be None if (and only if) the name refers to a field. """ attr = None try: field = model._meta.get_field_by_name(name)[0] if isinstance(field, RelatedObject): label = field.opts.verbose_name else: label = field.verbose_name except models.FieldDoesNotExist: if name == "__unicode__": label = force_text(model._meta.verbose_name) attr = six.text_type elif name == "__str__": label = force_str(model._meta.verbose_name) attr = bytes else: if callable(name): attr = name elif hasattr(model, name): attr = getattr(model, name) else: message = "Unable to lookup '%s' on %s" % (name, model._meta.object_name) raise AttributeError(message) if hasattr(attr, "short_description"): label = attr.short_description elif (isinstance(attr, property) and hasattr(attr, "fget") and hasattr(attr.fget, "short_description")): label = attr.fget.short_description elif callable(attr): if attr.__name__ == "<lambda>": label = "--" else: label = pretty_name(attr.__name__) else: label = pretty_name(name) if return_attr: return (label, attr) else: return label
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avalente/appmetrics
appmetrics/meter.py
EWMA.update
def update(self, value): """ Update the current rate with the given value. The value must be an integer. """ value = int(value) with self.lock: self.value += value
python
def update(self, value): """ Update the current rate with the given value. The value must be an integer. """ value = int(value) with self.lock: self.value += value
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https://github.com/avalente/appmetrics/blob/366fc7e1ca897e49a2227cbfa43bfa02a47f1acc/appmetrics/meter.py#L60-L69
avalente/appmetrics
appmetrics/meter.py
EWMA.tick
def tick(self): """Decay the current rate according to the elapsed time""" instant_rate = float(self.value) / float(self.tick_interval) with self.lock: if self.initialized: self.rate += (self.alpha * (instant_rate - self.rate)) else: self.initialized = True self.rate = instant_rate self.value = 0
python
def tick(self): """Decay the current rate according to the elapsed time""" instant_rate = float(self.value) / float(self.tick_interval) with self.lock: if self.initialized: self.rate += (self.alpha * (instant_rate - self.rate)) else: self.initialized = True self.rate = instant_rate self.value = 0
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https://github.com/avalente/appmetrics/blob/366fc7e1ca897e49a2227cbfa43bfa02a47f1acc/appmetrics/meter.py#L71-L83
avalente/appmetrics
appmetrics/meter.py
Meter.notify
def notify(self, value): """Add a new observation to the metric""" with self.lock: #TODO: this could slow down slow-rate incoming updates # since the number of ticks depends on the actual time # passed since the latest notification. Consider using # a real timer to tick the EWMA. self.tick() for avg in (self.m1, self.m5, self.m15, self.day): avg.update(value) self.count += value
python
def notify(self, value): """Add a new observation to the metric""" with self.lock: #TODO: this could slow down slow-rate incoming updates # since the number of ticks depends on the actual time # passed since the latest notification. Consider using # a real timer to tick the EWMA. self.tick() for avg in (self.m1, self.m5, self.m15, self.day): avg.update(value) self.count += value
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avalente/appmetrics
appmetrics/meter.py
Meter.tick_all
def tick_all(self, times): """ Tick all the EWMAs for the given number of times """ for i in range(times): for avg in (self.m1, self.m5, self.m15, self.day): avg.tick()
python
def tick_all(self, times): """ Tick all the EWMAs for the given number of times """ for i in range(times): for avg in (self.m1, self.m5, self.m15, self.day): avg.tick()
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avalente/appmetrics
appmetrics/meter.py
Meter.tick
def tick(self): """ Emulate a timer: in order to avoid a real timer we "tick" a number of times depending on the actual time passed since the last tick """ now = time.time() elapsed = now - self.latest_tick if elapsed > self.tick_interval: ticks = int(elapsed / self.tick_interval) self.tick_all(ticks) self.latest_tick = now
python
def tick(self): """ Emulate a timer: in order to avoid a real timer we "tick" a number of times depending on the actual time passed since the last tick """ now = time.time() elapsed = now - self.latest_tick if elapsed > self.tick_interval: ticks = int(elapsed / self.tick_interval) self.tick_all(ticks) self.latest_tick = now
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avalente/appmetrics
appmetrics/meter.py
Meter.get
def get(self): """ Return the computed statistics over the gathered data """ with self.lock: self.tick() data = dict( kind="meter", count=self.count, mean=self.count / (time.time() - self.started_on), one=self.m1.rate, five=self.m5.rate, fifteen=self.m15.rate, day=self.day.rate) return data
python
def get(self): """ Return the computed statistics over the gathered data """ with self.lock: self.tick() data = dict( kind="meter", count=self.count, mean=self.count / (time.time() - self.started_on), one=self.m1.rate, five=self.m5.rate, fifteen=self.m15.rate, day=self.day.rate) return data
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intiocean/pyinter
pyinter/interval.py
open
def open(lower_value, upper_value): """Helper function to construct an interval object with open lower and upper. For example: >>> open(100.2, 800.9) (100.2, 800.9) """ return Interval(Interval.OPEN, lower_value, upper_value, Interval.OPEN)
python
def open(lower_value, upper_value): """Helper function to construct an interval object with open lower and upper. For example: >>> open(100.2, 800.9) (100.2, 800.9) """ return Interval(Interval.OPEN, lower_value, upper_value, Interval.OPEN)
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intiocean/pyinter
pyinter/interval.py
closed
def closed(lower_value, upper_value): """Helper function to construct an interval object with closed lower and upper. For example: >>> closed(100.2, 800.9) [100.2, 800.9] """ return Interval(Interval.CLOSED, lower_value, upper_value, Interval.CLOSED)
python
def closed(lower_value, upper_value): """Helper function to construct an interval object with closed lower and upper. For example: >>> closed(100.2, 800.9) [100.2, 800.9] """ return Interval(Interval.CLOSED, lower_value, upper_value, Interval.CLOSED)
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intiocean/pyinter
pyinter/interval.py
openclosed
def openclosed(lower_value, upper_value): """Helper function to construct an interval object with a open lower and closed upper. For example: >>> openclosed(100.2, 800.9) (100.2, 800.9] """ return Interval(Interval.OPEN, lower_value, upper_value, Interval.CLOSED)
python
def openclosed(lower_value, upper_value): """Helper function to construct an interval object with a open lower and closed upper. For example: >>> openclosed(100.2, 800.9) (100.2, 800.9] """ return Interval(Interval.OPEN, lower_value, upper_value, Interval.CLOSED)
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intiocean/pyinter
pyinter/interval.py
closedopen
def closedopen(lower_value, upper_value): """Helper function to construct an interval object with a closed lower and open upper. For example: >>> closedopen(100.2, 800.9) [100.2, 800.9) """ return Interval(Interval.CLOSED, lower_value, upper_value, Interval.OPEN)
python
def closedopen(lower_value, upper_value): """Helper function to construct an interval object with a closed lower and open upper. For example: >>> closedopen(100.2, 800.9) [100.2, 800.9) """ return Interval(Interval.CLOSED, lower_value, upper_value, Interval.OPEN)
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intiocean/pyinter
pyinter/interval.py
Interval.copy
def copy(self): """Returns a new :class:`~pyinter.Interval` object with the same bounds and values.""" return Interval(self._lower, self._lower_value, self._upper_value, self._upper)
python
def copy(self): """Returns a new :class:`~pyinter.Interval` object with the same bounds and values.""" return Interval(self._lower, self._lower_value, self._upper_value, self._upper)
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intiocean/pyinter
pyinter/interval.py
Interval._contains_value
def _contains_value(self, value): """Helper function for __contains__ to check a single value is contained within the interval""" g = operator.gt if self._lower is self.OPEN else operator.ge l = operator.lt if self._upper is self.OPEN else operator.le return g(value, self.lower_value) and l(value, self._upper_value)
python
def _contains_value(self, value): """Helper function for __contains__ to check a single value is contained within the interval""" g = operator.gt if self._lower is self.OPEN else operator.ge l = operator.lt if self._upper is self.OPEN else operator.le return g(value, self.lower_value) and l(value, self._upper_value)
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intiocean/pyinter
pyinter/interval.py
Interval.overlaps
def overlaps(self, other): """If self and other have any overlapping values returns True, otherwise returns False""" if self > other: smaller, larger = other, self else: smaller, larger = self, other if larger.empty(): return False if smaller._upper_value == larger._lower_value: return smaller._upper == smaller.CLOSED and larger._lower == smaller.CLOSED return larger._lower_value < smaller._upper_value
python
def overlaps(self, other): """If self and other have any overlapping values returns True, otherwise returns False""" if self > other: smaller, larger = other, self else: smaller, larger = self, other if larger.empty(): return False if smaller._upper_value == larger._lower_value: return smaller._upper == smaller.CLOSED and larger._lower == smaller.CLOSED return larger._lower_value < smaller._upper_value
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intiocean/pyinter
pyinter/interval.py
Interval.intersect
def intersect(self, other): """Returns a new :class:`~pyinter.Interval` representing the intersection of this :class:`~pyinter.Interval` with the other :class:`~pyinter.Interval`""" if self.overlaps(other): newlower_value = max(self.lower_value, other.lower_value) new_upper_value = min(self._upper_value, other._upper_value) new_lower, new_upper = self._get_new_lower_upper(other, self.intersect) return Interval(new_lower, newlower_value, new_upper_value, new_upper) else: return None
python
def intersect(self, other): """Returns a new :class:`~pyinter.Interval` representing the intersection of this :class:`~pyinter.Interval` with the other :class:`~pyinter.Interval`""" if self.overlaps(other): newlower_value = max(self.lower_value, other.lower_value) new_upper_value = min(self._upper_value, other._upper_value) new_lower, new_upper = self._get_new_lower_upper(other, self.intersect) return Interval(new_lower, newlower_value, new_upper_value, new_upper) else: return None
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intiocean/pyinter
pyinter/interval.py
Interval.difference
def difference(self, other): """Returns a new Interval or an :class:`~pyinter.IntervalSet` representing the subtraction of this :class:`~pyinter.Interval` with the other :class:`~pyinter.Interval`. The result will contain everything that is contained by the left interval but not contained by the second interval. If the `other` interval is enclosed in this one then this will return a :class:`~pyinter.IntervalSet`, otherwise this returns a :class:`~pyinter.Interval`. """ if other.empty(): return self if self in other: return open(self._lower_value, self._lower_value) if self._lower == other._lower and self._lower_value == other._lower_value: return Interval(self._opposite_boundary_type(other._upper), other._upper_value, self._upper_value, self._upper) if self._upper == other._upper and self._upper_value == other._upper_value: return Interval(self._lower, self._lower_value, other._lower_value, self._opposite_boundary_type(other._lower)) if other in self: return IntervalSet([ Interval(self._lower, self._lower_value, other.lower_value, self._opposite_boundary_type(other._lower)), Interval(self._opposite_boundary_type(other._upper), other._upper_value, self.upper_value, self._upper), ]) if other.lower_value in self: return Interval(self._lower, self._lower_value, other._lower_value, self._opposite_boundary_type(other._lower)) if other.upper_value in self: return Interval(self._opposite_boundary_type(other._upper), other._upper_value, self._upper_value, self._upper) return Interval(self._lower, self._lower_value, self._upper_value, self._upper)
python
def difference(self, other): """Returns a new Interval or an :class:`~pyinter.IntervalSet` representing the subtraction of this :class:`~pyinter.Interval` with the other :class:`~pyinter.Interval`. The result will contain everything that is contained by the left interval but not contained by the second interval. If the `other` interval is enclosed in this one then this will return a :class:`~pyinter.IntervalSet`, otherwise this returns a :class:`~pyinter.Interval`. """ if other.empty(): return self if self in other: return open(self._lower_value, self._lower_value) if self._lower == other._lower and self._lower_value == other._lower_value: return Interval(self._opposite_boundary_type(other._upper), other._upper_value, self._upper_value, self._upper) if self._upper == other._upper and self._upper_value == other._upper_value: return Interval(self._lower, self._lower_value, other._lower_value, self._opposite_boundary_type(other._lower)) if other in self: return IntervalSet([ Interval(self._lower, self._lower_value, other.lower_value, self._opposite_boundary_type(other._lower)), Interval(self._opposite_boundary_type(other._upper), other._upper_value, self.upper_value, self._upper), ]) if other.lower_value in self: return Interval(self._lower, self._lower_value, other._lower_value, self._opposite_boundary_type(other._lower)) if other.upper_value in self: return Interval(self._opposite_boundary_type(other._upper), other._upper_value, self._upper_value, self._upper) return Interval(self._lower, self._lower_value, self._upper_value, self._upper)
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avalente/appmetrics
appmetrics/reporter.py
register
def register(callback, schedule, tag=None): """ Register a callback which will be called at scheduled intervals with the metrics that have the given tag (or all the metrics if None). Return an identifier which can be used to access the registered callback later. """ try: iter(schedule) except TypeError: raise TypeError("{} is not iterable".format(schedule)) if not callable(callback): raise TypeError("{} is not callable".format(callback)) thread = Timer(schedule, callback, tag) id_ = str(uuid.uuid4()) with LOCK: REGISTRY[id_] = thread thread.start() return id_
python
def register(callback, schedule, tag=None): """ Register a callback which will be called at scheduled intervals with the metrics that have the given tag (or all the metrics if None). Return an identifier which can be used to access the registered callback later. """ try: iter(schedule) except TypeError: raise TypeError("{} is not iterable".format(schedule)) if not callable(callback): raise TypeError("{} is not callable".format(callback)) thread = Timer(schedule, callback, tag) id_ = str(uuid.uuid4()) with LOCK: REGISTRY[id_] = thread thread.start() return id_
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avalente/appmetrics
appmetrics/reporter.py
remove
def remove(id_): """ Remove the callback and its schedule """ with LOCK: thread = REGISTRY.pop(id_, None) if thread is not None: thread.cancel() return thread
python
def remove(id_): """ Remove the callback and its schedule """ with LOCK: thread = REGISTRY.pop(id_, None) if thread is not None: thread.cancel() return thread
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train
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avalente/appmetrics
appmetrics/reporter.py
get_metrics
def get_metrics(tag): """ Return the values for the metrics with the given tag or all the available metrics if None """ if tag is None: return metrics.metrics_by_name_list(metrics.metrics()) else: return metrics.metrics_by_tag(tag)
python
def get_metrics(tag): """ Return the values for the metrics with the given tag or all the available metrics if None """ if tag is None: return metrics.metrics_by_name_list(metrics.metrics()) else: return metrics.metrics_by_tag(tag)
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avalente/appmetrics
appmetrics/reporter.py
fixed_interval_scheduler
def fixed_interval_scheduler(interval): """ A scheduler that ticks at fixed intervals of "interval" seconds """ start = time.time() next_tick = start while True: next_tick += interval yield next_tick
python
def fixed_interval_scheduler(interval): """ A scheduler that ticks at fixed intervals of "interval" seconds """ start = time.time() next_tick = start while True: next_tick += interval yield next_tick
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Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Game.wrap_search
def wrap_search(cls, response): """Wrap the response from a game search into instances and return them :param response: The response from searching a game :type response: :class:`requests.Response` :returns: the new game instances :rtype: :class:`list` of :class:`Game` :raises: None """ games = [] json = response.json() gamejsons = json['games'] for j in gamejsons: g = cls.wrap_json(j) games.append(g) return games
python
def wrap_search(cls, response): """Wrap the response from a game search into instances and return them :param response: The response from searching a game :type response: :class:`requests.Response` :returns: the new game instances :rtype: :class:`list` of :class:`Game` :raises: None """ games = [] json = response.json() gamejsons = json['games'] for j in gamejsons: g = cls.wrap_json(j) games.append(g) return games
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train
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Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Game.wrap_topgames
def wrap_topgames(cls, response): """Wrap the response from quering the top games into instances and return them :param response: The response for quering the top games :type response: :class:`requests.Response` :returns: the new game instances :rtype: :class:`list` of :class:`Game` :raises: None """ games = [] json = response.json() topjsons = json['top'] for t in topjsons: g = cls.wrap_json(json=t['game'], viewers=t['viewers'], channels=t['channels']) games.append(g) return games
python
def wrap_topgames(cls, response): """Wrap the response from quering the top games into instances and return them :param response: The response for quering the top games :type response: :class:`requests.Response` :returns: the new game instances :rtype: :class:`list` of :class:`Game` :raises: None """ games = [] json = response.json() topjsons = json['top'] for t in topjsons: g = cls.wrap_json(json=t['game'], viewers=t['viewers'], channels=t['channels']) games.append(g) return games
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train
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Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Game.wrap_json
def wrap_json(cls, json, viewers=None, channels=None): """Create a Game instance for the given json :param json: the dict with the information of the game :type json: :class:`dict` :param viewers: The viewer count :type viewers: :class:`int` :param channels: The viewer count :type channels: :class:`int` :returns: the new game instance :rtype: :class:`Game` :raises: None """ g = Game(name=json.get('name'), box=json.get('box'), logo=json.get('logo'), twitchid=json.get('_id'), viewers=viewers, channels=channels) return g
python
def wrap_json(cls, json, viewers=None, channels=None): """Create a Game instance for the given json :param json: the dict with the information of the game :type json: :class:`dict` :param viewers: The viewer count :type viewers: :class:`int` :param channels: The viewer count :type channels: :class:`int` :returns: the new game instance :rtype: :class:`Game` :raises: None """ g = Game(name=json.get('name'), box=json.get('box'), logo=json.get('logo'), twitchid=json.get('_id'), viewers=viewers, channels=channels) return g
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Create a Game instance for the given json :param json: the dict with the information of the game :type json: :class:`dict` :param viewers: The viewer count :type viewers: :class:`int` :param channels: The viewer count :type channels: :class:`int` :returns: the new game instance :rtype: :class:`Game` :raises: None
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/models.py#L51-L70
Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Channel.wrap_search
def wrap_search(cls, response): """Wrap the response from a channel search into instances and return them :param response: The response from searching a channel :type response: :class:`requests.Response` :returns: the new channel instances :rtype: :class:`list` of :class:`channel` :raises: None """ channels = [] json = response.json() channeljsons = json['channels'] for j in channeljsons: c = cls.wrap_json(j) channels.append(c) return channels
python
def wrap_search(cls, response): """Wrap the response from a channel search into instances and return them :param response: The response from searching a channel :type response: :class:`requests.Response` :returns: the new channel instances :rtype: :class:`list` of :class:`channel` :raises: None """ channels = [] json = response.json() channeljsons = json['channels'] for j in channeljsons: c = cls.wrap_json(j) channels.append(c) return channels
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train
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Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Channel.wrap_get_channel
def wrap_get_channel(cls, response): """Wrap the response from getting a channel into an instance and return it :param response: The response from getting a channel :type response: :class:`requests.Response` :returns: the new channel instance :rtype: :class:`list` of :class:`channel` :raises: None """ json = response.json() c = cls.wrap_json(json) return c
python
def wrap_get_channel(cls, response): """Wrap the response from getting a channel into an instance and return it :param response: The response from getting a channel :type response: :class:`requests.Response` :returns: the new channel instance :rtype: :class:`list` of :class:`channel` :raises: None """ json = response.json() c = cls.wrap_json(json) return c
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train
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Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Channel.wrap_json
def wrap_json(cls, json): """Create a Channel instance for the given json :param json: the dict with the information of the channel :type json: :class:`dict` :returns: the new channel instance :rtype: :class:`Channel` :raises: None """ c = Channel(name=json.get('name'), status=json.get('status'), displayname=json.get('display_name'), game=json.get('game'), twitchid=json.get('_id'), views=json.get('views'), followers=json.get('followers'), url=json.get('url'), language=json.get('language'), broadcaster_language=json.get('broadcaster_language'), mature=json.get('mature'), logo=json.get('logo'), banner=json.get('banner'), video_banner=json.get('video_banner'), delay=json.get('delay')) return c
python
def wrap_json(cls, json): """Create a Channel instance for the given json :param json: the dict with the information of the channel :type json: :class:`dict` :returns: the new channel instance :rtype: :class:`Channel` :raises: None """ c = Channel(name=json.get('name'), status=json.get('status'), displayname=json.get('display_name'), game=json.get('game'), twitchid=json.get('_id'), views=json.get('views'), followers=json.get('followers'), url=json.get('url'), language=json.get('language'), broadcaster_language=json.get('broadcaster_language'), mature=json.get('mature'), logo=json.get('logo'), banner=json.get('banner'), video_banner=json.get('video_banner'), delay=json.get('delay')) return c
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Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Stream.wrap_search
def wrap_search(cls, response): """Wrap the response from a stream search into instances and return them :param response: The response from searching a stream :type response: :class:`requests.Response` :returns: the new stream instances :rtype: :class:`list` of :class:`stream` :raises: None """ streams = [] json = response.json() streamjsons = json['streams'] for j in streamjsons: s = cls.wrap_json(j) streams.append(s) return streams
python
def wrap_search(cls, response): """Wrap the response from a stream search into instances and return them :param response: The response from searching a stream :type response: :class:`requests.Response` :returns: the new stream instances :rtype: :class:`list` of :class:`stream` :raises: None """ streams = [] json = response.json() streamjsons = json['streams'] for j in streamjsons: s = cls.wrap_json(j) streams.append(s) return streams
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Wrap the response from a stream search into instances and return them :param response: The response from searching a stream :type response: :class:`requests.Response` :returns: the new stream instances :rtype: :class:`list` of :class:`stream` :raises: None
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Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Stream.wrap_get_stream
def wrap_get_stream(cls, response): """Wrap the response from getting a stream into an instance and return it :param response: The response from getting a stream :type response: :class:`requests.Response` :returns: the new stream instance :rtype: :class:`list` of :class:`stream` :raises: None """ json = response.json() s = cls.wrap_json(json['stream']) return s
python
def wrap_get_stream(cls, response): """Wrap the response from getting a stream into an instance and return it :param response: The response from getting a stream :type response: :class:`requests.Response` :returns: the new stream instance :rtype: :class:`list` of :class:`stream` :raises: None """ json = response.json() s = cls.wrap_json(json['stream']) return s
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Wrap the response from getting a stream into an instance and return it :param response: The response from getting a stream :type response: :class:`requests.Response` :returns: the new stream instance :rtype: :class:`list` of :class:`stream` :raises: None
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/models.py#L283-L295
Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
Stream.wrap_json
def wrap_json(cls, json): """Create a Stream instance for the given json :param json: the dict with the information of the stream :type json: :class:`dict` | None :returns: the new stream instance :rtype: :class:`Stream` | None :raises: None """ if json is None: return None channel = Channel.wrap_json(json.get('channel')) s = Stream(game=json.get('game'), channel=channel, twitchid=json.get('_id'), viewers=json.get('viewers'), preview=json.get('preview')) return s
python
def wrap_json(cls, json): """Create a Stream instance for the given json :param json: the dict with the information of the stream :type json: :class:`dict` | None :returns: the new stream instance :rtype: :class:`Stream` | None :raises: None """ if json is None: return None channel = Channel.wrap_json(json.get('channel')) s = Stream(game=json.get('game'), channel=channel, twitchid=json.get('_id'), viewers=json.get('viewers'), preview=json.get('preview')) return s
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/models.py#L298-L315
Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
User.wrap_get_user
def wrap_get_user(cls, response): """Wrap the response from getting a user into an instance and return it :param response: The response from getting a user :type response: :class:`requests.Response` :returns: the new user instance :rtype: :class:`list` of :class:`User` :raises: None """ json = response.json() u = cls.wrap_json(json) return u
python
def wrap_get_user(cls, response): """Wrap the response from getting a user into an instance and return it :param response: The response from getting a user :type response: :class:`requests.Response` :returns: the new user instance :rtype: :class:`list` of :class:`User` :raises: None """ json = response.json() u = cls.wrap_json(json) return u
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Wrap the response from getting a user into an instance and return it :param response: The response from getting a user :type response: :class:`requests.Response` :returns: the new user instance :rtype: :class:`list` of :class:`User` :raises: None
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/models.py#L360-L372
Pytwitcher/pytwitcherapi
src/pytwitcherapi/models.py
User.wrap_json
def wrap_json(cls, json): """Create a User instance for the given json :param json: the dict with the information of the user :type json: :class:`dict` | None :returns: the new user instance :rtype: :class:`User` :raises: None """ u = User(usertype=json['type'], name=json['name'], logo=json['logo'], twitchid=json['_id'], displayname=json['display_name'], bio=json['bio']) return u
python
def wrap_json(cls, json): """Create a User instance for the given json :param json: the dict with the information of the user :type json: :class:`dict` | None :returns: the new user instance :rtype: :class:`User` :raises: None """ u = User(usertype=json['type'], name=json['name'], logo=json['logo'], twitchid=json['_id'], displayname=json['display_name'], bio=json['bio']) return u
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Create a User instance for the given json :param json: the dict with the information of the user :type json: :class:`dict` | None :returns: the new user instance :rtype: :class:`User` :raises: None
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/models.py#L375-L390
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/client.py
_wrap_execute_after
def _wrap_execute_after(funcname): """Warp the given method, so it gets executed by the reactor Wrap a method of :data:`IRCCLient.out_connection`. The returned function should be assigned to a :class:`irc.client.SimpleIRCClient` class. :param funcname: the name of a :class:`irc.client.ServerConnection` method :type funcname: :class:`str` :returns: a new function, that executes the given one via :class:`irc.schedule.IScheduler.execute_after` :raises: None """ def method(self, *args, **kwargs): f = getattr(self.out_connection, funcname) p = functools.partial(f, *args, **kwargs) self.reactor.scheduler.execute_after(0, p) method.__name__ = funcname return method
python
def _wrap_execute_after(funcname): """Warp the given method, so it gets executed by the reactor Wrap a method of :data:`IRCCLient.out_connection`. The returned function should be assigned to a :class:`irc.client.SimpleIRCClient` class. :param funcname: the name of a :class:`irc.client.ServerConnection` method :type funcname: :class:`str` :returns: a new function, that executes the given one via :class:`irc.schedule.IScheduler.execute_after` :raises: None """ def method(self, *args, **kwargs): f = getattr(self.out_connection, funcname) p = functools.partial(f, *args, **kwargs) self.reactor.scheduler.execute_after(0, p) method.__name__ = funcname return method
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/chat/client.py#L100-L117
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/client.py
add_serverconnection_methods
def add_serverconnection_methods(cls): """Add a bunch of methods to an :class:`irc.client.SimpleIRCClient` to send commands and messages. Basically it wraps a bunch of methdos from :class:`irc.client.ServerConnection` to be :meth:`irc.schedule.IScheduler.execute_after`. That way, you can easily send, even if the IRCClient is running in :class:`IRCClient.process_forever` in another thread. On the plus side you can use positional and keyword arguments instead of just positional ones. :param cls: The class to add the methods do. :type cls: :class:`irc.client.SimpleIRCClient` :returns: None """ methods = ['action', 'admin', 'cap', 'ctcp', 'ctcp_reply', 'globops', 'info', 'invite', 'ison', 'join', 'kick', 'links', 'list', 'lusers', 'mode', 'motd', 'names', 'nick', 'notice', 'oper', 'part', 'part', 'pass_', 'ping', 'pong', 'privmsg', 'privmsg_many', 'quit', 'send_raw', 'squit', 'stats', 'time', 'topic', 'trace', 'user', 'userhost', 'users', 'version', 'wallops', 'who', 'whois', 'whowas'] for m in methods: method = _wrap_execute_after(m) f = getattr(irc.client.ServerConnection, m) method.__doc__ = f.__doc__ setattr(cls, method.__name__, method) return cls
python
def add_serverconnection_methods(cls): """Add a bunch of methods to an :class:`irc.client.SimpleIRCClient` to send commands and messages. Basically it wraps a bunch of methdos from :class:`irc.client.ServerConnection` to be :meth:`irc.schedule.IScheduler.execute_after`. That way, you can easily send, even if the IRCClient is running in :class:`IRCClient.process_forever` in another thread. On the plus side you can use positional and keyword arguments instead of just positional ones. :param cls: The class to add the methods do. :type cls: :class:`irc.client.SimpleIRCClient` :returns: None """ methods = ['action', 'admin', 'cap', 'ctcp', 'ctcp_reply', 'globops', 'info', 'invite', 'ison', 'join', 'kick', 'links', 'list', 'lusers', 'mode', 'motd', 'names', 'nick', 'notice', 'oper', 'part', 'part', 'pass_', 'ping', 'pong', 'privmsg', 'privmsg_many', 'quit', 'send_raw', 'squit', 'stats', 'time', 'topic', 'trace', 'user', 'userhost', 'users', 'version', 'wallops', 'who', 'whois', 'whowas'] for m in methods: method = _wrap_execute_after(m) f = getattr(irc.client.ServerConnection, m) method.__doc__ = f.__doc__ setattr(cls, method.__name__, method) return cls
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train
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Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/client.py
Reactor.process_forever
def process_forever(self, timeout=0.2): """Run an infinite loop, processing data from connections. This method repeatedly calls process_once. :param timeout: Parameter to pass to :meth:`irc.client.Reactor.process_once` :type timeout: :class:`float` """ # This loop should specifically *not* be mutex-locked. # Otherwise no other thread would ever be able to change # the shared state of a Reactor object running this function. log.debug("process_forever(timeout=%s)", timeout) self._looping.set() while self._looping.is_set(): self.process_once(timeout)
python
def process_forever(self, timeout=0.2): """Run an infinite loop, processing data from connections. This method repeatedly calls process_once. :param timeout: Parameter to pass to :meth:`irc.client.Reactor.process_once` :type timeout: :class:`float` """ # This loop should specifically *not* be mutex-locked. # Otherwise no other thread would ever be able to change # the shared state of a Reactor object running this function. log.debug("process_forever(timeout=%s)", timeout) self._looping.set() while self._looping.is_set(): self.process_once(timeout)
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/chat/client.py#L51-L66
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/client.py
Reactor.shutdown
def shutdown(self): """Disconnect all connections and end the loop :returns: None :rtype: None :raises: None """ log.debug('Shutting down %s' % self) self.disconnect_all() self._looping.clear()
python
def shutdown(self): """Disconnect all connections and end the loop :returns: None :rtype: None :raises: None """ log.debug('Shutting down %s' % self) self.disconnect_all() self._looping.clear()
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/chat/client.py#L68-L77
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/client.py
Reactor3.server
def server(self, ): """Creates and returns a ServerConnection :returns: a server connection :rtype: :class:`connection.ServerConnection3` :raises: None """ c = connection.ServerConnection3(self) with self.mutex: self.connections.append(c) return c
python
def server(self, ): """Creates and returns a ServerConnection :returns: a server connection :rtype: :class:`connection.ServerConnection3` :raises: None """ c = connection.ServerConnection3(self) with self.mutex: self.connections.append(c) return c
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tkf/rash
rash/init.py
init_run
def init_run(shell, no_daemon, daemon_options, daemon_outfile): """ Configure your shell. Add the following line in your shell RC file and then you are ready to go:: eval $(%(prog)s) To check if your shell is supported, simply run:: %(prog)s --no-daemon If you want to specify shell other than $SHELL, you can give --shell option:: eval $(%(prog)s --shell zsh) By default, this command also starts daemon in background to automatically index shell history records. To not start daemon, use --no-daemon option like this:: eval $(%(prog)s --no-daemon) To see the other methods to launch the daemon process, see ``rash daemon --help``. """ import sys from .__init__ import __version__ init_file = find_init(shell) if os.path.exists(init_file): sys.stdout.write(INIT_TEMPLATE.format( file=init_file, version=__version__)) else: raise RuntimeError( "Shell '{0}' is not supported.".format(shell_name(shell))) if not no_daemon: from .daemon import start_daemon_in_subprocess start_daemon_in_subprocess(daemon_options, daemon_outfile)
python
def init_run(shell, no_daemon, daemon_options, daemon_outfile): """ Configure your shell. Add the following line in your shell RC file and then you are ready to go:: eval $(%(prog)s) To check if your shell is supported, simply run:: %(prog)s --no-daemon If you want to specify shell other than $SHELL, you can give --shell option:: eval $(%(prog)s --shell zsh) By default, this command also starts daemon in background to automatically index shell history records. To not start daemon, use --no-daemon option like this:: eval $(%(prog)s --no-daemon) To see the other methods to launch the daemon process, see ``rash daemon --help``. """ import sys from .__init__ import __version__ init_file = find_init(shell) if os.path.exists(init_file): sys.stdout.write(INIT_TEMPLATE.format( file=init_file, version=__version__)) else: raise RuntimeError( "Shell '{0}' is not supported.".format(shell_name(shell))) if not no_daemon: from .daemon import start_daemon_in_subprocess start_daemon_in_subprocess(daemon_options, daemon_outfile)
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Configure your shell. Add the following line in your shell RC file and then you are ready to go:: eval $(%(prog)s) To check if your shell is supported, simply run:: %(prog)s --no-daemon If you want to specify shell other than $SHELL, you can give --shell option:: eval $(%(prog)s --shell zsh) By default, this command also starts daemon in background to automatically index shell history records. To not start daemon, use --no-daemon option like this:: eval $(%(prog)s --no-daemon) To see the other methods to launch the daemon process, see ``rash daemon --help``.
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train
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alpha-xone/xone
xone/cache.py
cache_file
def cache_file(symbol, func, has_date, root, date_type='date'): """ Data file Args: symbol: symbol func: use function to categorize data has_date: contains date in data file root: root path date_type: parameters pass to utils.cur_time, [date, time, time_path, ...] Returns: str: date file """ cur_mod = sys.modules[func.__module__] data_tz = getattr(cur_mod, 'DATA_TZ') if hasattr(cur_mod, 'DATA_TZ') else 'UTC' cur_dt = utils.cur_time(typ=date_type, tz=data_tz, trading=False) if has_date: if hasattr(cur_mod, 'FILE_WITH_DATE'): file_fmt = getattr(cur_mod, 'FILE_WITH_DATE') else: file_fmt = '{root}/{typ}/{symbol}/{cur_dt}.parq' else: if hasattr(cur_mod, 'FILE_NO_DATE'): file_fmt = getattr(cur_mod, 'FILE_NO_DATE') else: file_fmt = '{root}/{typ}/{symbol}.parq' return data_file( file_fmt=file_fmt, root=root, cur_dt=cur_dt, typ=func.__name__, symbol=symbol )
python
def cache_file(symbol, func, has_date, root, date_type='date'): """ Data file Args: symbol: symbol func: use function to categorize data has_date: contains date in data file root: root path date_type: parameters pass to utils.cur_time, [date, time, time_path, ...] Returns: str: date file """ cur_mod = sys.modules[func.__module__] data_tz = getattr(cur_mod, 'DATA_TZ') if hasattr(cur_mod, 'DATA_TZ') else 'UTC' cur_dt = utils.cur_time(typ=date_type, tz=data_tz, trading=False) if has_date: if hasattr(cur_mod, 'FILE_WITH_DATE'): file_fmt = getattr(cur_mod, 'FILE_WITH_DATE') else: file_fmt = '{root}/{typ}/{symbol}/{cur_dt}.parq' else: if hasattr(cur_mod, 'FILE_NO_DATE'): file_fmt = getattr(cur_mod, 'FILE_NO_DATE') else: file_fmt = '{root}/{typ}/{symbol}.parq' return data_file( file_fmt=file_fmt, root=root, cur_dt=cur_dt, typ=func.__name__, symbol=symbol )
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Data file Args: symbol: symbol func: use function to categorize data has_date: contains date in data file root: root path date_type: parameters pass to utils.cur_time, [date, time, time_path, ...] Returns: str: date file
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train
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alpha-xone/xone
xone/cache.py
update_data
def update_data(func): """ Decorator to save data more easily. Use parquet as data format Args: func: function to load data from data source Returns: wrapped function """ default = dict([ (param.name, param.default) for param in inspect.signature(func).parameters.values() if param.default != getattr(inspect, '_empty') ]) @wraps(func) def wrapper(*args, **kwargs): default.update(kwargs) kwargs.update(default) cur_mod = sys.modules[func.__module__] logger = logs.get_logger(name_or_func=f'{cur_mod.__name__}.{func.__name__}', types='stream') root_path = cur_mod.DATA_PATH date_type = kwargs.pop('date_type', 'date') save_static = kwargs.pop('save_static', True) save_dynamic = kwargs.pop('save_dynamic', True) symbol = kwargs.get('symbol') file_kw = dict(func=func, symbol=symbol, root=root_path, date_type=date_type) d_file = cache_file(has_date=True, **file_kw) s_file = cache_file(has_date=False, **file_kw) cached = kwargs.pop('cached', False) if cached and save_static and files.exists(s_file): logger.info(f'Reading data from {s_file} ...') return pd.read_parquet(s_file) data = func(*args, **kwargs) if save_static: files.create_folder(s_file, is_file=True) save_data(data=data, file_fmt=s_file, append=False) logger.info(f'Saved data file to {s_file} ...') if save_dynamic: drop_dups = kwargs.pop('drop_dups', None) files.create_folder(d_file, is_file=True) save_data(data=data, file_fmt=d_file, append=True, drop_dups=drop_dups) logger.info(f'Saved data file to {d_file} ...') return data return wrapper
python
def update_data(func): """ Decorator to save data more easily. Use parquet as data format Args: func: function to load data from data source Returns: wrapped function """ default = dict([ (param.name, param.default) for param in inspect.signature(func).parameters.values() if param.default != getattr(inspect, '_empty') ]) @wraps(func) def wrapper(*args, **kwargs): default.update(kwargs) kwargs.update(default) cur_mod = sys.modules[func.__module__] logger = logs.get_logger(name_or_func=f'{cur_mod.__name__}.{func.__name__}', types='stream') root_path = cur_mod.DATA_PATH date_type = kwargs.pop('date_type', 'date') save_static = kwargs.pop('save_static', True) save_dynamic = kwargs.pop('save_dynamic', True) symbol = kwargs.get('symbol') file_kw = dict(func=func, symbol=symbol, root=root_path, date_type=date_type) d_file = cache_file(has_date=True, **file_kw) s_file = cache_file(has_date=False, **file_kw) cached = kwargs.pop('cached', False) if cached and save_static and files.exists(s_file): logger.info(f'Reading data from {s_file} ...') return pd.read_parquet(s_file) data = func(*args, **kwargs) if save_static: files.create_folder(s_file, is_file=True) save_data(data=data, file_fmt=s_file, append=False) logger.info(f'Saved data file to {s_file} ...') if save_dynamic: drop_dups = kwargs.pop('drop_dups', None) files.create_folder(d_file, is_file=True) save_data(data=data, file_fmt=d_file, append=True, drop_dups=drop_dups) logger.info(f'Saved data file to {d_file} ...') return data return wrapper
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train
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alpha-xone/xone
xone/cache.py
save_data
def save_data(data, file_fmt, append=False, drop_dups=None, info=None, **kwargs): """ Save data to file Args: data: pd.DataFrame file_fmt: data file format in terms of f-strings append: if append data to existing data drop_dups: list, drop duplicates in columns info: dict, infomation to be hashed and passed to f-strings **kwargs: additional parameters for f-strings Examples: >>> data = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b']) >>> # save_data( >>> # data, '{ROOT}/daily/{typ}.parq', >>> # ROOT='tests/data', typ='earnings' >>> # ) """ d_file = data_file(file_fmt=file_fmt, info=info, **kwargs) if append and files.exists(d_file): data = pd.DataFrame(pd.concat([pd.read_parquet(d_file), data], sort=False)) if drop_dups is not None: data.drop_duplicates(subset=utils.tolist(drop_dups), inplace=True) if not data.empty: data.to_parquet(d_file) return data
python
def save_data(data, file_fmt, append=False, drop_dups=None, info=None, **kwargs): """ Save data to file Args: data: pd.DataFrame file_fmt: data file format in terms of f-strings append: if append data to existing data drop_dups: list, drop duplicates in columns info: dict, infomation to be hashed and passed to f-strings **kwargs: additional parameters for f-strings Examples: >>> data = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b']) >>> # save_data( >>> # data, '{ROOT}/daily/{typ}.parq', >>> # ROOT='tests/data', typ='earnings' >>> # ) """ d_file = data_file(file_fmt=file_fmt, info=info, **kwargs) if append and files.exists(d_file): data = pd.DataFrame(pd.concat([pd.read_parquet(d_file), data], sort=False)) if drop_dups is not None: data.drop_duplicates(subset=utils.tolist(drop_dups), inplace=True) if not data.empty: data.to_parquet(d_file) return data
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train
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alpha-xone/xone
xone/cache.py
data_file
def data_file(file_fmt, info=None, **kwargs): """ Data file name for given infomation Args: file_fmt: file format in terms of f-strings info: dict, to be hashed and then pass to f-string using 'hash_key' these info will also be passed to f-strings **kwargs: arguments for f-strings Returns: str: data file name """ if isinstance(info, dict): kwargs['hash_key'] = hashlib.sha256(json.dumps(info).encode('utf-8')).hexdigest() kwargs.update(info) return utils.fstr(fmt=file_fmt, **kwargs)
python
def data_file(file_fmt, info=None, **kwargs): """ Data file name for given infomation Args: file_fmt: file format in terms of f-strings info: dict, to be hashed and then pass to f-string using 'hash_key' these info will also be passed to f-strings **kwargs: arguments for f-strings Returns: str: data file name """ if isinstance(info, dict): kwargs['hash_key'] = hashlib.sha256(json.dumps(info).encode('utf-8')).hexdigest() kwargs.update(info) return utils.fstr(fmt=file_fmt, **kwargs)
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train
https://github.com/alpha-xone/xone/blob/68534a30f7f1760b220ba58040be3927f7dfbcf4/xone/cache.py#L131-L148
alpha-xone/xone
xone/plots.py
plot_multi
def plot_multi(data, cols=None, spacing=.06, color_map=None, plot_kw=None, **kwargs): """ Plot data with multiple scaels together Args: data: DataFrame of data cols: columns to be plotted spacing: spacing between legends color_map: customized colors in map plot_kw: kwargs for each plot **kwargs: kwargs for the first plot Returns: ax for plot Examples: >>> import pandas as pd >>> import numpy as np >>> >>> idx = range(5) >>> data = pd.DataFrame(dict(a=np.exp(idx), b=idx), index=idx) >>> # plot_multi(data=data, cols=['a', 'b'], plot_kw=[dict(style='.-'), dict()]) """ import matplotlib.pyplot as plt from pandas import plotting if cols is None: cols = data.columns if plot_kw is None: plot_kw = [{}] * len(cols) if len(cols) == 0: return num_colors = len(utils.flatten(cols)) # Get default color style from pandas colors = getattr(getattr(plotting, '_style'), '_get_standard_colors')(num_colors=num_colors) if color_map is None: color_map = dict() fig = plt.figure() ax, lines, labels, c_idx = None, [], [], 0 for n, col in enumerate(cols): if isinstance(col, (list, tuple)): ylabel = ' / '.join(cols[n]) color = [ color_map.get(cols[n][_ - c_idx], colors[_ % len(colors)]) for _ in range(c_idx, c_idx + len(cols[n])) ] c_idx += len(col) else: ylabel = col color = color_map.get(col, colors[c_idx % len(colors)]) c_idx += 1 if 'color' in plot_kw[n]: color = plot_kw[n].pop('color') if ax is None: # First y-axes legend = plot_kw[0].pop('legend', kwargs.pop('legend', False)) ax = data.loc[:, col].plot( label=col, color=color, legend=legend, zorder=n, **plot_kw[0], **kwargs ) ax.set_ylabel(ylabel=ylabel) line, label = ax.get_legend_handles_labels() ax.spines['left'].set_edgecolor('#D5C4A1') ax.spines['left'].set_alpha(.5) else: # Multiple y-axes legend = plot_kw[n].pop('legend', False) ax_new = ax.twinx() ax_new.spines['right'].set_position(('axes', 1 + spacing * (n - 1))) data.loc[:, col].plot( ax=ax_new, label=col, color=color, legend=legend, zorder=n, **plot_kw[n] ) ax_new.set_ylabel(ylabel=ylabel) line, label = ax_new.get_legend_handles_labels() ax_new.spines['right'].set_edgecolor('#D5C4A1') ax_new.spines['right'].set_alpha(.5) ax_new.grid(False) # Proper legend position lines += line labels += label fig.legend(lines, labels, loc=8, prop=dict(), ncol=num_colors).set_zorder(len(cols)) ax.set_xlabel(' \n ') return ax
python
def plot_multi(data, cols=None, spacing=.06, color_map=None, plot_kw=None, **kwargs): """ Plot data with multiple scaels together Args: data: DataFrame of data cols: columns to be plotted spacing: spacing between legends color_map: customized colors in map plot_kw: kwargs for each plot **kwargs: kwargs for the first plot Returns: ax for plot Examples: >>> import pandas as pd >>> import numpy as np >>> >>> idx = range(5) >>> data = pd.DataFrame(dict(a=np.exp(idx), b=idx), index=idx) >>> # plot_multi(data=data, cols=['a', 'b'], plot_kw=[dict(style='.-'), dict()]) """ import matplotlib.pyplot as plt from pandas import plotting if cols is None: cols = data.columns if plot_kw is None: plot_kw = [{}] * len(cols) if len(cols) == 0: return num_colors = len(utils.flatten(cols)) # Get default color style from pandas colors = getattr(getattr(plotting, '_style'), '_get_standard_colors')(num_colors=num_colors) if color_map is None: color_map = dict() fig = plt.figure() ax, lines, labels, c_idx = None, [], [], 0 for n, col in enumerate(cols): if isinstance(col, (list, tuple)): ylabel = ' / '.join(cols[n]) color = [ color_map.get(cols[n][_ - c_idx], colors[_ % len(colors)]) for _ in range(c_idx, c_idx + len(cols[n])) ] c_idx += len(col) else: ylabel = col color = color_map.get(col, colors[c_idx % len(colors)]) c_idx += 1 if 'color' in plot_kw[n]: color = plot_kw[n].pop('color') if ax is None: # First y-axes legend = plot_kw[0].pop('legend', kwargs.pop('legend', False)) ax = data.loc[:, col].plot( label=col, color=color, legend=legend, zorder=n, **plot_kw[0], **kwargs ) ax.set_ylabel(ylabel=ylabel) line, label = ax.get_legend_handles_labels() ax.spines['left'].set_edgecolor('#D5C4A1') ax.spines['left'].set_alpha(.5) else: # Multiple y-axes legend = plot_kw[n].pop('legend', False) ax_new = ax.twinx() ax_new.spines['right'].set_position(('axes', 1 + spacing * (n - 1))) data.loc[:, col].plot( ax=ax_new, label=col, color=color, legend=legend, zorder=n, **plot_kw[n] ) ax_new.set_ylabel(ylabel=ylabel) line, label = ax_new.get_legend_handles_labels() ax_new.spines['right'].set_edgecolor('#D5C4A1') ax_new.spines['right'].set_alpha(.5) ax_new.grid(False) # Proper legend position lines += line labels += label fig.legend(lines, labels, loc=8, prop=dict(), ncol=num_colors).set_zorder(len(cols)) ax.set_xlabel(' \n ') return ax
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Plot data with multiple scaels together Args: data: DataFrame of data cols: columns to be plotted spacing: spacing between legends color_map: customized colors in map plot_kw: kwargs for each plot **kwargs: kwargs for the first plot Returns: ax for plot Examples: >>> import pandas as pd >>> import numpy as np >>> >>> idx = range(5) >>> data = pd.DataFrame(dict(a=np.exp(idx), b=idx), index=idx) >>> # plot_multi(data=data, cols=['a', 'b'], plot_kw=[dict(style='.-'), dict()])
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train
https://github.com/alpha-xone/xone/blob/68534a30f7f1760b220ba58040be3927f7dfbcf4/xone/plots.py#L4-L87
alpha-xone/xone
xone/plots.py
plot_h
def plot_h(data, cols, wspace=.1, plot_kw=None, **kwargs): """ Plot horizontally Args: data: DataFrame of data cols: columns to be plotted wspace: spacing between plots plot_kw: kwargs for each plot **kwargs: kwargs for the whole plot Returns: axes for plots Examples: >>> import pandas as pd >>> import numpy as np >>> >>> idx = range(5) >>> data = pd.DataFrame(dict(a=np.exp(idx), b=idx), index=idx) >>> # plot_h(data=data, cols=['a', 'b'], wspace=.2, plot_kw=[dict(style='.-'), dict()]) """ import matplotlib.pyplot as plt if plot_kw is None: plot_kw = [dict()] * len(cols) _, axes = plt.subplots(nrows=1, ncols=len(cols), **kwargs) plt.subplots_adjust(wspace=wspace) for n, col in enumerate(cols): data.loc[:, col].plot(ax=axes[n], **plot_kw[n]) return axes
python
def plot_h(data, cols, wspace=.1, plot_kw=None, **kwargs): """ Plot horizontally Args: data: DataFrame of data cols: columns to be plotted wspace: spacing between plots plot_kw: kwargs for each plot **kwargs: kwargs for the whole plot Returns: axes for plots Examples: >>> import pandas as pd >>> import numpy as np >>> >>> idx = range(5) >>> data = pd.DataFrame(dict(a=np.exp(idx), b=idx), index=idx) >>> # plot_h(data=data, cols=['a', 'b'], wspace=.2, plot_kw=[dict(style='.-'), dict()]) """ import matplotlib.pyplot as plt if plot_kw is None: plot_kw = [dict()] * len(cols) _, axes = plt.subplots(nrows=1, ncols=len(cols), **kwargs) plt.subplots_adjust(wspace=wspace) for n, col in enumerate(cols): data.loc[:, col].plot(ax=axes[n], **plot_kw[n]) return axes
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Plot horizontally Args: data: DataFrame of data cols: columns to be plotted wspace: spacing between plots plot_kw: kwargs for each plot **kwargs: kwargs for the whole plot Returns: axes for plots Examples: >>> import pandas as pd >>> import numpy as np >>> >>> idx = range(5) >>> data = pd.DataFrame(dict(a=np.exp(idx), b=idx), index=idx) >>> # plot_h(data=data, cols=['a', 'b'], wspace=.2, plot_kw=[dict(style='.-'), dict()])
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train
https://github.com/alpha-xone/xone/blob/68534a30f7f1760b220ba58040be3927f7dfbcf4/xone/plots.py#L90-L121
tkf/rash
rash/index.py
index_run
def index_run(record_path, keep_json, check_duplicate): """ Convert raw JSON records into sqlite3 DB. Normally RASH launches a daemon that takes care of indexing. See ``rash daemon --help``. """ from .config import ConfigStore from .indexer import Indexer cfstore = ConfigStore() indexer = Indexer(cfstore, check_duplicate, keep_json, record_path) indexer.index_all()
python
def index_run(record_path, keep_json, check_duplicate): """ Convert raw JSON records into sqlite3 DB. Normally RASH launches a daemon that takes care of indexing. See ``rash daemon --help``. """ from .config import ConfigStore from .indexer import Indexer cfstore = ConfigStore() indexer = Indexer(cfstore, check_duplicate, keep_json, record_path) indexer.index_all()
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/index.py#L17-L29
pebble/libpebble2
libpebble2/services/data_logging.py
DataLoggingService.list
def list(self): """ List all available data logging sessions """ # We have to open this queue before we make the request, to ensure we don't miss the response. queue = self._pebble.get_endpoint_queue(DataLogging) self._pebble.send_packet(DataLogging(data=DataLoggingReportOpenSessions(sessions=[]))) sessions = [] while True: try: result = queue.get(timeout=2).data except TimeoutError: break if isinstance(result, DataLoggingDespoolOpenSession): self._pebble.send_packet(DataLogging(data=DataLoggingACK( session_id=result.session_id))) sessions.append(result.__dict__) queue.close() return sessions
python
def list(self): """ List all available data logging sessions """ # We have to open this queue before we make the request, to ensure we don't miss the response. queue = self._pebble.get_endpoint_queue(DataLogging) self._pebble.send_packet(DataLogging(data=DataLoggingReportOpenSessions(sessions=[]))) sessions = [] while True: try: result = queue.get(timeout=2).data except TimeoutError: break if isinstance(result, DataLoggingDespoolOpenSession): self._pebble.send_packet(DataLogging(data=DataLoggingACK( session_id=result.session_id))) sessions.append(result.__dict__) queue.close() return sessions
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train
https://github.com/pebble/libpebble2/blob/23e2eb92cfc084e6f9e8c718711ac994ef606d18/libpebble2/services/data_logging.py#L23-L45
pebble/libpebble2
libpebble2/services/data_logging.py
DataLoggingService.download
def download(self, session_id): """ Download a specific session. Returns (session_info, data) """ # We have to open this queue before we make the request, to ensure we don't miss the response. queue = self._pebble.get_endpoint_queue(DataLogging) # First, we need to open up all sessions self._pebble.send_packet(DataLogging(data=DataLoggingReportOpenSessions(sessions=[]))) session = None while True: try: result = queue.get(timeout=2).data except TimeoutError: break if isinstance(result, DataLoggingDespoolOpenSession): self._pebble.send_packet(DataLogging(data=DataLoggingACK( session_id=result.session_id))) if session is None and result.session_id == session_id: session = result if session is None: queue.close() return (None, None) # ----------------------------------------------------------------------------- # Request an empty of this session logger.info("Requesting empty of session {}".format(session_id)) self._pebble.send_packet(DataLogging(data=DataLoggingEmptySession(session_id=session_id))) data = None timeout_count = 0 while True: logger.debug("Looping again. Time: {}".format(datetime.datetime.now())) try: result = queue.get(timeout=5).data timeout_count = 0 except TimeoutError: logger.debug("Got timeout error Time: {}".format(datetime.datetime.now())) timeout_count += 1 if timeout_count >= 2: break else: self._pebble.send_packet(DataLogging(data=DataLoggingEmptySession( session_id=session_id))) continue if isinstance(result, DataLoggingDespoolSendData): if result.session_id != session_id: self._pebble.send_packet(DataLogging( data=DataLoggingNACK(session_id=result.session_id))) else: logger.info("Received {} bytes of data: {}".format(len(result.data), result)) if data is None: data = result.data else: data += result.data self._pebble.send_packet(DataLogging( data=DataLoggingACK(session_id=session_id))) queue.close() return (session, data)
python
def download(self, session_id): """ Download a specific session. Returns (session_info, data) """ # We have to open this queue before we make the request, to ensure we don't miss the response. queue = self._pebble.get_endpoint_queue(DataLogging) # First, we need to open up all sessions self._pebble.send_packet(DataLogging(data=DataLoggingReportOpenSessions(sessions=[]))) session = None while True: try: result = queue.get(timeout=2).data except TimeoutError: break if isinstance(result, DataLoggingDespoolOpenSession): self._pebble.send_packet(DataLogging(data=DataLoggingACK( session_id=result.session_id))) if session is None and result.session_id == session_id: session = result if session is None: queue.close() return (None, None) # ----------------------------------------------------------------------------- # Request an empty of this session logger.info("Requesting empty of session {}".format(session_id)) self._pebble.send_packet(DataLogging(data=DataLoggingEmptySession(session_id=session_id))) data = None timeout_count = 0 while True: logger.debug("Looping again. Time: {}".format(datetime.datetime.now())) try: result = queue.get(timeout=5).data timeout_count = 0 except TimeoutError: logger.debug("Got timeout error Time: {}".format(datetime.datetime.now())) timeout_count += 1 if timeout_count >= 2: break else: self._pebble.send_packet(DataLogging(data=DataLoggingEmptySession( session_id=session_id))) continue if isinstance(result, DataLoggingDespoolSendData): if result.session_id != session_id: self._pebble.send_packet(DataLogging( data=DataLoggingNACK(session_id=result.session_id))) else: logger.info("Received {} bytes of data: {}".format(len(result.data), result)) if data is None: data = result.data else: data += result.data self._pebble.send_packet(DataLogging( data=DataLoggingACK(session_id=session_id))) queue.close() return (session, data)
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train
https://github.com/pebble/libpebble2/blob/23e2eb92cfc084e6f9e8c718711ac994ef606d18/libpebble2/services/data_logging.py#L48-L113
pebble/libpebble2
libpebble2/services/data_logging.py
DataLoggingService.get_send_enable
def get_send_enable(self): """ Return true if sending of sessions is enabled on the watch """ # We have to open this queue before we make the request, to ensure we don't miss the response. queue = self._pebble.get_endpoint_queue(DataLogging) self._pebble.send_packet(DataLogging(data=DataLoggingGetSendEnableRequest())) enabled = False while True: result = queue.get().data if isinstance(result, DataLoggingGetSendEnableResponse): enabled = result.enabled break queue.close() return enabled
python
def get_send_enable(self): """ Return true if sending of sessions is enabled on the watch """ # We have to open this queue before we make the request, to ensure we don't miss the response. queue = self._pebble.get_endpoint_queue(DataLogging) self._pebble.send_packet(DataLogging(data=DataLoggingGetSendEnableRequest())) enabled = False while True: result = queue.get().data if isinstance(result, DataLoggingGetSendEnableResponse): enabled = result.enabled break queue.close() return enabled
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train
https://github.com/pebble/libpebble2/blob/23e2eb92cfc084e6f9e8c718711ac994ef606d18/libpebble2/services/data_logging.py#L116-L133
pebble/libpebble2
libpebble2/services/data_logging.py
DataLoggingService.set_send_enable
def set_send_enable(self, setting): """ Set the send enable setting on the watch """ self._pebble.send_packet(DataLogging(data=DataLoggingSetSendEnable(enabled=setting)))
python
def set_send_enable(self, setting): """ Set the send enable setting on the watch """ self._pebble.send_packet(DataLogging(data=DataLoggingSetSendEnable(enabled=setting)))
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train
https://github.com/pebble/libpebble2/blob/23e2eb92cfc084e6f9e8c718711ac994ef606d18/libpebble2/services/data_logging.py#L136-L140
tkf/rash
rash/log.py
loglevel
def loglevel(level): """ Convert any representation of `level` to an int appropriately. :type level: int or str :rtype: int >>> loglevel('DEBUG') == logging.DEBUG True >>> loglevel(10) 10 >>> loglevel(None) Traceback (most recent call last): ... ValueError: None is not a proper log level. """ if isinstance(level, str): level = getattr(logging, level.upper()) elif isinstance(level, int): pass else: raise ValueError('{0!r} is not a proper log level.'.format(level)) return level
python
def loglevel(level): """ Convert any representation of `level` to an int appropriately. :type level: int or str :rtype: int >>> loglevel('DEBUG') == logging.DEBUG True >>> loglevel(10) 10 >>> loglevel(None) Traceback (most recent call last): ... ValueError: None is not a proper log level. """ if isinstance(level, str): level = getattr(logging, level.upper()) elif isinstance(level, int): pass else: raise ValueError('{0!r} is not a proper log level.'.format(level)) return level
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Convert any representation of `level` to an int appropriately. :type level: int or str :rtype: int >>> loglevel('DEBUG') == logging.DEBUG True >>> loglevel(10) 10 >>> loglevel(None) Traceback (most recent call last): ... ValueError: None is not a proper log level.
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/log.py#L20-L43
tkf/rash
rash/log.py
setup_daemon_log_file
def setup_daemon_log_file(cfstore): """ Attach file handler to RASH logger. :type cfstore: rash.config.ConfigStore """ level = loglevel(cfstore.daemon_log_level) handler = logging.FileHandler(filename=cfstore.daemon_log_path) handler.setLevel(level) logger.setLevel(level) logger.addHandler(handler)
python
def setup_daemon_log_file(cfstore): """ Attach file handler to RASH logger. :type cfstore: rash.config.ConfigStore """ level = loglevel(cfstore.daemon_log_level) handler = logging.FileHandler(filename=cfstore.daemon_log_path) handler.setLevel(level) logger.setLevel(level) logger.addHandler(handler)
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Attach file handler to RASH logger. :type cfstore: rash.config.ConfigStore
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train
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/log.py#L49-L60
mathiasertl/xmpp-backends
xmpp_backends/xmlrpclib.py
dumps
def dumps(params, methodname=None, methodresponse=None, encoding=None, allow_none=0, utf8_encoding='standard'): """data [,options] -> marshalled data Convert an argument tuple or a Fault instance to an XML-RPC request (or response, if the methodresponse option is used). In addition to the data object, the following options can be given as keyword arguments: methodname: the method name for a methodCall packet methodresponse: true to create a methodResponse packet. If this option is used with a tuple, the tuple must be a singleton (i.e. it can contain only one element). encoding: the packet encoding (default is UTF-8) All 8-bit strings in the data structure are assumed to use the packet encoding. Unicode strings are automatically converted, where necessary. """ assert isinstance(params, TupleType) or isinstance(params, Fault),\ "argument must be tuple or Fault instance" if isinstance(params, Fault): methodresponse = 1 elif methodresponse and isinstance(params, TupleType): assert len(params) == 1, "response tuple must be a singleton" if not encoding: encoding = "utf-8" if FastMarshaller: m = FastMarshaller(encoding) else: m = Marshaller(encoding, allow_none) data = m.dumps(params) if encoding != "utf-8": xmlheader = "<?xml version='1.0' encoding='%s'?>\n" % str(encoding) else: xmlheader = "<?xml version='1.0'?>\n" # utf-8 is default # standard XML-RPC wrappings if methodname: # a method call if not isinstance(methodname, StringType): methodname = methodname.encode(encoding) data = ( xmlheader, "<methodCall>\n" "<methodName>", methodname, "</methodName>\n", data, "</methodCall>\n" ) elif methodresponse: # a method response, or a fault structure data = ( xmlheader, "<methodResponse>\n", data, "</methodResponse>\n" ) else: return data # return as is return string.join(data, "")
python
def dumps(params, methodname=None, methodresponse=None, encoding=None, allow_none=0, utf8_encoding='standard'): """data [,options] -> marshalled data Convert an argument tuple or a Fault instance to an XML-RPC request (or response, if the methodresponse option is used). In addition to the data object, the following options can be given as keyword arguments: methodname: the method name for a methodCall packet methodresponse: true to create a methodResponse packet. If this option is used with a tuple, the tuple must be a singleton (i.e. it can contain only one element). encoding: the packet encoding (default is UTF-8) All 8-bit strings in the data structure are assumed to use the packet encoding. Unicode strings are automatically converted, where necessary. """ assert isinstance(params, TupleType) or isinstance(params, Fault),\ "argument must be tuple or Fault instance" if isinstance(params, Fault): methodresponse = 1 elif methodresponse and isinstance(params, TupleType): assert len(params) == 1, "response tuple must be a singleton" if not encoding: encoding = "utf-8" if FastMarshaller: m = FastMarshaller(encoding) else: m = Marshaller(encoding, allow_none) data = m.dumps(params) if encoding != "utf-8": xmlheader = "<?xml version='1.0' encoding='%s'?>\n" % str(encoding) else: xmlheader = "<?xml version='1.0'?>\n" # utf-8 is default # standard XML-RPC wrappings if methodname: # a method call if not isinstance(methodname, StringType): methodname = methodname.encode(encoding) data = ( xmlheader, "<methodCall>\n" "<methodName>", methodname, "</methodName>\n", data, "</methodCall>\n" ) elif methodresponse: # a method response, or a fault structure data = ( xmlheader, "<methodResponse>\n", data, "</methodResponse>\n" ) else: return data # return as is return string.join(data, "")
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data [,options] -> marshalled data Convert an argument tuple or a Fault instance to an XML-RPC request (or response, if the methodresponse option is used). In addition to the data object, the following options can be given as keyword arguments: methodname: the method name for a methodCall packet methodresponse: true to create a methodResponse packet. If this option is used with a tuple, the tuple must be a singleton (i.e. it can contain only one element). encoding: the packet encoding (default is UTF-8) All 8-bit strings in the data structure are assumed to use the packet encoding. Unicode strings are automatically converted, where necessary.
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train
https://github.com/mathiasertl/xmpp-backends/blob/214ef0664dbf90fa300c2483b9b3416559e5d171/xmpp_backends/xmlrpclib.py#L1139-L1207
mathiasertl/xmpp-backends
xmpp_backends/xmlrpclib.py
gzip_encode
def gzip_encode(data): """data -> gzip encoded data Encode data using the gzip content encoding as described in RFC 1952 """ if not gzip: raise NotImplementedError f = StringIO.StringIO() gzf = gzip.GzipFile(mode="wb", fileobj=f, compresslevel=1) gzf.write(data) gzf.close() encoded = f.getvalue() f.close() return encoded
python
def gzip_encode(data): """data -> gzip encoded data Encode data using the gzip content encoding as described in RFC 1952 """ if not gzip: raise NotImplementedError f = StringIO.StringIO() gzf = gzip.GzipFile(mode="wb", fileobj=f, compresslevel=1) gzf.write(data) gzf.close() encoded = f.getvalue() f.close() return encoded
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data -> gzip encoded data Encode data using the gzip content encoding as described in RFC 1952
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train
https://github.com/mathiasertl/xmpp-backends/blob/214ef0664dbf90fa300c2483b9b3416559e5d171/xmpp_backends/xmlrpclib.py#L1240-L1253
mathiasertl/xmpp-backends
xmpp_backends/xmlrpclib.py
gzip_decode
def gzip_decode(data, max_decode=20971520): """gzip encoded data -> unencoded data Decode data using the gzip content encoding as described in RFC 1952 """ if not gzip: raise NotImplementedError f = StringIO.StringIO(data) gzf = gzip.GzipFile(mode="rb", fileobj=f) try: if max_decode < 0: # no limit decoded = gzf.read() else: decoded = gzf.read(max_decode + 1) except IOError: raise ValueError("invalid data") f.close() gzf.close() if max_decode >= 0 and len(decoded) > max_decode: raise ValueError("max gzipped payload length exceeded") return decoded
python
def gzip_decode(data, max_decode=20971520): """gzip encoded data -> unencoded data Decode data using the gzip content encoding as described in RFC 1952 """ if not gzip: raise NotImplementedError f = StringIO.StringIO(data) gzf = gzip.GzipFile(mode="rb", fileobj=f) try: if max_decode < 0: # no limit decoded = gzf.read() else: decoded = gzf.read(max_decode + 1) except IOError: raise ValueError("invalid data") f.close() gzf.close() if max_decode >= 0 and len(decoded) > max_decode: raise ValueError("max gzipped payload length exceeded") return decoded
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gzip encoded data -> unencoded data Decode data using the gzip content encoding as described in RFC 1952
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train
https://github.com/mathiasertl/xmpp-backends/blob/214ef0664dbf90fa300c2483b9b3416559e5d171/xmpp_backends/xmlrpclib.py#L1267-L1287
staticdev/django-sorting-bootstrap
sorting_bootstrap/templatetags/sorting_tags.py
result_headers
def result_headers(context, cl): """ Generates the list column headers. """ for i, field_name in enumerate(cl.list_display): text, attr = label_for_field(field_name, cl.model, return_attr=True) if attr: # Potentially not sortable # if the field is the action checkbox: no sorting and special class if field_name == 'action_checkbox': yield { "text": text, "class_attrib": mark_safe(' class="action-checkbox-column"'), "sortable": False, } continue # if other_fields like Edit, Visualize, etc: # Not sortable # yield { # "text": text, # "class_attrib": format_html(' class="column-{0}"', field_name), # "sortable": False, # } # continue # OK, it is sortable if we got this far th_classes = ['sortable', 'column-{0}'.format(field_name)] ascending = None is_sorted = False # Is it currently being sorted on? if context.get('current_sort_field') == str(i + 1): is_sorted = True ascending = False th_classes.append('sorted descending') elif context.get('current_sort_field') == '-'+str(i + 1): is_sorted = True ascending = True th_classes.append('sorted ascending') if 'request' in context: url = context['request'].path else: url = "./" ### TODO: when start using action_checkbox use i instead of i + 1. This +1 is to correct enumerate index # builds url url += "?sort_by=" if ascending is False: url += "-" url += str(i + 1) if 'getsortvars' in context: extra_vars = context['getsortvars'] else: if 'request' in context: request = context['request'] getvars = request.GET.copy() if 'sort_by' in getvars: del getvars['sort_by'] if len(getvars.keys()) > 0: context['getsortvars'] = "&%s" % getvars.urlencode() else: context['getsortvars'] = '' extra_vars = context['getsortvars'] # append other vars to url url += extra_vars yield { "text": text, "url": url, "sortable": True, "sorted": is_sorted, "ascending": ascending, "class_attrib": format_html(' class="{0}"', ' '.join(th_classes)) if th_classes else '', }
python
def result_headers(context, cl): """ Generates the list column headers. """ for i, field_name in enumerate(cl.list_display): text, attr = label_for_field(field_name, cl.model, return_attr=True) if attr: # Potentially not sortable # if the field is the action checkbox: no sorting and special class if field_name == 'action_checkbox': yield { "text": text, "class_attrib": mark_safe(' class="action-checkbox-column"'), "sortable": False, } continue # if other_fields like Edit, Visualize, etc: # Not sortable # yield { # "text": text, # "class_attrib": format_html(' class="column-{0}"', field_name), # "sortable": False, # } # continue # OK, it is sortable if we got this far th_classes = ['sortable', 'column-{0}'.format(field_name)] ascending = None is_sorted = False # Is it currently being sorted on? if context.get('current_sort_field') == str(i + 1): is_sorted = True ascending = False th_classes.append('sorted descending') elif context.get('current_sort_field') == '-'+str(i + 1): is_sorted = True ascending = True th_classes.append('sorted ascending') if 'request' in context: url = context['request'].path else: url = "./" ### TODO: when start using action_checkbox use i instead of i + 1. This +1 is to correct enumerate index # builds url url += "?sort_by=" if ascending is False: url += "-" url += str(i + 1) if 'getsortvars' in context: extra_vars = context['getsortvars'] else: if 'request' in context: request = context['request'] getvars = request.GET.copy() if 'sort_by' in getvars: del getvars['sort_by'] if len(getvars.keys()) > 0: context['getsortvars'] = "&%s" % getvars.urlencode() else: context['getsortvars'] = '' extra_vars = context['getsortvars'] # append other vars to url url += extra_vars yield { "text": text, "url": url, "sortable": True, "sorted": is_sorted, "ascending": ascending, "class_attrib": format_html(' class="{0}"', ' '.join(th_classes)) if th_classes else '', }
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Generates the list column headers.
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train
https://github.com/staticdev/django-sorting-bootstrap/blob/cfdc6e671b1b57aad04e44b041b9df10ee8288d3/sorting_bootstrap/templatetags/sorting_tags.py#L16-L94
staticdev/django-sorting-bootstrap
sorting_bootstrap/templatetags/sorting_tags.py
sort_headers
def sort_headers(context, cl): """ Displays the headers and data list together """ headers = list(result_headers(context, cl)) sorted_fields = False for h in headers: if h['sortable'] and h['sorted']: sorted_fields = True return {'cl': cl, 'result_headers': headers, 'sorted_fields': sorted_fields}
python
def sort_headers(context, cl): """ Displays the headers and data list together """ headers = list(result_headers(context, cl)) sorted_fields = False for h in headers: if h['sortable'] and h['sorted']: sorted_fields = True return {'cl': cl, 'result_headers': headers, 'sorted_fields': sorted_fields}
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Displays the headers and data list together
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train
https://github.com/staticdev/django-sorting-bootstrap/blob/cfdc6e671b1b57aad04e44b041b9df10ee8288d3/sorting_bootstrap/templatetags/sorting_tags.py#L98-L109
staticdev/django-sorting-bootstrap
sorting_bootstrap/templatetags/sorting_tags.py
sort_link
def sort_link(context, text, sort_field, visible_name=None): """Usage: {% sort_link "text" "field_name" %} Usage: {% sort_link "text" "field_name" "Visible name" %} """ sorted_fields = False ascending = None class_attrib = 'sortable' orig_sort_field = sort_field if context.get('current_sort_field') == sort_field: sort_field = '-%s' % sort_field visible_name = '-%s' % (visible_name or orig_sort_field) sorted_fields = True ascending = False class_attrib += ' sorted descending' elif context.get('current_sort_field') == '-'+sort_field: visible_name = '%s' % (visible_name or orig_sort_field) sorted_fields = True ascending = True class_attrib += ' sorted ascending' if visible_name: if 'request' in context: request = context['request'] request.session[visible_name] = sort_field # builds url if 'request' in context: url = context['request'].path else: url = "./" url += "?sort_by=" if visible_name is None: url += sort_field else: url += visible_name if 'getsortvars' in context: extra_vars = context['getsortvars'] else: if 'request' in context: request = context['request'] getvars = request.GET.copy() if 'sort_by' in getvars: del getvars['sort_by'] if len(getvars.keys()) > 0: context['getsortvars'] = "&%s" % getvars.urlencode() else: context['getsortvars'] = '' extra_vars = context['getsortvars'] # append other vars to url url += extra_vars return { 'text': text, 'url': url, 'ascending': ascending, 'sorted_fields': sorted_fields, 'class_attrib': class_attrib }
python
def sort_link(context, text, sort_field, visible_name=None): """Usage: {% sort_link "text" "field_name" %} Usage: {% sort_link "text" "field_name" "Visible name" %} """ sorted_fields = False ascending = None class_attrib = 'sortable' orig_sort_field = sort_field if context.get('current_sort_field') == sort_field: sort_field = '-%s' % sort_field visible_name = '-%s' % (visible_name or orig_sort_field) sorted_fields = True ascending = False class_attrib += ' sorted descending' elif context.get('current_sort_field') == '-'+sort_field: visible_name = '%s' % (visible_name or orig_sort_field) sorted_fields = True ascending = True class_attrib += ' sorted ascending' if visible_name: if 'request' in context: request = context['request'] request.session[visible_name] = sort_field # builds url if 'request' in context: url = context['request'].path else: url = "./" url += "?sort_by=" if visible_name is None: url += sort_field else: url += visible_name if 'getsortvars' in context: extra_vars = context['getsortvars'] else: if 'request' in context: request = context['request'] getvars = request.GET.copy() if 'sort_by' in getvars: del getvars['sort_by'] if len(getvars.keys()) > 0: context['getsortvars'] = "&%s" % getvars.urlencode() else: context['getsortvars'] = '' extra_vars = context['getsortvars'] # append other vars to url url += extra_vars return { 'text': text, 'url': url, 'ascending': ascending, 'sorted_fields': sorted_fields, 'class_attrib': class_attrib }
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Usage: {% sort_link "text" "field_name" %} Usage: {% sort_link "text" "field_name" "Visible name" %}
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train
https://github.com/staticdev/django-sorting-bootstrap/blob/cfdc6e671b1b57aad04e44b041b9df10ee8288d3/sorting_bootstrap/templatetags/sorting_tags.py#L112-L168
staticdev/django-sorting-bootstrap
sorting_bootstrap/templatetags/sorting_tags.py
auto_sort
def auto_sort(parser, token): "usage: {% auto_sort queryset %}" try: tag_name, queryset = token.split_contents() except ValueError: raise template.TemplateSyntaxError("{0} tag requires a single argument".format(token.contents.split()[0])) return SortedQuerysetNode(queryset)
python
def auto_sort(parser, token): "usage: {% auto_sort queryset %}" try: tag_name, queryset = token.split_contents() except ValueError: raise template.TemplateSyntaxError("{0} tag requires a single argument".format(token.contents.split()[0])) return SortedQuerysetNode(queryset)
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usage: {% auto_sort queryset %}
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train
https://github.com/staticdev/django-sorting-bootstrap/blob/cfdc6e671b1b57aad04e44b041b9df10ee8288d3/sorting_bootstrap/templatetags/sorting_tags.py#L175-L181
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/message.py
Tag.from_str
def from_str(cls, tagstring): """Create a tag by parsing the tag of a message :param tagstring: A tag string described in the irc protocol :type tagstring: :class:`str` :returns: A tag :rtype: :class:`Tag` :raises: None """ m = cls._parse_regexp.match(tagstring) return cls(name=m.group('name'), value=m.group('value'), vendor=m.group('vendor'))
python
def from_str(cls, tagstring): """Create a tag by parsing the tag of a message :param tagstring: A tag string described in the irc protocol :type tagstring: :class:`str` :returns: A tag :rtype: :class:`Tag` :raises: None """ m = cls._parse_regexp.match(tagstring) return cls(name=m.group('name'), value=m.group('value'), vendor=m.group('vendor'))
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Create a tag by parsing the tag of a message :param tagstring: A tag string described in the irc protocol :type tagstring: :class:`str` :returns: A tag :rtype: :class:`Tag` :raises: None
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/chat/message.py#L61-L71
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/message.py
Emote.from_str
def from_str(cls, emotestr): """Create an emote from the emote tag key :param emotestr: the tag key, e.g. ``'123:0-4'`` :type emotestr: :class:`str` :returns: an emote :rtype: :class:`Emote` :raises: None """ emoteid, occstr = emotestr.split(':') occurences = [] for occ in occstr.split(','): start, end = occ.split('-') occurences.append((int(start), int(end))) return cls(int(emoteid), occurences)
python
def from_str(cls, emotestr): """Create an emote from the emote tag key :param emotestr: the tag key, e.g. ``'123:0-4'`` :type emotestr: :class:`str` :returns: an emote :rtype: :class:`Emote` :raises: None """ emoteid, occstr = emotestr.split(':') occurences = [] for occ in occstr.split(','): start, end = occ.split('-') occurences.append((int(start), int(end))) return cls(int(emoteid), occurences)
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Create an emote from the emote tag key :param emotestr: the tag key, e.g. ``'123:0-4'`` :type emotestr: :class:`str` :returns: an emote :rtype: :class:`Emote` :raises: None
[ "Create", "an", "emote", "from", "the", "emote", "tag", "key" ]
train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/chat/message.py#L113-L127
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/message.py
Message3.from_event
def from_event(cls, event): """Create a message from an event :param event: the event that was received of type ``pubmsg`` or ``privmsg`` :type event: :class:`Event3` :returns: a message that resembles the event :rtype: :class:`Message3` :raises: None """ source = Chatter(event.source) return cls(source, event.target, event.arguments[0], event.tags)
python
def from_event(cls, event): """Create a message from an event :param event: the event that was received of type ``pubmsg`` or ``privmsg`` :type event: :class:`Event3` :returns: a message that resembles the event :rtype: :class:`Message3` :raises: None """ source = Chatter(event.source) return cls(source, event.target, event.arguments[0], event.tags)
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Create a message from an event :param event: the event that was received of type ``pubmsg`` or ``privmsg`` :type event: :class:`Event3` :returns: a message that resembles the event :rtype: :class:`Message3` :raises: None
[ "Create", "a", "message", "from", "an", "event" ]
train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/chat/message.py#L265-L275
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/message.py
Message3.set_tags
def set_tags(self, tags): """For every known tag, set the appropriate attribute. Known tags are: :color: The user color :emotes: A list of emotes :subscriber: True, if subscriber :turbo: True, if turbo user :user_type: None, mod, staff, global_mod, admin :param tags: a list of tags :type tags: :class:`list` of :class:`Tag` | None :returns: None :rtype: None :raises: None """ if tags is None: return attrmap = {'color': 'color', 'emotes': 'emotes', 'subscriber': 'subscriber', 'turbo': 'turbo', 'user-type': 'user_type'} for t in tags: attr = attrmap.get(t.name) if not attr: continue else: setattr(self, attr, t.value)
python
def set_tags(self, tags): """For every known tag, set the appropriate attribute. Known tags are: :color: The user color :emotes: A list of emotes :subscriber: True, if subscriber :turbo: True, if turbo user :user_type: None, mod, staff, global_mod, admin :param tags: a list of tags :type tags: :class:`list` of :class:`Tag` | None :returns: None :rtype: None :raises: None """ if tags is None: return attrmap = {'color': 'color', 'emotes': 'emotes', 'subscriber': 'subscriber', 'turbo': 'turbo', 'user-type': 'user_type'} for t in tags: attr = attrmap.get(t.name) if not attr: continue else: setattr(self, attr, t.value)
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For every known tag, set the appropriate attribute. Known tags are: :color: The user color :emotes: A list of emotes :subscriber: True, if subscriber :turbo: True, if turbo user :user_type: None, mod, staff, global_mod, admin :param tags: a list of tags :type tags: :class:`list` of :class:`Tag` | None :returns: None :rtype: None :raises: None
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train
https://github.com/Pytwitcher/pytwitcherapi/blob/d53ac5ad5ca113ecb7da542e8cdcbbf8c762b336/src/pytwitcherapi/chat/message.py#L292-L319
Pytwitcher/pytwitcherapi
src/pytwitcherapi/chat/message.py
Message3.emotes
def emotes(self, emotes): """Set the emotes :param emotes: the key of the emotes tag :type emotes: :class:`str` :returns: None :rtype: None :raises: None """ if emotes is None: self._emotes = [] return es = [] for estr in emotes.split('/'): es.append(Emote.from_str(estr)) self._emotes = es
python
def emotes(self, emotes): """Set the emotes :param emotes: the key of the emotes tag :type emotes: :class:`str` :returns: None :rtype: None :raises: None """ if emotes is None: self._emotes = [] return es = [] for estr in emotes.split('/'): es.append(Emote.from_str(estr)) self._emotes = es
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Set the emotes :param emotes: the key of the emotes tag :type emotes: :class:`str` :returns: None :rtype: None :raises: None
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avalente/appmetrics
appmetrics/statistics.py
sum
def sum(data, start=0): """sum(data [, start]) -> value Return a high-precision sum of the given numeric data. If optional argument ``start`` is given, it is added to the total. If ``data`` is empty, ``start`` (defaulting to 0) is returned. """ n, d = exact_ratio(start) T = type(start) partials = {d: n} # map {denominator: sum of numerators} # Micro-optimizations. coerce_types_ = coerce_types exact_ratio_ = exact_ratio partials_get = partials.get # Add numerators for each denominator, and track the "current" type. for x in data: T = coerce_types_(T, type(x)) n, d = exact_ratio_(x) partials[d] = partials_get(d, 0) + n if None in partials: assert issubclass(T, (float, Decimal)) assert not isfinite(partials[None]) return T(partials[None]) total = Fraction() for d, n in sorted(partials.items()): total += Fraction(n, d) if issubclass(T, int): assert total.denominator == 1 return T(total.numerator) if issubclass(T, Decimal): return T(total.numerator) / total.denominator return T(total)
python
def sum(data, start=0): """sum(data [, start]) -> value Return a high-precision sum of the given numeric data. If optional argument ``start`` is given, it is added to the total. If ``data`` is empty, ``start`` (defaulting to 0) is returned. """ n, d = exact_ratio(start) T = type(start) partials = {d: n} # map {denominator: sum of numerators} # Micro-optimizations. coerce_types_ = coerce_types exact_ratio_ = exact_ratio partials_get = partials.get # Add numerators for each denominator, and track the "current" type. for x in data: T = coerce_types_(T, type(x)) n, d = exact_ratio_(x) partials[d] = partials_get(d, 0) + n if None in partials: assert issubclass(T, (float, Decimal)) assert not isfinite(partials[None]) return T(partials[None]) total = Fraction() for d, n in sorted(partials.items()): total += Fraction(n, d) if issubclass(T, int): assert total.denominator == 1 return T(total.numerator) if issubclass(T, Decimal): return T(total.numerator) / total.denominator return T(total)
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sum(data [, start]) -> value Return a high-precision sum of the given numeric data. If optional argument ``start`` is given, it is added to the total. If ``data`` is empty, ``start`` (defaulting to 0) is returned.
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avalente/appmetrics
appmetrics/statistics.py
exact_ratio
def exact_ratio(x): """Convert Real number x exactly to (numerator, denominator) pair. x is expected to be an int, Fraction, Decimal or float. """ try: try: # int, Fraction return x.numerator, x.denominator except AttributeError: # float try: return x.as_integer_ratio() except AttributeError: # Decimal try: return decimal_to_ratio(x) except AttributeError: msg = "can't convert type '{}' to numerator/denominator" raise TypeError(msg.format(type(x).__name__)) except (OverflowError, ValueError): # INF or NAN return (x, None)
python
def exact_ratio(x): """Convert Real number x exactly to (numerator, denominator) pair. x is expected to be an int, Fraction, Decimal or float. """ try: try: # int, Fraction return x.numerator, x.denominator except AttributeError: # float try: return x.as_integer_ratio() except AttributeError: # Decimal try: return decimal_to_ratio(x) except AttributeError: msg = "can't convert type '{}' to numerator/denominator" raise TypeError(msg.format(type(x).__name__)) except (OverflowError, ValueError): # INF or NAN return (x, None)
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avalente/appmetrics
appmetrics/statistics.py
decimal_to_ratio
def decimal_to_ratio(d): """Convert Decimal d to exact integer ratio (numerator, denominator). """ sign, digits, exp = d.as_tuple() if exp in ('F', 'n', 'N'): # INF, NAN, sNAN assert not d.is_finite() raise ValueError num = 0 for digit in digits: num = num * 10 + digit if sign: num = -num den = 10 ** -exp return (num, den)
python
def decimal_to_ratio(d): """Convert Decimal d to exact integer ratio (numerator, denominator). """ sign, digits, exp = d.as_tuple() if exp in ('F', 'n', 'N'): # INF, NAN, sNAN assert not d.is_finite() raise ValueError num = 0 for digit in digits: num = num * 10 + digit if sign: num = -num den = 10 ** -exp return (num, den)
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avalente/appmetrics
appmetrics/statistics.py
coerce_types
def coerce_types(T1, T2): """Coerce types T1 and T2 to a common type. Coercion is performed according to this table, where "N/A" means that a TypeError exception is raised. +----------+-----------+-----------+-----------+----------+ | | int | Fraction | Decimal | float | +----------+-----------+-----------+-----------+----------+ | int | int | Fraction | Decimal | float | | Fraction | Fraction | Fraction | N/A | float | | Decimal | Decimal | N/A | Decimal | float | | float | float | float | float | float | +----------+-----------+-----------+-----------+----------+ Subclasses trump their parent class; two subclasses of the same base class will be coerced to the second of the two. """ # Get the common/fast cases out of the way first. if T1 is T2: return T1 if T1 is int: return T2 if T2 is int: return T1 # Subclasses trump their parent class. if issubclass(T2, T1): return T2 if issubclass(T1, T2): return T1 # Floats trump everything else. if issubclass(T2, float): return T2 if issubclass(T1, float): return T1 # Subclasses of the same base class give priority to the second. if T1.__base__ is T2.__base__: return T2 # Otherwise, just give up. raise TypeError('cannot coerce types %r and %r' % (T1, T2))
python
def coerce_types(T1, T2): """Coerce types T1 and T2 to a common type. Coercion is performed according to this table, where "N/A" means that a TypeError exception is raised. +----------+-----------+-----------+-----------+----------+ | | int | Fraction | Decimal | float | +----------+-----------+-----------+-----------+----------+ | int | int | Fraction | Decimal | float | | Fraction | Fraction | Fraction | N/A | float | | Decimal | Decimal | N/A | Decimal | float | | float | float | float | float | float | +----------+-----------+-----------+-----------+----------+ Subclasses trump their parent class; two subclasses of the same base class will be coerced to the second of the two. """ # Get the common/fast cases out of the way first. if T1 is T2: return T1 if T1 is int: return T2 if T2 is int: return T1 # Subclasses trump their parent class. if issubclass(T2, T1): return T2 if issubclass(T1, T2): return T1 # Floats trump everything else. if issubclass(T2, float): return T2 if issubclass(T1, float): return T1 # Subclasses of the same base class give priority to the second. if T1.__base__ is T2.__base__: return T2 # Otherwise, just give up. raise TypeError('cannot coerce types %r and %r' % (T1, T2))
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avalente/appmetrics
appmetrics/statistics.py
counts
def counts(data): """ Generate a table of sorted (value, frequency) pairs. """ if data is None: raise TypeError('None is not iterable') table = collections.Counter(data).most_common() if not table: return table # Extract the values with the highest frequency. maxfreq = table[0][1] for i in range(1, len(table)): if table[i][1] != maxfreq: table = table[:i] break return table
python
def counts(data): """ Generate a table of sorted (value, frequency) pairs. """ if data is None: raise TypeError('None is not iterable') table = collections.Counter(data).most_common() if not table: return table # Extract the values with the highest frequency. maxfreq = table[0][1] for i in range(1, len(table)): if table[i][1] != maxfreq: table = table[:i] break return table
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avalente/appmetrics
appmetrics/statistics.py
mean
def mean(data): """Return the sample arithmetic mean of data. If ``data`` is empty, StatisticsError will be raised. """ if iter(data) is data: data = list(data) n = len(data) if n < 1: raise StatisticsError('mean requires at least one data point') return sum(data) / n
python
def mean(data): """Return the sample arithmetic mean of data. If ``data`` is empty, StatisticsError will be raised. """ if iter(data) is data: data = list(data) n = len(data) if n < 1: raise StatisticsError('mean requires at least one data point') return sum(data) / n
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avalente/appmetrics
appmetrics/statistics.py
median
def median(data): """Return the median (middle value) of numeric data. When the number of data points is odd, return the middle data point. When the number of data points is even, the median is interpolated by taking the average of the two middle values: """ data = sorted(data) n = len(data) if n == 0: raise StatisticsError("no median for empty data") if n % 2 == 1: return data[n // 2] else: i = n // 2 return (data[i - 1] + data[i]) / 2
python
def median(data): """Return the median (middle value) of numeric data. When the number of data points is odd, return the middle data point. When the number of data points is even, the median is interpolated by taking the average of the two middle values: """ data = sorted(data) n = len(data) if n == 0: raise StatisticsError("no median for empty data") if n % 2 == 1: return data[n // 2] else: i = n // 2 return (data[i - 1] + data[i]) / 2
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avalente/appmetrics
appmetrics/statistics.py
median_low
def median_low(data): """Return the low median of numeric data. When the number of data points is odd, the middle value is returned. When it is even, the smaller of the two middle values is returned. """ data = sorted(data) n = len(data) if n == 0: raise StatisticsError("no median for empty data") if n % 2 == 1: return data[n // 2] else: return data[n // 2 - 1]
python
def median_low(data): """Return the low median of numeric data. When the number of data points is odd, the middle value is returned. When it is even, the smaller of the two middle values is returned. """ data = sorted(data) n = len(data) if n == 0: raise StatisticsError("no median for empty data") if n % 2 == 1: return data[n // 2] else: return data[n // 2 - 1]
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avalente/appmetrics
appmetrics/statistics.py
median_high
def median_high(data): """Return the high median of data. When the number of data points is odd, the middle value is returned. When it is even, the larger of the two middle values is returned. """ data = sorted(data) n = len(data) if n == 0: raise StatisticsError("no median for empty data") return data[n // 2]
python
def median_high(data): """Return the high median of data. When the number of data points is odd, the middle value is returned. When it is even, the larger of the two middle values is returned. """ data = sorted(data) n = len(data) if n == 0: raise StatisticsError("no median for empty data") return data[n // 2]
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avalente/appmetrics
appmetrics/statistics.py
mode
def mode(data): """Return the most common data point from discrete or nominal data. ``mode`` assumes discrete data, and returns a single value. This is the standard treatment of the mode as commonly taught in schools: If there is not exactly one most common value, ``mode`` will raise StatisticsError. """ # Generate a table of sorted (value, frequency) pairs. table = counts(data) if len(table) == 1: return table[0][0] elif table: raise StatisticsError( 'no unique mode; found %d equally common values' % len(table) ) else: raise StatisticsError('no mode for empty data')
python
def mode(data): """Return the most common data point from discrete or nominal data. ``mode`` assumes discrete data, and returns a single value. This is the standard treatment of the mode as commonly taught in schools: If there is not exactly one most common value, ``mode`` will raise StatisticsError. """ # Generate a table of sorted (value, frequency) pairs. table = counts(data) if len(table) == 1: return table[0][0] elif table: raise StatisticsError( 'no unique mode; found %d equally common values' % len(table) ) else: raise StatisticsError('no mode for empty data')
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avalente/appmetrics
appmetrics/statistics.py
_ss
def _ss(data, c=None): """Return sum of square deviations of sequence data. If ``c`` is None, the mean is calculated in one pass, and the deviations from the mean are calculated in a second pass. Otherwise, deviations are calculated from ``c`` as given. Use the second case with care, as it can lead to garbage results. """ if c is None: c = mean(data) ss = sum((x - c) ** 2 for x in data) # The following sum should mathematically equal zero, but due to rounding # error may not. ss -= sum((x - c) for x in data) ** 2 / len(data) assert not ss < 0, 'negative sum of square deviations: %f' % ss return ss
python
def _ss(data, c=None): """Return sum of square deviations of sequence data. If ``c`` is None, the mean is calculated in one pass, and the deviations from the mean are calculated in a second pass. Otherwise, deviations are calculated from ``c`` as given. Use the second case with care, as it can lead to garbage results. """ if c is None: c = mean(data) ss = sum((x - c) ** 2 for x in data) # The following sum should mathematically equal zero, but due to rounding # error may not. ss -= sum((x - c) for x in data) ** 2 / len(data) assert not ss < 0, 'negative sum of square deviations: %f' % ss return ss
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avalente/appmetrics
appmetrics/statistics.py
variance
def variance(data, xbar=None): """Return the sample variance of data. data should be an iterable of Real-valued numbers, with at least two values. The optional argument xbar, if given, should be the mean of the data. If it is missing or None, the mean is automatically calculated. Use this function when your data is a sample from a population. To calculate the variance from the entire population, see ``pvariance``. If you have already calculated the mean of your data, you can pass it as the optional second argument ``xbar`` to avoid recalculating it: This function does not check that ``xbar`` is actually the mean of ``data``. Giving arbitrary values for ``xbar`` may lead to invalid or impossible results. Decimals and Fractions are supported """ if iter(data) is data: data = list(data) n = len(data) if n < 2: raise StatisticsError('variance requires at least two data points') ss = _ss(data, xbar) return ss / (n - 1)
python
def variance(data, xbar=None): """Return the sample variance of data. data should be an iterable of Real-valued numbers, with at least two values. The optional argument xbar, if given, should be the mean of the data. If it is missing or None, the mean is automatically calculated. Use this function when your data is a sample from a population. To calculate the variance from the entire population, see ``pvariance``. If you have already calculated the mean of your data, you can pass it as the optional second argument ``xbar`` to avoid recalculating it: This function does not check that ``xbar`` is actually the mean of ``data``. Giving arbitrary values for ``xbar`` may lead to invalid or impossible results. Decimals and Fractions are supported """ if iter(data) is data: data = list(data) n = len(data) if n < 2: raise StatisticsError('variance requires at least two data points') ss = _ss(data, xbar) return ss / (n - 1)
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avalente/appmetrics
appmetrics/statistics.py
pvariance
def pvariance(data, mu=None): """Return the population variance of ``data``. data should be an iterable of Real-valued numbers, with at least one value. The optional argument mu, if given, should be the mean of the data. If it is missing or None, the mean is automatically calculated. Use this function to calculate the variance from the entire population. To estimate the variance from a sample, the ``variance`` function is usually a better choice. If you have already calculated the mean of the data, you can pass it as the optional second argument to avoid recalculating it: This function does not check that ``mu`` is actually the mean of ``data``. Giving arbitrary values for ``mu`` may lead to invalid or impossible results. Decimals and Fractions are supported: """ if iter(data) is data: data = list(data) n = len(data) if n < 1: raise StatisticsError('pvariance requires at least one data point') ss = _ss(data, mu) return ss / n
python
def pvariance(data, mu=None): """Return the population variance of ``data``. data should be an iterable of Real-valued numbers, with at least one value. The optional argument mu, if given, should be the mean of the data. If it is missing or None, the mean is automatically calculated. Use this function to calculate the variance from the entire population. To estimate the variance from a sample, the ``variance`` function is usually a better choice. If you have already calculated the mean of the data, you can pass it as the optional second argument to avoid recalculating it: This function does not check that ``mu`` is actually the mean of ``data``. Giving arbitrary values for ``mu`` may lead to invalid or impossible results. Decimals and Fractions are supported: """ if iter(data) is data: data = list(data) n = len(data) if n < 1: raise StatisticsError('pvariance requires at least one data point') ss = _ss(data, mu) return ss / n
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Return the population variance of ``data``. data should be an iterable of Real-valued numbers, with at least one value. The optional argument mu, if given, should be the mean of the data. If it is missing or None, the mean is automatically calculated. Use this function to calculate the variance from the entire population. To estimate the variance from a sample, the ``variance`` function is usually a better choice. If you have already calculated the mean of the data, you can pass it as the optional second argument to avoid recalculating it: This function does not check that ``mu`` is actually the mean of ``data``. Giving arbitrary values for ``mu`` may lead to invalid or impossible results. Decimals and Fractions are supported:
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train
https://github.com/avalente/appmetrics/blob/366fc7e1ca897e49a2227cbfa43bfa02a47f1acc/appmetrics/statistics.py#L324-L353
avalente/appmetrics
appmetrics/statistics.py
stdev
def stdev(data, xbar=None): """Return the square root of the sample variance. See ``variance`` for arguments and other details. """ var = variance(data, xbar) try: return var.sqrt() except AttributeError: return math.sqrt(var)
python
def stdev(data, xbar=None): """Return the square root of the sample variance. See ``variance`` for arguments and other details. """ var = variance(data, xbar) try: return var.sqrt() except AttributeError: return math.sqrt(var)
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Return the square root of the sample variance. See ``variance`` for arguments and other details.
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train
https://github.com/avalente/appmetrics/blob/366fc7e1ca897e49a2227cbfa43bfa02a47f1acc/appmetrics/statistics.py#L356-L366