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iterative/dvc
dvc/analytics.py
Analytics.load
def load(path): """Loads analytics report from json file specified by path. Args: path (str): path to json file with analytics report. """ with open(path, "r") as fobj: analytics = Analytics(info=json.load(fobj)) os.unlink(path) return analytics
python
def load(path): """Loads analytics report from json file specified by path. Args: path (str): path to json file with analytics report. """ with open(path, "r") as fobj: analytics = Analytics(info=json.load(fobj)) os.unlink(path) return analytics
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Loads analytics report from json file specified by path. Args: path (str): path to json file with analytics report.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/analytics.py#L72-L81
train
iterative/dvc
dvc/analytics.py
Analytics.collect
def collect(self): """Collect analytics report.""" from dvc.scm import SCM from dvc.utils import is_binary from dvc.repo import Repo from dvc.exceptions import NotDvcRepoError self.info[self.PARAM_DVC_VERSION] = __version__ self.info[self.PARAM_IS_BINARY] = is_binary() self.info[self.PARAM_USER_ID] = self._get_user_id() self.info[self.PARAM_SYSTEM_INFO] = self._collect_system_info() try: scm = SCM(root_dir=Repo.find_root()) self.info[self.PARAM_SCM_CLASS] = type(scm).__name__ except NotDvcRepoError: pass
python
def collect(self): """Collect analytics report.""" from dvc.scm import SCM from dvc.utils import is_binary from dvc.repo import Repo from dvc.exceptions import NotDvcRepoError self.info[self.PARAM_DVC_VERSION] = __version__ self.info[self.PARAM_IS_BINARY] = is_binary() self.info[self.PARAM_USER_ID] = self._get_user_id() self.info[self.PARAM_SYSTEM_INFO] = self._collect_system_info() try: scm = SCM(root_dir=Repo.find_root()) self.info[self.PARAM_SCM_CLASS] = type(scm).__name__ except NotDvcRepoError: pass
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Collect analytics report.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/analytics.py#L164-L181
train
iterative/dvc
dvc/analytics.py
Analytics.collect_cmd
def collect_cmd(self, args, ret): """Collect analytics info from a CLI command.""" from dvc.command.daemon import CmdDaemonAnalytics assert isinstance(ret, int) or ret is None if ret is not None: self.info[self.PARAM_CMD_RETURN_CODE] = ret if args is not None and hasattr(args, "func"): assert args.func != CmdDaemonAnalytics self.info[self.PARAM_CMD_CLASS] = args.func.__name__
python
def collect_cmd(self, args, ret): """Collect analytics info from a CLI command.""" from dvc.command.daemon import CmdDaemonAnalytics assert isinstance(ret, int) or ret is None if ret is not None: self.info[self.PARAM_CMD_RETURN_CODE] = ret if args is not None and hasattr(args, "func"): assert args.func != CmdDaemonAnalytics self.info[self.PARAM_CMD_CLASS] = args.func.__name__
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Collect analytics info from a CLI command.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/analytics.py#L183-L194
train
iterative/dvc
dvc/analytics.py
Analytics.dump
def dump(self): """Save analytics report to a temporary file. Returns: str: path to the temporary file that contains the analytics report. """ import tempfile with tempfile.NamedTemporaryFile(delete=False, mode="w") as fobj: json.dump(self.info, fobj) return fobj.name
python
def dump(self): """Save analytics report to a temporary file. Returns: str: path to the temporary file that contains the analytics report. """ import tempfile with tempfile.NamedTemporaryFile(delete=False, mode="w") as fobj: json.dump(self.info, fobj) return fobj.name
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Save analytics report to a temporary file. Returns: str: path to the temporary file that contains the analytics report.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/analytics.py#L196-L206
train
iterative/dvc
dvc/analytics.py
Analytics.send_cmd
def send_cmd(cmd, args, ret): """Collect and send analytics for CLI command. Args: args (list): parsed args for the CLI command. ret (int): return value of the CLI command. """ from dvc.daemon import daemon if not Analytics._is_enabled(cmd): return analytics = Analytics() analytics.collect_cmd(args, ret) daemon(["analytics", analytics.dump()])
python
def send_cmd(cmd, args, ret): """Collect and send analytics for CLI command. Args: args (list): parsed args for the CLI command. ret (int): return value of the CLI command. """ from dvc.daemon import daemon if not Analytics._is_enabled(cmd): return analytics = Analytics() analytics.collect_cmd(args, ret) daemon(["analytics", analytics.dump()])
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Collect and send analytics for CLI command. Args: args (list): parsed args for the CLI command. ret (int): return value of the CLI command.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/analytics.py#L247-L261
train
iterative/dvc
dvc/analytics.py
Analytics.send
def send(self): """Collect and send analytics.""" import requests if not self._is_enabled(): return self.collect() logger.debug("Sending analytics: {}".format(self.info)) try: requests.post(self.URL, json=self.info, timeout=self.TIMEOUT_POST) except requests.exceptions.RequestException as exc: logger.debug("Failed to send analytics: {}".format(str(exc)))
python
def send(self): """Collect and send analytics.""" import requests if not self._is_enabled(): return self.collect() logger.debug("Sending analytics: {}".format(self.info)) try: requests.post(self.URL, json=self.info, timeout=self.TIMEOUT_POST) except requests.exceptions.RequestException as exc: logger.debug("Failed to send analytics: {}".format(str(exc)))
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Collect and send analytics.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/analytics.py#L263-L277
train
iterative/dvc
dvc/scm/git/tree.py
GitTree.walk
def walk(self, top, topdown=True, ignore_file_handler=None): """Directory tree generator. See `os.walk` for the docs. Differences: - no support for symlinks - it could raise exceptions, there is no onerror argument """ tree = self.git_object_by_path(top) if tree is None: raise IOError(errno.ENOENT, "No such file") for x in self._walk(tree, topdown): yield x
python
def walk(self, top, topdown=True, ignore_file_handler=None): """Directory tree generator. See `os.walk` for the docs. Differences: - no support for symlinks - it could raise exceptions, there is no onerror argument """ tree = self.git_object_by_path(top) if tree is None: raise IOError(errno.ENOENT, "No such file") for x in self._walk(tree, topdown): yield x
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Directory tree generator. See `os.walk` for the docs. Differences: - no support for symlinks - it could raise exceptions, there is no onerror argument
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/scm/git/tree.py#L126-L139
train
iterative/dvc
dvc/data_cloud.py
DataCloud.push
def push(self, targets, jobs=None, remote=None, show_checksums=False): """Push data items in a cloud-agnostic way. Args: targets (list): list of targets to push to the cloud. jobs (int): number of jobs that can be running simultaneously. remote (dvc.remote.base.RemoteBase): optional remote to push to. By default remote from core.remote config option is used. show_checksums (bool): show checksums instead of file names in information messages. """ return self.repo.cache.local.push( targets, jobs=jobs, remote=self._get_cloud(remote, "push"), show_checksums=show_checksums, )
python
def push(self, targets, jobs=None, remote=None, show_checksums=False): """Push data items in a cloud-agnostic way. Args: targets (list): list of targets to push to the cloud. jobs (int): number of jobs that can be running simultaneously. remote (dvc.remote.base.RemoteBase): optional remote to push to. By default remote from core.remote config option is used. show_checksums (bool): show checksums instead of file names in information messages. """ return self.repo.cache.local.push( targets, jobs=jobs, remote=self._get_cloud(remote, "push"), show_checksums=show_checksums, )
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Push data items in a cloud-agnostic way. Args: targets (list): list of targets to push to the cloud. jobs (int): number of jobs that can be running simultaneously. remote (dvc.remote.base.RemoteBase): optional remote to push to. By default remote from core.remote config option is used. show_checksums (bool): show checksums instead of file names in information messages.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/data_cloud.py#L117-L133
train
iterative/dvc
dvc/data_cloud.py
DataCloud.status
def status(self, targets, jobs=None, remote=None, show_checksums=False): """Check status of data items in a cloud-agnostic way. Args: targets (list): list of targets to check status for. jobs (int): number of jobs that can be running simultaneously. remote (dvc.remote.base.RemoteBase): optional remote to compare targets to. By default remote from core.remote config option is used. show_checksums (bool): show checksums instead of file names in information messages. """ cloud = self._get_cloud(remote, "status") return self.repo.cache.local.status( targets, jobs=jobs, remote=cloud, show_checksums=show_checksums )
python
def status(self, targets, jobs=None, remote=None, show_checksums=False): """Check status of data items in a cloud-agnostic way. Args: targets (list): list of targets to check status for. jobs (int): number of jobs that can be running simultaneously. remote (dvc.remote.base.RemoteBase): optional remote to compare targets to. By default remote from core.remote config option is used. show_checksums (bool): show checksums instead of file names in information messages. """ cloud = self._get_cloud(remote, "status") return self.repo.cache.local.status( targets, jobs=jobs, remote=cloud, show_checksums=show_checksums )
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/data_cloud.py#L153-L168
train
iterative/dvc
dvc/repo/brancher.py
brancher
def brancher( # noqa: E302 self, branches=None, all_branches=False, tags=None, all_tags=False ): """Generator that iterates over specified revisions. Args: branches (list): a list of branches to iterate over. all_branches (bool): iterate over all available branches. tags (list): a list of tags to iterate over. all_tags (bool): iterate over all available tags. Yields: str: the display name for the currently selected tree, it could be: - a git revision identifier - empty string it there is no branches to iterate over - "Working Tree" if there are uncommited changes in the SCM repo """ if not any([branches, all_branches, tags, all_tags]): yield "" return saved_tree = self.tree revs = [] scm = self.scm if self.scm.is_dirty(): from dvc.scm.tree import WorkingTree self.tree = WorkingTree(self.root_dir) yield "Working Tree" if all_branches: branches = scm.list_branches() if all_tags: tags = scm.list_tags() if branches is None: revs.extend([scm.active_branch()]) else: revs.extend(branches) if tags is not None: revs.extend(tags) # NOTE: it might be a good idea to wrap this loop in try/finally block # to don't leave the tree on some unexpected branch after the # `brancher()`, but this could cause problems on exception handling # code which might expect the tree on which exception was raised to # stay in place. This behavior is a subject to change. for rev in revs: self.tree = scm.get_tree(rev) yield rev self.tree = saved_tree
python
def brancher( # noqa: E302 self, branches=None, all_branches=False, tags=None, all_tags=False ): """Generator that iterates over specified revisions. Args: branches (list): a list of branches to iterate over. all_branches (bool): iterate over all available branches. tags (list): a list of tags to iterate over. all_tags (bool): iterate over all available tags. Yields: str: the display name for the currently selected tree, it could be: - a git revision identifier - empty string it there is no branches to iterate over - "Working Tree" if there are uncommited changes in the SCM repo """ if not any([branches, all_branches, tags, all_tags]): yield "" return saved_tree = self.tree revs = [] scm = self.scm if self.scm.is_dirty(): from dvc.scm.tree import WorkingTree self.tree = WorkingTree(self.root_dir) yield "Working Tree" if all_branches: branches = scm.list_branches() if all_tags: tags = scm.list_tags() if branches is None: revs.extend([scm.active_branch()]) else: revs.extend(branches) if tags is not None: revs.extend(tags) # NOTE: it might be a good idea to wrap this loop in try/finally block # to don't leave the tree on some unexpected branch after the # `brancher()`, but this could cause problems on exception handling # code which might expect the tree on which exception was raised to # stay in place. This behavior is a subject to change. for rev in revs: self.tree = scm.get_tree(rev) yield rev self.tree = saved_tree
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/repo/brancher.py#L1-L56
train
iterative/dvc
dvc/state.py
State.changed
def changed(self, path, md5): """Check if file/directory has the expected md5. Args: path (str): path to the file/directory to check. md5 (str): expected md5. Returns: bool: True if path has the expected md5, False otherwise. """ actual = self.update(path) msg = "File '{}', md5 '{}', actual '{}'" logger.debug(msg.format(path, md5, actual)) if not md5 or not actual: return True return actual.split(".")[0] != md5.split(".")[0]
python
def changed(self, path, md5): """Check if file/directory has the expected md5. Args: path (str): path to the file/directory to check. md5 (str): expected md5. Returns: bool: True if path has the expected md5, False otherwise. """ actual = self.update(path) msg = "File '{}', md5 '{}', actual '{}'" logger.debug(msg.format(path, md5, actual)) if not md5 or not actual: return True return actual.split(".")[0] != md5.split(".")[0]
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/state.py#L119-L137
train
iterative/dvc
dvc/state.py
State.load
def load(self): """Loads state database.""" retries = 1 while True: assert self.database is None assert self.cursor is None assert self.inserts == 0 empty = not os.path.exists(self.state_file) self.database = sqlite3.connect(self.state_file) self.cursor = self.database.cursor() # Try loading once to check that the file is indeed a database # and reformat it if it is not. try: self._prepare_db(empty=empty) return except sqlite3.DatabaseError: self.cursor.close() self.database.close() self.database = None self.cursor = None self.inserts = 0 if retries > 0: os.unlink(self.state_file) retries -= 1 else: raise
python
def load(self): """Loads state database.""" retries = 1 while True: assert self.database is None assert self.cursor is None assert self.inserts == 0 empty = not os.path.exists(self.state_file) self.database = sqlite3.connect(self.state_file) self.cursor = self.database.cursor() # Try loading once to check that the file is indeed a database # and reformat it if it is not. try: self._prepare_db(empty=empty) return except sqlite3.DatabaseError: self.cursor.close() self.database.close() self.database = None self.cursor = None self.inserts = 0 if retries > 0: os.unlink(self.state_file) retries -= 1 else: raise
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Loads state database.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/state.py#L214-L240
train
iterative/dvc
dvc/state.py
State.dump
def dump(self): """Saves state database.""" assert self.database is not None cmd = "SELECT count from {} WHERE rowid={}" self._execute(cmd.format(self.STATE_INFO_TABLE, self.STATE_INFO_ROW)) ret = self._fetchall() assert len(ret) == 1 assert len(ret[0]) == 1 count = self._from_sqlite(ret[0][0]) + self.inserts if count > self.row_limit: msg = "cleaning up state, this might take a while." logger.warning(msg) delete = count - self.row_limit delete += int(self.row_limit * (self.row_cleanup_quota / 100.0)) cmd = ( "DELETE FROM {} WHERE timestamp IN (" "SELECT timestamp FROM {} ORDER BY timestamp ASC LIMIT {});" ) self._execute( cmd.format(self.STATE_TABLE, self.STATE_TABLE, delete) ) self._vacuum() cmd = "SELECT COUNT(*) FROM {}" self._execute(cmd.format(self.STATE_TABLE)) ret = self._fetchall() assert len(ret) == 1 assert len(ret[0]) == 1 count = ret[0][0] cmd = "UPDATE {} SET count = {} WHERE rowid = {}" self._execute( cmd.format( self.STATE_INFO_TABLE, self._to_sqlite(count), self.STATE_INFO_ROW, ) ) self._update_cache_directory_state() self.database.commit() self.cursor.close() self.database.close() self.database = None self.cursor = None self.inserts = 0
python
def dump(self): """Saves state database.""" assert self.database is not None cmd = "SELECT count from {} WHERE rowid={}" self._execute(cmd.format(self.STATE_INFO_TABLE, self.STATE_INFO_ROW)) ret = self._fetchall() assert len(ret) == 1 assert len(ret[0]) == 1 count = self._from_sqlite(ret[0][0]) + self.inserts if count > self.row_limit: msg = "cleaning up state, this might take a while." logger.warning(msg) delete = count - self.row_limit delete += int(self.row_limit * (self.row_cleanup_quota / 100.0)) cmd = ( "DELETE FROM {} WHERE timestamp IN (" "SELECT timestamp FROM {} ORDER BY timestamp ASC LIMIT {});" ) self._execute( cmd.format(self.STATE_TABLE, self.STATE_TABLE, delete) ) self._vacuum() cmd = "SELECT COUNT(*) FROM {}" self._execute(cmd.format(self.STATE_TABLE)) ret = self._fetchall() assert len(ret) == 1 assert len(ret[0]) == 1 count = ret[0][0] cmd = "UPDATE {} SET count = {} WHERE rowid = {}" self._execute( cmd.format( self.STATE_INFO_TABLE, self._to_sqlite(count), self.STATE_INFO_ROW, ) ) self._update_cache_directory_state() self.database.commit() self.cursor.close() self.database.close() self.database = None self.cursor = None self.inserts = 0
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Saves state database.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/state.py#L248-L299
train
iterative/dvc
dvc/state.py
State.save
def save(self, path_info, checksum): """Save checksum for the specified path info. Args: path_info (dict): path_info to save checksum for. checksum (str): checksum to save. """ assert path_info["scheme"] == "local" assert checksum is not None path = path_info["path"] assert os.path.exists(path) actual_mtime, actual_size = get_mtime_and_size(path) actual_inode = get_inode(path) existing_record = self.get_state_record_for_inode(actual_inode) if not existing_record: self._insert_new_state_record( path, actual_inode, actual_mtime, actual_size, checksum ) return self._update_state_for_path_changed( path, actual_inode, actual_mtime, actual_size, checksum )
python
def save(self, path_info, checksum): """Save checksum for the specified path info. Args: path_info (dict): path_info to save checksum for. checksum (str): checksum to save. """ assert path_info["scheme"] == "local" assert checksum is not None path = path_info["path"] assert os.path.exists(path) actual_mtime, actual_size = get_mtime_and_size(path) actual_inode = get_inode(path) existing_record = self.get_state_record_for_inode(actual_inode) if not existing_record: self._insert_new_state_record( path, actual_inode, actual_mtime, actual_size, checksum ) return self._update_state_for_path_changed( path, actual_inode, actual_mtime, actual_size, checksum )
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Save checksum for the specified path info. Args: path_info (dict): path_info to save checksum for. checksum (str): checksum to save.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/state.py#L367-L392
train
iterative/dvc
dvc/state.py
State.get
def get(self, path_info): """Gets the checksum for the specified path info. Checksum will be retrieved from the state database if available. Args: path_info (dict): path info to get the checksum for. Returns: str or None: checksum for the specified path info or None if it doesn't exist in the state database. """ assert path_info["scheme"] == "local" path = path_info["path"] if not os.path.exists(path): return None actual_mtime, actual_size = get_mtime_and_size(path) actual_inode = get_inode(path) existing_record = self.get_state_record_for_inode(actual_inode) if not existing_record: return None mtime, size, checksum, _ = existing_record if self._file_metadata_changed(actual_mtime, mtime, actual_size, size): return None self._update_state_record_timestamp_for_inode(actual_inode) return checksum
python
def get(self, path_info): """Gets the checksum for the specified path info. Checksum will be retrieved from the state database if available. Args: path_info (dict): path info to get the checksum for. Returns: str or None: checksum for the specified path info or None if it doesn't exist in the state database. """ assert path_info["scheme"] == "local" path = path_info["path"] if not os.path.exists(path): return None actual_mtime, actual_size = get_mtime_and_size(path) actual_inode = get_inode(path) existing_record = self.get_state_record_for_inode(actual_inode) if not existing_record: return None mtime, size, checksum, _ = existing_record if self._file_metadata_changed(actual_mtime, mtime, actual_size, size): return None self._update_state_record_timestamp_for_inode(actual_inode) return checksum
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Gets the checksum for the specified path info. Checksum will be retrieved from the state database if available. Args: path_info (dict): path info to get the checksum for. Returns: str or None: checksum for the specified path info or None if it doesn't exist in the state database.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/state.py#L394-L423
train
iterative/dvc
dvc/state.py
State.save_link
def save_link(self, path_info): """Adds the specified path to the list of links created by dvc. This list is later used on `dvc checkout` to cleanup old links. Args: path_info (dict): path info to add to the list of links. """ assert path_info["scheme"] == "local" path = path_info["path"] if not os.path.exists(path): return mtime, _ = get_mtime_and_size(path) inode = get_inode(path) relpath = os.path.relpath(path, self.root_dir) cmd = ( "REPLACE INTO {}(path, inode, mtime) " 'VALUES ("{}", {}, "{}")'.format( self.LINK_STATE_TABLE, relpath, self._to_sqlite(inode), mtime ) ) self._execute(cmd)
python
def save_link(self, path_info): """Adds the specified path to the list of links created by dvc. This list is later used on `dvc checkout` to cleanup old links. Args: path_info (dict): path info to add to the list of links. """ assert path_info["scheme"] == "local" path = path_info["path"] if not os.path.exists(path): return mtime, _ = get_mtime_and_size(path) inode = get_inode(path) relpath = os.path.relpath(path, self.root_dir) cmd = ( "REPLACE INTO {}(path, inode, mtime) " 'VALUES ("{}", {}, "{}")'.format( self.LINK_STATE_TABLE, relpath, self._to_sqlite(inode), mtime ) ) self._execute(cmd)
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Adds the specified path to the list of links created by dvc. This list is later used on `dvc checkout` to cleanup old links. Args: path_info (dict): path info to add to the list of links.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/state.py#L425-L448
train
iterative/dvc
dvc/state.py
State.remove_unused_links
def remove_unused_links(self, used): """Removes all saved links except the ones that are used. Args: used (list): list of used links that should not be removed. """ unused = [] self._execute("SELECT * FROM {}".format(self.LINK_STATE_TABLE)) for row in self.cursor: relpath, inode, mtime = row inode = self._from_sqlite(inode) path = os.path.join(self.root_dir, relpath) if path in used: continue if not os.path.exists(path): continue actual_inode = get_inode(path) actual_mtime, _ = get_mtime_and_size(path) if inode == actual_inode and mtime == actual_mtime: logger.debug("Removing '{}' as unused link.".format(path)) remove(path) unused.append(relpath) for relpath in unused: cmd = 'DELETE FROM {} WHERE path = "{}"' self._execute(cmd.format(self.LINK_STATE_TABLE, relpath))
python
def remove_unused_links(self, used): """Removes all saved links except the ones that are used. Args: used (list): list of used links that should not be removed. """ unused = [] self._execute("SELECT * FROM {}".format(self.LINK_STATE_TABLE)) for row in self.cursor: relpath, inode, mtime = row inode = self._from_sqlite(inode) path = os.path.join(self.root_dir, relpath) if path in used: continue if not os.path.exists(path): continue actual_inode = get_inode(path) actual_mtime, _ = get_mtime_and_size(path) if inode == actual_inode and mtime == actual_mtime: logger.debug("Removing '{}' as unused link.".format(path)) remove(path) unused.append(relpath) for relpath in unused: cmd = 'DELETE FROM {} WHERE path = "{}"' self._execute(cmd.format(self.LINK_STATE_TABLE, relpath))
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Removes all saved links except the ones that are used. Args: used (list): list of used links that should not be removed.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/state.py#L450-L480
train
iterative/dvc
dvc/command/metrics.py
show_metrics
def show_metrics(metrics, all_branches=False, all_tags=False): """ Args: metrics (list): Where each element is either a `list` if an xpath was specified, otherwise a `str` """ for branch, val in metrics.items(): if all_branches or all_tags: logger.info("{branch}:".format(branch=branch)) for fname, metric in val.items(): lines = metric if type(metric) is list else metric.splitlines() if len(lines) > 1: logger.info("\t{fname}:".format(fname=fname)) for line in lines: logger.info("\t\t{content}".format(content=line)) else: logger.info("\t{}: {}".format(fname, metric))
python
def show_metrics(metrics, all_branches=False, all_tags=False): """ Args: metrics (list): Where each element is either a `list` if an xpath was specified, otherwise a `str` """ for branch, val in metrics.items(): if all_branches or all_tags: logger.info("{branch}:".format(branch=branch)) for fname, metric in val.items(): lines = metric if type(metric) is list else metric.splitlines() if len(lines) > 1: logger.info("\t{fname}:".format(fname=fname)) for line in lines: logger.info("\t\t{content}".format(content=line)) else: logger.info("\t{}: {}".format(fname, metric))
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Args: metrics (list): Where each element is either a `list` if an xpath was specified, otherwise a `str`
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/command/metrics.py#L13-L33
train
iterative/dvc
dvc/lock.py
Lock.lock
def lock(self): """Acquire lock for dvc repo.""" try: self._do_lock() return except LockError: time.sleep(self.TIMEOUT) self._do_lock()
python
def lock(self): """Acquire lock for dvc repo.""" try: self._do_lock() return except LockError: time.sleep(self.TIMEOUT) self._do_lock()
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Acquire lock for dvc repo.
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8bb21261e34c9632453e09090de7ebe50e38d341
https://github.com/iterative/dvc/blob/8bb21261e34c9632453e09090de7ebe50e38d341/dvc/lock.py#L41-L49
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Desktop_Widget_Email_Notification.py
read_mail
def read_mail(window): """ Reads late emails from IMAP server and displays them in the Window :param window: window to display emails in :return: """ mail = imaplib.IMAP4_SSL(IMAP_SERVER) (retcode, capabilities) = mail.login(LOGIN_EMAIL, LOGIN_PASSWORD) mail.list() typ, data = mail.select('Inbox') n = 0 now = datetime.now() # get messages from today search_string = '(SENTON {}-{}-{})'.format(now.day, calendar.month_abbr[now.month], now.year) (retcode, messages) = mail.search(None, search_string) if retcode == 'OK': msg_list = messages[0].split() # message numbers are separated by spaces, turn into list msg_list.sort(reverse=True) # sort messages descending for n, message in enumerate(msg_list): if n >= MAX_EMAILS: break from_elem = window.FindElement('{}from'.format(n)) date_elem = window.FindElement('{}date'.format(n)) from_elem.Update('') # erase them so you know they're changing date_elem.Update('') window.Refresh() typ, data = mail.fetch(message, '(RFC822)') for response_part in data: if isinstance(response_part, tuple): original = email.message_from_bytes(response_part[1]) date_str = original['Date'][:22] from_elem.Update(original['From']) date_elem.Update(date_str) window.Refresh()
python
def read_mail(window): """ Reads late emails from IMAP server and displays them in the Window :param window: window to display emails in :return: """ mail = imaplib.IMAP4_SSL(IMAP_SERVER) (retcode, capabilities) = mail.login(LOGIN_EMAIL, LOGIN_PASSWORD) mail.list() typ, data = mail.select('Inbox') n = 0 now = datetime.now() # get messages from today search_string = '(SENTON {}-{}-{})'.format(now.day, calendar.month_abbr[now.month], now.year) (retcode, messages) = mail.search(None, search_string) if retcode == 'OK': msg_list = messages[0].split() # message numbers are separated by spaces, turn into list msg_list.sort(reverse=True) # sort messages descending for n, message in enumerate(msg_list): if n >= MAX_EMAILS: break from_elem = window.FindElement('{}from'.format(n)) date_elem = window.FindElement('{}date'.format(n)) from_elem.Update('') # erase them so you know they're changing date_elem.Update('') window.Refresh() typ, data = mail.fetch(message, '(RFC822)') for response_part in data: if isinstance(response_part, tuple): original = email.message_from_bytes(response_part[1]) date_str = original['Date'][:22] from_elem.Update(original['From']) date_elem.Update(date_str) window.Refresh()
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Reads late emails from IMAP server and displays them in the Window :param window: window to display emails in :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Desktop_Widget_Email_Notification.py#L67-L101
train
PySimpleGUI/PySimpleGUI
exemaker/pysimplegui-exemaker/pysimplegui-exemaker.py
runCommand
def runCommand(cmd, timeout=None): """ run shell command @param cmd: command to execute @param timeout: timeout for command execution @return: (return code from command, command output) """ p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) output = '' out, err = p.communicate() p.wait(timeout) return (out, err)
python
def runCommand(cmd, timeout=None): """ run shell command @param cmd: command to execute @param timeout: timeout for command execution @return: (return code from command, command output) """ p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) output = '' out, err = p.communicate() p.wait(timeout) return (out, err)
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run shell command @param cmd: command to execute @param timeout: timeout for command execution @return: (return code from command, command output)
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/exemaker/pysimplegui-exemaker/pysimplegui-exemaker.py#L59-L73
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/Demo Programs/Web_psutil_Kill_Processes.py
kill_proc_tree
def kill_proc_tree(pid, sig=signal.SIGTERM, include_parent=True, timeout=None, on_terminate=None): """Kill a process tree (including grandchildren) with signal "sig" and return a (gone, still_alive) tuple. "on_terminate", if specified, is a callabck function which is called as soon as a child terminates. """ if pid == os.getpid(): raise RuntimeError("I refuse to kill myself") parent = psutil.Process(pid) children = parent.children(recursive=True) if include_parent: children.append(parent) for p in children: p.send_signal(sig) gone, alive = psutil.wait_procs(children, timeout=timeout, callback=on_terminate) return (gone, alive)
python
def kill_proc_tree(pid, sig=signal.SIGTERM, include_parent=True, timeout=None, on_terminate=None): """Kill a process tree (including grandchildren) with signal "sig" and return a (gone, still_alive) tuple. "on_terminate", if specified, is a callabck function which is called as soon as a child terminates. """ if pid == os.getpid(): raise RuntimeError("I refuse to kill myself") parent = psutil.Process(pid) children = parent.children(recursive=True) if include_parent: children.append(parent) for p in children: p.send_signal(sig) gone, alive = psutil.wait_procs(children, timeout=timeout, callback=on_terminate) return (gone, alive)
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Kill a process tree (including grandchildren) with signal "sig" and return a (gone, still_alive) tuple. "on_terminate", if specified, is a callabck function which is called as soon as a child terminates.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/Demo Programs/Web_psutil_Kill_Processes.py#L16-L33
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
Popup
def Popup(*args, **_3to2kwargs): if 'location' in _3to2kwargs: location = _3to2kwargs['location']; del _3to2kwargs['location'] else: location = (None, None) if 'keep_on_top' in _3to2kwargs: keep_on_top = _3to2kwargs['keep_on_top']; del _3to2kwargs['keep_on_top'] else: keep_on_top = False if 'grab_anywhere' in _3to2kwargs: grab_anywhere = _3to2kwargs['grab_anywhere']; del _3to2kwargs['grab_anywhere'] else: grab_anywhere = False if 'no_titlebar' in _3to2kwargs: no_titlebar = _3to2kwargs['no_titlebar']; del _3to2kwargs['no_titlebar'] else: no_titlebar = False if 'font' in _3to2kwargs: font = _3to2kwargs['font']; del _3to2kwargs['font'] else: font = None if 'line_width' in _3to2kwargs: line_width = _3to2kwargs['line_width']; del _3to2kwargs['line_width'] else: line_width = None if 'icon' in _3to2kwargs: icon = _3to2kwargs['icon']; del _3to2kwargs['icon'] else: icon = DEFAULT_WINDOW_ICON if 'non_blocking' in _3to2kwargs: non_blocking = _3to2kwargs['non_blocking']; del _3to2kwargs['non_blocking'] else: non_blocking = False if 'custom_text' in _3to2kwargs: custom_text = _3to2kwargs['custom_text']; del _3to2kwargs['custom_text'] else: custom_text = (None, None) if 'auto_close_duration' in _3to2kwargs: auto_close_duration = _3to2kwargs['auto_close_duration']; del _3to2kwargs['auto_close_duration'] else: auto_close_duration = None if 'auto_close' in _3to2kwargs: auto_close = _3to2kwargs['auto_close']; del _3to2kwargs['auto_close'] else: auto_close = False if 'button_type' in _3to2kwargs: button_type = _3to2kwargs['button_type']; del _3to2kwargs['button_type'] else: button_type = POPUP_BUTTONS_OK if 'text_color' in _3to2kwargs: text_color = _3to2kwargs['text_color']; del _3to2kwargs['text_color'] else: text_color = None if 'background_color' in _3to2kwargs: background_color = _3to2kwargs['background_color']; del _3to2kwargs['background_color'] else: background_color = None if 'button_color' in _3to2kwargs: button_color = _3to2kwargs['button_color']; del _3to2kwargs['button_color'] else: button_color = None if 'title' in _3to2kwargs: title = _3to2kwargs['title']; del _3to2kwargs['title'] else: title = None """ Popup - Display a popup box with as many parms as you wish to include :param args: :param button_color: :param background_color: :param text_color: :param button_type: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ if not args: args_to_print = [''] else: args_to_print = args if line_width != None: local_line_width = line_width else: local_line_width = MESSAGE_BOX_LINE_WIDTH _title = title if title is not None else args_to_print[0] window = Window(_title, auto_size_text=True, background_color=background_color, button_color=button_color, auto_close=auto_close, auto_close_duration=auto_close_duration, icon=icon, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) max_line_total, total_lines = 0, 0 for message in args_to_print: # fancy code to check if string and convert if not is not need. Just always convert to string :-) # if not isinstance(message, str): message = str(message) message = str(message) if message.count('\n'): message_wrapped = message else: message_wrapped = textwrap.fill(message, local_line_width) message_wrapped_lines = message_wrapped.count('\n') + 1 longest_line_len = max([len(l) for l in message.split('\n')]) width_used = min(longest_line_len, local_line_width) max_line_total = max(max_line_total, width_used) # height = _GetNumLinesNeeded(message, width_used) height = message_wrapped_lines window.AddRow( Text(message_wrapped, auto_size_text=True, text_color=text_color, background_color=background_color)) total_lines += height if non_blocking: PopupButton = DummyButton # important to use or else button will close other windows too! else: PopupButton = CloseButton # show either an OK or Yes/No depending on paramater if custom_text != (None, None): if type(custom_text) is not tuple: window.AddRow(PopupButton(custom_text,size=(len(custom_text),1), button_color=button_color, focus=True, bind_return_key=True)) elif custom_text[1] is None: window.AddRow(PopupButton(custom_text[0],size=(len(custom_text[0]),1), button_color=button_color, focus=True, bind_return_key=True)) else: window.AddRow(PopupButton(custom_text[0], button_color=button_color, focus=True, bind_return_key=True, size=(len(custom_text[0]), 1)), PopupButton(custom_text[1], button_color=button_color, size=(len(custom_text[0]), 1))) elif button_type is POPUP_BUTTONS_YES_NO: window.AddRow(PopupButton('Yes', button_color=button_color, focus=True, bind_return_key=True, pad=((20, 5), 3), size=(5, 1)), PopupButton('No', button_color=button_color, size=(5, 1))) elif button_type is POPUP_BUTTONS_CANCELLED: window.AddRow( PopupButton('Cancelled', button_color=button_color, focus=True, bind_return_key=True, pad=((20, 0), 3))) elif button_type is POPUP_BUTTONS_ERROR: window.AddRow(PopupButton('Error', size=(6, 1), button_color=button_color, focus=True, bind_return_key=True, pad=((20, 0), 3))) elif button_type is POPUP_BUTTONS_OK_CANCEL: window.AddRow(PopupButton('OK', size=(6, 1), button_color=button_color, focus=True, bind_return_key=True), PopupButton('Cancel', size=(6, 1), button_color=button_color)) elif button_type is POPUP_BUTTONS_NO_BUTTONS: pass else: window.AddRow(PopupButton('OK', size=(5, 1), button_color=button_color, focus=True, bind_return_key=True, pad=((20, 0), 3))) if non_blocking: button, values = window.Read(timeout=0) else: button, values = window.Read() return button
python
def Popup(*args, **_3to2kwargs): if 'location' in _3to2kwargs: location = _3to2kwargs['location']; del _3to2kwargs['location'] else: location = (None, None) if 'keep_on_top' in _3to2kwargs: keep_on_top = _3to2kwargs['keep_on_top']; del _3to2kwargs['keep_on_top'] else: keep_on_top = False if 'grab_anywhere' in _3to2kwargs: grab_anywhere = _3to2kwargs['grab_anywhere']; del _3to2kwargs['grab_anywhere'] else: grab_anywhere = False if 'no_titlebar' in _3to2kwargs: no_titlebar = _3to2kwargs['no_titlebar']; del _3to2kwargs['no_titlebar'] else: no_titlebar = False if 'font' in _3to2kwargs: font = _3to2kwargs['font']; del _3to2kwargs['font'] else: font = None if 'line_width' in _3to2kwargs: line_width = _3to2kwargs['line_width']; del _3to2kwargs['line_width'] else: line_width = None if 'icon' in _3to2kwargs: icon = _3to2kwargs['icon']; del _3to2kwargs['icon'] else: icon = DEFAULT_WINDOW_ICON if 'non_blocking' in _3to2kwargs: non_blocking = _3to2kwargs['non_blocking']; del _3to2kwargs['non_blocking'] else: non_blocking = False if 'custom_text' in _3to2kwargs: custom_text = _3to2kwargs['custom_text']; del _3to2kwargs['custom_text'] else: custom_text = (None, None) if 'auto_close_duration' in _3to2kwargs: auto_close_duration = _3to2kwargs['auto_close_duration']; del _3to2kwargs['auto_close_duration'] else: auto_close_duration = None if 'auto_close' in _3to2kwargs: auto_close = _3to2kwargs['auto_close']; del _3to2kwargs['auto_close'] else: auto_close = False if 'button_type' in _3to2kwargs: button_type = _3to2kwargs['button_type']; del _3to2kwargs['button_type'] else: button_type = POPUP_BUTTONS_OK if 'text_color' in _3to2kwargs: text_color = _3to2kwargs['text_color']; del _3to2kwargs['text_color'] else: text_color = None if 'background_color' in _3to2kwargs: background_color = _3to2kwargs['background_color']; del _3to2kwargs['background_color'] else: background_color = None if 'button_color' in _3to2kwargs: button_color = _3to2kwargs['button_color']; del _3to2kwargs['button_color'] else: button_color = None if 'title' in _3to2kwargs: title = _3to2kwargs['title']; del _3to2kwargs['title'] else: title = None """ Popup - Display a popup box with as many parms as you wish to include :param args: :param button_color: :param background_color: :param text_color: :param button_type: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ if not args: args_to_print = [''] else: args_to_print = args if line_width != None: local_line_width = line_width else: local_line_width = MESSAGE_BOX_LINE_WIDTH _title = title if title is not None else args_to_print[0] window = Window(_title, auto_size_text=True, background_color=background_color, button_color=button_color, auto_close=auto_close, auto_close_duration=auto_close_duration, icon=icon, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) max_line_total, total_lines = 0, 0 for message in args_to_print: # fancy code to check if string and convert if not is not need. Just always convert to string :-) # if not isinstance(message, str): message = str(message) message = str(message) if message.count('\n'): message_wrapped = message else: message_wrapped = textwrap.fill(message, local_line_width) message_wrapped_lines = message_wrapped.count('\n') + 1 longest_line_len = max([len(l) for l in message.split('\n')]) width_used = min(longest_line_len, local_line_width) max_line_total = max(max_line_total, width_used) # height = _GetNumLinesNeeded(message, width_used) height = message_wrapped_lines window.AddRow( Text(message_wrapped, auto_size_text=True, text_color=text_color, background_color=background_color)) total_lines += height if non_blocking: PopupButton = DummyButton # important to use or else button will close other windows too! else: PopupButton = CloseButton # show either an OK or Yes/No depending on paramater if custom_text != (None, None): if type(custom_text) is not tuple: window.AddRow(PopupButton(custom_text,size=(len(custom_text),1), button_color=button_color, focus=True, bind_return_key=True)) elif custom_text[1] is None: window.AddRow(PopupButton(custom_text[0],size=(len(custom_text[0]),1), button_color=button_color, focus=True, bind_return_key=True)) else: window.AddRow(PopupButton(custom_text[0], button_color=button_color, focus=True, bind_return_key=True, size=(len(custom_text[0]), 1)), PopupButton(custom_text[1], button_color=button_color, size=(len(custom_text[0]), 1))) elif button_type is POPUP_BUTTONS_YES_NO: window.AddRow(PopupButton('Yes', button_color=button_color, focus=True, bind_return_key=True, pad=((20, 5), 3), size=(5, 1)), PopupButton('No', button_color=button_color, size=(5, 1))) elif button_type is POPUP_BUTTONS_CANCELLED: window.AddRow( PopupButton('Cancelled', button_color=button_color, focus=True, bind_return_key=True, pad=((20, 0), 3))) elif button_type is POPUP_BUTTONS_ERROR: window.AddRow(PopupButton('Error', size=(6, 1), button_color=button_color, focus=True, bind_return_key=True, pad=((20, 0), 3))) elif button_type is POPUP_BUTTONS_OK_CANCEL: window.AddRow(PopupButton('OK', size=(6, 1), button_color=button_color, focus=True, bind_return_key=True), PopupButton('Cancel', size=(6, 1), button_color=button_color)) elif button_type is POPUP_BUTTONS_NO_BUTTONS: pass else: window.AddRow(PopupButton('OK', size=(5, 1), button_color=button_color, focus=True, bind_return_key=True, pad=((20, 0), 3))) if non_blocking: button, values = window.Read(timeout=0) else: button, values = window.Read() return button
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Popup - Display a popup box with as many parms as you wish to include :param args: :param button_color: :param background_color: :param text_color: :param button_type: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L7037-L7156
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
PopupNoButtons
def PopupNoButtons(*args, **_3to2kwargs): if 'location' in _3to2kwargs: location = _3to2kwargs['location']; del _3to2kwargs['location'] else: location = (None, None) if 'keep_on_top' in _3to2kwargs: keep_on_top = _3to2kwargs['keep_on_top']; del _3to2kwargs['keep_on_top'] else: keep_on_top = False if 'grab_anywhere' in _3to2kwargs: grab_anywhere = _3to2kwargs['grab_anywhere']; del _3to2kwargs['grab_anywhere'] else: grab_anywhere = False if 'no_titlebar' in _3to2kwargs: no_titlebar = _3to2kwargs['no_titlebar']; del _3to2kwargs['no_titlebar'] else: no_titlebar = False if 'font' in _3to2kwargs: font = _3to2kwargs['font']; del _3to2kwargs['font'] else: font = None if 'line_width' in _3to2kwargs: line_width = _3to2kwargs['line_width']; del _3to2kwargs['line_width'] else: line_width = None if 'icon' in _3to2kwargs: icon = _3to2kwargs['icon']; del _3to2kwargs['icon'] else: icon = DEFAULT_WINDOW_ICON if 'non_blocking' in _3to2kwargs: non_blocking = _3to2kwargs['non_blocking']; del _3to2kwargs['non_blocking'] else: non_blocking = False if 'auto_close_duration' in _3to2kwargs: auto_close_duration = _3to2kwargs['auto_close_duration']; del _3to2kwargs['auto_close_duration'] else: auto_close_duration = None if 'auto_close' in _3to2kwargs: auto_close = _3to2kwargs['auto_close']; del _3to2kwargs['auto_close'] else: auto_close = False if 'text_color' in _3to2kwargs: text_color = _3to2kwargs['text_color']; del _3to2kwargs['text_color'] else: text_color = None if 'background_color' in _3to2kwargs: background_color = _3to2kwargs['background_color']; del _3to2kwargs['background_color'] else: background_color = None if 'button_color' in _3to2kwargs: button_color = _3to2kwargs['button_color']; del _3to2kwargs['button_color'] else: button_color = None if 'title' in _3to2kwargs: title = _3to2kwargs['title']; del _3to2kwargs['title'] else: title = None """ Show a Popup but without any buttons :param args: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ Popup(*args, title=title, button_color=button_color, background_color=background_color, text_color=text_color, button_type=POPUP_BUTTONS_NO_BUTTONS, auto_close=auto_close, auto_close_duration=auto_close_duration, non_blocking=non_blocking, icon=icon, line_width=line_width, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location)
python
def PopupNoButtons(*args, **_3to2kwargs): if 'location' in _3to2kwargs: location = _3to2kwargs['location']; del _3to2kwargs['location'] else: location = (None, None) if 'keep_on_top' in _3to2kwargs: keep_on_top = _3to2kwargs['keep_on_top']; del _3to2kwargs['keep_on_top'] else: keep_on_top = False if 'grab_anywhere' in _3to2kwargs: grab_anywhere = _3to2kwargs['grab_anywhere']; del _3to2kwargs['grab_anywhere'] else: grab_anywhere = False if 'no_titlebar' in _3to2kwargs: no_titlebar = _3to2kwargs['no_titlebar']; del _3to2kwargs['no_titlebar'] else: no_titlebar = False if 'font' in _3to2kwargs: font = _3to2kwargs['font']; del _3to2kwargs['font'] else: font = None if 'line_width' in _3to2kwargs: line_width = _3to2kwargs['line_width']; del _3to2kwargs['line_width'] else: line_width = None if 'icon' in _3to2kwargs: icon = _3to2kwargs['icon']; del _3to2kwargs['icon'] else: icon = DEFAULT_WINDOW_ICON if 'non_blocking' in _3to2kwargs: non_blocking = _3to2kwargs['non_blocking']; del _3to2kwargs['non_blocking'] else: non_blocking = False if 'auto_close_duration' in _3to2kwargs: auto_close_duration = _3to2kwargs['auto_close_duration']; del _3to2kwargs['auto_close_duration'] else: auto_close_duration = None if 'auto_close' in _3to2kwargs: auto_close = _3to2kwargs['auto_close']; del _3to2kwargs['auto_close'] else: auto_close = False if 'text_color' in _3to2kwargs: text_color = _3to2kwargs['text_color']; del _3to2kwargs['text_color'] else: text_color = None if 'background_color' in _3to2kwargs: background_color = _3to2kwargs['background_color']; del _3to2kwargs['background_color'] else: background_color = None if 'button_color' in _3to2kwargs: button_color = _3to2kwargs['button_color']; del _3to2kwargs['button_color'] else: button_color = None if 'title' in _3to2kwargs: title = _3to2kwargs['title']; del _3to2kwargs['title'] else: title = None """ Show a Popup but without any buttons :param args: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ Popup(*args, title=title, button_color=button_color, background_color=background_color, text_color=text_color, button_type=POPUP_BUTTONS_NO_BUTTONS, auto_close=auto_close, auto_close_duration=auto_close_duration, non_blocking=non_blocking, icon=icon, line_width=line_width, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location)
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Show a Popup but without any buttons :param args: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L7169-L7220
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
PopupError
def PopupError(*args, **_3to2kwargs): if 'location' in _3to2kwargs: location = _3to2kwargs['location']; del _3to2kwargs['location'] else: location = (None, None) if 'keep_on_top' in _3to2kwargs: keep_on_top = _3to2kwargs['keep_on_top']; del _3to2kwargs['keep_on_top'] else: keep_on_top = False if 'grab_anywhere' in _3to2kwargs: grab_anywhere = _3to2kwargs['grab_anywhere']; del _3to2kwargs['grab_anywhere'] else: grab_anywhere = False if 'no_titlebar' in _3to2kwargs: no_titlebar = _3to2kwargs['no_titlebar']; del _3to2kwargs['no_titlebar'] else: no_titlebar = False if 'font' in _3to2kwargs: font = _3to2kwargs['font']; del _3to2kwargs['font'] else: font = None if 'line_width' in _3to2kwargs: line_width = _3to2kwargs['line_width']; del _3to2kwargs['line_width'] else: line_width = None if 'icon' in _3to2kwargs: icon = _3to2kwargs['icon']; del _3to2kwargs['icon'] else: icon = DEFAULT_WINDOW_ICON if 'non_blocking' in _3to2kwargs: non_blocking = _3to2kwargs['non_blocking']; del _3to2kwargs['non_blocking'] else: non_blocking = False if 'auto_close_duration' in _3to2kwargs: auto_close_duration = _3to2kwargs['auto_close_duration']; del _3to2kwargs['auto_close_duration'] else: auto_close_duration = None if 'auto_close' in _3to2kwargs: auto_close = _3to2kwargs['auto_close']; del _3to2kwargs['auto_close'] else: auto_close = False if 'text_color' in _3to2kwargs: text_color = _3to2kwargs['text_color']; del _3to2kwargs['text_color'] else: text_color = None if 'background_color' in _3to2kwargs: background_color = _3to2kwargs['background_color']; del _3to2kwargs['background_color'] else: background_color = None if 'button_color' in _3to2kwargs: button_color = _3to2kwargs['button_color']; del _3to2kwargs['button_color'] else: button_color = (None, None) if 'title' in _3to2kwargs: title = _3to2kwargs['title']; del _3to2kwargs['title'] else: title = None """ Popup with colored button and 'Error' as button text :param args: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ tbutton_color = DEFAULT_ERROR_BUTTON_COLOR if button_color == (None, None) else button_color Popup(*args, title=title, button_type=POPUP_BUTTONS_ERROR, background_color=background_color, text_color=text_color, non_blocking=non_blocking, icon=icon, line_width=line_width, button_color=tbutton_color, auto_close=auto_close, auto_close_duration=auto_close_duration, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location)
python
def PopupError(*args, **_3to2kwargs): if 'location' in _3to2kwargs: location = _3to2kwargs['location']; del _3to2kwargs['location'] else: location = (None, None) if 'keep_on_top' in _3to2kwargs: keep_on_top = _3to2kwargs['keep_on_top']; del _3to2kwargs['keep_on_top'] else: keep_on_top = False if 'grab_anywhere' in _3to2kwargs: grab_anywhere = _3to2kwargs['grab_anywhere']; del _3to2kwargs['grab_anywhere'] else: grab_anywhere = False if 'no_titlebar' in _3to2kwargs: no_titlebar = _3to2kwargs['no_titlebar']; del _3to2kwargs['no_titlebar'] else: no_titlebar = False if 'font' in _3to2kwargs: font = _3to2kwargs['font']; del _3to2kwargs['font'] else: font = None if 'line_width' in _3to2kwargs: line_width = _3to2kwargs['line_width']; del _3to2kwargs['line_width'] else: line_width = None if 'icon' in _3to2kwargs: icon = _3to2kwargs['icon']; del _3to2kwargs['icon'] else: icon = DEFAULT_WINDOW_ICON if 'non_blocking' in _3to2kwargs: non_blocking = _3to2kwargs['non_blocking']; del _3to2kwargs['non_blocking'] else: non_blocking = False if 'auto_close_duration' in _3to2kwargs: auto_close_duration = _3to2kwargs['auto_close_duration']; del _3to2kwargs['auto_close_duration'] else: auto_close_duration = None if 'auto_close' in _3to2kwargs: auto_close = _3to2kwargs['auto_close']; del _3to2kwargs['auto_close'] else: auto_close = False if 'text_color' in _3to2kwargs: text_color = _3to2kwargs['text_color']; del _3to2kwargs['text_color'] else: text_color = None if 'background_color' in _3to2kwargs: background_color = _3to2kwargs['background_color']; del _3to2kwargs['background_color'] else: background_color = None if 'button_color' in _3to2kwargs: button_color = _3to2kwargs['button_color']; del _3to2kwargs['button_color'] else: button_color = (None, None) if 'title' in _3to2kwargs: title = _3to2kwargs['title']; del _3to2kwargs['title'] else: title = None """ Popup with colored button and 'Error' as button text :param args: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ tbutton_color = DEFAULT_ERROR_BUTTON_COLOR if button_color == (None, None) else button_color Popup(*args, title=title, button_type=POPUP_BUTTONS_ERROR, background_color=background_color, text_color=text_color, non_blocking=non_blocking, icon=icon, line_width=line_width, button_color=tbutton_color, auto_close=auto_close, auto_close_duration=auto_close_duration, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location)
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L7522-L7573
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
TkScrollableFrame.set_scrollregion
def set_scrollregion(self, event=None): """ Set the scroll region on the canvas""" self.canvas.configure(scrollregion=self.canvas.bbox('all'))
python
def set_scrollregion(self, event=None): """ Set the scroll region on the canvas""" self.canvas.configure(scrollregion=self.canvas.bbox('all'))
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Set the scroll region on the canvas
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L2769-L2771
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
TKCalendar._show_selection
def _show_selection(self, text, bbox): """Configure canvas for a new selection.""" x, y, width, height = bbox textw = self._font.measure(text) canvas = self._canvas canvas.configure(width=width, height=height) canvas.coords(canvas.text, width - textw, height / 2 - 1) canvas.itemconfigure(canvas.text, text=text) canvas.place(in_=self._calendar, x=x, y=y)
python
def _show_selection(self, text, bbox): """Configure canvas for a new selection.""" x, y, width, height = bbox textw = self._font.measure(text) canvas = self._canvas canvas.configure(width=width, height=height) canvas.coords(canvas.text, width - textw, height / 2 - 1) canvas.itemconfigure(canvas.text, text=text) canvas.place(in_=self._calendar, x=x, y=y)
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Configure canvas for a new selection.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L3052-L3062
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
TKCalendar._pressed
def _pressed(self, evt): """Clicked somewhere in the calendar.""" x, y, widget = evt.x, evt.y, evt.widget item = widget.identify_row(y) column = widget.identify_column(x) if not column or not item in self._items: # clicked in the weekdays row or just outside the columns return item_values = widget.item(item)['values'] if not len(item_values): # row is empty for this month return text = item_values[int(column[1]) - 1] if not text: # date is empty return bbox = widget.bbox(item, column) if not bbox: # calendar not visible yet return # update and then show selection text = '%02d' % text self._selection = (text, item, column) self._show_selection(text, bbox) year, month = self._date.year, self._date.month try: self._TargetElement.Update(self.datetime(year, month, int(self._selection[0]))) if self._TargetElement.ChangeSubmits: self._TargetElement.ParentForm.LastButtonClicked = self._TargetElement.Key self._TargetElement.ParentForm.FormRemainedOpen = True self._TargetElement.ParentForm.TKroot.quit() # kick the users out of the mainloop except: pass if self.close_when_chosen: self._master.destroy()
python
def _pressed(self, evt): """Clicked somewhere in the calendar.""" x, y, widget = evt.x, evt.y, evt.widget item = widget.identify_row(y) column = widget.identify_column(x) if not column or not item in self._items: # clicked in the weekdays row or just outside the columns return item_values = widget.item(item)['values'] if not len(item_values): # row is empty for this month return text = item_values[int(column[1]) - 1] if not text: # date is empty return bbox = widget.bbox(item, column) if not bbox: # calendar not visible yet return # update and then show selection text = '%02d' % text self._selection = (text, item, column) self._show_selection(text, bbox) year, month = self._date.year, self._date.month try: self._TargetElement.Update(self.datetime(year, month, int(self._selection[0]))) if self._TargetElement.ChangeSubmits: self._TargetElement.ParentForm.LastButtonClicked = self._TargetElement.Key self._TargetElement.ParentForm.FormRemainedOpen = True self._TargetElement.ParentForm.TKroot.quit() # kick the users out of the mainloop except: pass if self.close_when_chosen: self._master.destroy()
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L3066-L3102
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
TKCalendar._prev_month
def _prev_month(self): """Updated calendar to show the previous month.""" self._canvas.place_forget() self._date = self._date - self.timedelta(days=1) self._date = self.datetime(self._date.year, self._date.month, 1) self._build_calendar()
python
def _prev_month(self): """Updated calendar to show the previous month.""" self._canvas.place_forget() self._date = self._date - self.timedelta(days=1) self._date = self.datetime(self._date.year, self._date.month, 1) self._build_calendar()
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Updated calendar to show the previous month.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L3104-L3110
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
TKCalendar._next_month
def _next_month(self): """Update calendar to show the next month.""" self._canvas.place_forget() year, month = self._date.year, self._date.month self._date = self._date + self.timedelta( days=calendar.monthrange(year, month)[1] + 1) self._date = self.datetime(self._date.year, self._date.month, 1) self._build_calendar()
python
def _next_month(self): """Update calendar to show the next month.""" self._canvas.place_forget() year, month = self._date.year, self._date.month self._date = self._date + self.timedelta( days=calendar.monthrange(year, month)[1] + 1) self._date = self.datetime(self._date.year, self._date.month, 1) self._build_calendar()
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Update calendar to show the next month.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L3112-L3120
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
TKCalendar.selection
def selection(self): """Return a datetime representing the current selected date.""" if not self._selection: return None year, month = self._date.year, self._date.month return self.datetime(year, month, int(self._selection[0]))
python
def selection(self): """Return a datetime representing the current selected date.""" if not self._selection: return None year, month = self._date.year, self._date.month return self.datetime(year, month, int(self._selection[0]))
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Return a datetime representing the current selected date.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L3125-L3131
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
Window.AddRow
def AddRow(self, *args): ''' Parms are a variable number of Elements ''' NumRows = len(self.Rows) # number of existing rows is our row number CurrentRowNumber = NumRows # this row's number CurrentRow = [] # start with a blank row and build up # ------------------------- Add the elements to a row ------------------------- # for i, element in enumerate(args): # Loop through list of elements and add them to the row element.Position = (CurrentRowNumber, i) element.ParentContainer = self CurrentRow.append(element) # ------------------------- Append the row to list of Rows ------------------------- # self.Rows.append(CurrentRow)
python
def AddRow(self, *args): ''' Parms are a variable number of Elements ''' NumRows = len(self.Rows) # number of existing rows is our row number CurrentRowNumber = NumRows # this row's number CurrentRow = [] # start with a blank row and build up # ------------------------- Add the elements to a row ------------------------- # for i, element in enumerate(args): # Loop through list of elements and add them to the row element.Position = (CurrentRowNumber, i) element.ParentContainer = self CurrentRow.append(element) # ------------------------- Append the row to list of Rows ------------------------- # self.Rows.append(CurrentRow)
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Parms are a variable number of Elements
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L3638-L3649
train
PySimpleGUI/PySimpleGUI
PySimpleGUI27.py
Window.SetAlpha
def SetAlpha(self, alpha): ''' Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return: ''' self._AlphaChannel = alpha self.TKroot.attributes('-alpha', alpha)
python
def SetAlpha(self, alpha): ''' Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return: ''' self._AlphaChannel = alpha self.TKroot.attributes('-alpha', alpha)
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Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUI27.py#L4079-L4086
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Uno_Card_Game.py
Card.setColor
def setColor(self, color): '''Sets Card's color and escape code.''' if color == 'blue': self.color = 'blue' self.colorCode = self.colors['blue'] self.colorCodeDark = self.colors['dblue'] elif color == 'red': self.color = 'red' self.colorCode = self.colors['red'] self.colorCodeDark = self.colors['dred'] elif color == 'yellow': self.color = 'yellow' self.colorCode = self.colors['yellow'] self.colorCodeDark = self.colors['dyellow'] elif color == 'green': self.color = 'green' self.colorCode = self.colors['green'] self.colorCodeDark = self.colors['dgreen'] elif color == 'wild': # No color modification self.wild = True self.color = 'wild' self.colorCodeDark = self.colors['dwild'] self.colorCode = self.colors['wild']
python
def setColor(self, color): '''Sets Card's color and escape code.''' if color == 'blue': self.color = 'blue' self.colorCode = self.colors['blue'] self.colorCodeDark = self.colors['dblue'] elif color == 'red': self.color = 'red' self.colorCode = self.colors['red'] self.colorCodeDark = self.colors['dred'] elif color == 'yellow': self.color = 'yellow' self.colorCode = self.colors['yellow'] self.colorCodeDark = self.colors['dyellow'] elif color == 'green': self.color = 'green' self.colorCode = self.colors['green'] self.colorCodeDark = self.colors['dgreen'] elif color == 'wild': # No color modification self.wild = True self.color = 'wild' self.colorCodeDark = self.colors['dwild'] self.colorCode = self.colors['wild']
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Sets Card's color and escape code.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Uno_Card_Game.py#L633-L655
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Img_Viewer.py
get_img_data
def get_img_data(f, maxsize = (1200, 850), first = False): """Generate image data using PIL """ img = Image.open(f) img.thumbnail(maxsize) if first: # tkinter is inactive the first time bio = io.BytesIO() img.save(bio, format = "PNG") del img return bio.getvalue() return ImageTk.PhotoImage(img)
python
def get_img_data(f, maxsize = (1200, 850), first = False): """Generate image data using PIL """ img = Image.open(f) img.thumbnail(maxsize) if first: # tkinter is inactive the first time bio = io.BytesIO() img.save(bio, format = "PNG") del img return bio.getvalue() return ImageTk.PhotoImage(img)
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Generate image data using PIL
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Img_Viewer.py#L50-L60
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Matplotlib_Ping_Graph.py
do_one
def do_one(myStats, destIP, hostname, timeout, mySeqNumber, packet_size, quiet=False): """ Returns either the delay (in ms) or None on timeout. """ delay = None try: # One could use UDP here, but it's obscure mySocket = socket.socket(socket.AF_INET, socket.SOCK_RAW, socket.getprotobyname("icmp")) except socket.error as e: print("failed. (socket error: '%s')" % e.args[1]) raise # raise the original error my_ID = os.getpid() & 0xFFFF sentTime = send_one_ping(mySocket, destIP, my_ID, mySeqNumber, packet_size) if sentTime == None: mySocket.close() return delay myStats.pktsSent += 1 recvTime, dataSize, iphSrcIP, icmpSeqNumber, iphTTL = receive_one_ping(mySocket, my_ID, timeout) mySocket.close() if recvTime: delay = (recvTime - sentTime) * 1000 if not quiet: print("%d bytes from %s: icmp_seq=%d ttl=%d time=%d ms" % ( dataSize, socket.inet_ntoa(struct.pack("!I", iphSrcIP)), icmpSeqNumber, iphTTL, delay) ) myStats.pktsRcvd += 1 myStats.totTime += delay if myStats.minTime > delay: myStats.minTime = delay if myStats.maxTime < delay: myStats.maxTime = delay else: delay = None print("Request timed out.") return delay
python
def do_one(myStats, destIP, hostname, timeout, mySeqNumber, packet_size, quiet=False): """ Returns either the delay (in ms) or None on timeout. """ delay = None try: # One could use UDP here, but it's obscure mySocket = socket.socket(socket.AF_INET, socket.SOCK_RAW, socket.getprotobyname("icmp")) except socket.error as e: print("failed. (socket error: '%s')" % e.args[1]) raise # raise the original error my_ID = os.getpid() & 0xFFFF sentTime = send_one_ping(mySocket, destIP, my_ID, mySeqNumber, packet_size) if sentTime == None: mySocket.close() return delay myStats.pktsSent += 1 recvTime, dataSize, iphSrcIP, icmpSeqNumber, iphTTL = receive_one_ping(mySocket, my_ID, timeout) mySocket.close() if recvTime: delay = (recvTime - sentTime) * 1000 if not quiet: print("%d bytes from %s: icmp_seq=%d ttl=%d time=%d ms" % ( dataSize, socket.inet_ntoa(struct.pack("!I", iphSrcIP)), icmpSeqNumber, iphTTL, delay) ) myStats.pktsRcvd += 1 myStats.totTime += delay if myStats.minTime > delay: myStats.minTime = delay if myStats.maxTime < delay: myStats.maxTime = delay else: delay = None print("Request timed out.") return delay
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Returns either the delay (in ms) or None on timeout.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Matplotlib_Ping_Graph.py#L315-L356
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Matplotlib_Ping_Graph.py
quiet_ping
def quiet_ping(hostname, timeout=WAIT_TIMEOUT, count=NUM_PACKETS, packet_size=PACKET_SIZE, path_finder=False): """ Same as verbose_ping, but the results are returned as tuple """ myStats = MyStats() # Reset the stats mySeqNumber = 0 # Starting value try: destIP = socket.gethostbyname(hostname) except socket.gaierror as e: return 0,0,0,0 myStats.thisIP = destIP # This will send packet that we dont care about 0.5 seconds before it starts # acrutally pinging. This is needed in big MAN/LAN networks where you sometimes # loose the first packet. (while the switches find the way... :/ ) if path_finder: fakeStats = MyStats() do_one(fakeStats, destIP, hostname, timeout, mySeqNumber, packet_size, quiet=True) time.sleep(0.5) for i in range(count): delay = do_one(myStats, destIP, hostname, timeout, mySeqNumber, packet_size, quiet=True) if delay == None: delay = 0 mySeqNumber += 1 # Pause for the remainder of the MAX_SLEEP period (if applicable) if (MAX_SLEEP > delay): time.sleep((MAX_SLEEP - delay)/1000) if myStats.pktsSent > 0: myStats.fracLoss = (myStats.pktsSent - myStats.pktsRcvd)/myStats.pktsSent if myStats.pktsRcvd > 0: myStats.avrgTime = myStats.totTime / myStats.pktsRcvd # return tuple(max_rtt, min_rtt, avrg_rtt, percent_lost) return myStats.maxTime, myStats.minTime, myStats.avrgTime, myStats.fracLoss
python
def quiet_ping(hostname, timeout=WAIT_TIMEOUT, count=NUM_PACKETS, packet_size=PACKET_SIZE, path_finder=False): """ Same as verbose_ping, but the results are returned as tuple """ myStats = MyStats() # Reset the stats mySeqNumber = 0 # Starting value try: destIP = socket.gethostbyname(hostname) except socket.gaierror as e: return 0,0,0,0 myStats.thisIP = destIP # This will send packet that we dont care about 0.5 seconds before it starts # acrutally pinging. This is needed in big MAN/LAN networks where you sometimes # loose the first packet. (while the switches find the way... :/ ) if path_finder: fakeStats = MyStats() do_one(fakeStats, destIP, hostname, timeout, mySeqNumber, packet_size, quiet=True) time.sleep(0.5) for i in range(count): delay = do_one(myStats, destIP, hostname, timeout, mySeqNumber, packet_size, quiet=True) if delay == None: delay = 0 mySeqNumber += 1 # Pause for the remainder of the MAX_SLEEP period (if applicable) if (MAX_SLEEP > delay): time.sleep((MAX_SLEEP - delay)/1000) if myStats.pktsSent > 0: myStats.fracLoss = (myStats.pktsSent - myStats.pktsRcvd)/myStats.pktsSent if myStats.pktsRcvd > 0: myStats.avrgTime = myStats.totTime / myStats.pktsRcvd # return tuple(max_rtt, min_rtt, avrg_rtt, percent_lost) return myStats.maxTime, myStats.minTime, myStats.avrgTime, myStats.fracLoss
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Same as verbose_ping, but the results are returned as tuple
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Matplotlib_Ping_Graph.py#L527-L570
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_DOC_Viewer_PIL.py
get_page
def get_page(pno, zoom = False, max_size = None, first = False): """Return a PNG image for a document page number. """ dlist = dlist_tab[pno] # get display list of page number if not dlist: # create if not yet there dlist_tab[pno] = doc[pno].getDisplayList() dlist = dlist_tab[pno] r = dlist.rect # the page rectangle clip = r # ensure image fits screen: # exploit, but do not exceed width or height zoom_0 = 1 if max_size: zoom_0 = min(1, max_size[0] / r.width, max_size[1] / r.height) if zoom_0 == 1: zoom_0 = min(max_size[0] / r.width, max_size[1] / r.height) mat_0 = fitz.Matrix(zoom_0, zoom_0) if not zoom: # show total page pix = dlist.getPixmap(matrix = mat_0, alpha=False) else: mp = r.tl + (r.br - r.tl) * 0.5 # page rect center w2 = r.width / 2 h2 = r.height / 2 clip = r * 0.5 tl = zoom[0] # old top-left tl.x += zoom[1] * (w2 / 2) tl.x = max(0, tl.x) tl.x = min(w2, tl.x) tl.y += zoom[2] * (h2 / 2) tl.y = max(0, tl.y) tl.y = min(h2, tl.y) clip = fitz.Rect(tl, tl.x + w2, tl.y + h2) mat = mat_0 * fitz.Matrix(2, 2) # zoom matrix pix = dlist.getPixmap(alpha=False, matrix=mat, clip=clip) if first: # first call: tkinter still inactive img = pix.getPNGData() # so use fitz png output else: # else take tk photo image pilimg = Image.frombytes("RGB", [pix.width, pix.height], pix.samples) img = ImageTk.PhotoImage(pilimg) return img, clip.tl
python
def get_page(pno, zoom = False, max_size = None, first = False): """Return a PNG image for a document page number. """ dlist = dlist_tab[pno] # get display list of page number if not dlist: # create if not yet there dlist_tab[pno] = doc[pno].getDisplayList() dlist = dlist_tab[pno] r = dlist.rect # the page rectangle clip = r # ensure image fits screen: # exploit, but do not exceed width or height zoom_0 = 1 if max_size: zoom_0 = min(1, max_size[0] / r.width, max_size[1] / r.height) if zoom_0 == 1: zoom_0 = min(max_size[0] / r.width, max_size[1] / r.height) mat_0 = fitz.Matrix(zoom_0, zoom_0) if not zoom: # show total page pix = dlist.getPixmap(matrix = mat_0, alpha=False) else: mp = r.tl + (r.br - r.tl) * 0.5 # page rect center w2 = r.width / 2 h2 = r.height / 2 clip = r * 0.5 tl = zoom[0] # old top-left tl.x += zoom[1] * (w2 / 2) tl.x = max(0, tl.x) tl.x = min(w2, tl.x) tl.y += zoom[2] * (h2 / 2) tl.y = max(0, tl.y) tl.y = min(h2, tl.y) clip = fitz.Rect(tl, tl.x + w2, tl.y + h2) mat = mat_0 * fitz.Matrix(2, 2) # zoom matrix pix = dlist.getPixmap(alpha=False, matrix=mat, clip=clip) if first: # first call: tkinter still inactive img = pix.getPNGData() # so use fitz png output else: # else take tk photo image pilimg = Image.frombytes("RGB", [pix.width, pix.height], pix.samples) img = ImageTk.PhotoImage(pilimg) return img, clip.tl
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Return a PNG image for a document page number.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_DOC_Viewer_PIL.py#L75-L118
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Conways_Game_of_Life.py
GameOfLife.live_neighbours
def live_neighbours(self, i, j): """ Count the number of live neighbours around point (i, j). """ s = 0 # The total number of live neighbours. # Loop over all the neighbours. for x in [i - 1, i, i + 1]: for y in [j - 1, j, j + 1]: if (x == i and y == j): continue # Skip the current point itself - we only want to count the neighbours! if (x != self.N and y != self.N): s += self.old_grid[x][y] # The remaining branches handle the case where the neighbour is off the end of the grid. # In this case, we loop back round such that the grid becomes a "toroidal array". elif (x == self.N and y != self.N): s += self.old_grid[0][y] elif (x != self.N and y == self.N): s += self.old_grid[x][0] else: s += self.old_grid[0][0] return s
python
def live_neighbours(self, i, j): """ Count the number of live neighbours around point (i, j). """ s = 0 # The total number of live neighbours. # Loop over all the neighbours. for x in [i - 1, i, i + 1]: for y in [j - 1, j, j + 1]: if (x == i and y == j): continue # Skip the current point itself - we only want to count the neighbours! if (x != self.N and y != self.N): s += self.old_grid[x][y] # The remaining branches handle the case where the neighbour is off the end of the grid. # In this case, we loop back round such that the grid becomes a "toroidal array". elif (x == self.N and y != self.N): s += self.old_grid[0][y] elif (x != self.N and y == self.N): s += self.old_grid[x][0] else: s += self.old_grid[0][0] return s
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Count the number of live neighbours around point (i, j).
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Conways_Game_of_Life.py#L49-L67
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Conways_Game_of_Life.py
GameOfLife.play
def play(self): """ Play Conway's Game of Life. """ # Write the initial configuration to file. self.t = 1 # Current time level while self.t <= self.T: # Evolve! # print( "At time level %d" % t) # Loop over each cell of the grid and apply Conway's rules. for i in range(self.N): for j in range(self.N): live = self.live_neighbours(i, j) if (self.old_grid[i][j] == 1 and live < 2): self.new_grid[i][j] = 0 # Dead from starvation. elif (self.old_grid[i][j] == 1 and (live == 2 or live == 3)): self.new_grid[i][j] = 1 # Continue living. elif (self.old_grid[i][j] == 1 and live > 3): self.new_grid[i][j] = 0 # Dead from overcrowding. elif (self.old_grid[i][j] == 0 and live == 3): self.new_grid[i][j] = 1 # Alive from reproduction. # Output the new configuration. # The new configuration becomes the old configuration for the next generation. self.old_grid = self.new_grid.copy() self.draw_board() # Move on to the next time level self.t += 1
python
def play(self): """ Play Conway's Game of Life. """ # Write the initial configuration to file. self.t = 1 # Current time level while self.t <= self.T: # Evolve! # print( "At time level %d" % t) # Loop over each cell of the grid and apply Conway's rules. for i in range(self.N): for j in range(self.N): live = self.live_neighbours(i, j) if (self.old_grid[i][j] == 1 and live < 2): self.new_grid[i][j] = 0 # Dead from starvation. elif (self.old_grid[i][j] == 1 and (live == 2 or live == 3)): self.new_grid[i][j] = 1 # Continue living. elif (self.old_grid[i][j] == 1 and live > 3): self.new_grid[i][j] = 0 # Dead from overcrowding. elif (self.old_grid[i][j] == 0 and live == 3): self.new_grid[i][j] = 1 # Alive from reproduction. # Output the new configuration. # The new configuration becomes the old configuration for the next generation. self.old_grid = self.new_grid.copy() self.draw_board() # Move on to the next time level self.t += 1
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Play Conway's Game of Life.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Conways_Game_of_Life.py#L69-L97
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Desktop_Widget_psutil_Dashboard.py
human_size
def human_size(bytes, units=[' bytes','KB','MB','GB','TB', 'PB', 'EB']): """ Returns a human readable string reprentation of bytes""" return str(bytes) + units[0] if bytes < 1024 else human_size(bytes>>10, units[1:])
python
def human_size(bytes, units=[' bytes','KB','MB','GB','TB', 'PB', 'EB']): """ Returns a human readable string reprentation of bytes""" return str(bytes) + units[0] if bytes < 1024 else human_size(bytes>>10, units[1:])
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Returns a human readable string reprentation of bytes
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Desktop_Widget_psutil_Dashboard.py#L51-L53
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/Demo Programs/Web_Demo_HowDoI.py
HowDoI
def HowDoI(): ''' Make and show a window (PySimpleGUI form) that takes user input and sends to the HowDoI web oracle Excellent example of 2 GUI concepts 1. Output Element that will show text in a scrolled window 2. Non-Window-Closing Buttons - These buttons will cause the form to return with the form's values, but doesn't close the form :return: never returns ''' # ------- Make a new Window ------- # sg.ChangeLookAndFeel('GreenTan') # give our form a spiffy set of colors layout = [ [sg.Text('Ask and your answer will appear here....', size=(40, 1))], [sg.MultilineOutput(size_px=(980, 400),key='_OUTPUT_' )], # [ sg.Spin(values=(1, 2, 3, 4), initial_value=1, size=(2, 1), key='Num Answers', font='Helvetica 15'), [ sg.Checkbox('Display Full Text', key='full text', font='Helvetica 15'), sg.T('Command History', font='Helvetica 15'), sg.T('', size=(40,3), text_color=sg.BLUES[0], key='history')], [sg.Multiline(size=(85, 5), enter_submits=True, key='query', do_not_clear=False), sg.ReadButton('SEND', button_color=(sg.YELLOWS[0], sg.BLUES[0]), bind_return_key=True), sg.Button('EXIT', button_color=(sg.YELLOWS[0], sg.GREENS[0]))] ] window = sg.Window('How Do I ??', default_element_size=(30,1), icon=DEFAULT_ICON, font=('Helvetica',' 17'), default_button_element_size=(8,2), return_keyboard_events=False, ) window.Layout(layout) # ---===--- Loop taking in user input and using it to query HowDoI --- # command_history = [] history_offset = 0 while True: event, values = window.Read() # print(event, values) if type(event) is int: event = str(event) if event == 'SEND': query = values['query'].rstrip() window.Element('_OUTPUT_').Update(query, append=True) print(query) QueryHowDoI(query, 1, values['full text'], window) # send the string to HowDoI command_history.append(query) history_offset = len(command_history)-1 window.FindElement('query').Update('') # manually clear input because keyboard events blocks clear window.FindElement('history').Update('\n'.join(command_history[-3:])) elif event == None or event == 'EXIT': # if exit button or closed using X break elif 'Up' in event and len(command_history): # scroll back in history command = command_history[history_offset] history_offset -= 1 * (history_offset > 0) # decrement is not zero window.FindElement('query').Update(command) elif 'Down' in event and len(command_history): # scroll forward in history history_offset += 1 * (history_offset < len(command_history)-1) # increment up to end of list command = command_history[history_offset] window.FindElement('query').Update(command) elif 'Escape' in event: # clear currently line window.FindElement('query').Update('') window.Close()
python
def HowDoI(): ''' Make and show a window (PySimpleGUI form) that takes user input and sends to the HowDoI web oracle Excellent example of 2 GUI concepts 1. Output Element that will show text in a scrolled window 2. Non-Window-Closing Buttons - These buttons will cause the form to return with the form's values, but doesn't close the form :return: never returns ''' # ------- Make a new Window ------- # sg.ChangeLookAndFeel('GreenTan') # give our form a spiffy set of colors layout = [ [sg.Text('Ask and your answer will appear here....', size=(40, 1))], [sg.MultilineOutput(size_px=(980, 400),key='_OUTPUT_' )], # [ sg.Spin(values=(1, 2, 3, 4), initial_value=1, size=(2, 1), key='Num Answers', font='Helvetica 15'), [ sg.Checkbox('Display Full Text', key='full text', font='Helvetica 15'), sg.T('Command History', font='Helvetica 15'), sg.T('', size=(40,3), text_color=sg.BLUES[0], key='history')], [sg.Multiline(size=(85, 5), enter_submits=True, key='query', do_not_clear=False), sg.ReadButton('SEND', button_color=(sg.YELLOWS[0], sg.BLUES[0]), bind_return_key=True), sg.Button('EXIT', button_color=(sg.YELLOWS[0], sg.GREENS[0]))] ] window = sg.Window('How Do I ??', default_element_size=(30,1), icon=DEFAULT_ICON, font=('Helvetica',' 17'), default_button_element_size=(8,2), return_keyboard_events=False, ) window.Layout(layout) # ---===--- Loop taking in user input and using it to query HowDoI --- # command_history = [] history_offset = 0 while True: event, values = window.Read() # print(event, values) if type(event) is int: event = str(event) if event == 'SEND': query = values['query'].rstrip() window.Element('_OUTPUT_').Update(query, append=True) print(query) QueryHowDoI(query, 1, values['full text'], window) # send the string to HowDoI command_history.append(query) history_offset = len(command_history)-1 window.FindElement('query').Update('') # manually clear input because keyboard events blocks clear window.FindElement('history').Update('\n'.join(command_history[-3:])) elif event == None or event == 'EXIT': # if exit button or closed using X break elif 'Up' in event and len(command_history): # scroll back in history command = command_history[history_offset] history_offset -= 1 * (history_offset > 0) # decrement is not zero window.FindElement('query').Update(command) elif 'Down' in event and len(command_history): # scroll forward in history history_offset += 1 * (history_offset < len(command_history)-1) # increment up to end of list command = command_history[history_offset] window.FindElement('query').Update(command) elif 'Escape' in event: # clear currently line window.FindElement('query').Update('') window.Close()
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/Demo Programs/Web_Demo_HowDoI.py#L14-L68
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/Demo Programs/Web_Demo_HowDoI.py
QueryHowDoI
def QueryHowDoI(Query, num_answers, full_text, window:sg.Window): ''' Kicks off a subprocess to send the 'Query' to HowDoI Prints the result, which in this program will route to a gooeyGUI window :param Query: text english question to ask the HowDoI web engine :return: nothing ''' howdoi_command = HOW_DO_I_COMMAND full_text_option = ' -a' if full_text else '' t = subprocess.Popen(howdoi_command + ' \"'+ Query + '\" -n ' + str(num_answers)+full_text_option, stdout=subprocess.PIPE) (output, err) = t.communicate() window.Element('_OUTPUT_').Update('{:^88}'.format(Query.rstrip()), append=True) window.Element('_OUTPUT_').Update('_'*60, append=True) window.Element('_OUTPUT_').Update(output.decode("utf-8"), append=True) exit_code = t.wait()
python
def QueryHowDoI(Query, num_answers, full_text, window:sg.Window): ''' Kicks off a subprocess to send the 'Query' to HowDoI Prints the result, which in this program will route to a gooeyGUI window :param Query: text english question to ask the HowDoI web engine :return: nothing ''' howdoi_command = HOW_DO_I_COMMAND full_text_option = ' -a' if full_text else '' t = subprocess.Popen(howdoi_command + ' \"'+ Query + '\" -n ' + str(num_answers)+full_text_option, stdout=subprocess.PIPE) (output, err) = t.communicate() window.Element('_OUTPUT_').Update('{:^88}'.format(Query.rstrip()), append=True) window.Element('_OUTPUT_').Update('_'*60, append=True) window.Element('_OUTPUT_').Update(output.decode("utf-8"), append=True) exit_code = t.wait()
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/Demo Programs/Web_Demo_HowDoI.py#L70-L84
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/Demo Programs/widgets_overview_app.py
MyApp.list_view_on_selected
def list_view_on_selected(self, widget, selected_item_key): """ The selection event of the listView, returns a key of the clicked event. You can retrieve the item rapidly """ self.lbl.set_text('List selection: ' + self.listView.children[selected_item_key].get_text())
python
def list_view_on_selected(self, widget, selected_item_key): """ The selection event of the listView, returns a key of the clicked event. You can retrieve the item rapidly """ self.lbl.set_text('List selection: ' + self.listView.children[selected_item_key].get_text())
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The selection event of the listView, returns a key of the clicked event. You can retrieve the item rapidly
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/Demo Programs/widgets_overview_app.py#L281-L285
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Matplotlib_Browser_Paned.py
PyplotHistogram
def PyplotHistogram(): """ ============================================================= Demo of the histogram (hist) function with multiple data sets ============================================================= Plot histogram with multiple sample sets and demonstrate: * Use of legend with multiple sample sets * Stacked bars * Step curve with no fill * Data sets of different sample sizes Selecting different bin counts and sizes can significantly affect the shape of a histogram. The Astropy docs have a great section on how to select these parameters: http://docs.astropy.org/en/stable/visualization/histogram.html """ import numpy as np import matplotlib.pyplot as plt np.random.seed(0) n_bins = 10 x = np.random.randn(1000, 3) fig, axes = plt.subplots(nrows=2, ncols=2) ax0, ax1, ax2, ax3 = axes.flatten() colors = ['red', 'tan', 'lime'] ax0.hist(x, n_bins, normed=1, histtype='bar', color=colors, label=colors) ax0.legend(prop={'size': 10}) ax0.set_title('bars with legend') ax1.hist(x, n_bins, normed=1, histtype='bar', stacked=True) ax1.set_title('stacked bar') ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False) ax2.set_title('stack step (unfilled)') # Make a multiple-histogram of data-sets with different length. x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]] ax3.hist(x_multi, n_bins, histtype='bar') ax3.set_title('different sample sizes') fig.tight_layout() return fig
python
def PyplotHistogram(): """ ============================================================= Demo of the histogram (hist) function with multiple data sets ============================================================= Plot histogram with multiple sample sets and demonstrate: * Use of legend with multiple sample sets * Stacked bars * Step curve with no fill * Data sets of different sample sizes Selecting different bin counts and sizes can significantly affect the shape of a histogram. The Astropy docs have a great section on how to select these parameters: http://docs.astropy.org/en/stable/visualization/histogram.html """ import numpy as np import matplotlib.pyplot as plt np.random.seed(0) n_bins = 10 x = np.random.randn(1000, 3) fig, axes = plt.subplots(nrows=2, ncols=2) ax0, ax1, ax2, ax3 = axes.flatten() colors = ['red', 'tan', 'lime'] ax0.hist(x, n_bins, normed=1, histtype='bar', color=colors, label=colors) ax0.legend(prop={'size': 10}) ax0.set_title('bars with legend') ax1.hist(x, n_bins, normed=1, histtype='bar', stacked=True) ax1.set_title('stacked bar') ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False) ax2.set_title('stack step (unfilled)') # Make a multiple-histogram of data-sets with different length. x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]] ax3.hist(x_multi, n_bins, histtype='bar') ax3.set_title('different sample sizes') fig.tight_layout() return fig
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============================================================= Demo of the histogram (hist) function with multiple data sets ============================================================= Plot histogram with multiple sample sets and demonstrate: * Use of legend with multiple sample sets * Stacked bars * Step curve with no fill * Data sets of different sample sizes Selecting different bin counts and sizes can significantly affect the shape of a histogram. The Astropy docs have a great section on how to select these parameters: http://docs.astropy.org/en/stable/visualization/histogram.html
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Matplotlib_Browser_Paned.py#L44-L91
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Matplotlib_Browser_Paned.py
PyplotArtistBoxPlots
def PyplotArtistBoxPlots(): """ ========================================= Demo of artist customization in box plots ========================================= This example demonstrates how to use the various kwargs to fully customize box plots. The first figure demonstrates how to remove and add individual components (note that the mean is the only value not shown by default). The second figure demonstrates how the styles of the artists can be customized. It also demonstrates how to set the limit of the whiskers to specific percentiles (lower right axes) A good general reference on boxplots and their history can be found here: http://vita.had.co.nz/papers/boxplots.pdf """ import numpy as np import matplotlib.pyplot as plt # fake data np.random.seed(937) data = np.random.lognormal(size=(37, 4), mean=1.5, sigma=1.75) labels = list('ABCD') fs = 10 # fontsize # demonstrate how to toggle the display of different elements: fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(6, 6), sharey=True) axes[0, 0].boxplot(data, labels=labels) axes[0, 0].set_title('Default', fontsize=fs) axes[0, 1].boxplot(data, labels=labels, showmeans=True) axes[0, 1].set_title('showmeans=True', fontsize=fs) axes[0, 2].boxplot(data, labels=labels, showmeans=True, meanline=True) axes[0, 2].set_title('showmeans=True,\nmeanline=True', fontsize=fs) axes[1, 0].boxplot(data, labels=labels, showbox=False, showcaps=False) tufte_title = 'Tufte Style \n(showbox=False,\nshowcaps=False)' axes[1, 0].set_title(tufte_title, fontsize=fs) axes[1, 1].boxplot(data, labels=labels, notch=True, bootstrap=10000) axes[1, 1].set_title('notch=True,\nbootstrap=10000', fontsize=fs) axes[1, 2].boxplot(data, labels=labels, showfliers=False) axes[1, 2].set_title('showfliers=False', fontsize=fs) for ax in axes.flatten(): ax.set_yscale('log') ax.set_yticklabels([]) fig.subplots_adjust(hspace=0.4) return fig
python
def PyplotArtistBoxPlots(): """ ========================================= Demo of artist customization in box plots ========================================= This example demonstrates how to use the various kwargs to fully customize box plots. The first figure demonstrates how to remove and add individual components (note that the mean is the only value not shown by default). The second figure demonstrates how the styles of the artists can be customized. It also demonstrates how to set the limit of the whiskers to specific percentiles (lower right axes) A good general reference on boxplots and their history can be found here: http://vita.had.co.nz/papers/boxplots.pdf """ import numpy as np import matplotlib.pyplot as plt # fake data np.random.seed(937) data = np.random.lognormal(size=(37, 4), mean=1.5, sigma=1.75) labels = list('ABCD') fs = 10 # fontsize # demonstrate how to toggle the display of different elements: fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(6, 6), sharey=True) axes[0, 0].boxplot(data, labels=labels) axes[0, 0].set_title('Default', fontsize=fs) axes[0, 1].boxplot(data, labels=labels, showmeans=True) axes[0, 1].set_title('showmeans=True', fontsize=fs) axes[0, 2].boxplot(data, labels=labels, showmeans=True, meanline=True) axes[0, 2].set_title('showmeans=True,\nmeanline=True', fontsize=fs) axes[1, 0].boxplot(data, labels=labels, showbox=False, showcaps=False) tufte_title = 'Tufte Style \n(showbox=False,\nshowcaps=False)' axes[1, 0].set_title(tufte_title, fontsize=fs) axes[1, 1].boxplot(data, labels=labels, notch=True, bootstrap=10000) axes[1, 1].set_title('notch=True,\nbootstrap=10000', fontsize=fs) axes[1, 2].boxplot(data, labels=labels, showfliers=False) axes[1, 2].set_title('showfliers=False', fontsize=fs) for ax in axes.flatten(): ax.set_yscale('log') ax.set_yticklabels([]) fig.subplots_adjust(hspace=0.4) return fig
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========================================= Demo of artist customization in box plots ========================================= This example demonstrates how to use the various kwargs to fully customize box plots. The first figure demonstrates how to remove and add individual components (note that the mean is the only value not shown by default). The second figure demonstrates how the styles of the artists can be customized. It also demonstrates how to set the limit of the whiskers to specific percentiles (lower right axes) A good general reference on boxplots and their history can be found here: http://vita.had.co.nz/papers/boxplots.pdf
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Matplotlib_Browser_Paned.py#L93-L147
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Matplotlib_Browser_Paned.py
PyplotLineStyles
def PyplotLineStyles(): """ ========== Linestyles ========== This examples showcases different linestyles copying those of Tikz/PGF. """ import numpy as np import matplotlib.pyplot as plt from collections import OrderedDict from matplotlib.transforms import blended_transform_factory linestyles = OrderedDict( [('solid', (0, ())), ('loosely dotted', (0, (1, 10))), ('dotted', (0, (1, 5))), ('densely dotted', (0, (1, 1))), ('loosely dashed', (0, (5, 10))), ('dashed', (0, (5, 5))), ('densely dashed', (0, (5, 1))), ('loosely dashdotted', (0, (3, 10, 1, 10))), ('dashdotted', (0, (3, 5, 1, 5))), ('densely dashdotted', (0, (3, 1, 1, 1))), ('loosely dashdotdotted', (0, (3, 10, 1, 10, 1, 10))), ('dashdotdotted', (0, (3, 5, 1, 5, 1, 5))), ('densely dashdotdotted', (0, (3, 1, 1, 1, 1, 1)))]) plt.figure(figsize=(10, 6)) ax = plt.subplot(1, 1, 1) X, Y = np.linspace(0, 100, 10), np.zeros(10) for i, (name, linestyle) in enumerate(linestyles.items()): ax.plot(X, Y + i, linestyle=linestyle, linewidth=1.5, color='black') ax.set_ylim(-0.5, len(linestyles) - 0.5) plt.yticks(np.arange(len(linestyles)), linestyles.keys()) plt.xticks([]) # For each line style, add a text annotation with a small offset from # the reference point (0 in Axes coords, y tick value in Data coords). reference_transform = blended_transform_factory(ax.transAxes, ax.transData) for i, (name, linestyle) in enumerate(linestyles.items()): ax.annotate(str(linestyle), xy=(0.0, i), xycoords=reference_transform, xytext=(-6, -12), textcoords='offset points', color="blue", fontsize=8, ha="right", family="monospace") plt.tight_layout() return plt.gcf()
python
def PyplotLineStyles(): """ ========== Linestyles ========== This examples showcases different linestyles copying those of Tikz/PGF. """ import numpy as np import matplotlib.pyplot as plt from collections import OrderedDict from matplotlib.transforms import blended_transform_factory linestyles = OrderedDict( [('solid', (0, ())), ('loosely dotted', (0, (1, 10))), ('dotted', (0, (1, 5))), ('densely dotted', (0, (1, 1))), ('loosely dashed', (0, (5, 10))), ('dashed', (0, (5, 5))), ('densely dashed', (0, (5, 1))), ('loosely dashdotted', (0, (3, 10, 1, 10))), ('dashdotted', (0, (3, 5, 1, 5))), ('densely dashdotted', (0, (3, 1, 1, 1))), ('loosely dashdotdotted', (0, (3, 10, 1, 10, 1, 10))), ('dashdotdotted', (0, (3, 5, 1, 5, 1, 5))), ('densely dashdotdotted', (0, (3, 1, 1, 1, 1, 1)))]) plt.figure(figsize=(10, 6)) ax = plt.subplot(1, 1, 1) X, Y = np.linspace(0, 100, 10), np.zeros(10) for i, (name, linestyle) in enumerate(linestyles.items()): ax.plot(X, Y + i, linestyle=linestyle, linewidth=1.5, color='black') ax.set_ylim(-0.5, len(linestyles) - 0.5) plt.yticks(np.arange(len(linestyles)), linestyles.keys()) plt.xticks([]) # For each line style, add a text annotation with a small offset from # the reference point (0 in Axes coords, y tick value in Data coords). reference_transform = blended_transform_factory(ax.transAxes, ax.transData) for i, (name, linestyle) in enumerate(linestyles.items()): ax.annotate(str(linestyle), xy=(0.0, i), xycoords=reference_transform, xytext=(-6, -12), textcoords='offset points', color="blue", fontsize=8, ha="right", family="monospace") plt.tight_layout() return plt.gcf()
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========== Linestyles ========== This examples showcases different linestyles copying those of Tikz/PGF.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Matplotlib_Browser_Paned.py#L211-L262
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
convert_tkinter_size_to_Qt
def convert_tkinter_size_to_Qt(size): """ Converts size in characters to size in pixels :param size: size in characters, rows :return: size in pixels, pixels """ qtsize = size if size[1] is not None and size[1] < DEFAULT_PIXEL_TO_CHARS_CUTOFF: # change from character based size to pixels (roughly) qtsize = size[0]*DEFAULT_PIXELS_TO_CHARS_SCALING[0], size[1]*DEFAULT_PIXELS_TO_CHARS_SCALING[1] return qtsize
python
def convert_tkinter_size_to_Qt(size): """ Converts size in characters to size in pixels :param size: size in characters, rows :return: size in pixels, pixels """ qtsize = size if size[1] is not None and size[1] < DEFAULT_PIXEL_TO_CHARS_CUTOFF: # change from character based size to pixels (roughly) qtsize = size[0]*DEFAULT_PIXELS_TO_CHARS_SCALING[0], size[1]*DEFAULT_PIXELS_TO_CHARS_SCALING[1] return qtsize
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L3730-L3739
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
create_style_from_font
def create_style_from_font(font): """ Convert from font string/tyuple into a Qt style sheet string :param font: "Arial 10 Bold" or ('Arial', 10, 'Bold) :return: style string that can be combined with other style strings """ if font is None: return '' if type(font) is str: _font = font.split(' ') else: _font = font style = '' style += 'font-family: %s;\n' % _font[0] style += 'font-size: %spt;\n' % _font[1] font_items = '' for item in _font[2:]: if item == 'underline': style += 'text-decoration: underline;\n' else: font_items += item + ' ' if font_items != '': style += 'font: %s;\n' % (font_items) return style
python
def create_style_from_font(font): """ Convert from font string/tyuple into a Qt style sheet string :param font: "Arial 10 Bold" or ('Arial', 10, 'Bold) :return: style string that can be combined with other style strings """ if font is None: return '' if type(font) is str: _font = font.split(' ') else: _font = font style = '' style += 'font-family: %s;\n' % _font[0] style += 'font-size: %spt;\n' % _font[1] font_items = '' for item in _font[2:]: if item == 'underline': style += 'text-decoration: underline;\n' else: font_items += item + ' ' if font_items != '': style += 'font: %s;\n' % (font_items) return style
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Convert from font string/tyuple into a Qt style sheet string :param font: "Arial 10 Bold" or ('Arial', 10, 'Bold) :return: style string that can be combined with other style strings
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L3756-L3782
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
PopupGetFolder
def PopupGetFolder(message, title=None, default_path='', no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for folder :param message: :param default_path: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Contents of text field. None if closed using X or cancelled """ if no_window: if Window.QTApplication is None: Window.QTApplication = QApplication(sys.argv) folder_name = QFileDialog.getExistingDirectory(dir=initial_folder) return folder_name layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=size), FolderBrowse(initial_folder=initial_folder)], [CloseButton('Ok', size=(60, 20), bind_return_key=True), CloseButton('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, background_color=background_color, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() if button != 'Ok': return None else: path = input_values[0] return path
python
def PopupGetFolder(message, title=None, default_path='', no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for folder :param message: :param default_path: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Contents of text field. None if closed using X or cancelled """ if no_window: if Window.QTApplication is None: Window.QTApplication = QApplication(sys.argv) folder_name = QFileDialog.getExistingDirectory(dir=initial_folder) return folder_name layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=size), FolderBrowse(initial_folder=initial_folder)], [CloseButton('Ok', size=(60, 20), bind_return_key=True), CloseButton('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, background_color=background_color, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() if button != 'Ok': return None else: path = input_values[0] return path
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L7025-L7070
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
PopupGetFile
def PopupGetFile(message, title=None, default_path='', default_extension='', save_as=False, file_types=(("ALL Files", "*"),), no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for file :param message: :param default_path: :param default_extension: :param save_as: :param file_types: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: string representing the path chosen, None if cancelled or window closed with X """ if no_window: if Window.QTApplication is None: Window.QTApplication = QApplication(sys.argv) if save_as: qt_types = convert_tkinter_filetypes_to_qt(file_types) filename = QFileDialog.getSaveFileName(dir=initial_folder, filter=qt_types) else: qt_types = convert_tkinter_filetypes_to_qt(file_types) filename = QFileDialog.getOpenFileName(dir=initial_folder, filter=qt_types) return filename[0] browse_button = SaveAs(file_types=file_types, initial_folder=initial_folder) if save_as else FileBrowse( file_types=file_types, initial_folder=initial_folder) layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=(30,1)), browse_button], [CButton('Ok', size=(60, 20), bind_return_key=True), CButton('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, font=font, background_color=background_color, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() # window.Close() if button != 'Ok': return None else: path = input_values[0] return path
python
def PopupGetFile(message, title=None, default_path='', default_extension='', save_as=False, file_types=(("ALL Files", "*"),), no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for file :param message: :param default_path: :param default_extension: :param save_as: :param file_types: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: string representing the path chosen, None if cancelled or window closed with X """ if no_window: if Window.QTApplication is None: Window.QTApplication = QApplication(sys.argv) if save_as: qt_types = convert_tkinter_filetypes_to_qt(file_types) filename = QFileDialog.getSaveFileName(dir=initial_folder, filter=qt_types) else: qt_types = convert_tkinter_filetypes_to_qt(file_types) filename = QFileDialog.getOpenFileName(dir=initial_folder, filter=qt_types) return filename[0] browse_button = SaveAs(file_types=file_types, initial_folder=initial_folder) if save_as else FileBrowse( file_types=file_types, initial_folder=initial_folder) layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=(30,1)), browse_button], [CButton('Ok', size=(60, 20), bind_return_key=True), CButton('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, font=font, background_color=background_color, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() # window.Close() if button != 'Ok': return None else: path = input_values[0] return path
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L7075-L7132
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
PopupGetText
def PopupGetText(message, title=None, default_text='', password_char='', size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None)): """ Display Popup with text entry field :param message: :param default_text: :param password_char: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Text entered or None if window was closed """ layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color, font=font)], [InputText(default_text=default_text, size=size, password_char=password_char)], [CloseButton('Ok', size=(60, 20), bind_return_key=True), CloseButton('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, no_titlebar=no_titlebar, background_color=background_color, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() if button != 'Ok': return None else: return input_values[0]
python
def PopupGetText(message, title=None, default_text='', password_char='', size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None)): """ Display Popup with text entry field :param message: :param default_text: :param password_char: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Text entered or None if window was closed """ layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color, font=font)], [InputText(default_text=default_text, size=size, password_char=password_char)], [CloseButton('Ok', size=(60, 20), bind_return_key=True), CloseButton('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, no_titlebar=no_titlebar, background_color=background_color, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() if button != 'Ok': return None else: return input_values[0]
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L7137-L7173
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
SystemTray.Read
def Read(self, timeout=None): ''' Reads the context menu :param timeout: Optional. Any value other than None indicates a non-blocking read :return: ''' if not self.Shown: self.Shown = True self.TrayIcon.show() if timeout is None: self.App.exec_() elif timeout == 0: self.App.processEvents() else: self.timer = start_systray_read_timer(self, timeout) self.App.exec_() if self.timer: stop_timer(self.timer) item = self.MenuItemChosen self.MenuItemChosen = TIMEOUT_KEY return item
python
def Read(self, timeout=None): ''' Reads the context menu :param timeout: Optional. Any value other than None indicates a non-blocking read :return: ''' if not self.Shown: self.Shown = True self.TrayIcon.show() if timeout is None: self.App.exec_() elif timeout == 0: self.App.processEvents() else: self.timer = start_systray_read_timer(self, timeout) self.App.exec_() if self.timer: stop_timer(self.timer) item = self.MenuItemChosen self.MenuItemChosen = TIMEOUT_KEY return item
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L2953-L2975
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
SystemTray.ShowMessage
def ShowMessage(self, title, message, filename=None, data=None, data_base64=None, messageicon=None, time=10000): ''' Shows a balloon above icon in system tray :param title: Title shown in balloon :param message: Message to be displayed :param filename: Optional icon filename :param data: Optional in-ram icon :param data_base64: Optional base64 icon :param time: How long to display message in milliseconds :return: ''' qicon = None if filename is not None: qicon = QIcon(filename) elif data is not None: ba = QtCore.QByteArray.fromRawData(data) pixmap = QtGui.QPixmap() pixmap.loadFromData(ba) qicon = QIcon(pixmap) elif data_base64 is not None: ba = QtCore.QByteArray.fromBase64(data_base64) pixmap = QtGui.QPixmap() pixmap.loadFromData(ba) qicon = QIcon(pixmap) if qicon is not None: self.TrayIcon.showMessage(title, message, qicon, time) elif messageicon is not None: self.TrayIcon.showMessage(title, message, messageicon, time) else: self.TrayIcon.showMessage(title, message, QIcon(), time) self.LastMessage = message self.LastTitle = title return self
python
def ShowMessage(self, title, message, filename=None, data=None, data_base64=None, messageicon=None, time=10000): ''' Shows a balloon above icon in system tray :param title: Title shown in balloon :param message: Message to be displayed :param filename: Optional icon filename :param data: Optional in-ram icon :param data_base64: Optional base64 icon :param time: How long to display message in milliseconds :return: ''' qicon = None if filename is not None: qicon = QIcon(filename) elif data is not None: ba = QtCore.QByteArray.fromRawData(data) pixmap = QtGui.QPixmap() pixmap.loadFromData(ba) qicon = QIcon(pixmap) elif data_base64 is not None: ba = QtCore.QByteArray.fromBase64(data_base64) pixmap = QtGui.QPixmap() pixmap.loadFromData(ba) qicon = QIcon(pixmap) if qicon is not None: self.TrayIcon.showMessage(title, message, qicon, time) elif messageicon is not None: self.TrayIcon.showMessage(title, message, messageicon, time) else: self.TrayIcon.showMessage(title, message, QIcon(), time) self.LastMessage = message self.LastTitle = title return self
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L2988-L3022
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
SystemTray.Update
def Update(self, menu=None, tooltip=None,filename=None, data=None, data_base64=None,): ''' Updates the menu, tooltip or icon :param menu: menu defintion :param tooltip: string representing tooltip :param filename: icon filename :param data: icon raw image :param data_base64: icon base 64 image :return: ''' # Menu if menu is not None: self.Menu = menu qmenu = QMenu() qmenu.setTitle(self.Menu[0]) AddTrayMenuItem(qmenu, self.Menu[1], self) self.TrayIcon.setContextMenu(qmenu) # Tooltip if tooltip is not None: self.TrayIcon.setToolTip(str(tooltip)) # Icon qicon = None if filename is not None: qicon = QIcon(filename) elif data is not None: ba = QtCore.QByteArray.fromRawData(data) pixmap = QtGui.QPixmap() pixmap.loadFromData(ba) qicon = QIcon(pixmap) elif data_base64 is not None: ba = QtCore.QByteArray.fromBase64(data_base64) pixmap = QtGui.QPixmap() pixmap.loadFromData(ba) qicon = QIcon(pixmap) if qicon is not None: self.TrayIcon.setIcon(qicon)
python
def Update(self, menu=None, tooltip=None,filename=None, data=None, data_base64=None,): ''' Updates the menu, tooltip or icon :param menu: menu defintion :param tooltip: string representing tooltip :param filename: icon filename :param data: icon raw image :param data_base64: icon base 64 image :return: ''' # Menu if menu is not None: self.Menu = menu qmenu = QMenu() qmenu.setTitle(self.Menu[0]) AddTrayMenuItem(qmenu, self.Menu[1], self) self.TrayIcon.setContextMenu(qmenu) # Tooltip if tooltip is not None: self.TrayIcon.setToolTip(str(tooltip)) # Icon qicon = None if filename is not None: qicon = QIcon(filename) elif data is not None: ba = QtCore.QByteArray.fromRawData(data) pixmap = QtGui.QPixmap() pixmap.loadFromData(ba) qicon = QIcon(pixmap) elif data_base64 is not None: ba = QtCore.QByteArray.fromBase64(data_base64) pixmap = QtGui.QPixmap() pixmap.loadFromData(ba) qicon = QIcon(pixmap) if qicon is not None: self.TrayIcon.setIcon(qicon)
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L3034-L3069
train
PySimpleGUI/PySimpleGUI
PySimpleGUIQt/PySimpleGUIQt.py
Window.SetAlpha
def SetAlpha(self, alpha): ''' Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return: ''' self._AlphaChannel = alpha if self._AlphaChannel is not None: self.QT_QMainWindow.setWindowOpacity(self._AlphaChannel)
python
def SetAlpha(self, alpha): ''' Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return: ''' self._AlphaChannel = alpha if self._AlphaChannel is not None: self.QT_QMainWindow.setWindowOpacity(self._AlphaChannel)
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Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIQt/PySimpleGUIQt.py#L3576-L3584
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
convert_tkinter_size_to_Wx
def convert_tkinter_size_to_Wx(size): """ Converts size in characters to size in pixels :param size: size in characters, rows :return: size in pixels, pixels """ qtsize = size if size[1] is not None and size[1] < DEFAULT_PIXEL_TO_CHARS_CUTOFF: # change from character based size to pixels (roughly) qtsize = size[0]*DEFAULT_PIXELS_TO_CHARS_SCALING[0], size[1]*DEFAULT_PIXELS_TO_CHARS_SCALING[1] return qtsize
python
def convert_tkinter_size_to_Wx(size): """ Converts size in characters to size in pixels :param size: size in characters, rows :return: size in pixels, pixels """ qtsize = size if size[1] is not None and size[1] < DEFAULT_PIXEL_TO_CHARS_CUTOFF: # change from character based size to pixels (roughly) qtsize = size[0]*DEFAULT_PIXELS_TO_CHARS_SCALING[0], size[1]*DEFAULT_PIXELS_TO_CHARS_SCALING[1] return qtsize
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Converts size in characters to size in pixels :param size: size in characters, rows :return: size in pixels, pixels
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L3570-L3579
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
font_to_wx_font
def font_to_wx_font(font): """ Convert from font string/tyuple into a Qt style sheet string :param font: "Arial 10 Bold" or ('Arial', 10, 'Bold) :return: style string that can be combined with other style strings """ if font is None: return '' if type(font) is str: _font = font.split(' ') else: _font = font name = _font[0] family = _font[0] point_size = int(_font[1]) # style = _font[2] underline = 'underline' in _font[2:] bold = 'bold' in _font wxfont = wx.Font(point_size, wx.FONTFAMILY_DEFAULT, wx.FONTSTYLE_NORMAL, wx.FONTWEIGHT_BOLD if bold else wx.FONTWEIGHT_NORMAL, underline, faceName=family) return wxfont
python
def font_to_wx_font(font): """ Convert from font string/tyuple into a Qt style sheet string :param font: "Arial 10 Bold" or ('Arial', 10, 'Bold) :return: style string that can be combined with other style strings """ if font is None: return '' if type(font) is str: _font = font.split(' ') else: _font = font name = _font[0] family = _font[0] point_size = int(_font[1]) # style = _font[2] underline = 'underline' in _font[2:] bold = 'bold' in _font wxfont = wx.Font(point_size, wx.FONTFAMILY_DEFAULT, wx.FONTSTYLE_NORMAL, wx.FONTWEIGHT_BOLD if bold else wx.FONTWEIGHT_NORMAL, underline, faceName=family) return wxfont
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L3582-L3612
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
PopupError
def PopupError(*args, button_color=DEFAULT_ERROR_BUTTON_COLOR, background_color=None, text_color=None, auto_close=False, auto_close_duration=None, non_blocking=False, icon=DEFAULT_WINDOW_ICON, line_width=None, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None)): """ Popup with colored button and 'Error' as button text :param args: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ Popup(*args, button_type=POPUP_BUTTONS_ERROR, background_color=background_color, text_color=text_color, non_blocking=non_blocking, icon=icon, line_width=line_width, button_color=button_color, auto_close=auto_close, auto_close_duration=auto_close_duration, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location)
python
def PopupError(*args, button_color=DEFAULT_ERROR_BUTTON_COLOR, background_color=None, text_color=None, auto_close=False, auto_close_duration=None, non_blocking=False, icon=DEFAULT_WINDOW_ICON, line_width=None, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None)): """ Popup with colored button and 'Error' as button text :param args: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ Popup(*args, button_type=POPUP_BUTTONS_ERROR, background_color=background_color, text_color=text_color, non_blocking=non_blocking, icon=icon, line_width=line_width, button_color=button_color, auto_close=auto_close, auto_close_duration=auto_close_duration, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location)
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L6621-L6645
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
PopupGetFolder
def PopupGetFolder(message, title=None, default_path='', no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for folder :param message: :param default_path: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Contents of text field. None if closed using X or cancelled """ if no_window: app = wx.App(False) frame = wx.Frame() if initial_folder: dialog = wx.DirDialog(frame, style=wx.FD_OPEN) else: dialog = wx.DirDialog(frame) folder_name = '' if dialog.ShowModal() == wx.ID_OK: folder_name = dialog.GetPath() return folder_name layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=size), FolderBrowse(initial_folder=initial_folder)], [Button('Ok', size=(60, 20), bind_return_key=True), Button('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, background_color=background_color, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() window.Close() if button != 'Ok': return None else: path = input_values[0] return path
python
def PopupGetFolder(message, title=None, default_path='', no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for folder :param message: :param default_path: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Contents of text field. None if closed using X or cancelled """ if no_window: app = wx.App(False) frame = wx.Frame() if initial_folder: dialog = wx.DirDialog(frame, style=wx.FD_OPEN) else: dialog = wx.DirDialog(frame) folder_name = '' if dialog.ShowModal() == wx.ID_OK: folder_name = dialog.GetPath() return folder_name layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=size), FolderBrowse(initial_folder=initial_folder)], [Button('Ok', size=(60, 20), bind_return_key=True), Button('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, background_color=background_color, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() window.Close() if button != 'Ok': return None else: path = input_values[0] return path
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Display popup with text entry field and browse button. Browse for folder :param message: :param default_path: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Contents of text field. None if closed using X or cancelled
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L6768-L6821
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
PopupGetFile
def PopupGetFile(message, title=None, default_path='', default_extension='', save_as=False, file_types=(("ALL Files", "*"),), no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for file :param message: :param default_path: :param default_extension: :param save_as: :param file_types: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: string representing the path chosen, None if cancelled or window closed with X """ if no_window: app = wx.App(False) frame = wx.Frame() qt_types = convert_tkinter_filetypes_to_wx(file_types) style = wx.FD_SAVE if save_as else wx.FD_OPEN if initial_folder: dialog = wx.FileDialog(frame, defaultDir=initial_folder, wildcard=qt_types, style=style) else: dialog = wx.FileDialog(frame, wildcard=qt_types, style=style) if dialog.ShowModal() == wx.ID_OK: file_name = dialog.GetPath() else: file_name = '' return file_name browse_button = SaveAs(file_types=file_types, initial_folder=initial_folder) if save_as else FileBrowse( file_types=file_types, initial_folder=initial_folder) layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=(30,1)), browse_button], [Button('Ok', size=(60, 20), bind_return_key=True), Button('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, font=font, background_color=background_color, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() window.Close() # window.Close() if button != 'Ok': return None else: path = input_values[0] return path
python
def PopupGetFile(message, title=None, default_path='', default_extension='', save_as=False, file_types=(("ALL Files", "*"),), no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for file :param message: :param default_path: :param default_extension: :param save_as: :param file_types: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: string representing the path chosen, None if cancelled or window closed with X """ if no_window: app = wx.App(False) frame = wx.Frame() qt_types = convert_tkinter_filetypes_to_wx(file_types) style = wx.FD_SAVE if save_as else wx.FD_OPEN if initial_folder: dialog = wx.FileDialog(frame, defaultDir=initial_folder, wildcard=qt_types, style=style) else: dialog = wx.FileDialog(frame, wildcard=qt_types, style=style) if dialog.ShowModal() == wx.ID_OK: file_name = dialog.GetPath() else: file_name = '' return file_name browse_button = SaveAs(file_types=file_types, initial_folder=initial_folder) if save_as else FileBrowse( file_types=file_types, initial_folder=initial_folder) layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=(30,1)), browse_button], [Button('Ok', size=(60, 20), bind_return_key=True), Button('Cancel', size=(60, 20))]] _title = title if title is not None else message window = Window(title=_title, icon=icon, auto_size_text=True, button_color=button_color, font=font, background_color=background_color, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() window.Close() # window.Close() if button != 'Ok': return None else: path = input_values[0] return path
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L6826-L6888
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
SystemTray.Read
def Read(self, timeout=None): ''' Reads the context menu :param timeout: Optional. Any value other than None indicates a non-blocking read :return: ''' # if not self.Shown: # self.Shown = True # self.TrayIcon.show() timeout1 = timeout # if timeout1 == 0: # timeout1 = 1 # if wx.GetApp(): # wx.GetApp().ProcessPendingEvents() # self.App.ProcessPendingEvents() # self.App.ProcessIdle() # return self.MenuItemChosen if timeout1 is not None: try: self.timer = wx.Timer(self.TaskBarIcon) self.TaskBarIcon.Bind(wx.EVT_TIMER, self.timer_timeout) self.timer.Start(milliseconds=timeout1, oneShot=wx.TIMER_ONE_SHOT) except: print('*** Got error in Read ***') self.RunningMainLoop = True self.App.MainLoop() self.RunningMainLoop = False if self.timer: self.timer.Stop() self.MenuItemChosen = self.TaskBarIcon.menu_item_chosen return self.MenuItemChosen
python
def Read(self, timeout=None): ''' Reads the context menu :param timeout: Optional. Any value other than None indicates a non-blocking read :return: ''' # if not self.Shown: # self.Shown = True # self.TrayIcon.show() timeout1 = timeout # if timeout1 == 0: # timeout1 = 1 # if wx.GetApp(): # wx.GetApp().ProcessPendingEvents() # self.App.ProcessPendingEvents() # self.App.ProcessIdle() # return self.MenuItemChosen if timeout1 is not None: try: self.timer = wx.Timer(self.TaskBarIcon) self.TaskBarIcon.Bind(wx.EVT_TIMER, self.timer_timeout) self.timer.Start(milliseconds=timeout1, oneShot=wx.TIMER_ONE_SHOT) except: print('*** Got error in Read ***') self.RunningMainLoop = True self.App.MainLoop() self.RunningMainLoop = False if self.timer: self.timer.Stop() self.MenuItemChosen = self.TaskBarIcon.menu_item_chosen return self.MenuItemChosen
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Reads the context menu :param timeout: Optional. Any value other than None indicates a non-blocking read :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L2817-L2847
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
SystemTray.ShowMessage
def ShowMessage(self, title, message, filename=None, data=None, data_base64=None, messageicon=None, time=10000): ''' Shows a balloon above icon in system tray :param title: Title shown in balloon :param message: Message to be displayed :param filename: Optional icon filename :param data: Optional in-ram icon :param data_base64: Optional base64 icon :param time: How long to display message in milliseconds :return: ''' if messageicon is None: self.TaskBarIcon.ShowBalloon(title, message, msec=time) else: self.TaskBarIcon.ShowBalloon(title, message, msec=time, flags=messageicon) return self
python
def ShowMessage(self, title, message, filename=None, data=None, data_base64=None, messageicon=None, time=10000): ''' Shows a balloon above icon in system tray :param title: Title shown in balloon :param message: Message to be displayed :param filename: Optional icon filename :param data: Optional in-ram icon :param data_base64: Optional base64 icon :param time: How long to display message in milliseconds :return: ''' if messageicon is None: self.TaskBarIcon.ShowBalloon(title, message, msec=time) else: self.TaskBarIcon.ShowBalloon(title, message, msec=time, flags=messageicon) return self
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Shows a balloon above icon in system tray :param title: Title shown in balloon :param message: Message to be displayed :param filename: Optional icon filename :param data: Optional in-ram icon :param data_base64: Optional base64 icon :param time: How long to display message in milliseconds :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L2863-L2879
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
SystemTray.Update
def Update(self, menu=None, tooltip=None,filename=None, data=None, data_base64=None,): ''' Updates the menu, tooltip or icon :param menu: menu defintion :param tooltip: string representing tooltip :param filename: icon filename :param data: icon raw image :param data_base64: icon base 64 image :return: ''' # Menu if menu is not None: self.TaskBarIcon.menu = menu if filename: self.icon = wx.Icon(filename, wx.BITMAP_TYPE_ANY) elif data_base64: self.icon = PyEmbeddedImage(data_base64).GetIcon() elif not self.icon: self.icon = PyEmbeddedImage(DEFAULT_BASE64_ICON).GetIcon() if self.icon: self.Tooltip = tooltip or self.Tooltip self.TaskBarIcon.SetIcon(self.icon, tooltip=self.Tooltip)
python
def Update(self, menu=None, tooltip=None,filename=None, data=None, data_base64=None,): ''' Updates the menu, tooltip or icon :param menu: menu defintion :param tooltip: string representing tooltip :param filename: icon filename :param data: icon raw image :param data_base64: icon base 64 image :return: ''' # Menu if menu is not None: self.TaskBarIcon.menu = menu if filename: self.icon = wx.Icon(filename, wx.BITMAP_TYPE_ANY) elif data_base64: self.icon = PyEmbeddedImage(data_base64).GetIcon() elif not self.icon: self.icon = PyEmbeddedImage(DEFAULT_BASE64_ICON).GetIcon() if self.icon: self.Tooltip = tooltip or self.Tooltip self.TaskBarIcon.SetIcon(self.icon, tooltip=self.Tooltip)
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Updates the menu, tooltip or icon :param menu: menu defintion :param tooltip: string representing tooltip :param filename: icon filename :param data: icon raw image :param data_base64: icon base 64 image :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L2894-L2915
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
DragFrame.on_mouse
def on_mouse(self, event): ''' implement dragging ''' # print('on_mouse') if not event.Dragging(): self._dragPos = None return # self.CaptureMouse() if not self._dragPos: self._dragPos = event.GetPosition() else: pos = event.GetPosition() displacement = self._dragPos - pos self.SetPosition( self.GetPosition() - displacement )
python
def on_mouse(self, event): ''' implement dragging ''' # print('on_mouse') if not event.Dragging(): self._dragPos = None return # self.CaptureMouse() if not self._dragPos: self._dragPos = event.GetPosition() else: pos = event.GetPosition() displacement = self._dragPos - pos self.SetPosition( self.GetPosition() - displacement )
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implement dragging
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L2947-L2961
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWx/PySimpleGUIWx.py
Window.SetAlpha
def SetAlpha(self, alpha): ''' Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return: ''' self._AlphaChannel = alpha * 255 if self._AlphaChannel is not None: self.MasterFrame.SetTransparent(self._AlphaChannel)
python
def SetAlpha(self, alpha): ''' Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return: ''' self._AlphaChannel = alpha * 255 if self._AlphaChannel is not None: self.MasterFrame.SetTransparent(self._AlphaChannel)
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Change the window's transparency :param alpha: From 0 to 1 with 0 being completely transparent :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWx/PySimpleGUIWx.py#L3460-L3468
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Multithreaded_Queued.py
worker_thread
def worker_thread(thread_name, run_freq, gui_queue): """ A worker thrread that communicates with the GUI These threads can call functions that block withouth affecting the GUI (a good thing) Note that this function is the code started as each thread. All threads are identical in this way :param thread_name: Text name used for displaying info :param run_freq: How often the thread should run in milliseconds :param gui_queue: Queue used to communicate with the GUI :return: """ print('Starting thread - {} that runds every {} ms'.format(thread_name, run_freq)) for i in itertools.count(): # loop forever, keeping count in i as it loops time.sleep(run_freq/1000) # sleep for a while gui_queue.put('{} - {}'.format(thread_name, i)) # put a message into queue for GUI print('..')
python
def worker_thread(thread_name, run_freq, gui_queue): """ A worker thrread that communicates with the GUI These threads can call functions that block withouth affecting the GUI (a good thing) Note that this function is the code started as each thread. All threads are identical in this way :param thread_name: Text name used for displaying info :param run_freq: How often the thread should run in milliseconds :param gui_queue: Queue used to communicate with the GUI :return: """ print('Starting thread - {} that runds every {} ms'.format(thread_name, run_freq)) for i in itertools.count(): # loop forever, keeping count in i as it loops time.sleep(run_freq/1000) # sleep for a while gui_queue.put('{} - {}'.format(thread_name, i)) # put a message into queue for GUI print('..')
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A worker thrread that communicates with the GUI These threads can call functions that block withouth affecting the GUI (a good thing) Note that this function is the code started as each thread. All threads are identical in this way :param thread_name: Text name used for displaying info :param run_freq: How often the thread should run in milliseconds :param gui_queue: Queue used to communicate with the GUI :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Multithreaded_Queued.py#L44-L58
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Multithreaded_Queued.py
the_gui
def the_gui(gui_queue): """ Starts and executes the GUI Reads data from a Queue and displays the data to the window Returns when the user exits / closes the window (that means it does NOT return until the user exits the window) :param gui_queue: Queue the GUI should read from :return: """ layout = [ [sg.Text('Multithreaded Window Example')], [sg.Text('', size=(15,1), key='_OUTPUT_')], [sg.Output(size=(40,6))], [sg.Button('Exit')],] window = sg.Window('Multithreaded Window').Layout(layout) # --------------------- EVENT LOOP --------------------- while True: event, values = window.Read(timeout=100) # wait for up to 100 ms for a GUI event if event is None or event == 'Exit': break #--------------- Loop through all messages coming in from threads --------------- while True: # loop executes until runs out of messages in Queue try: # see if something has been posted to Queue message = gui_queue.get_nowait() except queue.Empty: # get_nowait() will get exception when Queue is empty break # break from the loop if no more messages are queued up # if message received from queue, display the message in the Window if message: window.Element('_OUTPUT_').Update(message) window.Refresh() # do a refresh because could be showing multiple messages before next Read # if user exits the window, then close the window and exit the GUI func window.Close()
python
def the_gui(gui_queue): """ Starts and executes the GUI Reads data from a Queue and displays the data to the window Returns when the user exits / closes the window (that means it does NOT return until the user exits the window) :param gui_queue: Queue the GUI should read from :return: """ layout = [ [sg.Text('Multithreaded Window Example')], [sg.Text('', size=(15,1), key='_OUTPUT_')], [sg.Output(size=(40,6))], [sg.Button('Exit')],] window = sg.Window('Multithreaded Window').Layout(layout) # --------------------- EVENT LOOP --------------------- while True: event, values = window.Read(timeout=100) # wait for up to 100 ms for a GUI event if event is None or event == 'Exit': break #--------------- Loop through all messages coming in from threads --------------- while True: # loop executes until runs out of messages in Queue try: # see if something has been posted to Queue message = gui_queue.get_nowait() except queue.Empty: # get_nowait() will get exception when Queue is empty break # break from the loop if no more messages are queued up # if message received from queue, display the message in the Window if message: window.Element('_OUTPUT_').Update(message) window.Refresh() # do a refresh because could be showing multiple messages before next Read # if user exits the window, then close the window and exit the GUI func window.Close()
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Starts and executes the GUI Reads data from a Queue and displays the data to the window Returns when the user exits / closes the window (that means it does NOT return until the user exits the window) :param gui_queue: Queue the GUI should read from :return:
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Multithreaded_Queued.py#L68-L100
train
PySimpleGUI/PySimpleGUI
DemoPrograms/ping.py
send_one_ping
def send_one_ping(mySocket, destIP, myID, mySeqNumber, packet_size): """ Send one ping to the given >destIP<. """ #destIP = socket.gethostbyname(destIP) # Header is type (8), code (8), checksum (16), id (16), sequence (16) # (packet_size - 8) - Remove header size from packet size myChecksum = 0 # Make a dummy heder with a 0 checksum. header = struct.pack( "!BBHHH", ICMP_ECHO, 0, myChecksum, myID, mySeqNumber ) padBytes = [] startVal = 0x42 # 'cose of the string/byte changes in python 2/3 we have # to build the data differnely for different version # or it will make packets with unexpected size. if sys.version[:1] == '2': bytes = struct.calcsize("d") data = ((packet_size - 8) - bytes) * "Q" data = struct.pack("d", default_timer()) + data else: for i in range(startVal, startVal + (packet_size-8)): padBytes += [(i & 0xff)] # Keep chars in the 0-255 range #data = bytes(padBytes) data = bytearray(padBytes) # Calculate the checksum on the data and the dummy header. myChecksum = checksum(header + data) # Checksum is in network order # Now that we have the right checksum, we put that in. It's just easier # to make up a new header than to stuff it into the dummy. header = struct.pack( "!BBHHH", ICMP_ECHO, 0, myChecksum, myID, mySeqNumber ) packet = header + data sendTime = default_timer() try: mySocket.sendto(packet, (destIP, 1)) # Port number is irrelevant for ICMP except socket.error as e: print("General failure (%s)" % (e.args[1])) return return sendTime
python
def send_one_ping(mySocket, destIP, myID, mySeqNumber, packet_size): """ Send one ping to the given >destIP<. """ #destIP = socket.gethostbyname(destIP) # Header is type (8), code (8), checksum (16), id (16), sequence (16) # (packet_size - 8) - Remove header size from packet size myChecksum = 0 # Make a dummy heder with a 0 checksum. header = struct.pack( "!BBHHH", ICMP_ECHO, 0, myChecksum, myID, mySeqNumber ) padBytes = [] startVal = 0x42 # 'cose of the string/byte changes in python 2/3 we have # to build the data differnely for different version # or it will make packets with unexpected size. if sys.version[:1] == '2': bytes = struct.calcsize("d") data = ((packet_size - 8) - bytes) * "Q" data = struct.pack("d", default_timer()) + data else: for i in range(startVal, startVal + (packet_size-8)): padBytes += [(i & 0xff)] # Keep chars in the 0-255 range #data = bytes(padBytes) data = bytearray(padBytes) # Calculate the checksum on the data and the dummy header. myChecksum = checksum(header + data) # Checksum is in network order # Now that we have the right checksum, we put that in. It's just easier # to make up a new header than to stuff it into the dummy. header = struct.pack( "!BBHHH", ICMP_ECHO, 0, myChecksum, myID, mySeqNumber ) packet = header + data sendTime = default_timer() try: mySocket.sendto(packet, (destIP, 1)) # Port number is irrelevant for ICMP except socket.error as e: print("General failure (%s)" % (e.args[1])) return return sendTime
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Send one ping to the given >destIP<.
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/ping.py#L337-L387
train
PySimpleGUI/PySimpleGUI
DemoPrograms/ping.py
receive_one_ping
def receive_one_ping(mySocket, myID, timeout): """ Receive the ping from the socket. Timeout = in ms """ timeLeft = timeout/1000 while True: # Loop while waiting for packet or timeout startedSelect = default_timer() whatReady = select.select([mySocket], [], [], timeLeft) howLongInSelect = (default_timer() - startedSelect) if whatReady[0] == []: # Timeout return None, 0, 0, 0, 0 timeReceived = default_timer() recPacket, addr = mySocket.recvfrom(ICMP_MAX_RECV) ipHeader = recPacket[:20] iphVersion, iphTypeOfSvc, iphLength, \ iphID, iphFlags, iphTTL, iphProtocol, \ iphChecksum, iphSrcIP, iphDestIP = struct.unpack( "!BBHHHBBHII", ipHeader ) icmpHeader = recPacket[20:28] icmpType, icmpCode, icmpChecksum, \ icmpPacketID, icmpSeqNumber = struct.unpack( "!BBHHH", icmpHeader ) if icmpPacketID == myID: # Our packet dataSize = len(recPacket) - 28 #print (len(recPacket.encode())) return timeReceived, (dataSize+8), iphSrcIP, icmpSeqNumber, iphTTL timeLeft = timeLeft - howLongInSelect if timeLeft <= 0: return None, 0, 0, 0, 0
python
def receive_one_ping(mySocket, myID, timeout): """ Receive the ping from the socket. Timeout = in ms """ timeLeft = timeout/1000 while True: # Loop while waiting for packet or timeout startedSelect = default_timer() whatReady = select.select([mySocket], [], [], timeLeft) howLongInSelect = (default_timer() - startedSelect) if whatReady[0] == []: # Timeout return None, 0, 0, 0, 0 timeReceived = default_timer() recPacket, addr = mySocket.recvfrom(ICMP_MAX_RECV) ipHeader = recPacket[:20] iphVersion, iphTypeOfSvc, iphLength, \ iphID, iphFlags, iphTTL, iphProtocol, \ iphChecksum, iphSrcIP, iphDestIP = struct.unpack( "!BBHHHBBHII", ipHeader ) icmpHeader = recPacket[20:28] icmpType, icmpCode, icmpChecksum, \ icmpPacketID, icmpSeqNumber = struct.unpack( "!BBHHH", icmpHeader ) if icmpPacketID == myID: # Our packet dataSize = len(recPacket) - 28 #print (len(recPacket.encode())) return timeReceived, (dataSize+8), iphSrcIP, icmpSeqNumber, iphTTL timeLeft = timeLeft - howLongInSelect if timeLeft <= 0: return None, 0, 0, 0, 0
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Receive the ping from the socket. Timeout = in ms
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/ping.py#L390-L427
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Script_Launcher_Realtime_Output.py
runCommand
def runCommand(cmd, timeout=None, window=None): """ run shell command @param cmd: command to execute @param timeout: timeout for command execution @param window: the PySimpleGUI window that the output is going to (needed to do refresh on) @return: (return code from command, command output) """ p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) output = '' for line in p.stdout: line = line.decode(errors='replace' if (sys.version_info) < (3, 5) else 'backslashreplace').rstrip() output += line print(line) window.Refresh() if window else None # yes, a 1-line if, so shoot me retval = p.wait(timeout) return (retval, output)
python
def runCommand(cmd, timeout=None, window=None): """ run shell command @param cmd: command to execute @param timeout: timeout for command execution @param window: the PySimpleGUI window that the output is going to (needed to do refresh on) @return: (return code from command, command output) """ p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) output = '' for line in p.stdout: line = line.decode(errors='replace' if (sys.version_info) < (3, 5) else 'backslashreplace').rstrip() output += line print(line) window.Refresh() if window else None # yes, a 1-line if, so shoot me retval = p.wait(timeout) return (retval, output)
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run shell command @param cmd: command to execute @param timeout: timeout for command execution @param window: the PySimpleGUI window that the output is going to (needed to do refresh on) @return: (return code from command, command output)
[ "run", "shell", "command" ]
08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Script_Launcher_Realtime_Output.py#L29-L45
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/PySimpleGUIWeb.py
font_parse_string
def font_parse_string(font): """ Convert from font string/tyuple into a Qt style sheet string :param font: "Arial 10 Bold" or ('Arial', 10, 'Bold) :return: style string that can be combined with other style strings """ if font is None: return '' if type(font) is str: _font = font.split(' ') else: _font = font family = _font[0] point_size = int(_font[1]) style = _font[2:] if len(_font) > 1 else None # underline = 'underline' in _font[2:] # bold = 'bold' in _font return family, point_size, style
python
def font_parse_string(font): """ Convert from font string/tyuple into a Qt style sheet string :param font: "Arial 10 Bold" or ('Arial', 10, 'Bold) :return: style string that can be combined with other style strings """ if font is None: return '' if type(font) is str: _font = font.split(' ') else: _font = font family = _font[0] point_size = int(_font[1]) style = _font[2:] if len(_font) > 1 else None # underline = 'underline' in _font[2:] # bold = 'bold' in _font return family, point_size, style
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Convert from font string/tyuple into a Qt style sheet string :param font: "Arial 10 Bold" or ('Arial', 10, 'Bold) :return: style string that can be combined with other style strings
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/PySimpleGUIWeb.py#L3449-L3471
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/PySimpleGUIWeb.py
_ProgressMeter
def _ProgressMeter(title, max_value, *args, orientation=None, bar_color=(None, None), button_color=None, size=DEFAULT_PROGRESS_BAR_SIZE, border_width=None, grab_anywhere=False): ''' Create and show a form on tbe caller's behalf. :param title: :param max_value: :param args: ANY number of arguments the caller wants to display :param orientation: :param bar_color: :param size: :param Style: :param StyleOffset: :return: ProgressBar object that is in the form ''' local_orientation = DEFAULT_METER_ORIENTATION if orientation is None else orientation local_border_width = DEFAULT_PROGRESS_BAR_BORDER_WIDTH if border_width is None else border_width bar2 = ProgressBar(max_value, orientation=local_orientation, size=size, bar_color=bar_color, border_width=local_border_width, relief=DEFAULT_PROGRESS_BAR_RELIEF) form = Window(title, auto_size_text=True, grab_anywhere=grab_anywhere) # Form using a horizontal bar if local_orientation[0].lower() == 'h': single_line_message, width, height = ConvertArgsToSingleString(*args) bar2.TextToDisplay = single_line_message bar2.TextToDisplay = single_line_message bar2.MaxValue = max_value bar2.CurrentValue = 0 bar_text = Text(single_line_message, size=(width, height + 3), auto_size_text=True) form.AddRow(bar_text) form.AddRow((bar2)) form.AddRow((CloseButton('Cancel', button_color=button_color))) else: single_line_message, width, height = ConvertArgsToSingleString(*args) bar2.TextToDisplay = single_line_message bar2.MaxValue = max_value bar2.CurrentValue = 0 bar_text = Text(single_line_message, size=(width, height + 3), auto_size_text=True) form.AddRow(bar2, bar_text) form.AddRow((CloseButton('Cancel', button_color=button_color))) form.NonBlocking = True form.Show(non_blocking=True) return bar2, bar_text
python
def _ProgressMeter(title, max_value, *args, orientation=None, bar_color=(None, None), button_color=None, size=DEFAULT_PROGRESS_BAR_SIZE, border_width=None, grab_anywhere=False): ''' Create and show a form on tbe caller's behalf. :param title: :param max_value: :param args: ANY number of arguments the caller wants to display :param orientation: :param bar_color: :param size: :param Style: :param StyleOffset: :return: ProgressBar object that is in the form ''' local_orientation = DEFAULT_METER_ORIENTATION if orientation is None else orientation local_border_width = DEFAULT_PROGRESS_BAR_BORDER_WIDTH if border_width is None else border_width bar2 = ProgressBar(max_value, orientation=local_orientation, size=size, bar_color=bar_color, border_width=local_border_width, relief=DEFAULT_PROGRESS_BAR_RELIEF) form = Window(title, auto_size_text=True, grab_anywhere=grab_anywhere) # Form using a horizontal bar if local_orientation[0].lower() == 'h': single_line_message, width, height = ConvertArgsToSingleString(*args) bar2.TextToDisplay = single_line_message bar2.TextToDisplay = single_line_message bar2.MaxValue = max_value bar2.CurrentValue = 0 bar_text = Text(single_line_message, size=(width, height + 3), auto_size_text=True) form.AddRow(bar_text) form.AddRow((bar2)) form.AddRow((CloseButton('Cancel', button_color=button_color))) else: single_line_message, width, height = ConvertArgsToSingleString(*args) bar2.TextToDisplay = single_line_message bar2.MaxValue = max_value bar2.CurrentValue = 0 bar_text = Text(single_line_message, size=(width, height + 3), auto_size_text=True) form.AddRow(bar2, bar_text) form.AddRow((CloseButton('Cancel', button_color=button_color))) form.NonBlocking = True form.Show(non_blocking=True) return bar2, bar_text
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/PySimpleGUIWeb.py#L5237-L5279
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/PySimpleGUIWeb.py
_ProgressMeterUpdate
def _ProgressMeterUpdate(bar, value, text_elem, *args): ''' Update the progress meter for a form :param form: class ProgressBar :param value: int :return: True if not cancelled, OK....False if Error ''' global _my_windows if bar == None: return False if bar.BarExpired: return False message, w, h = ConvertArgsToSingleString(*args) text_elem.Update(message) # bar.TextToDisplay = message bar.CurrentValue = value rc = bar.UpdateBar(value) if value >= bar.MaxValue or not rc: bar.BarExpired = True bar.ParentForm._Close() if rc: # if update was OK but bar expired, decrement num windows _my_windows.Decrement() if bar.ParentForm.RootNeedsDestroying: try: bar.ParentForm.TKroot.destroy() # there is a bug with progress meters not decrementing the number of windows # correctly when the X is used to close the window # uncommenting this line fixes that problem, but causes a double-decrement when # the cancel button is used... damned if you do, damned if you don't, so I'm choosing # don't, as in don't decrement too many times. It's OK now to have a mismatch in # number of windows because of the "hidden" master window. This ensures all windows # will be toplevel. Sorry about the bug, but the user never sees any problems as a result # _my_windows.Decrement() except: pass bar.ParentForm.RootNeedsDestroying = False bar.ParentForm.__del__() return False return rc
python
def _ProgressMeterUpdate(bar, value, text_elem, *args): ''' Update the progress meter for a form :param form: class ProgressBar :param value: int :return: True if not cancelled, OK....False if Error ''' global _my_windows if bar == None: return False if bar.BarExpired: return False message, w, h = ConvertArgsToSingleString(*args) text_elem.Update(message) # bar.TextToDisplay = message bar.CurrentValue = value rc = bar.UpdateBar(value) if value >= bar.MaxValue or not rc: bar.BarExpired = True bar.ParentForm._Close() if rc: # if update was OK but bar expired, decrement num windows _my_windows.Decrement() if bar.ParentForm.RootNeedsDestroying: try: bar.ParentForm.TKroot.destroy() # there is a bug with progress meters not decrementing the number of windows # correctly when the X is used to close the window # uncommenting this line fixes that problem, but causes a double-decrement when # the cancel button is used... damned if you do, damned if you don't, so I'm choosing # don't, as in don't decrement too many times. It's OK now to have a mismatch in # number of windows because of the "hidden" master window. This ensures all windows # will be toplevel. Sorry about the bug, but the user never sees any problems as a result # _my_windows.Decrement() except: pass bar.ParentForm.RootNeedsDestroying = False bar.ParentForm.__del__() return False return rc
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Update the progress meter for a form :param form: class ProgressBar :param value: int :return: True if not cancelled, OK....False if Error
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/PySimpleGUIWeb.py#L5283-L5320
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/PySimpleGUIWeb.py
EasyProgressMeter
def EasyProgressMeter(title, current_value, max_value, *args, orientation=None, bar_color=(None, None), button_color=None, size=DEFAULT_PROGRESS_BAR_SIZE, border_width=None): ''' A ONE-LINE progress meter. Add to your code where ever you need a meter. No need for a second function call before your loop. You've got enough code to write! :param title: Title will be shown on the window :param current_value: Current count of your items :param max_value: Max value your count will ever reach. This indicates it should be closed :param args: VARIABLE number of arguements... you request it, we'll print it no matter what the item! :param orientation: :param bar_color: :param size: :param Style: :param StyleOffset: :return: False if should stop the meter ''' local_border_width = DEFAULT_PROGRESS_BAR_BORDER_WIDTH if not border_width else border_width # STATIC VARIABLE! # This is a very clever form of static variable using a function attribute # If the variable doesn't yet exist, then it will create it and initialize with the 3rd parameter EasyProgressMeter.Data = getattr(EasyProgressMeter, 'Data', EasyProgressMeterDataClass()) # if no meter currently running if EasyProgressMeter.Data.MeterID is None: # Starting a new meter print( "Please change your call of EasyProgressMeter to use OneLineProgressMeter. EasyProgressMeter will be removed soon") if int(current_value) >= int(max_value): return False del (EasyProgressMeter.Data) EasyProgressMeter.Data = EasyProgressMeterDataClass(title, 1, int(max_value), datetime.datetime.utcnow(), []) EasyProgressMeter.Data.ComputeProgressStats() message = "\n".join([line for line in EasyProgressMeter.Data.StatMessages]) EasyProgressMeter.Data.MeterID, EasyProgressMeter.Data.MeterText = _ProgressMeter(title, int(max_value), message, *args, orientation=orientation, bar_color=bar_color, size=size, button_color=button_color, border_width=local_border_width) EasyProgressMeter.Data.ParentForm = EasyProgressMeter.Data.MeterID.ParentForm return True # if exactly the same values as before, then ignore. if EasyProgressMeter.Data.MaxValue == max_value and EasyProgressMeter.Data.CurrentValue == current_value: return True if EasyProgressMeter.Data.MaxValue != int(max_value): EasyProgressMeter.Data.MeterID = None EasyProgressMeter.Data.ParentForm = None del (EasyProgressMeter.Data) EasyProgressMeter.Data = EasyProgressMeterDataClass() # setup a new progress meter return True # HAVE to return TRUE or else the new meter will thing IT is failing when it hasn't EasyProgressMeter.Data.CurrentValue = int(current_value) EasyProgressMeter.Data.MaxValue = int(max_value) EasyProgressMeter.Data.ComputeProgressStats() message = '' for line in EasyProgressMeter.Data.StatMessages: message = message + str(line) + '\n' message = "\n".join(EasyProgressMeter.Data.StatMessages) args = args + (message,) rc = _ProgressMeterUpdate(EasyProgressMeter.Data.MeterID, current_value, EasyProgressMeter.Data.MeterText, *args) # if counter >= max then the progress meter is all done. Indicate none running if current_value >= EasyProgressMeter.Data.MaxValue or not rc: EasyProgressMeter.Data.MeterID = None del (EasyProgressMeter.Data) EasyProgressMeter.Data = EasyProgressMeterDataClass() # setup a new progress meter return False # even though at the end, return True so don't cause error with the app return rc
python
def EasyProgressMeter(title, current_value, max_value, *args, orientation=None, bar_color=(None, None), button_color=None, size=DEFAULT_PROGRESS_BAR_SIZE, border_width=None): ''' A ONE-LINE progress meter. Add to your code where ever you need a meter. No need for a second function call before your loop. You've got enough code to write! :param title: Title will be shown on the window :param current_value: Current count of your items :param max_value: Max value your count will ever reach. This indicates it should be closed :param args: VARIABLE number of arguements... you request it, we'll print it no matter what the item! :param orientation: :param bar_color: :param size: :param Style: :param StyleOffset: :return: False if should stop the meter ''' local_border_width = DEFAULT_PROGRESS_BAR_BORDER_WIDTH if not border_width else border_width # STATIC VARIABLE! # This is a very clever form of static variable using a function attribute # If the variable doesn't yet exist, then it will create it and initialize with the 3rd parameter EasyProgressMeter.Data = getattr(EasyProgressMeter, 'Data', EasyProgressMeterDataClass()) # if no meter currently running if EasyProgressMeter.Data.MeterID is None: # Starting a new meter print( "Please change your call of EasyProgressMeter to use OneLineProgressMeter. EasyProgressMeter will be removed soon") if int(current_value) >= int(max_value): return False del (EasyProgressMeter.Data) EasyProgressMeter.Data = EasyProgressMeterDataClass(title, 1, int(max_value), datetime.datetime.utcnow(), []) EasyProgressMeter.Data.ComputeProgressStats() message = "\n".join([line for line in EasyProgressMeter.Data.StatMessages]) EasyProgressMeter.Data.MeterID, EasyProgressMeter.Data.MeterText = _ProgressMeter(title, int(max_value), message, *args, orientation=orientation, bar_color=bar_color, size=size, button_color=button_color, border_width=local_border_width) EasyProgressMeter.Data.ParentForm = EasyProgressMeter.Data.MeterID.ParentForm return True # if exactly the same values as before, then ignore. if EasyProgressMeter.Data.MaxValue == max_value and EasyProgressMeter.Data.CurrentValue == current_value: return True if EasyProgressMeter.Data.MaxValue != int(max_value): EasyProgressMeter.Data.MeterID = None EasyProgressMeter.Data.ParentForm = None del (EasyProgressMeter.Data) EasyProgressMeter.Data = EasyProgressMeterDataClass() # setup a new progress meter return True # HAVE to return TRUE or else the new meter will thing IT is failing when it hasn't EasyProgressMeter.Data.CurrentValue = int(current_value) EasyProgressMeter.Data.MaxValue = int(max_value) EasyProgressMeter.Data.ComputeProgressStats() message = '' for line in EasyProgressMeter.Data.StatMessages: message = message + str(line) + '\n' message = "\n".join(EasyProgressMeter.Data.StatMessages) args = args + (message,) rc = _ProgressMeterUpdate(EasyProgressMeter.Data.MeterID, current_value, EasyProgressMeter.Data.MeterText, *args) # if counter >= max then the progress meter is all done. Indicate none running if current_value >= EasyProgressMeter.Data.MaxValue or not rc: EasyProgressMeter.Data.MeterID = None del (EasyProgressMeter.Data) EasyProgressMeter.Data = EasyProgressMeterDataClass() # setup a new progress meter return False # even though at the end, return True so don't cause error with the app return rc
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/PySimpleGUIWeb.py#L5367-L5432
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/PySimpleGUIWeb.py
PopupNonBlocking
def PopupNonBlocking(*args, button_type=POPUP_BUTTONS_OK, button_color=None, background_color=None, text_color=None, auto_close=False, auto_close_duration=None, non_blocking=True, icon=DEFAULT_WINDOW_ICON, line_width=None, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None)): """ Show Popup box and immediately return (does not block) :param args: :param button_type: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ Popup(*args, button_color=button_color, background_color=background_color, text_color=text_color, button_type=button_type, auto_close=auto_close, auto_close_duration=auto_close_duration, non_blocking=non_blocking, icon=icon, line_width=line_width, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location)
python
def PopupNonBlocking(*args, button_type=POPUP_BUTTONS_OK, button_color=None, background_color=None, text_color=None, auto_close=False, auto_close_duration=None, non_blocking=True, icon=DEFAULT_WINDOW_ICON, line_width=None, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None)): """ Show Popup box and immediately return (does not block) :param args: :param button_type: :param button_color: :param background_color: :param text_color: :param auto_close: :param auto_close_duration: :param non_blocking: :param icon: :param line_width: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: """ Popup(*args, button_color=button_color, background_color=background_color, text_color=text_color, button_type=button_type, auto_close=auto_close, auto_close_duration=auto_close_duration, non_blocking=non_blocking, icon=icon, line_width=line_width, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location)
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/PySimpleGUIWeb.py#L6286-L6313
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/PySimpleGUIWeb.py
PopupGetFolder
def PopupGetFolder(message, default_path='', no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for folder :param message: :param default_path: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Contents of text field. None if closed using X or cancelled """ global _my_windows if no_window: if _my_windows.NumOpenWindows: root = tk.Toplevel() else: root = tk.Tk() try: root.attributes('-alpha', 0) # hide window while building it. makes for smoother 'paint' except: pass folder_name = tk.filedialog.askdirectory() # show the 'get folder' dialog box root.destroy() return folder_name layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=size), FolderBrowse(initial_folder=initial_folder)], [Button('Ok', size=(5, 1), bind_return_key=True), Button('Cancel', size=(5, 1))]] window = Window(title=message, icon=icon, auto_size_text=True, button_color=button_color, background_color=background_color, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.LayoutAndRead(layout) window.Close() if button != 'Ok': return None else: path = input_values[0] return path
python
def PopupGetFolder(message, default_path='', no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for folder :param message: :param default_path: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: Contents of text field. None if closed using X or cancelled """ global _my_windows if no_window: if _my_windows.NumOpenWindows: root = tk.Toplevel() else: root = tk.Tk() try: root.attributes('-alpha', 0) # hide window while building it. makes for smoother 'paint' except: pass folder_name = tk.filedialog.askdirectory() # show the 'get folder' dialog box root.destroy() return folder_name layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=size), FolderBrowse(initial_folder=initial_folder)], [Button('Ok', size=(5, 1), bind_return_key=True), Button('Cancel', size=(5, 1))]] window = Window(title=message, icon=icon, auto_size_text=True, button_color=button_color, background_color=background_color, font=font, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.LayoutAndRead(layout) window.Close() if button != 'Ok': return None else: path = input_values[0] return path
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/PySimpleGUIWeb.py#L6596-L6647
train
PySimpleGUI/PySimpleGUI
PySimpleGUIWeb/PySimpleGUIWeb.py
PopupGetFile
def PopupGetFile(message, default_path='', default_extension='', save_as=False, file_types=(("ALL Files", "*.*"),), no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for file :param message: :param default_path: :param default_extension: :param save_as: :param file_types: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: string representing the path chosen, None if cancelled or window closed with X """ global _my_windows if no_window: if _my_windows.NumOpenWindows: root = tk.Toplevel() else: root = tk.Tk() try: root.attributes('-alpha', 0) # hide window while building it. makes for smoother 'paint' except: pass if save_as: filename = tk.filedialog.asksaveasfilename(filetypes=file_types, defaultextension=default_extension) # show the 'get file' dialog box else: filename = tk.filedialog.askopenfilename(filetypes=file_types, defaultextension=default_extension) # show the 'get file' dialog box root.destroy() return filename browse_button = SaveAs(file_types=file_types, initial_folder=initial_folder) if save_as else FileBrowse( file_types=file_types, initial_folder=initial_folder) layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=size), browse_button], [Button('Ok', size=(6, 1), bind_return_key=True), Button('Cancel', size=(6, 1))]] window = Window(title=message, icon=icon, auto_size_text=True, button_color=button_color, font=font, background_color=background_color, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() window.Close() if button != 'Ok': return None else: path = input_values[0] return path
python
def PopupGetFile(message, default_path='', default_extension='', save_as=False, file_types=(("ALL Files", "*.*"),), no_window=False, size=(None, None), button_color=None, background_color=None, text_color=None, icon=DEFAULT_WINDOW_ICON, font=None, no_titlebar=False, grab_anywhere=False, keep_on_top=False, location=(None, None), initial_folder=None): """ Display popup with text entry field and browse button. Browse for file :param message: :param default_path: :param default_extension: :param save_as: :param file_types: :param no_window: :param size: :param button_color: :param background_color: :param text_color: :param icon: :param font: :param no_titlebar: :param grab_anywhere: :param keep_on_top: :param location: :return: string representing the path chosen, None if cancelled or window closed with X """ global _my_windows if no_window: if _my_windows.NumOpenWindows: root = tk.Toplevel() else: root = tk.Tk() try: root.attributes('-alpha', 0) # hide window while building it. makes for smoother 'paint' except: pass if save_as: filename = tk.filedialog.asksaveasfilename(filetypes=file_types, defaultextension=default_extension) # show the 'get file' dialog box else: filename = tk.filedialog.askopenfilename(filetypes=file_types, defaultextension=default_extension) # show the 'get file' dialog box root.destroy() return filename browse_button = SaveAs(file_types=file_types, initial_folder=initial_folder) if save_as else FileBrowse( file_types=file_types, initial_folder=initial_folder) layout = [[Text(message, auto_size_text=True, text_color=text_color, background_color=background_color)], [InputText(default_text=default_path, size=size), browse_button], [Button('Ok', size=(6, 1), bind_return_key=True), Button('Cancel', size=(6, 1))]] window = Window(title=message, icon=icon, auto_size_text=True, button_color=button_color, font=font, background_color=background_color, no_titlebar=no_titlebar, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top, location=location) (button, input_values) = window.Layout(layout).Read() window.Close() if button != 'Ok': return None else: path = input_values[0] return path
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/PySimpleGUIWeb/PySimpleGUIWeb.py#L6652-L6714
train
PySimpleGUI/PySimpleGUI
DemoPrograms/Demo_Table_Simulation.py
TableSimulation
def TableSimulation(): """ Display data in a table format """ sg.SetOptions(element_padding=(0,0)) menu_def = [['File', ['Open', 'Save', 'Exit']], ['Edit', ['Paste', ['Special', 'Normal',], 'Undo'],], ['Help', 'About...'],] columm_layout = [[]] MAX_ROWS = 20 MAX_COL = 10 for i in range(MAX_ROWS): inputs = [sg.T('{}'.format(i), size=(4,1), justification='right')] + [sg.In(size=(10, 1), pad=(1, 1), justification='right', key=(i,j), do_not_clear=True) for j in range(MAX_COL)] columm_layout.append(inputs) layout = [ [sg.Menu(menu_def)], [sg.T('Table Using Combos and Input Elements', font='Any 18')], [sg.T('Type in a row, column and value. The form will update the values in realtime as you type'), sg.In(key='inputrow', justification='right', size=(8,1), pad=(1,1), do_not_clear=True), sg.In(key='inputcol', size=(8,1), pad=(1,1), justification='right', do_not_clear=True), sg.In(key='value', size=(8,1), pad=(1,1), justification='right', do_not_clear=True)], [sg.Column(columm_layout, size=(800,600), scrollable=True)] ] window = sg.Window('Table', return_keyboard_events=True).Layout(layout) while True: event, values = window.Read() # --- Process buttons --- # if event is None or event == 'Exit': break elif event == 'About...': sg.Popup('Demo of table capabilities') elif event == 'Open': filename = sg.PopupGetFile('filename to open', no_window=True, file_types=(("CSV Files","*.csv"),)) # --- populate table with file contents --- # if filename is not None: with open(filename, "r") as infile: reader = csv.reader(infile) try: data = list(reader) # read everything else into a list of rows except: sg.PopupError('Error reading file') continue # clear the table [window.FindElement((i,j)).Update('') for j in range(MAX_COL) for i in range(MAX_ROWS)] for i, row in enumerate(data): for j, item in enumerate(row): location = (i,j) try: # try the best we can at reading and filling the table target_element = window.FindElement(location) new_value = item if target_element is not None and new_value != '': target_element.Update(new_value) except: pass # if a valid table location entered, change that location's value try: location = (int(values['inputrow']), int(values['inputcol'])) target_element = window.FindElement(location) new_value = values['value'] if target_element is not None and new_value != '': target_element.Update(new_value) except: pass
python
def TableSimulation(): """ Display data in a table format """ sg.SetOptions(element_padding=(0,0)) menu_def = [['File', ['Open', 'Save', 'Exit']], ['Edit', ['Paste', ['Special', 'Normal',], 'Undo'],], ['Help', 'About...'],] columm_layout = [[]] MAX_ROWS = 20 MAX_COL = 10 for i in range(MAX_ROWS): inputs = [sg.T('{}'.format(i), size=(4,1), justification='right')] + [sg.In(size=(10, 1), pad=(1, 1), justification='right', key=(i,j), do_not_clear=True) for j in range(MAX_COL)] columm_layout.append(inputs) layout = [ [sg.Menu(menu_def)], [sg.T('Table Using Combos and Input Elements', font='Any 18')], [sg.T('Type in a row, column and value. The form will update the values in realtime as you type'), sg.In(key='inputrow', justification='right', size=(8,1), pad=(1,1), do_not_clear=True), sg.In(key='inputcol', size=(8,1), pad=(1,1), justification='right', do_not_clear=True), sg.In(key='value', size=(8,1), pad=(1,1), justification='right', do_not_clear=True)], [sg.Column(columm_layout, size=(800,600), scrollable=True)] ] window = sg.Window('Table', return_keyboard_events=True).Layout(layout) while True: event, values = window.Read() # --- Process buttons --- # if event is None or event == 'Exit': break elif event == 'About...': sg.Popup('Demo of table capabilities') elif event == 'Open': filename = sg.PopupGetFile('filename to open', no_window=True, file_types=(("CSV Files","*.csv"),)) # --- populate table with file contents --- # if filename is not None: with open(filename, "r") as infile: reader = csv.reader(infile) try: data = list(reader) # read everything else into a list of rows except: sg.PopupError('Error reading file') continue # clear the table [window.FindElement((i,j)).Update('') for j in range(MAX_COL) for i in range(MAX_ROWS)] for i, row in enumerate(data): for j, item in enumerate(row): location = (i,j) try: # try the best we can at reading and filling the table target_element = window.FindElement(location) new_value = item if target_element is not None and new_value != '': target_element.Update(new_value) except: pass # if a valid table location entered, change that location's value try: location = (int(values['inputrow']), int(values['inputcol'])) target_element = window.FindElement(location) new_value = values['value'] if target_element is not None and new_value != '': target_element.Update(new_value) except: pass
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Display data in a table format
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/DemoPrograms/Demo_Table_Simulation.py#L10-L78
train
PySimpleGUI/PySimpleGUI
HowDoI/PySimpleGUI-HowDoI.py
HowDoI
def HowDoI(): ''' Make and show a window (PySimpleGUI form) that takes user input and sends to the HowDoI web oracle Excellent example of 2 GUI concepts 1. Output Element that will show text in a scrolled window 2. Non-Window-Closing Buttons - These buttons will cause the form to return with the form's values, but doesn't close the form :return: never returns ''' # ------- Make a new Window ------- # sg.ChangeLookAndFeel('GreenTan') # give our form a spiffy set of colors layout = [ [sg.Text('Ask and your answer will appear here....', size=(40, 1))], [sg.Output(size=(127, 30), font=('Helvetica 10'))], [ sg.Spin(values=(1, 2, 3, 4), initial_value=1, size=(2, 1), key='Num Answers', font='Helvetica 15'), sg.Text('Num Answers',font='Helvetica 15'), sg.Checkbox('Display Full Text', key='full text', font='Helvetica 15'), sg.T('Command History', font='Helvetica 15'), sg.T('', size=(40,3), text_color=sg.BLUES[0], key='history')], [sg.Multiline(size=(85, 5), enter_submits=True, key='query', do_not_clear=False), sg.ReadButton('SEND', button_color=(sg.YELLOWS[0], sg.BLUES[0]), bind_return_key=True), sg.Button('EXIT', button_color=(sg.YELLOWS[0], sg.GREENS[0]))] ] window = sg.Window('How Do I ??', default_element_size=(30, 2), font=('Helvetica',' 13'), default_button_element_size=(8,2), icon=DEFAULT_ICON, return_keyboard_events=True).Layout(layout) # ---===--- Loop taking in user input and using it to query HowDoI --- # command_history = [] history_offset = 0 while True: (button, value) = window.Read() if button is 'SEND': query = value['query'].rstrip() print(query) QueryHowDoI(query, value['Num Answers'], value['full text']) # send the string to HowDoI command_history.append(query) history_offset = len(command_history)-1 window.FindElement('query').Update('') # manually clear input because keyboard events blocks clear window.FindElement('history').Update('\n'.join(command_history[-3:])) elif button is None or button is 'EXIT': # if exit button or closed using X break elif 'Up' in button and len(command_history): # scroll back in history command = command_history[history_offset] history_offset -= 1 * (history_offset > 0) # decrement is not zero window.FindElement('query').Update(command) elif 'Down' in button and len(command_history): # scroll forward in history history_offset += 1 * (history_offset < len(command_history)-1) # increment up to end of list command = command_history[history_offset] window.FindElement('query').Update(command) elif 'Escape' in button: # clear currently line window.FindElement('query').Update('')
python
def HowDoI(): ''' Make and show a window (PySimpleGUI form) that takes user input and sends to the HowDoI web oracle Excellent example of 2 GUI concepts 1. Output Element that will show text in a scrolled window 2. Non-Window-Closing Buttons - These buttons will cause the form to return with the form's values, but doesn't close the form :return: never returns ''' # ------- Make a new Window ------- # sg.ChangeLookAndFeel('GreenTan') # give our form a spiffy set of colors layout = [ [sg.Text('Ask and your answer will appear here....', size=(40, 1))], [sg.Output(size=(127, 30), font=('Helvetica 10'))], [ sg.Spin(values=(1, 2, 3, 4), initial_value=1, size=(2, 1), key='Num Answers', font='Helvetica 15'), sg.Text('Num Answers',font='Helvetica 15'), sg.Checkbox('Display Full Text', key='full text', font='Helvetica 15'), sg.T('Command History', font='Helvetica 15'), sg.T('', size=(40,3), text_color=sg.BLUES[0], key='history')], [sg.Multiline(size=(85, 5), enter_submits=True, key='query', do_not_clear=False), sg.ReadButton('SEND', button_color=(sg.YELLOWS[0], sg.BLUES[0]), bind_return_key=True), sg.Button('EXIT', button_color=(sg.YELLOWS[0], sg.GREENS[0]))] ] window = sg.Window('How Do I ??', default_element_size=(30, 2), font=('Helvetica',' 13'), default_button_element_size=(8,2), icon=DEFAULT_ICON, return_keyboard_events=True).Layout(layout) # ---===--- Loop taking in user input and using it to query HowDoI --- # command_history = [] history_offset = 0 while True: (button, value) = window.Read() if button is 'SEND': query = value['query'].rstrip() print(query) QueryHowDoI(query, value['Num Answers'], value['full text']) # send the string to HowDoI command_history.append(query) history_offset = len(command_history)-1 window.FindElement('query').Update('') # manually clear input because keyboard events blocks clear window.FindElement('history').Update('\n'.join(command_history[-3:])) elif button is None or button is 'EXIT': # if exit button or closed using X break elif 'Up' in button and len(command_history): # scroll back in history command = command_history[history_offset] history_offset -= 1 * (history_offset > 0) # decrement is not zero window.FindElement('query').Update(command) elif 'Down' in button and len(command_history): # scroll forward in history history_offset += 1 * (history_offset < len(command_history)-1) # increment up to end of list command = command_history[history_offset] window.FindElement('query').Update(command) elif 'Escape' in button: # clear currently line window.FindElement('query').Update('')
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/HowDoI/PySimpleGUI-HowDoI.py#L16-L69
train
PySimpleGUI/PySimpleGUI
HowDoI/PySimpleGUI-HowDoI.py
QueryHowDoI
def QueryHowDoI(Query, num_answers, full_text): ''' Kicks off a subprocess to send the 'Query' to HowDoI Prints the result, which in this program will route to a gooeyGUI window :param Query: text english question to ask the HowDoI web engine :return: nothing ''' howdoi_command = HOW_DO_I_COMMAND full_text_option = ' -a' if full_text else '' t = subprocess.Popen(howdoi_command + ' \"'+ Query + '\" -n ' + str(num_answers)+full_text_option, stdout=subprocess.PIPE) (output, err) = t.communicate() print('{:^88}'.format(Query.rstrip())) print('_'*60) print(output.decode("utf-8") ) exit_code = t.wait()
python
def QueryHowDoI(Query, num_answers, full_text): ''' Kicks off a subprocess to send the 'Query' to HowDoI Prints the result, which in this program will route to a gooeyGUI window :param Query: text english question to ask the HowDoI web engine :return: nothing ''' howdoi_command = HOW_DO_I_COMMAND full_text_option = ' -a' if full_text else '' t = subprocess.Popen(howdoi_command + ' \"'+ Query + '\" -n ' + str(num_answers)+full_text_option, stdout=subprocess.PIPE) (output, err) = t.communicate() print('{:^88}'.format(Query.rstrip())) print('_'*60) print(output.decode("utf-8") ) exit_code = t.wait()
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08184197f5bd4580ab5e5aca28bdda30f87b86fc
https://github.com/PySimpleGUI/PySimpleGUI/blob/08184197f5bd4580ab5e5aca28bdda30f87b86fc/HowDoI/PySimpleGUI-HowDoI.py#L72-L86
train
tensorflow/hub
tensorflow_hub/module_spec.py
ModuleSpec.export
def export(self, path, _sentinel=None, # pylint: disable=invalid-name checkpoint_path=None, name_transform_fn=None): """Exports a ModuleSpec with weights taken from a checkpoint. This is an helper to export modules directly from a ModuleSpec without having to create a session and set the variables to the intended values. Example usage: ```python spec = hub.create_module_spec(module_fn) spec.export("/path/to/export_module", checkpoint_path="/path/to/training_model") ``` In some cases, the variable name in the checkpoint does not match the variable name in the module. It is possible to work around that by providing a checkpoint_map_fn that performs the variable mapping. For example with: `name_transform_fn = lambda x: "extra_scope/" + x`. Args: path: path where to export the module to. _sentinel: used to prevent positional arguments besides `path`. checkpoint_path: path where to load the weights for the module. Mandatory parameter and must be passed by name. name_transform_fn: optional function to provide mapping between variable name in the module and the variable name in the checkpoint. Raises: ValueError: if missing mandatory `checkpoint_path` parameter. """ from tensorflow_hub.module import export_module_spec # pylint: disable=g-import-not-at-top if not checkpoint_path: raise ValueError("Missing mandatory `checkpoint_path` parameter") name_transform_fn = name_transform_fn or (lambda x: x) export_module_spec(self, path, checkpoint_path, name_transform_fn)
python
def export(self, path, _sentinel=None, # pylint: disable=invalid-name checkpoint_path=None, name_transform_fn=None): """Exports a ModuleSpec with weights taken from a checkpoint. This is an helper to export modules directly from a ModuleSpec without having to create a session and set the variables to the intended values. Example usage: ```python spec = hub.create_module_spec(module_fn) spec.export("/path/to/export_module", checkpoint_path="/path/to/training_model") ``` In some cases, the variable name in the checkpoint does not match the variable name in the module. It is possible to work around that by providing a checkpoint_map_fn that performs the variable mapping. For example with: `name_transform_fn = lambda x: "extra_scope/" + x`. Args: path: path where to export the module to. _sentinel: used to prevent positional arguments besides `path`. checkpoint_path: path where to load the weights for the module. Mandatory parameter and must be passed by name. name_transform_fn: optional function to provide mapping between variable name in the module and the variable name in the checkpoint. Raises: ValueError: if missing mandatory `checkpoint_path` parameter. """ from tensorflow_hub.module import export_module_spec # pylint: disable=g-import-not-at-top if not checkpoint_path: raise ValueError("Missing mandatory `checkpoint_path` parameter") name_transform_fn = name_transform_fn or (lambda x: x) export_module_spec(self, path, checkpoint_path, name_transform_fn)
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Exports a ModuleSpec with weights taken from a checkpoint. This is an helper to export modules directly from a ModuleSpec without having to create a session and set the variables to the intended values. Example usage: ```python spec = hub.create_module_spec(module_fn) spec.export("/path/to/export_module", checkpoint_path="/path/to/training_model") ``` In some cases, the variable name in the checkpoint does not match the variable name in the module. It is possible to work around that by providing a checkpoint_map_fn that performs the variable mapping. For example with: `name_transform_fn = lambda x: "extra_scope/" + x`. Args: path: path where to export the module to. _sentinel: used to prevent positional arguments besides `path`. checkpoint_path: path where to load the weights for the module. Mandatory parameter and must be passed by name. name_transform_fn: optional function to provide mapping between variable name in the module and the variable name in the checkpoint. Raises: ValueError: if missing mandatory `checkpoint_path` parameter.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/tensorflow_hub/module_spec.py#L41-L77
train
tensorflow/hub
tensorflow_hub/module_spec.py
ModuleSpec.get_attached_message
def get_attached_message(self, key, message_type, tags=None, required=False): """Returns the message attached to the module under the given key, or None. Module publishers can attach protocol messages to modules at creation time to provide module consumers with additional information, e.g., on module usage or provenance (see see hub.attach_message()). A typical use would be to store a small set of named values with modules of a certain type so that a support library for consumers of such modules can be parametric in those values. This method can also be called on a Module instantiated from a ModuleSpec, then `tags` are set to those used in module instatiation. Args: key: A string with the key of an attached message. message_type: A concrete protocol message class (*not* object) used to parse the attached message from its serialized representation. The message type for a particular key must be advertised with the key. tags: Optional set of strings, specifying the graph variant from which to read the attached message. required: An optional boolean. Setting it true changes the effect of an unknown `key` from returning None to raising a KeyError with text about attached messages. Returns: An instance of `message_type` with the message contents attached to the module, or `None` if `key` is unknown and `required` is False. Raises: KeyError: if `key` is unknown and `required` is True. """ attached_bytes = self._get_attached_bytes(key, tags) if attached_bytes is None: if required: raise KeyError("No attached message for key '%s' in graph version %s " "of Hub Module" % (key, sorted(tags or []))) else: return None message = message_type() message.ParseFromString(attached_bytes) return message
python
def get_attached_message(self, key, message_type, tags=None, required=False): """Returns the message attached to the module under the given key, or None. Module publishers can attach protocol messages to modules at creation time to provide module consumers with additional information, e.g., on module usage or provenance (see see hub.attach_message()). A typical use would be to store a small set of named values with modules of a certain type so that a support library for consumers of such modules can be parametric in those values. This method can also be called on a Module instantiated from a ModuleSpec, then `tags` are set to those used in module instatiation. Args: key: A string with the key of an attached message. message_type: A concrete protocol message class (*not* object) used to parse the attached message from its serialized representation. The message type for a particular key must be advertised with the key. tags: Optional set of strings, specifying the graph variant from which to read the attached message. required: An optional boolean. Setting it true changes the effect of an unknown `key` from returning None to raising a KeyError with text about attached messages. Returns: An instance of `message_type` with the message contents attached to the module, or `None` if `key` is unknown and `required` is False. Raises: KeyError: if `key` is unknown and `required` is True. """ attached_bytes = self._get_attached_bytes(key, tags) if attached_bytes is None: if required: raise KeyError("No attached message for key '%s' in graph version %s " "of Hub Module" % (key, sorted(tags or []))) else: return None message = message_type() message.ParseFromString(attached_bytes) return message
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Returns the message attached to the module under the given key, or None. Module publishers can attach protocol messages to modules at creation time to provide module consumers with additional information, e.g., on module usage or provenance (see see hub.attach_message()). A typical use would be to store a small set of named values with modules of a certain type so that a support library for consumers of such modules can be parametric in those values. This method can also be called on a Module instantiated from a ModuleSpec, then `tags` are set to those used in module instatiation. Args: key: A string with the key of an attached message. message_type: A concrete protocol message class (*not* object) used to parse the attached message from its serialized representation. The message type for a particular key must be advertised with the key. tags: Optional set of strings, specifying the graph variant from which to read the attached message. required: An optional boolean. Setting it true changes the effect of an unknown `key` from returning None to raising a KeyError with text about attached messages. Returns: An instance of `message_type` with the message contents attached to the module, or `None` if `key` is unknown and `required` is False. Raises: KeyError: if `key` is unknown and `required` is True.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/tensorflow_hub/module_spec.py#L129-L169
train
tensorflow/hub
examples/image_retraining/retrain.py
create_image_lists
def create_image_lists(image_dir, testing_percentage, validation_percentage): """Builds a list of training images from the file system. Analyzes the sub folders in the image directory, splits them into stable training, testing, and validation sets, and returns a data structure describing the lists of images for each label and their paths. Args: image_dir: String path to a folder containing subfolders of images. testing_percentage: Integer percentage of the images to reserve for tests. validation_percentage: Integer percentage of images reserved for validation. Returns: An OrderedDict containing an entry for each label subfolder, with images split into training, testing, and validation sets within each label. The order of items defines the class indices. """ if not tf.gfile.Exists(image_dir): tf.logging.error("Image directory '" + image_dir + "' not found.") return None result = collections.OrderedDict() sub_dirs = sorted(x[0] for x in tf.gfile.Walk(image_dir)) # The root directory comes first, so skip it. is_root_dir = True for sub_dir in sub_dirs: if is_root_dir: is_root_dir = False continue extensions = sorted(set(os.path.normcase(ext) # Smash case on Windows. for ext in ['JPEG', 'JPG', 'jpeg', 'jpg', 'png'])) file_list = [] dir_name = os.path.basename( # tf.gfile.Walk() returns sub-directory with trailing '/' when it is in # Google Cloud Storage, which confuses os.path.basename(). sub_dir[:-1] if sub_dir.endswith('/') else sub_dir) if dir_name == image_dir: continue tf.logging.info("Looking for images in '" + dir_name + "'") for extension in extensions: file_glob = os.path.join(image_dir, dir_name, '*.' + extension) file_list.extend(tf.gfile.Glob(file_glob)) if not file_list: tf.logging.warning('No files found') continue if len(file_list) < 20: tf.logging.warning( 'WARNING: Folder has less than 20 images, which may cause issues.') elif len(file_list) > MAX_NUM_IMAGES_PER_CLASS: tf.logging.warning( 'WARNING: Folder {} has more than {} images. Some images will ' 'never be selected.'.format(dir_name, MAX_NUM_IMAGES_PER_CLASS)) label_name = re.sub(r'[^a-z0-9]+', ' ', dir_name.lower()) training_images = [] testing_images = [] validation_images = [] for file_name in file_list: base_name = os.path.basename(file_name) # We want to ignore anything after '_nohash_' in the file name when # deciding which set to put an image in, the data set creator has a way of # grouping photos that are close variations of each other. For example # this is used in the plant disease data set to group multiple pictures of # the same leaf. hash_name = re.sub(r'_nohash_.*$', '', file_name) # This looks a bit magical, but we need to decide whether this file should # go into the training, testing, or validation sets, and we want to keep # existing files in the same set even if more files are subsequently # added. # To do that, we need a stable way of deciding based on just the file name # itself, so we do a hash of that and then use that to generate a # probability value that we use to assign it. hash_name_hashed = hashlib.sha1(tf.compat.as_bytes(hash_name)).hexdigest() percentage_hash = ((int(hash_name_hashed, 16) % (MAX_NUM_IMAGES_PER_CLASS + 1)) * (100.0 / MAX_NUM_IMAGES_PER_CLASS)) if percentage_hash < validation_percentage: validation_images.append(base_name) elif percentage_hash < (testing_percentage + validation_percentage): testing_images.append(base_name) else: training_images.append(base_name) result[label_name] = { 'dir': dir_name, 'training': training_images, 'testing': testing_images, 'validation': validation_images, } return result
python
def create_image_lists(image_dir, testing_percentage, validation_percentage): """Builds a list of training images from the file system. Analyzes the sub folders in the image directory, splits them into stable training, testing, and validation sets, and returns a data structure describing the lists of images for each label and their paths. Args: image_dir: String path to a folder containing subfolders of images. testing_percentage: Integer percentage of the images to reserve for tests. validation_percentage: Integer percentage of images reserved for validation. Returns: An OrderedDict containing an entry for each label subfolder, with images split into training, testing, and validation sets within each label. The order of items defines the class indices. """ if not tf.gfile.Exists(image_dir): tf.logging.error("Image directory '" + image_dir + "' not found.") return None result = collections.OrderedDict() sub_dirs = sorted(x[0] for x in tf.gfile.Walk(image_dir)) # The root directory comes first, so skip it. is_root_dir = True for sub_dir in sub_dirs: if is_root_dir: is_root_dir = False continue extensions = sorted(set(os.path.normcase(ext) # Smash case on Windows. for ext in ['JPEG', 'JPG', 'jpeg', 'jpg', 'png'])) file_list = [] dir_name = os.path.basename( # tf.gfile.Walk() returns sub-directory with trailing '/' when it is in # Google Cloud Storage, which confuses os.path.basename(). sub_dir[:-1] if sub_dir.endswith('/') else sub_dir) if dir_name == image_dir: continue tf.logging.info("Looking for images in '" + dir_name + "'") for extension in extensions: file_glob = os.path.join(image_dir, dir_name, '*.' + extension) file_list.extend(tf.gfile.Glob(file_glob)) if not file_list: tf.logging.warning('No files found') continue if len(file_list) < 20: tf.logging.warning( 'WARNING: Folder has less than 20 images, which may cause issues.') elif len(file_list) > MAX_NUM_IMAGES_PER_CLASS: tf.logging.warning( 'WARNING: Folder {} has more than {} images. Some images will ' 'never be selected.'.format(dir_name, MAX_NUM_IMAGES_PER_CLASS)) label_name = re.sub(r'[^a-z0-9]+', ' ', dir_name.lower()) training_images = [] testing_images = [] validation_images = [] for file_name in file_list: base_name = os.path.basename(file_name) # We want to ignore anything after '_nohash_' in the file name when # deciding which set to put an image in, the data set creator has a way of # grouping photos that are close variations of each other. For example # this is used in the plant disease data set to group multiple pictures of # the same leaf. hash_name = re.sub(r'_nohash_.*$', '', file_name) # This looks a bit magical, but we need to decide whether this file should # go into the training, testing, or validation sets, and we want to keep # existing files in the same set even if more files are subsequently # added. # To do that, we need a stable way of deciding based on just the file name # itself, so we do a hash of that and then use that to generate a # probability value that we use to assign it. hash_name_hashed = hashlib.sha1(tf.compat.as_bytes(hash_name)).hexdigest() percentage_hash = ((int(hash_name_hashed, 16) % (MAX_NUM_IMAGES_PER_CLASS + 1)) * (100.0 / MAX_NUM_IMAGES_PER_CLASS)) if percentage_hash < validation_percentage: validation_images.append(base_name) elif percentage_hash < (testing_percentage + validation_percentage): testing_images.append(base_name) else: training_images.append(base_name) result[label_name] = { 'dir': dir_name, 'training': training_images, 'testing': testing_images, 'validation': validation_images, } return result
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Builds a list of training images from the file system. Analyzes the sub folders in the image directory, splits them into stable training, testing, and validation sets, and returns a data structure describing the lists of images for each label and their paths. Args: image_dir: String path to a folder containing subfolders of images. testing_percentage: Integer percentage of the images to reserve for tests. validation_percentage: Integer percentage of images reserved for validation. Returns: An OrderedDict containing an entry for each label subfolder, with images split into training, testing, and validation sets within each label. The order of items defines the class indices.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L147-L234
train
tensorflow/hub
examples/image_retraining/retrain.py
get_image_path
def get_image_path(image_lists, label_name, index, image_dir, category): """Returns a path to an image for a label at the given index. Args: image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Int offset of the image we want. This will be moduloed by the available number of images for the label, so it can be arbitrarily large. image_dir: Root folder string of the subfolders containing the training images. category: Name string of set to pull images from - training, testing, or validation. Returns: File system path string to an image that meets the requested parameters. """ if label_name not in image_lists: tf.logging.fatal('Label does not exist %s.', label_name) label_lists = image_lists[label_name] if category not in label_lists: tf.logging.fatal('Category does not exist %s.', category) category_list = label_lists[category] if not category_list: tf.logging.fatal('Label %s has no images in the category %s.', label_name, category) mod_index = index % len(category_list) base_name = category_list[mod_index] sub_dir = label_lists['dir'] full_path = os.path.join(image_dir, sub_dir, base_name) return full_path
python
def get_image_path(image_lists, label_name, index, image_dir, category): """Returns a path to an image for a label at the given index. Args: image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Int offset of the image we want. This will be moduloed by the available number of images for the label, so it can be arbitrarily large. image_dir: Root folder string of the subfolders containing the training images. category: Name string of set to pull images from - training, testing, or validation. Returns: File system path string to an image that meets the requested parameters. """ if label_name not in image_lists: tf.logging.fatal('Label does not exist %s.', label_name) label_lists = image_lists[label_name] if category not in label_lists: tf.logging.fatal('Category does not exist %s.', category) category_list = label_lists[category] if not category_list: tf.logging.fatal('Label %s has no images in the category %s.', label_name, category) mod_index = index % len(category_list) base_name = category_list[mod_index] sub_dir = label_lists['dir'] full_path = os.path.join(image_dir, sub_dir, base_name) return full_path
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Returns a path to an image for a label at the given index. Args: image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Int offset of the image we want. This will be moduloed by the available number of images for the label, so it can be arbitrarily large. image_dir: Root folder string of the subfolders containing the training images. category: Name string of set to pull images from - training, testing, or validation. Returns: File system path string to an image that meets the requested parameters.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L237-L267
train
tensorflow/hub
examples/image_retraining/retrain.py
get_bottleneck_path
def get_bottleneck_path(image_lists, label_name, index, bottleneck_dir, category, module_name): """Returns a path to a bottleneck file for a label at the given index. Args: image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Integer offset of the image we want. This will be moduloed by the available number of images for the label, so it can be arbitrarily large. bottleneck_dir: Folder string holding cached files of bottleneck values. category: Name string of set to pull images from - training, testing, or validation. module_name: The name of the image module being used. Returns: File system path string to an image that meets the requested parameters. """ module_name = (module_name.replace('://', '~') # URL scheme. .replace('/', '~') # URL and Unix paths. .replace(':', '~').replace('\\', '~')) # Windows paths. return get_image_path(image_lists, label_name, index, bottleneck_dir, category) + '_' + module_name + '.txt'
python
def get_bottleneck_path(image_lists, label_name, index, bottleneck_dir, category, module_name): """Returns a path to a bottleneck file for a label at the given index. Args: image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Integer offset of the image we want. This will be moduloed by the available number of images for the label, so it can be arbitrarily large. bottleneck_dir: Folder string holding cached files of bottleneck values. category: Name string of set to pull images from - training, testing, or validation. module_name: The name of the image module being used. Returns: File system path string to an image that meets the requested parameters. """ module_name = (module_name.replace('://', '~') # URL scheme. .replace('/', '~') # URL and Unix paths. .replace(':', '~').replace('\\', '~')) # Windows paths. return get_image_path(image_lists, label_name, index, bottleneck_dir, category) + '_' + module_name + '.txt'
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Returns a path to a bottleneck file for a label at the given index. Args: image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Integer offset of the image we want. This will be moduloed by the available number of images for the label, so it can be arbitrarily large. bottleneck_dir: Folder string holding cached files of bottleneck values. category: Name string of set to pull images from - training, testing, or validation. module_name: The name of the image module being used. Returns: File system path string to an image that meets the requested parameters.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L270-L291
train
tensorflow/hub
examples/image_retraining/retrain.py
create_module_graph
def create_module_graph(module_spec): """Creates a graph and loads Hub Module into it. Args: module_spec: the hub.ModuleSpec for the image module being used. Returns: graph: the tf.Graph that was created. bottleneck_tensor: the bottleneck values output by the module. resized_input_tensor: the input images, resized as expected by the module. wants_quantization: a boolean, whether the module has been instrumented with fake quantization ops. """ height, width = hub.get_expected_image_size(module_spec) with tf.Graph().as_default() as graph: resized_input_tensor = tf.placeholder(tf.float32, [None, height, width, 3]) m = hub.Module(module_spec) bottleneck_tensor = m(resized_input_tensor) wants_quantization = any(node.op in FAKE_QUANT_OPS for node in graph.as_graph_def().node) return graph, bottleneck_tensor, resized_input_tensor, wants_quantization
python
def create_module_graph(module_spec): """Creates a graph and loads Hub Module into it. Args: module_spec: the hub.ModuleSpec for the image module being used. Returns: graph: the tf.Graph that was created. bottleneck_tensor: the bottleneck values output by the module. resized_input_tensor: the input images, resized as expected by the module. wants_quantization: a boolean, whether the module has been instrumented with fake quantization ops. """ height, width = hub.get_expected_image_size(module_spec) with tf.Graph().as_default() as graph: resized_input_tensor = tf.placeholder(tf.float32, [None, height, width, 3]) m = hub.Module(module_spec) bottleneck_tensor = m(resized_input_tensor) wants_quantization = any(node.op in FAKE_QUANT_OPS for node in graph.as_graph_def().node) return graph, bottleneck_tensor, resized_input_tensor, wants_quantization
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Creates a graph and loads Hub Module into it. Args: module_spec: the hub.ModuleSpec for the image module being used. Returns: graph: the tf.Graph that was created. bottleneck_tensor: the bottleneck values output by the module. resized_input_tensor: the input images, resized as expected by the module. wants_quantization: a boolean, whether the module has been instrumented with fake quantization ops.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L294-L314
train
tensorflow/hub
examples/image_retraining/retrain.py
run_bottleneck_on_image
def run_bottleneck_on_image(sess, image_data, image_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor): """Runs inference on an image to extract the 'bottleneck' summary layer. Args: sess: Current active TensorFlow Session. image_data: String of raw JPEG data. image_data_tensor: Input data layer in the graph. decoded_image_tensor: Output of initial image resizing and preprocessing. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: Layer before the final softmax. Returns: Numpy array of bottleneck values. """ # First decode the JPEG image, resize it, and rescale the pixel values. resized_input_values = sess.run(decoded_image_tensor, {image_data_tensor: image_data}) # Then run it through the recognition network. bottleneck_values = sess.run(bottleneck_tensor, {resized_input_tensor: resized_input_values}) bottleneck_values = np.squeeze(bottleneck_values) return bottleneck_values
python
def run_bottleneck_on_image(sess, image_data, image_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor): """Runs inference on an image to extract the 'bottleneck' summary layer. Args: sess: Current active TensorFlow Session. image_data: String of raw JPEG data. image_data_tensor: Input data layer in the graph. decoded_image_tensor: Output of initial image resizing and preprocessing. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: Layer before the final softmax. Returns: Numpy array of bottleneck values. """ # First decode the JPEG image, resize it, and rescale the pixel values. resized_input_values = sess.run(decoded_image_tensor, {image_data_tensor: image_data}) # Then run it through the recognition network. bottleneck_values = sess.run(bottleneck_tensor, {resized_input_tensor: resized_input_values}) bottleneck_values = np.squeeze(bottleneck_values) return bottleneck_values
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Runs inference on an image to extract the 'bottleneck' summary layer. Args: sess: Current active TensorFlow Session. image_data: String of raw JPEG data. image_data_tensor: Input data layer in the graph. decoded_image_tensor: Output of initial image resizing and preprocessing. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: Layer before the final softmax. Returns: Numpy array of bottleneck values.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L317-L340
train
tensorflow/hub
examples/image_retraining/retrain.py
create_bottleneck_file
def create_bottleneck_file(bottleneck_path, image_lists, label_name, index, image_dir, category, sess, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor): """Create a single bottleneck file.""" tf.logging.debug('Creating bottleneck at ' + bottleneck_path) image_path = get_image_path(image_lists, label_name, index, image_dir, category) if not tf.gfile.Exists(image_path): tf.logging.fatal('File does not exist %s', image_path) image_data = tf.gfile.GFile(image_path, 'rb').read() try: bottleneck_values = run_bottleneck_on_image( sess, image_data, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor) except Exception as e: raise RuntimeError('Error during processing file %s (%s)' % (image_path, str(e))) bottleneck_string = ','.join(str(x) for x in bottleneck_values) with open(bottleneck_path, 'w') as bottleneck_file: bottleneck_file.write(bottleneck_string)
python
def create_bottleneck_file(bottleneck_path, image_lists, label_name, index, image_dir, category, sess, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor): """Create a single bottleneck file.""" tf.logging.debug('Creating bottleneck at ' + bottleneck_path) image_path = get_image_path(image_lists, label_name, index, image_dir, category) if not tf.gfile.Exists(image_path): tf.logging.fatal('File does not exist %s', image_path) image_data = tf.gfile.GFile(image_path, 'rb').read() try: bottleneck_values = run_bottleneck_on_image( sess, image_data, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor) except Exception as e: raise RuntimeError('Error during processing file %s (%s)' % (image_path, str(e))) bottleneck_string = ','.join(str(x) for x in bottleneck_values) with open(bottleneck_path, 'w') as bottleneck_file: bottleneck_file.write(bottleneck_string)
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Create a single bottleneck file.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L353-L373
train
tensorflow/hub
examples/image_retraining/retrain.py
get_or_create_bottleneck
def get_or_create_bottleneck(sess, image_lists, label_name, index, image_dir, category, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name): """Retrieves or calculates bottleneck values for an image. If a cached version of the bottleneck data exists on-disk, return that, otherwise calculate the data and save it to disk for future use. Args: sess: The current active TensorFlow Session. image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Integer offset of the image we want. This will be modulo-ed by the available number of images for the label, so it can be arbitrarily large. image_dir: Root folder string of the subfolders containing the training images. category: Name string of which set to pull images from - training, testing, or validation. bottleneck_dir: Folder string holding cached files of bottleneck values. jpeg_data_tensor: The tensor to feed loaded jpeg data into. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The output tensor for the bottleneck values. module_name: The name of the image module being used. Returns: Numpy array of values produced by the bottleneck layer for the image. """ label_lists = image_lists[label_name] sub_dir = label_lists['dir'] sub_dir_path = os.path.join(bottleneck_dir, sub_dir) ensure_dir_exists(sub_dir_path) bottleneck_path = get_bottleneck_path(image_lists, label_name, index, bottleneck_dir, category, module_name) if not os.path.exists(bottleneck_path): create_bottleneck_file(bottleneck_path, image_lists, label_name, index, image_dir, category, sess, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor) with open(bottleneck_path, 'r') as bottleneck_file: bottleneck_string = bottleneck_file.read() did_hit_error = False try: bottleneck_values = [float(x) for x in bottleneck_string.split(',')] except ValueError: tf.logging.warning('Invalid float found, recreating bottleneck') did_hit_error = True if did_hit_error: create_bottleneck_file(bottleneck_path, image_lists, label_name, index, image_dir, category, sess, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor) with open(bottleneck_path, 'r') as bottleneck_file: bottleneck_string = bottleneck_file.read() # Allow exceptions to propagate here, since they shouldn't happen after a # fresh creation bottleneck_values = [float(x) for x in bottleneck_string.split(',')] return bottleneck_values
python
def get_or_create_bottleneck(sess, image_lists, label_name, index, image_dir, category, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name): """Retrieves or calculates bottleneck values for an image. If a cached version of the bottleneck data exists on-disk, return that, otherwise calculate the data and save it to disk for future use. Args: sess: The current active TensorFlow Session. image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Integer offset of the image we want. This will be modulo-ed by the available number of images for the label, so it can be arbitrarily large. image_dir: Root folder string of the subfolders containing the training images. category: Name string of which set to pull images from - training, testing, or validation. bottleneck_dir: Folder string holding cached files of bottleneck values. jpeg_data_tensor: The tensor to feed loaded jpeg data into. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The output tensor for the bottleneck values. module_name: The name of the image module being used. Returns: Numpy array of values produced by the bottleneck layer for the image. """ label_lists = image_lists[label_name] sub_dir = label_lists['dir'] sub_dir_path = os.path.join(bottleneck_dir, sub_dir) ensure_dir_exists(sub_dir_path) bottleneck_path = get_bottleneck_path(image_lists, label_name, index, bottleneck_dir, category, module_name) if not os.path.exists(bottleneck_path): create_bottleneck_file(bottleneck_path, image_lists, label_name, index, image_dir, category, sess, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor) with open(bottleneck_path, 'r') as bottleneck_file: bottleneck_string = bottleneck_file.read() did_hit_error = False try: bottleneck_values = [float(x) for x in bottleneck_string.split(',')] except ValueError: tf.logging.warning('Invalid float found, recreating bottleneck') did_hit_error = True if did_hit_error: create_bottleneck_file(bottleneck_path, image_lists, label_name, index, image_dir, category, sess, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor) with open(bottleneck_path, 'r') as bottleneck_file: bottleneck_string = bottleneck_file.read() # Allow exceptions to propagate here, since they shouldn't happen after a # fresh creation bottleneck_values = [float(x) for x in bottleneck_string.split(',')] return bottleneck_values
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Retrieves or calculates bottleneck values for an image. If a cached version of the bottleneck data exists on-disk, return that, otherwise calculate the data and save it to disk for future use. Args: sess: The current active TensorFlow Session. image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Integer offset of the image we want. This will be modulo-ed by the available number of images for the label, so it can be arbitrarily large. image_dir: Root folder string of the subfolders containing the training images. category: Name string of which set to pull images from - training, testing, or validation. bottleneck_dir: Folder string holding cached files of bottleneck values. jpeg_data_tensor: The tensor to feed loaded jpeg data into. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The output tensor for the bottleneck values. module_name: The name of the image module being used. Returns: Numpy array of values produced by the bottleneck layer for the image.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L376-L434
train
tensorflow/hub
examples/image_retraining/retrain.py
cache_bottlenecks
def cache_bottlenecks(sess, image_lists, image_dir, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name): """Ensures all the training, testing, and validation bottlenecks are cached. Because we're likely to read the same image multiple times (if there are no distortions applied during training) it can speed things up a lot if we calculate the bottleneck layer values once for each image during preprocessing, and then just read those cached values repeatedly during training. Here we go through all the images we've found, calculate those values, and save them off. Args: sess: The current active TensorFlow Session. image_lists: OrderedDict of training images for each label. image_dir: Root folder string of the subfolders containing the training images. bottleneck_dir: Folder string holding cached files of bottleneck values. jpeg_data_tensor: Input tensor for jpeg data from file. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The penultimate output layer of the graph. module_name: The name of the image module being used. Returns: Nothing. """ how_many_bottlenecks = 0 ensure_dir_exists(bottleneck_dir) for label_name, label_lists in image_lists.items(): for category in ['training', 'testing', 'validation']: category_list = label_lists[category] for index, unused_base_name in enumerate(category_list): get_or_create_bottleneck( sess, image_lists, label_name, index, image_dir, category, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name) how_many_bottlenecks += 1 if how_many_bottlenecks % 100 == 0: tf.logging.info( str(how_many_bottlenecks) + ' bottleneck files created.')
python
def cache_bottlenecks(sess, image_lists, image_dir, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name): """Ensures all the training, testing, and validation bottlenecks are cached. Because we're likely to read the same image multiple times (if there are no distortions applied during training) it can speed things up a lot if we calculate the bottleneck layer values once for each image during preprocessing, and then just read those cached values repeatedly during training. Here we go through all the images we've found, calculate those values, and save them off. Args: sess: The current active TensorFlow Session. image_lists: OrderedDict of training images for each label. image_dir: Root folder string of the subfolders containing the training images. bottleneck_dir: Folder string holding cached files of bottleneck values. jpeg_data_tensor: Input tensor for jpeg data from file. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The penultimate output layer of the graph. module_name: The name of the image module being used. Returns: Nothing. """ how_many_bottlenecks = 0 ensure_dir_exists(bottleneck_dir) for label_name, label_lists in image_lists.items(): for category in ['training', 'testing', 'validation']: category_list = label_lists[category] for index, unused_base_name in enumerate(category_list): get_or_create_bottleneck( sess, image_lists, label_name, index, image_dir, category, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name) how_many_bottlenecks += 1 if how_many_bottlenecks % 100 == 0: tf.logging.info( str(how_many_bottlenecks) + ' bottleneck files created.')
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Ensures all the training, testing, and validation bottlenecks are cached. Because we're likely to read the same image multiple times (if there are no distortions applied during training) it can speed things up a lot if we calculate the bottleneck layer values once for each image during preprocessing, and then just read those cached values repeatedly during training. Here we go through all the images we've found, calculate those values, and save them off. Args: sess: The current active TensorFlow Session. image_lists: OrderedDict of training images for each label. image_dir: Root folder string of the subfolders containing the training images. bottleneck_dir: Folder string holding cached files of bottleneck values. jpeg_data_tensor: Input tensor for jpeg data from file. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The penultimate output layer of the graph. module_name: The name of the image module being used. Returns: Nothing.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L437-L478
train
tensorflow/hub
examples/image_retraining/retrain.py
get_random_cached_bottlenecks
def get_random_cached_bottlenecks(sess, image_lists, how_many, category, bottleneck_dir, image_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name): """Retrieves bottleneck values for cached images. If no distortions are being applied, this function can retrieve the cached bottleneck values directly from disk for images. It picks a random set of images from the specified category. Args: sess: Current TensorFlow Session. image_lists: OrderedDict of training images for each label. how_many: If positive, a random sample of this size will be chosen. If negative, all bottlenecks will be retrieved. category: Name string of which set to pull from - training, testing, or validation. bottleneck_dir: Folder string holding cached files of bottleneck values. image_dir: Root folder string of the subfolders containing the training images. jpeg_data_tensor: The layer to feed jpeg image data into. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph. module_name: The name of the image module being used. Returns: List of bottleneck arrays, their corresponding ground truths, and the relevant filenames. """ class_count = len(image_lists.keys()) bottlenecks = [] ground_truths = [] filenames = [] if how_many >= 0: # Retrieve a random sample of bottlenecks. for unused_i in range(how_many): label_index = random.randrange(class_count) label_name = list(image_lists.keys())[label_index] image_index = random.randrange(MAX_NUM_IMAGES_PER_CLASS + 1) image_name = get_image_path(image_lists, label_name, image_index, image_dir, category) bottleneck = get_or_create_bottleneck( sess, image_lists, label_name, image_index, image_dir, category, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name) bottlenecks.append(bottleneck) ground_truths.append(label_index) filenames.append(image_name) else: # Retrieve all bottlenecks. for label_index, label_name in enumerate(image_lists.keys()): for image_index, image_name in enumerate( image_lists[label_name][category]): image_name = get_image_path(image_lists, label_name, image_index, image_dir, category) bottleneck = get_or_create_bottleneck( sess, image_lists, label_name, image_index, image_dir, category, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name) bottlenecks.append(bottleneck) ground_truths.append(label_index) filenames.append(image_name) return bottlenecks, ground_truths, filenames
python
def get_random_cached_bottlenecks(sess, image_lists, how_many, category, bottleneck_dir, image_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name): """Retrieves bottleneck values for cached images. If no distortions are being applied, this function can retrieve the cached bottleneck values directly from disk for images. It picks a random set of images from the specified category. Args: sess: Current TensorFlow Session. image_lists: OrderedDict of training images for each label. how_many: If positive, a random sample of this size will be chosen. If negative, all bottlenecks will be retrieved. category: Name string of which set to pull from - training, testing, or validation. bottleneck_dir: Folder string holding cached files of bottleneck values. image_dir: Root folder string of the subfolders containing the training images. jpeg_data_tensor: The layer to feed jpeg image data into. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph. module_name: The name of the image module being used. Returns: List of bottleneck arrays, their corresponding ground truths, and the relevant filenames. """ class_count = len(image_lists.keys()) bottlenecks = [] ground_truths = [] filenames = [] if how_many >= 0: # Retrieve a random sample of bottlenecks. for unused_i in range(how_many): label_index = random.randrange(class_count) label_name = list(image_lists.keys())[label_index] image_index = random.randrange(MAX_NUM_IMAGES_PER_CLASS + 1) image_name = get_image_path(image_lists, label_name, image_index, image_dir, category) bottleneck = get_or_create_bottleneck( sess, image_lists, label_name, image_index, image_dir, category, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name) bottlenecks.append(bottleneck) ground_truths.append(label_index) filenames.append(image_name) else: # Retrieve all bottlenecks. for label_index, label_name in enumerate(image_lists.keys()): for image_index, image_name in enumerate( image_lists[label_name][category]): image_name = get_image_path(image_lists, label_name, image_index, image_dir, category) bottleneck = get_or_create_bottleneck( sess, image_lists, label_name, image_index, image_dir, category, bottleneck_dir, jpeg_data_tensor, decoded_image_tensor, resized_input_tensor, bottleneck_tensor, module_name) bottlenecks.append(bottleneck) ground_truths.append(label_index) filenames.append(image_name) return bottlenecks, ground_truths, filenames
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Retrieves bottleneck values for cached images. If no distortions are being applied, this function can retrieve the cached bottleneck values directly from disk for images. It picks a random set of images from the specified category. Args: sess: Current TensorFlow Session. image_lists: OrderedDict of training images for each label. how_many: If positive, a random sample of this size will be chosen. If negative, all bottlenecks will be retrieved. category: Name string of which set to pull from - training, testing, or validation. bottleneck_dir: Folder string holding cached files of bottleneck values. image_dir: Root folder string of the subfolders containing the training images. jpeg_data_tensor: The layer to feed jpeg image data into. decoded_image_tensor: The output of decoding and resizing the image. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph. module_name: The name of the image module being used. Returns: List of bottleneck arrays, their corresponding ground truths, and the relevant filenames.
[ "Retrieves", "bottleneck", "values", "for", "cached", "images", "." ]
09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L481-L544
train
tensorflow/hub
examples/image_retraining/retrain.py
get_random_distorted_bottlenecks
def get_random_distorted_bottlenecks( sess, image_lists, how_many, category, image_dir, input_jpeg_tensor, distorted_image, resized_input_tensor, bottleneck_tensor): """Retrieves bottleneck values for training images, after distortions. If we're training with distortions like crops, scales, or flips, we have to recalculate the full model for every image, and so we can't use cached bottleneck values. Instead we find random images for the requested category, run them through the distortion graph, and then the full graph to get the bottleneck results for each. Args: sess: Current TensorFlow Session. image_lists: OrderedDict of training images for each label. how_many: The integer number of bottleneck values to return. category: Name string of which set of images to fetch - training, testing, or validation. image_dir: Root folder string of the subfolders containing the training images. input_jpeg_tensor: The input layer we feed the image data to. distorted_image: The output node of the distortion graph. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph. Returns: List of bottleneck arrays and their corresponding ground truths. """ class_count = len(image_lists.keys()) bottlenecks = [] ground_truths = [] for unused_i in range(how_many): label_index = random.randrange(class_count) label_name = list(image_lists.keys())[label_index] image_index = random.randrange(MAX_NUM_IMAGES_PER_CLASS + 1) image_path = get_image_path(image_lists, label_name, image_index, image_dir, category) if not tf.gfile.Exists(image_path): tf.logging.fatal('File does not exist %s', image_path) jpeg_data = tf.gfile.GFile(image_path, 'rb').read() # Note that we materialize the distorted_image_data as a numpy array before # sending running inference on the image. This involves 2 memory copies and # might be optimized in other implementations. distorted_image_data = sess.run(distorted_image, {input_jpeg_tensor: jpeg_data}) bottleneck_values = sess.run(bottleneck_tensor, {resized_input_tensor: distorted_image_data}) bottleneck_values = np.squeeze(bottleneck_values) bottlenecks.append(bottleneck_values) ground_truths.append(label_index) return bottlenecks, ground_truths
python
def get_random_distorted_bottlenecks( sess, image_lists, how_many, category, image_dir, input_jpeg_tensor, distorted_image, resized_input_tensor, bottleneck_tensor): """Retrieves bottleneck values for training images, after distortions. If we're training with distortions like crops, scales, or flips, we have to recalculate the full model for every image, and so we can't use cached bottleneck values. Instead we find random images for the requested category, run them through the distortion graph, and then the full graph to get the bottleneck results for each. Args: sess: Current TensorFlow Session. image_lists: OrderedDict of training images for each label. how_many: The integer number of bottleneck values to return. category: Name string of which set of images to fetch - training, testing, or validation. image_dir: Root folder string of the subfolders containing the training images. input_jpeg_tensor: The input layer we feed the image data to. distorted_image: The output node of the distortion graph. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph. Returns: List of bottleneck arrays and their corresponding ground truths. """ class_count = len(image_lists.keys()) bottlenecks = [] ground_truths = [] for unused_i in range(how_many): label_index = random.randrange(class_count) label_name = list(image_lists.keys())[label_index] image_index = random.randrange(MAX_NUM_IMAGES_PER_CLASS + 1) image_path = get_image_path(image_lists, label_name, image_index, image_dir, category) if not tf.gfile.Exists(image_path): tf.logging.fatal('File does not exist %s', image_path) jpeg_data = tf.gfile.GFile(image_path, 'rb').read() # Note that we materialize the distorted_image_data as a numpy array before # sending running inference on the image. This involves 2 memory copies and # might be optimized in other implementations. distorted_image_data = sess.run(distorted_image, {input_jpeg_tensor: jpeg_data}) bottleneck_values = sess.run(bottleneck_tensor, {resized_input_tensor: distorted_image_data}) bottleneck_values = np.squeeze(bottleneck_values) bottlenecks.append(bottleneck_values) ground_truths.append(label_index) return bottlenecks, ground_truths
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Retrieves bottleneck values for training images, after distortions. If we're training with distortions like crops, scales, or flips, we have to recalculate the full model for every image, and so we can't use cached bottleneck values. Instead we find random images for the requested category, run them through the distortion graph, and then the full graph to get the bottleneck results for each. Args: sess: Current TensorFlow Session. image_lists: OrderedDict of training images for each label. how_many: The integer number of bottleneck values to return. category: Name string of which set of images to fetch - training, testing, or validation. image_dir: Root folder string of the subfolders containing the training images. input_jpeg_tensor: The input layer we feed the image data to. distorted_image: The output node of the distortion graph. resized_input_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph. Returns: List of bottleneck arrays and their corresponding ground truths.
[ "Retrieves", "bottleneck", "values", "for", "training", "images", "after", "distortions", "." ]
09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L547-L596
train
tensorflow/hub
examples/image_retraining/retrain.py
add_input_distortions
def add_input_distortions(flip_left_right, random_crop, random_scale, random_brightness, module_spec): """Creates the operations to apply the specified distortions. During training it can help to improve the results if we run the images through simple distortions like crops, scales, and flips. These reflect the kind of variations we expect in the real world, and so can help train the model to cope with natural data more effectively. Here we take the supplied parameters and construct a network of operations to apply them to an image. Cropping ~~~~~~~~ Cropping is done by placing a bounding box at a random position in the full image. The cropping parameter controls the size of that box relative to the input image. If it's zero, then the box is the same size as the input and no cropping is performed. If the value is 50%, then the crop box will be half the width and height of the input. In a diagram it looks like this: < width > +---------------------+ | | | width - crop% | | < > | | +------+ | | | | | | | | | | | | | | +------+ | | | | | +---------------------+ Scaling ~~~~~~~ Scaling is a lot like cropping, except that the bounding box is always centered and its size varies randomly within the given range. For example if the scale percentage is zero, then the bounding box is the same size as the input and no scaling is applied. If it's 50%, then the bounding box will be in a random range between half the width and height and full size. Args: flip_left_right: Boolean whether to randomly mirror images horizontally. random_crop: Integer percentage setting the total margin used around the crop box. random_scale: Integer percentage of how much to vary the scale by. random_brightness: Integer range to randomly multiply the pixel values by. graph. module_spec: The hub.ModuleSpec for the image module being used. Returns: The jpeg input layer and the distorted result tensor. """ input_height, input_width = hub.get_expected_image_size(module_spec) input_depth = hub.get_num_image_channels(module_spec) jpeg_data = tf.placeholder(tf.string, name='DistortJPGInput') decoded_image = tf.image.decode_jpeg(jpeg_data, channels=input_depth) # Convert from full range of uint8 to range [0,1] of float32. decoded_image_as_float = tf.image.convert_image_dtype(decoded_image, tf.float32) decoded_image_4d = tf.expand_dims(decoded_image_as_float, 0) margin_scale = 1.0 + (random_crop / 100.0) resize_scale = 1.0 + (random_scale / 100.0) margin_scale_value = tf.constant(margin_scale) resize_scale_value = tf.random_uniform(shape=[], minval=1.0, maxval=resize_scale) scale_value = tf.multiply(margin_scale_value, resize_scale_value) precrop_width = tf.multiply(scale_value, input_width) precrop_height = tf.multiply(scale_value, input_height) precrop_shape = tf.stack([precrop_height, precrop_width]) precrop_shape_as_int = tf.cast(precrop_shape, dtype=tf.int32) precropped_image = tf.image.resize_bilinear(decoded_image_4d, precrop_shape_as_int) precropped_image_3d = tf.squeeze(precropped_image, axis=[0]) cropped_image = tf.random_crop(precropped_image_3d, [input_height, input_width, input_depth]) if flip_left_right: flipped_image = tf.image.random_flip_left_right(cropped_image) else: flipped_image = cropped_image brightness_min = 1.0 - (random_brightness / 100.0) brightness_max = 1.0 + (random_brightness / 100.0) brightness_value = tf.random_uniform(shape=[], minval=brightness_min, maxval=brightness_max) brightened_image = tf.multiply(flipped_image, brightness_value) distort_result = tf.expand_dims(brightened_image, 0, name='DistortResult') return jpeg_data, distort_result
python
def add_input_distortions(flip_left_right, random_crop, random_scale, random_brightness, module_spec): """Creates the operations to apply the specified distortions. During training it can help to improve the results if we run the images through simple distortions like crops, scales, and flips. These reflect the kind of variations we expect in the real world, and so can help train the model to cope with natural data more effectively. Here we take the supplied parameters and construct a network of operations to apply them to an image. Cropping ~~~~~~~~ Cropping is done by placing a bounding box at a random position in the full image. The cropping parameter controls the size of that box relative to the input image. If it's zero, then the box is the same size as the input and no cropping is performed. If the value is 50%, then the crop box will be half the width and height of the input. In a diagram it looks like this: < width > +---------------------+ | | | width - crop% | | < > | | +------+ | | | | | | | | | | | | | | +------+ | | | | | +---------------------+ Scaling ~~~~~~~ Scaling is a lot like cropping, except that the bounding box is always centered and its size varies randomly within the given range. For example if the scale percentage is zero, then the bounding box is the same size as the input and no scaling is applied. If it's 50%, then the bounding box will be in a random range between half the width and height and full size. Args: flip_left_right: Boolean whether to randomly mirror images horizontally. random_crop: Integer percentage setting the total margin used around the crop box. random_scale: Integer percentage of how much to vary the scale by. random_brightness: Integer range to randomly multiply the pixel values by. graph. module_spec: The hub.ModuleSpec for the image module being used. Returns: The jpeg input layer and the distorted result tensor. """ input_height, input_width = hub.get_expected_image_size(module_spec) input_depth = hub.get_num_image_channels(module_spec) jpeg_data = tf.placeholder(tf.string, name='DistortJPGInput') decoded_image = tf.image.decode_jpeg(jpeg_data, channels=input_depth) # Convert from full range of uint8 to range [0,1] of float32. decoded_image_as_float = tf.image.convert_image_dtype(decoded_image, tf.float32) decoded_image_4d = tf.expand_dims(decoded_image_as_float, 0) margin_scale = 1.0 + (random_crop / 100.0) resize_scale = 1.0 + (random_scale / 100.0) margin_scale_value = tf.constant(margin_scale) resize_scale_value = tf.random_uniform(shape=[], minval=1.0, maxval=resize_scale) scale_value = tf.multiply(margin_scale_value, resize_scale_value) precrop_width = tf.multiply(scale_value, input_width) precrop_height = tf.multiply(scale_value, input_height) precrop_shape = tf.stack([precrop_height, precrop_width]) precrop_shape_as_int = tf.cast(precrop_shape, dtype=tf.int32) precropped_image = tf.image.resize_bilinear(decoded_image_4d, precrop_shape_as_int) precropped_image_3d = tf.squeeze(precropped_image, axis=[0]) cropped_image = tf.random_crop(precropped_image_3d, [input_height, input_width, input_depth]) if flip_left_right: flipped_image = tf.image.random_flip_left_right(cropped_image) else: flipped_image = cropped_image brightness_min = 1.0 - (random_brightness / 100.0) brightness_max = 1.0 + (random_brightness / 100.0) brightness_value = tf.random_uniform(shape=[], minval=brightness_min, maxval=brightness_max) brightened_image = tf.multiply(flipped_image, brightness_value) distort_result = tf.expand_dims(brightened_image, 0, name='DistortResult') return jpeg_data, distort_result
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Creates the operations to apply the specified distortions. During training it can help to improve the results if we run the images through simple distortions like crops, scales, and flips. These reflect the kind of variations we expect in the real world, and so can help train the model to cope with natural data more effectively. Here we take the supplied parameters and construct a network of operations to apply them to an image. Cropping ~~~~~~~~ Cropping is done by placing a bounding box at a random position in the full image. The cropping parameter controls the size of that box relative to the input image. If it's zero, then the box is the same size as the input and no cropping is performed. If the value is 50%, then the crop box will be half the width and height of the input. In a diagram it looks like this: < width > +---------------------+ | | | width - crop% | | < > | | +------+ | | | | | | | | | | | | | | +------+ | | | | | +---------------------+ Scaling ~~~~~~~ Scaling is a lot like cropping, except that the bounding box is always centered and its size varies randomly within the given range. For example if the scale percentage is zero, then the bounding box is the same size as the input and no scaling is applied. If it's 50%, then the bounding box will be in a random range between half the width and height and full size. Args: flip_left_right: Boolean whether to randomly mirror images horizontally. random_crop: Integer percentage setting the total margin used around the crop box. random_scale: Integer percentage of how much to vary the scale by. random_brightness: Integer range to randomly multiply the pixel values by. graph. module_spec: The hub.ModuleSpec for the image module being used. Returns: The jpeg input layer and the distorted result tensor.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L617-L706
train
tensorflow/hub
examples/image_retraining/retrain.py
variable_summaries
def variable_summaries(var): """Attach a lot of summaries to a Tensor (for TensorBoard visualization).""" with tf.name_scope('summaries'): mean = tf.reduce_mean(var) tf.summary.scalar('mean', mean) with tf.name_scope('stddev'): stddev = tf.sqrt(tf.reduce_mean(tf.square(var - mean))) tf.summary.scalar('stddev', stddev) tf.summary.scalar('max', tf.reduce_max(var)) tf.summary.scalar('min', tf.reduce_min(var)) tf.summary.histogram('histogram', var)
python
def variable_summaries(var): """Attach a lot of summaries to a Tensor (for TensorBoard visualization).""" with tf.name_scope('summaries'): mean = tf.reduce_mean(var) tf.summary.scalar('mean', mean) with tf.name_scope('stddev'): stddev = tf.sqrt(tf.reduce_mean(tf.square(var - mean))) tf.summary.scalar('stddev', stddev) tf.summary.scalar('max', tf.reduce_max(var)) tf.summary.scalar('min', tf.reduce_min(var)) tf.summary.histogram('histogram', var)
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Attach a lot of summaries to a Tensor (for TensorBoard visualization).
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L709-L719
train
tensorflow/hub
examples/image_retraining/retrain.py
add_final_retrain_ops
def add_final_retrain_ops(class_count, final_tensor_name, bottleneck_tensor, quantize_layer, is_training): """Adds a new softmax and fully-connected layer for training and eval. We need to retrain the top layer to identify our new classes, so this function adds the right operations to the graph, along with some variables to hold the weights, and then sets up all the gradients for the backward pass. The set up for the softmax and fully-connected layers is based on: https://www.tensorflow.org/tutorials/mnist/beginners/index.html Args: class_count: Integer of how many categories of things we're trying to recognize. final_tensor_name: Name string for the new final node that produces results. bottleneck_tensor: The output of the main CNN graph. quantize_layer: Boolean, specifying whether the newly added layer should be instrumented for quantization with TF-Lite. is_training: Boolean, specifying whether the newly add layer is for training or eval. Returns: The tensors for the training and cross entropy results, and tensors for the bottleneck input and ground truth input. """ batch_size, bottleneck_tensor_size = bottleneck_tensor.get_shape().as_list() assert batch_size is None, 'We want to work with arbitrary batch size.' with tf.name_scope('input'): bottleneck_input = tf.placeholder_with_default( bottleneck_tensor, shape=[batch_size, bottleneck_tensor_size], name='BottleneckInputPlaceholder') ground_truth_input = tf.placeholder( tf.int64, [batch_size], name='GroundTruthInput') # Organizing the following ops so they are easier to see in TensorBoard. layer_name = 'final_retrain_ops' with tf.name_scope(layer_name): with tf.name_scope('weights'): initial_value = tf.truncated_normal( [bottleneck_tensor_size, class_count], stddev=0.001) layer_weights = tf.Variable(initial_value, name='final_weights') variable_summaries(layer_weights) with tf.name_scope('biases'): layer_biases = tf.Variable(tf.zeros([class_count]), name='final_biases') variable_summaries(layer_biases) with tf.name_scope('Wx_plus_b'): logits = tf.matmul(bottleneck_input, layer_weights) + layer_biases tf.summary.histogram('pre_activations', logits) final_tensor = tf.nn.softmax(logits, name=final_tensor_name) # The tf.contrib.quantize functions rewrite the graph in place for # quantization. The imported model graph has already been rewritten, so upon # calling these rewrites, only the newly added final layer will be # transformed. if quantize_layer: if is_training: tf.contrib.quantize.create_training_graph() else: tf.contrib.quantize.create_eval_graph() tf.summary.histogram('activations', final_tensor) # If this is an eval graph, we don't need to add loss ops or an optimizer. if not is_training: return None, None, bottleneck_input, ground_truth_input, final_tensor with tf.name_scope('cross_entropy'): cross_entropy_mean = tf.losses.sparse_softmax_cross_entropy( labels=ground_truth_input, logits=logits) tf.summary.scalar('cross_entropy', cross_entropy_mean) with tf.name_scope('train'): optimizer = tf.train.GradientDescentOptimizer(FLAGS.learning_rate) train_step = optimizer.minimize(cross_entropy_mean) return (train_step, cross_entropy_mean, bottleneck_input, ground_truth_input, final_tensor)
python
def add_final_retrain_ops(class_count, final_tensor_name, bottleneck_tensor, quantize_layer, is_training): """Adds a new softmax and fully-connected layer for training and eval. We need to retrain the top layer to identify our new classes, so this function adds the right operations to the graph, along with some variables to hold the weights, and then sets up all the gradients for the backward pass. The set up for the softmax and fully-connected layers is based on: https://www.tensorflow.org/tutorials/mnist/beginners/index.html Args: class_count: Integer of how many categories of things we're trying to recognize. final_tensor_name: Name string for the new final node that produces results. bottleneck_tensor: The output of the main CNN graph. quantize_layer: Boolean, specifying whether the newly added layer should be instrumented for quantization with TF-Lite. is_training: Boolean, specifying whether the newly add layer is for training or eval. Returns: The tensors for the training and cross entropy results, and tensors for the bottleneck input and ground truth input. """ batch_size, bottleneck_tensor_size = bottleneck_tensor.get_shape().as_list() assert batch_size is None, 'We want to work with arbitrary batch size.' with tf.name_scope('input'): bottleneck_input = tf.placeholder_with_default( bottleneck_tensor, shape=[batch_size, bottleneck_tensor_size], name='BottleneckInputPlaceholder') ground_truth_input = tf.placeholder( tf.int64, [batch_size], name='GroundTruthInput') # Organizing the following ops so they are easier to see in TensorBoard. layer_name = 'final_retrain_ops' with tf.name_scope(layer_name): with tf.name_scope('weights'): initial_value = tf.truncated_normal( [bottleneck_tensor_size, class_count], stddev=0.001) layer_weights = tf.Variable(initial_value, name='final_weights') variable_summaries(layer_weights) with tf.name_scope('biases'): layer_biases = tf.Variable(tf.zeros([class_count]), name='final_biases') variable_summaries(layer_biases) with tf.name_scope('Wx_plus_b'): logits = tf.matmul(bottleneck_input, layer_weights) + layer_biases tf.summary.histogram('pre_activations', logits) final_tensor = tf.nn.softmax(logits, name=final_tensor_name) # The tf.contrib.quantize functions rewrite the graph in place for # quantization. The imported model graph has already been rewritten, so upon # calling these rewrites, only the newly added final layer will be # transformed. if quantize_layer: if is_training: tf.contrib.quantize.create_training_graph() else: tf.contrib.quantize.create_eval_graph() tf.summary.histogram('activations', final_tensor) # If this is an eval graph, we don't need to add loss ops or an optimizer. if not is_training: return None, None, bottleneck_input, ground_truth_input, final_tensor with tf.name_scope('cross_entropy'): cross_entropy_mean = tf.losses.sparse_softmax_cross_entropy( labels=ground_truth_input, logits=logits) tf.summary.scalar('cross_entropy', cross_entropy_mean) with tf.name_scope('train'): optimizer = tf.train.GradientDescentOptimizer(FLAGS.learning_rate) train_step = optimizer.minimize(cross_entropy_mean) return (train_step, cross_entropy_mean, bottleneck_input, ground_truth_input, final_tensor)
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Adds a new softmax and fully-connected layer for training and eval. We need to retrain the top layer to identify our new classes, so this function adds the right operations to the graph, along with some variables to hold the weights, and then sets up all the gradients for the backward pass. The set up for the softmax and fully-connected layers is based on: https://www.tensorflow.org/tutorials/mnist/beginners/index.html Args: class_count: Integer of how many categories of things we're trying to recognize. final_tensor_name: Name string for the new final node that produces results. bottleneck_tensor: The output of the main CNN graph. quantize_layer: Boolean, specifying whether the newly added layer should be instrumented for quantization with TF-Lite. is_training: Boolean, specifying whether the newly add layer is for training or eval. Returns: The tensors for the training and cross entropy results, and tensors for the bottleneck input and ground truth input.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L722-L804
train
tensorflow/hub
examples/image_retraining/retrain.py
add_evaluation_step
def add_evaluation_step(result_tensor, ground_truth_tensor): """Inserts the operations we need to evaluate the accuracy of our results. Args: result_tensor: The new final node that produces results. ground_truth_tensor: The node we feed ground truth data into. Returns: Tuple of (evaluation step, prediction). """ with tf.name_scope('accuracy'): with tf.name_scope('correct_prediction'): prediction = tf.argmax(result_tensor, 1) correct_prediction = tf.equal(prediction, ground_truth_tensor) with tf.name_scope('accuracy'): evaluation_step = tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) tf.summary.scalar('accuracy', evaluation_step) return evaluation_step, prediction
python
def add_evaluation_step(result_tensor, ground_truth_tensor): """Inserts the operations we need to evaluate the accuracy of our results. Args: result_tensor: The new final node that produces results. ground_truth_tensor: The node we feed ground truth data into. Returns: Tuple of (evaluation step, prediction). """ with tf.name_scope('accuracy'): with tf.name_scope('correct_prediction'): prediction = tf.argmax(result_tensor, 1) correct_prediction = tf.equal(prediction, ground_truth_tensor) with tf.name_scope('accuracy'): evaluation_step = tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) tf.summary.scalar('accuracy', evaluation_step) return evaluation_step, prediction
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Inserts the operations we need to evaluate the accuracy of our results. Args: result_tensor: The new final node that produces results. ground_truth_tensor: The node we feed ground truth data into. Returns: Tuple of (evaluation step, prediction).
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L807-L825
train
tensorflow/hub
examples/image_retraining/retrain.py
run_final_eval
def run_final_eval(train_session, module_spec, class_count, image_lists, jpeg_data_tensor, decoded_image_tensor, resized_image_tensor, bottleneck_tensor): """Runs a final evaluation on an eval graph using the test data set. Args: train_session: Session for the train graph with the tensors below. module_spec: The hub.ModuleSpec for the image module being used. class_count: Number of classes image_lists: OrderedDict of training images for each label. jpeg_data_tensor: The layer to feed jpeg image data into. decoded_image_tensor: The output of decoding and resizing the image. resized_image_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph. """ test_bottlenecks, test_ground_truth, test_filenames = ( get_random_cached_bottlenecks(train_session, image_lists, FLAGS.test_batch_size, 'testing', FLAGS.bottleneck_dir, FLAGS.image_dir, jpeg_data_tensor, decoded_image_tensor, resized_image_tensor, bottleneck_tensor, FLAGS.tfhub_module)) (eval_session, _, bottleneck_input, ground_truth_input, evaluation_step, prediction) = build_eval_session(module_spec, class_count) test_accuracy, predictions = eval_session.run( [evaluation_step, prediction], feed_dict={ bottleneck_input: test_bottlenecks, ground_truth_input: test_ground_truth }) tf.logging.info('Final test accuracy = %.1f%% (N=%d)' % (test_accuracy * 100, len(test_bottlenecks))) if FLAGS.print_misclassified_test_images: tf.logging.info('=== MISCLASSIFIED TEST IMAGES ===') for i, test_filename in enumerate(test_filenames): if predictions[i] != test_ground_truth[i]: tf.logging.info('%70s %s' % (test_filename, list(image_lists.keys())[predictions[i]]))
python
def run_final_eval(train_session, module_spec, class_count, image_lists, jpeg_data_tensor, decoded_image_tensor, resized_image_tensor, bottleneck_tensor): """Runs a final evaluation on an eval graph using the test data set. Args: train_session: Session for the train graph with the tensors below. module_spec: The hub.ModuleSpec for the image module being used. class_count: Number of classes image_lists: OrderedDict of training images for each label. jpeg_data_tensor: The layer to feed jpeg image data into. decoded_image_tensor: The output of decoding and resizing the image. resized_image_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph. """ test_bottlenecks, test_ground_truth, test_filenames = ( get_random_cached_bottlenecks(train_session, image_lists, FLAGS.test_batch_size, 'testing', FLAGS.bottleneck_dir, FLAGS.image_dir, jpeg_data_tensor, decoded_image_tensor, resized_image_tensor, bottleneck_tensor, FLAGS.tfhub_module)) (eval_session, _, bottleneck_input, ground_truth_input, evaluation_step, prediction) = build_eval_session(module_spec, class_count) test_accuracy, predictions = eval_session.run( [evaluation_step, prediction], feed_dict={ bottleneck_input: test_bottlenecks, ground_truth_input: test_ground_truth }) tf.logging.info('Final test accuracy = %.1f%% (N=%d)' % (test_accuracy * 100, len(test_bottlenecks))) if FLAGS.print_misclassified_test_images: tf.logging.info('=== MISCLASSIFIED TEST IMAGES ===') for i, test_filename in enumerate(test_filenames): if predictions[i] != test_ground_truth[i]: tf.logging.info('%70s %s' % (test_filename, list(image_lists.keys())[predictions[i]]))
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Runs a final evaluation on an eval graph using the test data set. Args: train_session: Session for the train graph with the tensors below. module_spec: The hub.ModuleSpec for the image module being used. class_count: Number of classes image_lists: OrderedDict of training images for each label. jpeg_data_tensor: The layer to feed jpeg image data into. decoded_image_tensor: The output of decoding and resizing the image. resized_image_tensor: The input node of the recognition graph. bottleneck_tensor: The bottleneck output layer of the CNN graph.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L828-L867
train
tensorflow/hub
examples/image_retraining/retrain.py
build_eval_session
def build_eval_session(module_spec, class_count): """Builds an restored eval session without train operations for exporting. Args: module_spec: The hub.ModuleSpec for the image module being used. class_count: Number of classes Returns: Eval session containing the restored eval graph. The bottleneck input, ground truth, eval step, and prediction tensors. """ # If quantized, we need to create the correct eval graph for exporting. eval_graph, bottleneck_tensor, resized_input_tensor, wants_quantization = ( create_module_graph(module_spec)) eval_sess = tf.Session(graph=eval_graph) with eval_graph.as_default(): # Add the new layer for exporting. (_, _, bottleneck_input, ground_truth_input, final_tensor) = add_final_retrain_ops( class_count, FLAGS.final_tensor_name, bottleneck_tensor, wants_quantization, is_training=False) # Now we need to restore the values from the training graph to the eval # graph. tf.train.Saver().restore(eval_sess, CHECKPOINT_NAME) evaluation_step, prediction = add_evaluation_step(final_tensor, ground_truth_input) return (eval_sess, resized_input_tensor, bottleneck_input, ground_truth_input, evaluation_step, prediction)
python
def build_eval_session(module_spec, class_count): """Builds an restored eval session without train operations for exporting. Args: module_spec: The hub.ModuleSpec for the image module being used. class_count: Number of classes Returns: Eval session containing the restored eval graph. The bottleneck input, ground truth, eval step, and prediction tensors. """ # If quantized, we need to create the correct eval graph for exporting. eval_graph, bottleneck_tensor, resized_input_tensor, wants_quantization = ( create_module_graph(module_spec)) eval_sess = tf.Session(graph=eval_graph) with eval_graph.as_default(): # Add the new layer for exporting. (_, _, bottleneck_input, ground_truth_input, final_tensor) = add_final_retrain_ops( class_count, FLAGS.final_tensor_name, bottleneck_tensor, wants_quantization, is_training=False) # Now we need to restore the values from the training graph to the eval # graph. tf.train.Saver().restore(eval_sess, CHECKPOINT_NAME) evaluation_step, prediction = add_evaluation_step(final_tensor, ground_truth_input) return (eval_sess, resized_input_tensor, bottleneck_input, ground_truth_input, evaluation_step, prediction)
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Builds an restored eval session without train operations for exporting. Args: module_spec: The hub.ModuleSpec for the image module being used. class_count: Number of classes Returns: Eval session containing the restored eval graph. The bottleneck input, ground truth, eval step, and prediction tensors.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L870-L901
train
tensorflow/hub
examples/image_retraining/retrain.py
save_graph_to_file
def save_graph_to_file(graph_file_name, module_spec, class_count): """Saves an graph to file, creating a valid quantized one if necessary.""" sess, _, _, _, _, _ = build_eval_session(module_spec, class_count) graph = sess.graph output_graph_def = tf.graph_util.convert_variables_to_constants( sess, graph.as_graph_def(), [FLAGS.final_tensor_name]) with tf.gfile.GFile(graph_file_name, 'wb') as f: f.write(output_graph_def.SerializeToString())
python
def save_graph_to_file(graph_file_name, module_spec, class_count): """Saves an graph to file, creating a valid quantized one if necessary.""" sess, _, _, _, _, _ = build_eval_session(module_spec, class_count) graph = sess.graph output_graph_def = tf.graph_util.convert_variables_to_constants( sess, graph.as_graph_def(), [FLAGS.final_tensor_name]) with tf.gfile.GFile(graph_file_name, 'wb') as f: f.write(output_graph_def.SerializeToString())
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Saves an graph to file, creating a valid quantized one if necessary.
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09f45963f6787322967b6fec61459f3ac56fbb27
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/image_retraining/retrain.py#L904-L913
train