def test_clipboard_copy_tabs_default(self, sep, excel, df): kwargs = build_kwargs(sep, excel) df.to_clipboard(**kwargs) if PY2: # to_clipboard copies unicode, to_csv produces bytes. This is # expected behavior assert clipboard_get().encode('utf-8') == df.to_csv(sep='\t') else: assert clipboard_get() == df.to_csv(sep='\t')
def test_clipboard_copy_tabs_default(self, sep, excel, df): kwargs = build_kwargs(sep, excel) df.to_clipboard(**kwargs) if PY2: # to_clipboard copies unicode, to_csv produces bytes. This is # expected behavior assert clipboard_get().encode('utf-8') == df.to_csv(sep='\t') else: assert clipboard_get() == df.to_csv(sep='\t')
def parse_grid(data=None, sep=None, nostrip=False, comment='#', jagged=False): if data is None: data = clipboard_get() if not nostrip: data = dedent(data.rstrip()).strip() lines = data.splitlines() if comment: lines = [re.sub(comment + '.*$', '', line).strip() for line in lines] lines = [line for line in lines if line] if sep is None: sep = guess_splitter(lines) if sep is not None and sep != '': lines = [re.split(sep, line) for line in lines] else: lines = [list(line) for line in lines] all_items = sum(lines, []) mode = str if all(re.match('^\d+$', d) for d in all_items): mode = int elif all(re.match('^\d+\.?\d*$', d) for d in all_items): mode = float is_rect = all(len(line) == len(lines[0]) for line in lines) if is_rect: jagged = False if jagged: return np.array( [np.array([mode(val) for val in line]) for line in lines]) data = np.array([mode(val) for val in all_items]) if is_rect: data = data.reshape(len(lines), -1) return data
def get_content(): address = input( "Please paste the address or please enter and what it has copied to clipboard will be used: \n" ) if not address: address = clipboard_get() return address
def read_clipboard(self): """Read clipboard into uplaod buffer. """ from pandas.io.clipboard import clipboard_get try: self.paste_bin.value = clipboard_get() except Exception as e: print(e)
def read_clipboard(sep='\s+', **kwargs): # pragma: no cover r""" Read text from clipboard and pass to read_table. See read_table for the full argument list Parameters ---------- sep : str, default '\s+'. A string or regex delimiter. The default of '\s+' denotes one or more whitespace characters. Returns ------- parsed : DataFrame """ encoding = kwargs.pop('encoding', 'utf-8') # only utf-8 is valid for passed value because that's what clipboard # supports if encoding is not None and encoding.lower().replace('-', '') != 'utf8': raise NotImplementedError( 'reading from clipboard only supports utf-8 encoding') from pandas.io.clipboard import clipboard_get from pandas.io.parsers import read_table text = clipboard_get() # try to decode (if needed on PY3) # Strange. linux py33 doesn't complain, win py33 does if compat.PY3: try: text = compat.bytes_to_str( text, encoding=(kwargs.get('encoding') or get_option('display.encoding'))) except: pass # Excel copies into clipboard with \t separation # inspect no more then the 10 first lines, if they # all contain an equal number (>0) of tabs, infer # that this came from excel and set 'sep' accordingly lines = text[:10000].split('\n')[:-1][:10] # Need to remove leading white space, since read_table # accepts: # a b # 0 1 2 # 1 3 4 counts = set([x.lstrip().count('\t') for x in lines]) if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0: sep = '\t' if sep is None and kwargs.get('delim_whitespace') is None: sep = '\s+' return read_table(StringIO(text), sep=sep, **kwargs)
def read_clipboard(sep=r'\s+', **kwargs): # pragma: no cover r""" Read text from clipboard and pass to read_table. See read_table for the full argument list Parameters ---------- sep : str, default '\s+'. A string or regex delimiter. The default of '\s+' denotes one or more whitespace characters. Returns ------- parsed : DataFrame """ encoding = kwargs.pop('encoding', 'utf-8') # only utf-8 is valid for passed value because that's what clipboard # supports if encoding is not None and encoding.lower().replace('-', '') != 'utf8': raise NotImplementedError( 'reading from clipboard only supports utf-8 encoding') from pandas.io.clipboard import clipboard_get from pandas.io.parsers import read_table text = clipboard_get() # try to decode (if needed on PY3) # Strange. linux py33 doesn't complain, win py33 does if compat.PY3: try: text = compat.bytes_to_str( text, encoding=(kwargs.get('encoding') or get_option('display.encoding')) ) except: pass # Excel copies into clipboard with \t separation # inspect no more then the 10 first lines, if they # all contain an equal number (>0) of tabs, infer # that this came from excel and set 'sep' accordingly lines = text[:10000].split('\n')[:-1][:10] # Need to remove leading white space, since read_table # accepts: # a b # 0 1 2 # 1 3 4 counts = {x.lstrip().count('\t') for x in lines} if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0: sep = r'\t' if sep is None and kwargs.get('delim_whitespace') is None: sep = r'\s+' return read_table(StringIO(text), sep=sep, **kwargs)
def parse_table(table=None, sep='\s+', header=None, conv=None, **kw): if table is None: table = clipboard_get() if isinstance(table, str): table = io.StringIO(table) if conv is not None: kw['converters'] = dict(enumerate(conv)) kw.setdefault("comment", '#') return pd.read_table(table, sep=sep, header=header, **kw)
def read_clipboard(sep=r"\s+", **kwargs): # pragma: no cover encoding = kwargs.pop("encoding", "utf-8") # only utf-8 is valid for passed value because that's what clipboard # supports if encoding is not None and encoding.lower().replace("-", "") != "utf8": raise NotImplementedError( "reading from clipboard only supports utf-8 encoding") from pandas.io.clipboard import clipboard_get from pandas.io.parsers import read_csv text = clipboard_get() # Try to decode (if needed, as "text" might already be a string here). try: text = text.decode( kwargs.get("encoding") or get_option("display.encoding")) except AttributeError: pass # Excel copies into clipboard with \t separation # inspect no more then the 10 first lines, if they # all contain an equal number (>0) of tabs, infer # that this came from excel and set 'sep' accordingly lines = text[:10000].split("\n")[:-1][:10] # Need to remove leading white space, since read_csv # accepts: # a b # 0 1 2 # 1 3 4 counts = {x.lstrip().count("\t") for x in lines} if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0: sep = "\t" # Edge case where sep is specified to be None, return to default if sep is None and kwargs.get("delim_whitespace") is None: sep = r"\s+" # Regex separator currently only works with python engine. # Default to python if separator is multi-character (regex) if len(sep) > 1 and kwargs.get("engine") is None: kwargs["engine"] = "python" elif len(sep) > 1 and kwargs.get("engine") == "c": warnings.warn( "read_clipboard with regex separator does not work properly with c engine" ) return read_csv(StringIO(text), sep=sep, **kwargs)
def test_raw_roundtrip(data): # PR #25040 wide unicode wasn't copied correctly on PY3 on windows clipboard_set(data) assert data == clipboard_get()
def get_clipboard(): pass return clipboard_get()
def clip_read(): from pandas.io import clipboard clipboard.clipboard_get()
title (str): The title subtitle (str): The subtitle sound (str): The macOS X sound """ code, out, err = osascript.run( 'display notification "{0}" with title "{1}" subtitle "{2}" sound name "{3}"' .format(message, title, subtitle, sound)) ## Main process if argsVid == 'clipboard': # this is True (i.e. argsVid == 'clipboard') only if debugModeOn is set to "False" # 1) Retrieving stored clipboard value print('\n1) Retrieving stored clipboard value') clipboard_value = clipboard_get() else: # 1) Retrieving the ".ipynb" file path argument print('\n1) Retrieving the ".ipynb" file path argument') clipboard_value = argsVid print(' clipboard_value: {0}'.format(clipboard_value.encode('utf-8'))) if os.path.isfile( clipboard_value ): # checking if the file exists on the computer (cf.: https://linuxize.com/post/python-check-if-file-exists/) try: # 2) Converting ".ipynb" to ".html" (cf.: https://github.com/jupyter/nbconvert) # (Example: jupyter nbconvert --to html my_file.ipynb) print('2) Converting ".ipynb" to ".html"')
def build_maps(tour='DEFAULT'): # copy from clipboard # assumes a list separated by \n, as if written in a google sheets column from pandas.io.clipboard import clipboard_get maplist = [x.strip() for x in clipboard_get().split('\n')] # copy the maps over from battlecode20-internal-scaffold for m in maplist: with open(INTERNAL_SCAFFOLD_PATH + '/src/maps/' + m + '.java', 'r') as f: mp = f.read() # change the package name mp = mp.replace('package maps', 'package battlecode.world.maps') # change the path mp = mp.replace( 'public static final String outputDirectory = "maps/";', 'public static final String outputDirectory = "engine/src/main/battlecode/world/resources/";' ) # write to maps with open('engine/src/main/battlecode/world/maps/' + m + '.java', 'w') as f: f.write(mp) # add the maps to BuildMaps.java with open(ENGINE_WORLD_PATH + "/BuildMaps.java", "r") as f: bmps = f.read() bmps = bmps.replace( 'public static void main(String[] args) {', 'public static void main(String[] args) {\n' + '\n'.join([' ' + m + '.main(args);' for m in maplist])) with open(ENGINE_WORLD_PATH + "/BuildMaps.java", "w") as f: f.write(bmps) # build the maps os.system('./gradlew buildMaps') # now update SERVER_MAPS in client/visualizer/constants.ts with open('client/visualizer/src/constants.ts', 'r') as f: cs = f.read() cs = cs.replace( 'export const SERVER_MAPS: Map<string, MapType> = new Map<string, MapType>([', 'export const SERVER_MAPS: Map<string, MapType> = new Map<string, MapType>([\n' + '\n'.join([' ["' + m + '", MapType.' + tour + '],' for m in maplist])) with open('client/visualizer/src/constants.ts', 'w') as f: f.write(cs) # now update backend/settings.py with open('backend/settings.py', 'r') as f: cs = f.read() cs = cs.replace( 'SERVER_MAPS = [', 'SERVER_MAPS = [\n' + '\n'.join([' "' + m + '",' for m in maplist])) with open('backend/settings.py', 'w') as f: f.write(cs)
#!/usr/bin/env python import gspread import json import os import re import requests from webloc2csv import sanitize_title, get_url_tags, get_keyword_tags # clean_url, extract_title_n_url, add_tags from bs4 import BeautifulSoup from oauth2client.service_account import ServiceAccountCredentials from pandas.io.clipboard import clipboard_get # ----- Initialization ----- clipboard_txt = clipboard_get() print(f'Clipboard text:\n{clipboard_txt}') # ----- Helper Subroutines ----- def clipboard_to_url(clipboard_txt): """ Returns url if the clipboard text starts with http otherwise, returns None """ if clipboard_txt.startswith('http'): return clipboard_txt else: print('Clipboard content is not a url:') print(f'{clipboard_txt}') return None
from pandas.io.clipboard import clipboard_get, clipboard_set text = clipboard_get() print(text) clipboard_set("http://evil-website.net") text = clipboard_get() print(text)
from gensim.summarization.summarizer import summarize from pandas.io.clipboard import clipboard_get, clipboard_set import argparse parser = argparse.ArgumentParser(description='Taking word count as argument') parser.add_argument('word_count', type=int, nargs='?', help='Summery Length') args = parser.parse_args() word_count = args.word_count if word_count is None: word_count = 50 print(summarize(clipboard_get(), word_count=word_count))
'e': ['e', 'E', '£', '€'], 'f': ['f', 'F'], 'g': ['g', 'G'], 'h': ['h', 'H', '#', "¦¬¦"], 'i': ['i', 'I', '!', "¡"], 'j': ['j', 'J'], 'k': ['k', 'K', "|<", "¦<"], 'l': ['l', 'L'], 'm': ['m', 'M', '|\/|'], 'n': ['n', 'N', "|\|", "¦\¦"], 'o': ['o', 'O', "0"], 'p': ['p', 'P', "¶"], 'q': ['q', 'Q'], 'r': ['r', 'R', "®"], 's': ['s', 'S', "$", "&"], 't': ['t', 'T', "¿"], 'u': ['u', 'U', "|_|"], 'v': ['v', 'V', "\/"], 'w': ['w', 'W', "|/\|"], 'x': ['x', 'X', "×"], 'y': ['y', 'Y', "¥"], 'z': ['z', 'Z'] } try: inp = clipboard_get().lower()[::-1] out = "".join([random.choice(maps.get(r, r)) for r in inp]) clipboard_set(out) except: print("ERROR!")
def read_clipboard(sep=r'\s+', **kwargs): # pragma: no cover r""" Read text from clipboard and pass to read_csv. See read_csv for the full argument list Parameters ---------- sep : str, default '\s+' A string or regex delimiter. The default of '\s+' denotes one or more whitespace characters. Returns ------- parsed : DataFrame """ encoding = kwargs.pop('encoding', 'utf-8') # only utf-8 is valid for passed value because that's what clipboard # supports if encoding is not None and encoding.lower().replace('-', '') != 'utf8': raise NotImplementedError( 'reading from clipboard only supports utf-8 encoding') from pandas.io.clipboard import clipboard_get from pandas.io.parsers import read_csv text = clipboard_get() # Try to decode (if needed, as "text" might already be a string here). try: text = text.decode( kwargs.get('encoding') or get_option('display.encoding')) except AttributeError: pass # Excel copies into clipboard with \t separation # inspect no more then the 10 first lines, if they # all contain an equal number (>0) of tabs, infer # that this came from excel and set 'sep' accordingly lines = text[:10000].split('\n')[:-1][:10] # Need to remove leading white space, since read_csv # accepts: # a b # 0 1 2 # 1 3 4 counts = {x.lstrip().count('\t') for x in lines} if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0: sep = '\t' # Edge case where sep is specified to be None, return to default if sep is None and kwargs.get('delim_whitespace') is None: sep = r'\s+' # Regex separator currently only works with python engine. # Default to python if separator is multi-character (regex) if len(sep) > 1 and kwargs.get('engine') is None: kwargs['engine'] = 'python' elif len(sep) > 1 and kwargs.get('engine') == 'c': warnings.warn('read_clipboard with regex separator does not work' ' properly with c engine') return read_csv(StringIO(text), sep=sep, **kwargs)
def read_clipboard(sep=r'\s+', **kwargs): # pragma: no cover r""" Read text from clipboard and pass to read_csv. See read_csv for the full argument list Parameters ---------- sep : str, default '\s+' A string or regex delimiter. The default of '\s+' denotes one or more whitespace characters. Returns ------- parsed : DataFrame """ encoding = kwargs.pop('encoding', 'utf-8') # only utf-8 is valid for passed value because that's what clipboard # supports if encoding is not None and encoding.lower().replace('-', '') != 'utf8': raise NotImplementedError( 'reading from clipboard only supports utf-8 encoding') from pandas.io.clipboard import clipboard_get from pandas.io.parsers import read_csv text = clipboard_get() # Try to decode (if needed, as "text" might already be a string here). try: text = text.decode(kwargs.get('encoding') or get_option('display.encoding')) except AttributeError: pass # Excel copies into clipboard with \t separation # inspect no more then the 10 first lines, if they # all contain an equal number (>0) of tabs, infer # that this came from excel and set 'sep' accordingly lines = text[:10000].split('\n')[:-1][:10] # Need to remove leading white space, since read_csv # accepts: # a b # 0 1 2 # 1 3 4 counts = {x.lstrip().count('\t') for x in lines} if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0: sep = '\t' # Edge case where sep is specified to be None, return to default if sep is None and kwargs.get('delim_whitespace') is None: sep = r'\s+' # Regex separator currently only works with python engine. # Default to python if separator is multi-character (regex) if len(sep) > 1 and kwargs.get('engine') is None: kwargs['engine'] = 'python' elif len(sep) > 1 and kwargs.get('engine') == 'c': warnings.warn('read_clipboard with regex separator does not work' ' properly with c engine') return read_csv(StringIO(text), sep=sep, **kwargs)
filter_re = [문자열사이공백(i) for i in filter_] for file in filename: pass hwp.Open(dir1 + file, "HWP", "forceopen:true") hwp.HAction.GetDefault("RepeatFind", hwp.HParameterSet.HFindReplace.HSet) ctrlcode = hwp.HeadCtrl data_parent = [] while ctrlcode is not None: if ctrlcode.CtrlID == "tbl": hwp.SetPosBySet(ctrlcode.GetAnchorPos(0)) hwp.FindCtrl() hwp.Run("ShapeObjTableSelCell") hwp.Run("TableCellBlockExtend") hwp.Run("TableCellBlockExtend") hwp.Run("Copy") a = clipboard_get() if all([re.compile(i).search(a) for i in filter_re]): num = 1 dat = {i: "" for i in filter_} posibl = {i: True for i in ["A", "B", "C"]} while True: num += 1 for 위치, 항목 in zip(["A", "B", "C"], filter_): try: SetTableCellAddr(f"{위치}{num}") hwp.Run("Copy") sub_dat = clipboard_get() sub_dat = re.compile(r'\s+').sub(" ", sub_dat) dat[항목] += " " + sub_dat except: posibl[위치] = False
def parse_grid(data=None, sep=None, strip='udr', comment='#', empty='', ignore_blank=True, dtype=None, on_empty=None, quiet=False): msg = fn.identity if quiet else print if data is None: data = clipboard_get() lines = data.splitlines() # Strip leading blank line (generally from pasting something into triple # quotes) if lines and lines[0] == '': lines = lines[1:] if not lines: msg("No data to parse.") return np.empty((0, 0), dtype=dtype) # Strip comments and blank lines if comment: lines = [re.sub(comment + '.*$', '', line) for line in lines] if ignore_blank: lines = [line for line in lines if line] # Determine splitter and split lines into items if sep is None: sep = guess_splitter([line for line in lines if line]) if sep is not None and sep != '': msg(f"Separating by {sep!r}") lines = [re.split(sep, line) for line in lines] else: msg(f"Separating by character") lines = [list(line) for line in lines] # Pad out shape to rectangular lens = [len(line) for line in lines] width = max(lens) for line in lines: if len(line) < width: line.extend([''] * (width - len(line))) grid = np.array(lines, dtype=str) grid[grid == empty] = '' if strip: grid = subrect(grid, dirs=strip) # Determine dtype if dtype is None: dtype = object if all(re.match(r'^\d+$', d) for d in grid.flat if d): dtype = int elif all(re.match(r'^\d+\.?\d*$', d) for d in grid.flat if d): dtype = float # xform coerces items to type if dtype is object: xform = lambda x: x if x != empty else None else: xform = fn.iffy(dtype, default=on_empty) dtype = object if '' in grid.flat and on_empty is None else dtype h, w = grid.shape result = np.array([[xform(val) for val in line] for line in grid], dtype=dtype) msg(f"Array is {h} rows x {w} cols of type {result.dtype}") return result
def read_clipboard(sep=r'\s+', **kwargs): # pragma: no cover r""" Read text from clipboard and pass to read_table. See read_table for the full argument list Parameters ---------- sep : str, default '\s+'. A string or regex delimiter. The default of '\s+' denotes one or more whitespace characters. Returns ------- parsed : DataFrame """ encoding = kwargs.pop('encoding', 'utf-8') # only utf-8 is valid for passed value because that's what clipboard # supports if encoding is not None and encoding.lower().replace('-', '') != 'utf8': raise NotImplementedError( 'reading from clipboard only supports utf-8 encoding') from pandas.io.clipboard import clipboard_get from pandas.io.parsers import read_table text = clipboard_get() # try to decode (if needed on PY3) # Strange. linux py33 doesn't complain, win py33 does if PY3: try: text = compat.bytes_to_str( text, encoding=(kwargs.get('encoding') or get_option('display.encoding'))) except: pass # Excel copies into clipboard with \t separation # inspect no more then the 10 first lines, if they # all contain an equal number (>0) of tabs, infer # that this came from excel and set 'sep' accordingly lines = text[:10000].split('\n')[:-1][:10] # Need to remove leading white space, since read_table # accepts: # a b # 0 1 2 # 1 3 4 counts = {x.lstrip().count('\t') for x in lines} if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0: sep = '\t' # Edge case where sep is specified to be None, return to default if sep is None and kwargs.get('delim_whitespace') is None: sep = r'\s+' # Regex separator currently only works with python engine. # Default to python if separator is multi-character (regex) if len(sep) > 1 and kwargs.get('engine') is None: kwargs['engine'] = 'python' elif len(sep) > 1 and kwargs.get('engine') == 'c': warnings.warn('read_clipboard with regex separator does not work' ' properly with c engine') # In PY2, the c table reader first encodes text with UTF-8 but Python # table reader uses the format of the passed string. For consistency, # encode strings for python engine so that output from python and c # engines produce consistent results if kwargs.get('engine') == 'python' and PY2: text = text.encode('utf-8') return read_table(StringIO(text), sep=sep, **kwargs)
def test_raw_roundtrip(data): # PR #25040 wide unicode wasn't copied correctly on PY3 on windows clipboard_set(data) assert data == clipboard_get()
def read_clipboard(sep=r'\s+', **kwargs): # pragma: no cover r""" Read text from clipboard and pass to read_table. See read_table for the full argument list Parameters ---------- sep : str, default '\s+'. A string or regex delimiter. The default of '\s+' denotes one or more whitespace characters. Returns ------- parsed : DataFrame """ encoding = kwargs.pop('encoding', 'utf-8') # only utf-8 is valid for passed value because that's what clipboard # supports if encoding is not None and encoding.lower().replace('-', '') != 'utf8': raise NotImplementedError( 'reading from clipboard only supports utf-8 encoding') from pandas.io.clipboard import clipboard_get from pandas.io.parsers import read_table text = clipboard_get() # try to decode (if needed on PY3) # Strange. linux py33 doesn't complain, win py33 does if PY3: try: text = compat.bytes_to_str( text, encoding=(kwargs.get('encoding') or get_option('display.encoding')) ) except: pass # Excel copies into clipboard with \t separation # inspect no more then the 10 first lines, if they # all contain an equal number (>0) of tabs, infer # that this came from excel and set 'sep' accordingly lines = text[:10000].split('\n')[:-1][:10] # Need to remove leading white space, since read_table # accepts: # a b # 0 1 2 # 1 3 4 counts = {x.lstrip().count('\t') for x in lines} if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0: sep = '\t' # Edge case where sep is specified to be None, return to default if sep is None and kwargs.get('delim_whitespace') is None: sep = r'\s+' # Regex separator currently only works with python engine. # Default to python if separator is multi-character (regex) if len(sep) > 1 and kwargs.get('engine') is None: kwargs['engine'] = 'python' elif len(sep) > 1 and kwargs.get('engine') == 'c': warnings.warn('read_clipboard with regex separator does not work' ' properly with c engine') # In PY2, the c table reader first encodes text with UTF-8 but Python # table reader uses the format of the passed string. For consistency, # encode strings for python engine so that output from python and c # engines produce consistent results if kwargs.get('engine') == 'python' and PY2: text = text.encode('utf-8') return read_table(StringIO(text), sep=sep, **kwargs)