def to_clipboard(obj, excel=True, sep=None, **kwargs): # pragma: no cover
"""
Attempt to write text representation of object to the system clipboard
The clipboard can be then pasted into Excel for example.
Parameters
----------
obj : the object to write to the clipboard
excel : boolean, defaults to True
if True, use the provided separator, writing in a csv
format for allowing easy pasting into excel.
if False, write a string representation of the object
to the clipboard
sep : optional, defaults to tab
other keywords are passed to to_csv
Notes
-----
Requirements for your platform
- Linux: xclip, or xsel (with PyQt4 modules)
- Windows:
- OS X:
"""
encoding = kwargs.pop("encoding", "utf-8")
# testing if an invalid encoding is passed to clipboard
if encoding is not None and encoding.lower().replace("-", "") != "utf8":
raise ValueError("clipboard only supports utf-8 encoding")
from pandas.io.clipboard import clipboard_set
if excel is None:
excel = True
if excel:
try:
if sep is None:
sep = "\t"
buf = StringIO()
# clipboard_set (pyperclip) expects unicode
obj.to_csv(buf, sep=sep, encoding="utf-8", **kwargs)
text = buf.getvalue()
clipboard_set(text)
return
except TypeError:
warnings.warn(
"to_clipboard in excel mode requires a single character separator."
)
elif sep is not None:
warnings.warn("to_clipboard with excel=False ignores the sep argument")
if isinstance(obj, ABCDataFrame):
# str(df) has various unhelpful defaults, like truncation
with option_context("display.max_colwidth", None):
objstr = obj.to_string(**kwargs)
else:
objstr = str(obj)
clipboard_set(objstr)
def to_clipboard(obj, excel=True, sep=None, **kwargs): # pragma: no cover
"""
Attempt to write text representation of object to the system clipboard
The clipboard can be then pasted into Excel for example.
Parameters
----------
obj : the object to write to the clipboard
excel : boolean, defaults to True
if True, use the provided separator, writing in a csv
format for allowing easy pasting into excel.
if False, write a string representation of the object
to the clipboard
sep : optional, defaults to tab
other keywords are passed to to_csv
Notes
-----
Requirements for your platform
- Linux: xclip, or xsel (with gtk or PyQt4 modules)
- Windows:
- OS X:
"""
encoding = kwargs.pop('encoding', 'utf-8')
# testing if an invalid encoding is passed to clipboard
if encoding is not None and encoding.lower().replace('-', '') != 'utf8':
raise ValueError('clipboard only supports utf-8 encoding')
from pandas.io.clipboard import clipboard_set
if excel is None:
excel = True
if excel:
try:
if sep is None:
sep = '\t'
buf = StringIO()
# clipboard_set (pyperclip) expects unicode
obj.to_csv(buf, sep=sep, encoding='utf-8', **kwargs)
text = buf.getvalue()
clipboard_set(text)
return
except TypeError:
warnings.warn('to_clipboard in excel mode requires a single '
'character separator.')
elif sep is not None:
warnings.warn('to_clipboard with excel=False ignores the sep argument')
if isinstance(obj, ABCDataFrame):
# str(df) has various unhelpful defaults, like truncation
with option_context('display.max_colwidth', 999999):
objstr = obj.to_string(**kwargs)
else:
objstr = str(obj)
clipboard_set(objstr)
def to_clipboard(obj, excel=None, sep=None, **kwargs): # pragma: no cover
"""
Attempt to write text representation of object to the system clipboard
The clipboard can be then pasted into Excel for example.
Parameters
----------
obj : the object to write to the clipboard
excel : boolean, defaults to True
if True, use the provided separator, writing in a csv
format for allowing easy pasting into excel.
if False, write a string representation of the object
to the clipboard
sep : optional, defaults to tab
other keywords are passed to to_csv
Notes
-----
Requirements for your platform
- Linux: xclip, or xsel (with gtk or PyQt4 modules)
- Windows:
- OS X:
"""
encoding = kwargs.pop('encoding', 'utf-8')
# testing if an invalid encoding is passed to clipboard
if encoding is not None and encoding.lower().replace('-', '') != 'utf8':
raise ValueError('clipboard only supports utf-8 encoding')
from pandas.io.clipboard import clipboard_set
if excel is None:
excel = True
if excel:
try:
if sep is None:
sep = '\t'
buf = StringIO()
# clipboard_set (pyperclip) expects unicode
obj.to_csv(buf, sep=sep, encoding='utf-8', **kwargs)
text = buf.getvalue()
if PY2:
text = text.decode('utf-8')
clipboard_set(text)
return
except:
pass
if isinstance(obj, DataFrame):
# str(df) has various unhelpful defaults, like truncation
with option_context('display.max_colwidth', 999999):
objstr = obj.to_string(**kwargs)
else:
objstr = str(obj)
clipboard_set(objstr)
def main():
passw = ''
start = time.perf_counter()
try:
load_time = time.perf_counter()
data = json.load(
open("/Users/mattmcmahon/Desktop/repos/password_gen/sorted.json"))
if args.verbose:
print(f"load time: {round(time.perf_counter() - load_time, 2)}")
if args.passphrase:
passw = phrase(data, args.passphrase)
else:
passw = generate(data, args.length)
if args.show:
print(f"password:\t{passw}\n")
print(len(passw))
if args.file:
writer(passw, len(passw))
if args.verbose:
print(f"done in: {round(time.perf_counter() - start, 2)}")
if not args.show and not args.file:
clipboard_set(passw)
print("password copied...\n")
for i in range(args.time, 0, -1):
sys.stdout.write("\r\t{:2d} secs remaining".format(i))
sys.stdout.flush()
time.sleep(1)
sys.stdout.write("\r --- done --- \n\n")
sys.stdout.flush()
clipboard_set("")
except Exception as e:
print(f"\nerror in main\n{e}")
signal.signal(signal.SIGTSTP, handler)
def test_read_clipboard_infer_excel(self):
# gh-19010: avoid warnings
clip_kwargs = dict(engine="python")
text = dedent("""
John James Charlie Mingus
1 2
4 Harry Carney
""".strip())
clipboard_set(text)
df = pd.read_clipboard(**clip_kwargs)
# excel data is parsed correctly
assert df.iloc[1][1] == 'Harry Carney'
# having diff tab counts doesn't trigger it
text = dedent("""
a\t b
1 2
3 4
""".strip())
clipboard_set(text)
res = pd.read_clipboard(**clip_kwargs)
text = dedent("""
a b
1 2
3 4
""".strip())
clipboard_set(text)
exp = pd.read_clipboard(**clip_kwargs)
tm.assert_frame_equal(res, exp)
def test_read_clipboard_infer_excel(self):
# gh-19010: avoid warnings
clip_kwargs = dict(engine="python")
text = dedent("""
John James Charlie Mingus
1 2
4 Harry Carney
""".strip())
clipboard_set(text)
df = pd.read_clipboard(**clip_kwargs)
# excel data is parsed correctly
assert df.iloc[1][1] == 'Harry Carney'
# having diff tab counts doesn't trigger it
text = dedent("""
a\t b
1 2
3 4
""".strip())
clipboard_set(text)
res = pd.read_clipboard(**clip_kwargs)
text = dedent("""
a b
1 2
3 4
""".strip())
clipboard_set(text)
exp = pd.read_clipboard(**clip_kwargs)
tm.assert_frame_equal(res, exp)
def test_read_clipboard_infer_excel(self):
text = dedent("""
John James Charlie Mingus
1 2
4 Harry Carney
""".strip())
clipboard_set(text)
df = pd.read_clipboard()
# excel data is parsed correctly
assert df.iloc[1][1] == 'Harry Carney'
# having diff tab counts doesn't trigger it
text = dedent("""
a\t b
1 2
3 4
""".strip())
clipboard_set(text)
res = pd.read_clipboard()
text = dedent("""
a b
1 2
3 4
""".strip())
clipboard_set(text)
exp = pd.read_clipboard()
tm.assert_frame_equal(res, exp)
def to_clipboard(obj, excel=True, sep=None, **kwargs): # pragma: no cover
encoding = kwargs.pop("encoding", "utf-8")
# testing if an invalid encoding is passed to clipboard
if encoding is not None and encoding.lower().replace("-", "") != "utf8":
raise ValueError("clipboard only supports utf-8 encoding")
from pandas.io.clipboard import clipboard_set
if excel is None:
excel = True
if excel:
try:
if sep is None:
sep = "\t"
buf = StringIO()
# clipboard_set (pyperclip) expects unicode
obj.to_csv(buf, sep=sep, encoding="utf-8", **kwargs)
text = buf.getvalue()
clipboard_set(text)
return
except TypeError:
warnings.warn(
"to_clipboard in excel mode requires a single character separator."
)
elif sep is not None:
warnings.warn("to_clipboard with excel=False ignores the sep argument")
if isinstance(obj, ABCDataFrame):
# str(df) has various unhelpful defaults, like truncation
with option_context("display.max_colwidth", None):
objstr = obj.to_string(**kwargs)
else:
objstr = str(obj)
clipboard_set(objstr)
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 clip_write(x):
from pandas.io import clipboard
clipboard.clipboard_set(x)
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 copy_and_print(text):
""" Copy the text to clipboard and print it out"""
from pandas.io.clipboard import clipboard_set
clipboard_set(text)
print(text)
def handler(x, frame):
clipboard_set("")
print()
sys.exit(0)
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)
def main(args):
if not os.path.isfile(MONGO_CONF_PATH):
raise ValueError('File {} must exist'.format(MONGO_CONF_PATH))
runs = get_runs(args.sacred_ids, args.slurm_ids, MONGO_CONF_PATH)
viz = visdom.Visdom(args.host, port=args.port)
envs = []
tot_time = 0
n_replayed = 0
configs = {}
results = {}
failed = []
index = None
for run in runs:
slurm_id = run['host']['ENV'].get('SLURM_JOB_ID', None)
logger.info('\nProcessing run {} ({})'.format(run['_id'], slurm_id))
if args.replay:
# Replay part
env, n, time = replay_run(run, viz, args, MONGO_CONF_PATH, logger)
envs.append(env)
tot_time += time
n_replayed += n
# Results aggregation part
res = run['result']
if not res:
failed.append(run)
continue
configs[run['_id']] = run['config']
if index is None:
index = res['model']
assert res['model'] == index
# results[run['_id']] = {'Avg acc': res['accuracy']}
metrics = ['accuracy', 'speed']
accs = [((metric, mod), val) for metric in metrics
for mod, val in zip(res['model'], res[metric])]
results[run['_id']] = dict(accs)
# results[(get_key(run['config']), run['_id'])] = res['accuracy']
logger.info('Done.')
logger.info('Replayed {} envs in {:.3f} seconds.'.format(
n_replayed, tot_time))
logger.info(envs)
log_failed(failed)
key, values = validate_configurations(configs)
# res = pd.DataFrame(results, index=index)
res = pd.DataFrame(results)
# res.loc['ids'] = res.columns
ref_val = next(iter(values.values()))
new_cols = [(values.get(k, ref_val), k) for k in res.columns]
new_cols = pd.MultiIndex.from_tuples(new_cols, names=[key, '_id'])
res.columns = new_cols
res.sort_index(axis=1, inplace=True)
if args.group:
# Group and compute statistics over runs
res = res.transpose().groupby(level=key).agg([np.mean,
np.std]).transpose()
# agg_funcs = {'accuracy': lambda grp: grp.groupby(level=0).apply(lambda x: x.round(3).astype(str).apply('±'.join, 0)),
# 'speed': lambda grp: grp.groupby(level=0).apply(lambda x: x.round(1).astype(str).apply('±'.join, 0))}
# Process the results to get everything in the "mean±std" format
res = res.groupby(level=[0, 1]).apply(
lambda x: x.round(3).astype(str).apply('±'.join, 0))
sacred_ids = list(results.keys())
print(sacred_ids)
print(res)
id_str = ' '.join(map(str, sacred_ids))
id_row = 'ids\t{}'.format(id_str)
buf = io.StringIO()
res.to_csv(
buf,
sep='\t',
encoding='utf-8',
)
txt = buf.getvalue()
txt += id_row
clipboard_set(txt)
viz = visdom.Visdom(args.host, port=args.port)
viz.text(res.to_html(classes=['table', 'table-bordered', 'table-hover']))
logger.info(get_env_url(viz))
log_failed(failed)
'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!")