mirror of https://github.com/tqdm/tqdm.git
flake8, .gitignore ipy
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@ -25,6 +25,9 @@ __pycache__
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# PyCharm
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.idea
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# IPython
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.ipynb_checkpoints
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# asv
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.asv/
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benchmarks/*.py[co]
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3
Makefile
3
Makefile
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@ -47,7 +47,8 @@ all:
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@+make build
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flake8:
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@+flake8 --max-line-length=80 --exclude .asv,.tox -j 8 --count --statistics --exit-zero .
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@+flake8 --max-line-length=80 --exclude .asv,.tox,.ipynb_checkpoints \
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-j 8 --count --statistics --exit-zero .
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test:
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tox --skip-missing-interpreters
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@ -79,8 +79,8 @@ class TqdmDefaultWriteLock(object):
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an argument to joblib or the parallelism lib you use.
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"""
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def __init__(self):
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# Create global parallelism locks to avoid racing issues with parallel bars
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# works only if fork available (Linux/MacOSX, but not Windows)
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# Create global parallelism locks to avoid racing issues with parallel
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# bars works only if fork available (Linux/MacOSX, but not Windows)
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self.create_mp_lock()
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self.create_th_lock()
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cls = type(self)
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@ -210,8 +210,8 @@ class tqdm(Comparable):
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@staticmethod
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def ema(x, mu=None, alpha=0.3):
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"""
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Exponential moving average: smoothing to give progressively lower
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weights to older values.
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Exponential moving average: smoothing to give progressively lower
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weights to older values.
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Parameters
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----------
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@ -222,7 +222,7 @@ class tqdm(Comparable):
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alpha : float, optional
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Smoothing factor in range [0, 1], [default: 0.3].
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Increase to give more weight to recent values.
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Ranges from 0 (yields mu) to 1 (yields x).
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Ranges from 0 (yields mu) to 1 (yields x).
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"""
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return x if mu is None else (alpha * x) + (1 - alpha) * mu
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@ -1098,7 +1098,8 @@ Please use `tqdm_gui(...)` instead of `tqdm(..., gui=True)`
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# EMA (not just overall average)
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if self.smoothing and delta_t and delta_it:
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rate = delta_t / delta_it
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self.avg_time = self.ema(rate, self.avg_time, self.smoothing)
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self.avg_time = self.ema(
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rate, self.avg_time, self.smoothing)
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if not hasattr(self, "sp"):
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raise TqdmDeprecationWarning("""\
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@ -243,7 +243,8 @@ class tqdm_gui(tqdm): # pragma: no cover
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# EMA (not just overall average)
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if self.smoothing and delta_t and delta_it:
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rate = delta_t / delta_it
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self.avg_time = self.ema(rate, self.avg_time, self.smoothing)
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self.avg_time = self.ema(
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rate, self.avg_time, self.smoothing)
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# Inline due to multiple calls
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total = self.total
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@ -6,7 +6,8 @@ CUR_OS = _curos()
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IS_WIN = CUR_OS in ['Windows', 'cli']
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IS_NIX = (not IS_WIN) and any(
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CUR_OS.startswith(i) for i in
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['CYGWIN', 'MSYS', 'Linux', 'Darwin', 'SunOS', 'FreeBSD', 'NetBSD', 'OpenBSD'])
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['CYGWIN', 'MSYS', 'Linux', 'Darwin', 'SunOS',
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'FreeBSD', 'NetBSD', 'OpenBSD'])
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RE_ANSI = re.compile(r"\x1b\[[;\d]*[A-Za-z]")
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