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salu133445/pypianoroll
pypianoroll/multitrack.py
Multitrack.transpose
def transpose(self, semitone): """ Transpose the pianorolls of all tracks by a number of semitones, where positive values are for higher key, while negative values are for lower key. The drum tracks are ignored. Parameters ---------- semitone : int Th...
python
def transpose(self, semitone): """ Transpose the pianorolls of all tracks by a number of semitones, where positive values are for higher key, while negative values are for lower key. The drum tracks are ignored. Parameters ---------- semitone : int Th...
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train
https://github.com/salu133445/pypianoroll/blob/6224dc1e29222de2124d249acb80f3d072166917/pypianoroll/multitrack.py#L954-L968
salu133445/pypianoroll
pypianoroll/multitrack.py
Multitrack.trim_trailing_silence
def trim_trailing_silence(self): """Trim the trailing silences of the pianorolls of all tracks. Trailing silences are considered globally.""" active_length = self.get_active_length() for track in self.tracks: track.pianoroll = track.pianoroll[:active_length]
python
def trim_trailing_silence(self): """Trim the trailing silences of the pianorolls of all tracks. Trailing silences are considered globally.""" active_length = self.get_active_length() for track in self.tracks: track.pianoroll = track.pianoroll[:active_length]
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train
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salu133445/pypianoroll
pypianoroll/multitrack.py
Multitrack.write
def write(self, filename): """ Write the multitrack pianoroll to a MIDI file. Parameters ---------- filename : str The name of the MIDI file to which the multitrack pianoroll is written. """ if not filename.endswith(('.mid', '.midi', '.MI...
python
def write(self, filename): """ Write the multitrack pianoroll to a MIDI file. Parameters ---------- filename : str The name of the MIDI file to which the multitrack pianoroll is written. """ if not filename.endswith(('.mid', '.midi', '.MI...
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salu133445/pypianoroll
pypianoroll/utilities.py
check_pianoroll
def check_pianoroll(arr): """ Return True if the array is a standard piano-roll matrix. Otherwise, return False. Raise TypeError if the input object is not a numpy array. """ if not isinstance(arr, np.ndarray): raise TypeError("`arr` must be of np.ndarray type") if not (np.issubdtype(ar...
python
def check_pianoroll(arr): """ Return True if the array is a standard piano-roll matrix. Otherwise, return False. Raise TypeError if the input object is not a numpy array. """ if not isinstance(arr, np.ndarray): raise TypeError("`arr` must be of np.ndarray type") if not (np.issubdtype(ar...
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salu133445/pypianoroll
pypianoroll/utilities.py
binarize
def binarize(obj, threshold=0): """ Return a copy of the object with binarized piano-roll(s). Parameters ---------- threshold : int or float Threshold to binarize the piano-roll(s). Default to zero. """ _check_supported(obj) copied = deepcopy(obj) copied.binarize(threshold)...
python
def binarize(obj, threshold=0): """ Return a copy of the object with binarized piano-roll(s). Parameters ---------- threshold : int or float Threshold to binarize the piano-roll(s). Default to zero. """ _check_supported(obj) copied = deepcopy(obj) copied.binarize(threshold)...
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train
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salu133445/pypianoroll
pypianoroll/utilities.py
clip
def clip(obj, lower=0, upper=127): """ Return a copy of the object with piano-roll(s) clipped by a lower bound and an upper bound specified by `lower` and `upper`, respectively. Parameters ---------- lower : int or float The lower bound to clip the piano-roll. Default to 0. upper : ...
python
def clip(obj, lower=0, upper=127): """ Return a copy of the object with piano-roll(s) clipped by a lower bound and an upper bound specified by `lower` and `upper`, respectively. Parameters ---------- lower : int or float The lower bound to clip the piano-roll. Default to 0. upper : ...
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train
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salu133445/pypianoroll
pypianoroll/utilities.py
pad
def pad(obj, pad_length): """ Return a copy of the object with piano-roll padded with zeros at the end along the time axis. Parameters ---------- pad_length : int The length to pad along the time axis with zeros. """ _check_supported(obj) copied = deepcopy(obj) copied.p...
python
def pad(obj, pad_length): """ Return a copy of the object with piano-roll padded with zeros at the end along the time axis. Parameters ---------- pad_length : int The length to pad along the time axis with zeros. """ _check_supported(obj) copied = deepcopy(obj) copied.p...
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salu133445/pypianoroll
pypianoroll/utilities.py
pad_to_multiple
def pad_to_multiple(obj, factor): """ Return a copy of the object with its piano-roll padded with zeros at the end along the time axis with the minimal length that make the length of the resulting piano-roll a multiple of `factor`. Parameters ---------- factor : int The value which ...
python
def pad_to_multiple(obj, factor): """ Return a copy of the object with its piano-roll padded with zeros at the end along the time axis with the minimal length that make the length of the resulting piano-roll a multiple of `factor`. Parameters ---------- factor : int The value which ...
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train
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salu133445/pypianoroll
pypianoroll/utilities.py
pad_to_same
def pad_to_same(obj): """ Return a copy of the object with shorter piano-rolls padded with zeros at the end along the time axis to the length of the piano-roll with the maximal length. """ if not isinstance(obj, Multitrack): raise TypeError("Support only `pypianoroll.Multitrack` class o...
python
def pad_to_same(obj): """ Return a copy of the object with shorter piano-rolls padded with zeros at the end along the time axis to the length of the piano-roll with the maximal length. """ if not isinstance(obj, Multitrack): raise TypeError("Support only `pypianoroll.Multitrack` class o...
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salu133445/pypianoroll
pypianoroll/utilities.py
parse
def parse(filepath, beat_resolution=24, name='unknown'): """ Return a :class:`pypianoroll.Multitrack` object loaded from a MIDI (.mid, .midi, .MID, .MIDI) file. Parameters ---------- filepath : str The file path to the MIDI file. """ if not filepath.endswith(('.mid', '.midi', '...
python
def parse(filepath, beat_resolution=24, name='unknown'): """ Return a :class:`pypianoroll.Multitrack` object loaded from a MIDI (.mid, .midi, .MID, .MIDI) file. Parameters ---------- filepath : str The file path to the MIDI file. """ if not filepath.endswith(('.mid', '.midi', '...
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salu133445/pypianoroll
pypianoroll/utilities.py
save
def save(filepath, obj, compressed=True): """ Save the object to a .npz file. Parameters ---------- filepath : str The path to save the file. obj: `pypianoroll.Multitrack` objects The object to be saved. """ if not isinstance(obj, Multitrack): raise TypeError("S...
python
def save(filepath, obj, compressed=True): """ Save the object to a .npz file. Parameters ---------- filepath : str The path to save the file. obj: `pypianoroll.Multitrack` objects The object to be saved. """ if not isinstance(obj, Multitrack): raise TypeError("S...
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salu133445/pypianoroll
pypianoroll/utilities.py
transpose
def transpose(obj, semitone): """ Return a copy of the object with piano-roll(s) transposed by `semitones` semitones. Parameters ---------- semitone : int Number of semitones to transpose the piano-roll(s). """ _check_supported(obj) copied = deepcopy(obj) copied.transpo...
python
def transpose(obj, semitone): """ Return a copy of the object with piano-roll(s) transposed by `semitones` semitones. Parameters ---------- semitone : int Number of semitones to transpose the piano-roll(s). """ _check_supported(obj) copied = deepcopy(obj) copied.transpo...
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salu133445/pypianoroll
pypianoroll/utilities.py
trim_trailing_silence
def trim_trailing_silence(obj): """ Return a copy of the object with trimmed trailing silence of the piano-roll(s). """ _check_supported(obj) copied = deepcopy(obj) length = copied.get_active_length() copied.pianoroll = copied.pianoroll[:length] return copied
python
def trim_trailing_silence(obj): """ Return a copy of the object with trimmed trailing silence of the piano-roll(s). """ _check_supported(obj) copied = deepcopy(obj) length = copied.get_active_length() copied.pianoroll = copied.pianoroll[:length] return copied
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salu133445/pypianoroll
pypianoroll/utilities.py
write
def write(obj, filepath): """ Write the object to a MIDI file. Parameters ---------- filepath : str The path to write the MIDI file. """ if not isinstance(obj, Multitrack): raise TypeError("Support only `pypianoroll.Multitrack` class objects") obj.write(filepath)
python
def write(obj, filepath): """ Write the object to a MIDI file. Parameters ---------- filepath : str The path to write the MIDI file. """ if not isinstance(obj, Multitrack): raise TypeError("Support only `pypianoroll.Multitrack` class objects") obj.write(filepath)
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salu133445/pypianoroll
pypianoroll/metrics.py
_validate_pianoroll
def _validate_pianoroll(pianoroll): """Raise an error if the input array is not a standard pianoroll.""" if not isinstance(pianoroll, np.ndarray): raise TypeError("`pianoroll` must be of np.ndarray type.") if not (np.issubdtype(pianoroll.dtype, np.bool_) or np.issubdtype(pianoroll.dtype,...
python
def _validate_pianoroll(pianoroll): """Raise an error if the input array is not a standard pianoroll.""" if not isinstance(pianoroll, np.ndarray): raise TypeError("`pianoroll` must be of np.ndarray type.") if not (np.issubdtype(pianoroll.dtype, np.bool_) or np.issubdtype(pianoroll.dtype,...
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salu133445/pypianoroll
pypianoroll/metrics.py
_to_chroma
def _to_chroma(pianoroll): """Return the unnormalized chroma features of a pianoroll.""" _validate_pianoroll(pianoroll) reshaped = pianoroll[:, :120].reshape(-1, 12, 10) reshaped[..., :8] += pianoroll[:, 120:].reshape(-1, 1, 8) return np.sum(reshaped, 1)
python
def _to_chroma(pianoroll): """Return the unnormalized chroma features of a pianoroll.""" _validate_pianoroll(pianoroll) reshaped = pianoroll[:, :120].reshape(-1, 12, 10) reshaped[..., :8] += pianoroll[:, 120:].reshape(-1, 1, 8) return np.sum(reshaped, 1)
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salu133445/pypianoroll
pypianoroll/metrics.py
empty_beat_rate
def empty_beat_rate(pianoroll, beat_resolution): """Return the ratio of empty beats to the total number of beats in a pianoroll.""" _validate_pianoroll(pianoroll) reshaped = pianoroll.reshape(-1, beat_resolution * pianoroll.shape[1]) n_empty_beats = np.count_nonzero(reshaped.any(1)) return n_emp...
python
def empty_beat_rate(pianoroll, beat_resolution): """Return the ratio of empty beats to the total number of beats in a pianoroll.""" _validate_pianoroll(pianoroll) reshaped = pianoroll.reshape(-1, beat_resolution * pianoroll.shape[1]) n_empty_beats = np.count_nonzero(reshaped.any(1)) return n_emp...
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train
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salu133445/pypianoroll
pypianoroll/metrics.py
n_pitche_classes_used
def n_pitche_classes_used(pianoroll): """Return the number of unique pitch classes used in a pianoroll.""" _validate_pianoroll(pianoroll) chroma = _to_chroma(pianoroll) return np.count_nonzero(np.any(chroma, 0))
python
def n_pitche_classes_used(pianoroll): """Return the number of unique pitch classes used in a pianoroll.""" _validate_pianoroll(pianoroll) chroma = _to_chroma(pianoroll) return np.count_nonzero(np.any(chroma, 0))
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Return the number of unique pitch classes used in a pianoroll.
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train
https://github.com/salu133445/pypianoroll/blob/6224dc1e29222de2124d249acb80f3d072166917/pypianoroll/metrics.py#L41-L45
salu133445/pypianoroll
pypianoroll/metrics.py
qualified_note_rate
def qualified_note_rate(pianoroll, threshold=2): """Return the ratio of the number of the qualified notes (notes longer than `threshold` (in time step)) to the total number of notes in a pianoroll.""" _validate_pianoroll(pianoroll) if np.issubdtype(pianoroll.dtype, np.bool_): pianoroll = pianoro...
python
def qualified_note_rate(pianoroll, threshold=2): """Return the ratio of the number of the qualified notes (notes longer than `threshold` (in time step)) to the total number of notes in a pianoroll.""" _validate_pianoroll(pianoroll) if np.issubdtype(pianoroll.dtype, np.bool_): pianoroll = pianoro...
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Return the ratio of the number of the qualified notes (notes longer than `threshold` (in time step)) to the total number of notes in a pianoroll.
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train
https://github.com/salu133445/pypianoroll/blob/6224dc1e29222de2124d249acb80f3d072166917/pypianoroll/metrics.py#L47-L58
salu133445/pypianoroll
pypianoroll/metrics.py
polyphonic_rate
def polyphonic_rate(pianoroll, threshold=2): """Return the ratio of the number of time steps where the number of pitches being played is larger than `threshold` to the total number of time steps in a pianoroll.""" _validate_pianoroll(pianoroll) n_poly = np.count_nonzero(np.count_nonzero(pianoroll, 1...
python
def polyphonic_rate(pianoroll, threshold=2): """Return the ratio of the number of time steps where the number of pitches being played is larger than `threshold` to the total number of time steps in a pianoroll.""" _validate_pianoroll(pianoroll) n_poly = np.count_nonzero(np.count_nonzero(pianoroll, 1...
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Return the ratio of the number of time steps where the number of pitches being played is larger than `threshold` to the total number of time steps in a pianoroll.
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train
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salu133445/pypianoroll
pypianoroll/metrics.py
drum_in_pattern_rate
def drum_in_pattern_rate(pianoroll, beat_resolution, tolerance=0.1): """Return the ratio of the number of drum notes that lie on the drum pattern (i.e., at certain time steps) to the total number of drum notes.""" if beat_resolution not in (4, 6, 8, 9, 12, 16, 18, 24): raise ValueError("Unsupported ...
python
def drum_in_pattern_rate(pianoroll, beat_resolution, tolerance=0.1): """Return the ratio of the number of drum notes that lie on the drum pattern (i.e., at certain time steps) to the total number of drum notes.""" if beat_resolution not in (4, 6, 8, 9, 12, 16, 18, 24): raise ValueError("Unsupported ...
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Return the ratio of the number of drum notes that lie on the drum pattern (i.e., at certain time steps) to the total number of drum notes.
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train
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salu133445/pypianoroll
pypianoroll/metrics.py
in_scale_rate
def in_scale_rate(pianoroll, key=3, kind='major'): """Return the ratio of the number of nonzero entries that lie in a specific scale to the total number of nonzero entries in a pianoroll. Default to C major scale.""" if not isinstance(key, int): raise TypeError("`key` must an integer.") if k...
python
def in_scale_rate(pianoroll, key=3, kind='major'): """Return the ratio of the number of nonzero entries that lie in a specific scale to the total number of nonzero entries in a pianoroll. Default to C major scale.""" if not isinstance(key, int): raise TypeError("`key` must an integer.") if k...
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Return the ratio of the number of nonzero entries that lie in a specific scale to the total number of nonzero entries in a pianoroll. Default to C major scale.
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train
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salu133445/pypianoroll
pypianoroll/metrics.py
tonal_distance
def tonal_distance(pianoroll_1, pianoroll_2, beat_resolution, r1=1.0, r2=1.0, r3=0.5): """Return the tonal distance [1] between the two input pianorolls. [1] Christopher Harte, Mark Sandler, and Martin Gasser. Detecting harmonic change in musical audio. In Proc. ACM Workshop on Audio...
python
def tonal_distance(pianoroll_1, pianoroll_2, beat_resolution, r1=1.0, r2=1.0, r3=0.5): """Return the tonal distance [1] between the two input pianorolls. [1] Christopher Harte, Mark Sandler, and Martin Gasser. Detecting harmonic change in musical audio. In Proc. ACM Workshop on Audio...
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Return the tonal distance [1] between the two input pianorolls. [1] Christopher Harte, Mark Sandler, and Martin Gasser. Detecting harmonic change in musical audio. In Proc. ACM Workshop on Audio and Music Computing Multimedia, 2006.
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salu133445/pypianoroll
pypianoroll/track.py
Track.assign_constant
def assign_constant(self, value, dtype=None): """ Assign a constant value to all nonzeros in the pianoroll. If the pianoroll is not binarized, its data type will be preserved. If the pianoroll is binarized, it will be casted to the type of `value`. Arguments --------- ...
python
def assign_constant(self, value, dtype=None): """ Assign a constant value to all nonzeros in the pianoroll. If the pianoroll is not binarized, its data type will be preserved. If the pianoroll is binarized, it will be casted to the type of `value`. Arguments --------- ...
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train
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salu133445/pypianoroll
pypianoroll/track.py
Track.binarize
def binarize(self, threshold=0): """ Binarize the pianoroll. Parameters ---------- threshold : int or float A threshold used to binarize the pianorolls. Defaults to zero. """ if not self.is_binarized(): self.pianoroll = (self.pianoroll > ...
python
def binarize(self, threshold=0): """ Binarize the pianoroll. Parameters ---------- threshold : int or float A threshold used to binarize the pianorolls. Defaults to zero. """ if not self.is_binarized(): self.pianoroll = (self.pianoroll > ...
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train
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salu133445/pypianoroll
pypianoroll/track.py
Track.check_validity
def check_validity(self): """"Raise error if any invalid attribute found.""" # pianoroll if not isinstance(self.pianoroll, np.ndarray): raise TypeError("`pianoroll` must be a numpy array.") if not (np.issubdtype(self.pianoroll.dtype, np.bool_) or np.issubdtype...
python
def check_validity(self): """"Raise error if any invalid attribute found.""" # pianoroll if not isinstance(self.pianoroll, np.ndarray): raise TypeError("`pianoroll` must be a numpy array.") if not (np.issubdtype(self.pianoroll.dtype, np.bool_) or np.issubdtype...
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train
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salu133445/pypianoroll
pypianoroll/track.py
Track.clip
def clip(self, lower=0, upper=127): """ Clip the pianoroll by the given lower and upper bounds. Parameters ---------- lower : int or float The lower bound to clip the pianoroll. Defaults to 0. upper : int or float The upper bound to clip the piano...
python
def clip(self, lower=0, upper=127): """ Clip the pianoroll by the given lower and upper bounds. Parameters ---------- lower : int or float The lower bound to clip the pianoroll. Defaults to 0. upper : int or float The upper bound to clip the piano...
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train
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salu133445/pypianoroll
pypianoroll/track.py
Track.get_active_length
def get_active_length(self): """ Return the active length (i.e., without trailing silence) of the pianoroll. The unit is time step. Returns ------- active_length : int The active length (i.e., without trailing silence) of the pianoroll. """ n...
python
def get_active_length(self): """ Return the active length (i.e., without trailing silence) of the pianoroll. The unit is time step. Returns ------- active_length : int The active length (i.e., without trailing silence) of the pianoroll. """ n...
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Return the active length (i.e., without trailing silence) of the pianoroll. The unit is time step. Returns ------- active_length : int The active length (i.e., without trailing silence) of the pianoroll.
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salu133445/pypianoroll
pypianoroll/track.py
Track.get_active_pitch_range
def get_active_pitch_range(self): """ Return the active pitch range as a tuple (lowest, highest). Returns ------- lowest : int The lowest active pitch in the pianoroll. highest : int The highest active pitch in the pianoroll. """ ...
python
def get_active_pitch_range(self): """ Return the active pitch range as a tuple (lowest, highest). Returns ------- lowest : int The lowest active pitch in the pianoroll. highest : int The highest active pitch in the pianoroll. """ ...
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salu133445/pypianoroll
pypianoroll/track.py
Track.is_binarized
def is_binarized(self): """ Return True if the pianoroll is already binarized. Otherwise, return False. Returns ------- is_binarized : bool True if the pianoroll is already binarized; otherwise, False. """ is_binarized = np.issubdtype(self.pi...
python
def is_binarized(self): """ Return True if the pianoroll is already binarized. Otherwise, return False. Returns ------- is_binarized : bool True if the pianoroll is already binarized; otherwise, False. """ is_binarized = np.issubdtype(self.pi...
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salu133445/pypianoroll
pypianoroll/track.py
Track.pad
def pad(self, pad_length): """ Pad the pianoroll with zeros at the end along the time axis. Parameters ---------- pad_length : int The length to pad with zeros along the time axis. """ self.pianoroll = np.pad( self.pianoroll, ((0, pad_len...
python
def pad(self, pad_length): """ Pad the pianoroll with zeros at the end along the time axis. Parameters ---------- pad_length : int The length to pad with zeros along the time axis. """ self.pianoroll = np.pad( self.pianoroll, ((0, pad_len...
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train
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salu133445/pypianoroll
pypianoroll/track.py
Track.pad_to_multiple
def pad_to_multiple(self, factor): """ Pad the pianoroll with zeros at the end along the time axis with the minimum length that makes the resulting pianoroll length a multiple of `factor`. Parameters ---------- factor : int The value which the length ...
python
def pad_to_multiple(self, factor): """ Pad the pianoroll with zeros at the end along the time axis with the minimum length that makes the resulting pianoroll length a multiple of `factor`. Parameters ---------- factor : int The value which the length ...
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train
https://github.com/salu133445/pypianoroll/blob/6224dc1e29222de2124d249acb80f3d072166917/pypianoroll/track.py#L252-L268
salu133445/pypianoroll
pypianoroll/track.py
Track.transpose
def transpose(self, semitone): """ Transpose the pianoroll by a number of semitones, where positive values are for higher key, while negative values are for lower key. Parameters ---------- semitone : int The number of semitones to transpose the pianoroll. ...
python
def transpose(self, semitone): """ Transpose the pianoroll by a number of semitones, where positive values are for higher key, while negative values are for lower key. Parameters ---------- semitone : int The number of semitones to transpose the pianoroll. ...
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salu133445/pypianoroll
pypianoroll/track.py
Track.trim_trailing_silence
def trim_trailing_silence(self): """Trim the trailing silence of the pianoroll.""" length = self.get_active_length() self.pianoroll = self.pianoroll[:length]
python
def trim_trailing_silence(self): """Trim the trailing silence of the pianoroll.""" length = self.get_active_length() self.pianoroll = self.pianoroll[:length]
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dnouri/nolearn
nolearn/lasagne/visualize.py
plot_conv_weights
def plot_conv_weights(layer, figsize=(6, 6)): """Plot the weights of a specific layer. Only really makes sense with convolutional layers. Parameters ---------- layer : lasagne.layers.Layer """ W = layer.W.get_value() shape = W.shape nrows = np.ceil(np.sqrt(shape[0])).astype(int) ...
python
def plot_conv_weights(layer, figsize=(6, 6)): """Plot the weights of a specific layer. Only really makes sense with convolutional layers. Parameters ---------- layer : lasagne.layers.Layer """ W = layer.W.get_value() shape = W.shape nrows = np.ceil(np.sqrt(shape[0])).astype(int) ...
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Plot the weights of a specific layer. Only really makes sense with convolutional layers. Parameters ---------- layer : lasagne.layers.Layer
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train
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dnouri/nolearn
nolearn/lasagne/visualize.py
plot_conv_activity
def plot_conv_activity(layer, x, figsize=(6, 8)): """Plot the acitivities of a specific layer. Only really makes sense with layers that work 2D data (2D convolutional layers, 2D pooling layers ...). Parameters ---------- layer : lasagne.layers.Layer x : numpy.ndarray Only takes one ...
python
def plot_conv_activity(layer, x, figsize=(6, 8)): """Plot the acitivities of a specific layer. Only really makes sense with layers that work 2D data (2D convolutional layers, 2D pooling layers ...). Parameters ---------- layer : lasagne.layers.Layer x : numpy.ndarray Only takes one ...
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dnouri/nolearn
nolearn/lasagne/visualize.py
occlusion_heatmap
def occlusion_heatmap(net, x, target, square_length=7): """An occlusion test that checks an image for its critical parts. In this function, a square part of the image is occluded (i.e. set to 0) and then the net is tested for its propensity to predict the correct label. One should expect that this prop...
python
def occlusion_heatmap(net, x, target, square_length=7): """An occlusion test that checks an image for its critical parts. In this function, a square part of the image is occluded (i.e. set to 0) and then the net is tested for its propensity to predict the correct label. One should expect that this prop...
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An occlusion test that checks an image for its critical parts. In this function, a square part of the image is occluded (i.e. set to 0) and then the net is tested for its propensity to predict the correct label. One should expect that this propensity shrinks of critical parts of the image are occluded....
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dnouri/nolearn
nolearn/lasagne/visualize.py
plot_occlusion
def plot_occlusion(net, X, target, square_length=7, figsize=(9, None)): """Plot which parts of an image are particularly import for the net to classify the image correctly. See paper: Zeiler, Fergus 2013 Parameters ---------- net : NeuralNet instance The neural net to test. X : nump...
python
def plot_occlusion(net, X, target, square_length=7, figsize=(9, None)): """Plot which parts of an image are particularly import for the net to classify the image correctly. See paper: Zeiler, Fergus 2013 Parameters ---------- net : NeuralNet instance The neural net to test. X : nump...
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Plot which parts of an image are particularly import for the net to classify the image correctly. See paper: Zeiler, Fergus 2013 Parameters ---------- net : NeuralNet instance The neural net to test. X : numpy.array The input data, should be of shape (b, c, 0, 1). Only makes ...
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dnouri/nolearn
nolearn/lasagne/visualize.py
get_hex_color
def get_hex_color(layer_type): """ Determines the hex color for a layer. :parameters: - layer_type : string Class name of the layer :returns: - color : string containing a hex color for filling block. """ COLORS = ['#4A88B3', '#98C1DE', '#6CA2C8', '#3173A2', '#17649B'...
python
def get_hex_color(layer_type): """ Determines the hex color for a layer. :parameters: - layer_type : string Class name of the layer :returns: - color : string containing a hex color for filling block. """ COLORS = ['#4A88B3', '#98C1DE', '#6CA2C8', '#3173A2', '#17649B'...
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Determines the hex color for a layer. :parameters: - layer_type : string Class name of the layer :returns: - color : string containing a hex color for filling block.
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dnouri/nolearn
nolearn/lasagne/visualize.py
make_pydot_graph
def make_pydot_graph(layers, output_shape=True, verbose=False): """ :parameters: - layers : list List of the layers, as obtained from lasagne.layers.get_all_layers - output_shape: (default `True`) If `True`, the output shape of each layer will be displayed. - verb...
python
def make_pydot_graph(layers, output_shape=True, verbose=False): """ :parameters: - layers : list List of the layers, as obtained from lasagne.layers.get_all_layers - output_shape: (default `True`) If `True`, the output shape of each layer will be displayed. - verb...
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dnouri/nolearn
nolearn/lasagne/visualize.py
draw_to_file
def draw_to_file(layers, filename, **kwargs): """ Draws a network diagram to a file :parameters: - layers : list or NeuralNet instance List of layers or the neural net to draw. - filename : string The filename to save output to - **kwargs: see docstring of mak...
python
def draw_to_file(layers, filename, **kwargs): """ Draws a network diagram to a file :parameters: - layers : list or NeuralNet instance List of layers or the neural net to draw. - filename : string The filename to save output to - **kwargs: see docstring of mak...
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dnouri/nolearn
nolearn/lasagne/visualize.py
draw_to_notebook
def draw_to_notebook(layers, **kwargs): """ Draws a network diagram in an IPython notebook :parameters: - layers : list or NeuralNet instance List of layers or the neural net to draw. - **kwargs : see the docstring of make_pydot_graph for other options """ from IPython.di...
python
def draw_to_notebook(layers, **kwargs): """ Draws a network diagram in an IPython notebook :parameters: - layers : list or NeuralNet instance List of layers or the neural net to draw. - **kwargs : see the docstring of make_pydot_graph for other options """ from IPython.di...
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dnouri/nolearn
nolearn/lasagne/util.py
get_real_filter
def get_real_filter(layers, img_size): """Get the real filter sizes of each layer involved in convoluation. See Xudong Cao: https://www.kaggle.com/c/datasciencebowl/forums/t/13166/happy-lantern-festival-report-and-code This does not yet take into consideration feature pooling, padding, striding and ...
python
def get_real_filter(layers, img_size): """Get the real filter sizes of each layer involved in convoluation. See Xudong Cao: https://www.kaggle.com/c/datasciencebowl/forums/t/13166/happy-lantern-festival-report-and-code This does not yet take into consideration feature pooling, padding, striding and ...
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Get the real filter sizes of each layer involved in convoluation. See Xudong Cao: https://www.kaggle.com/c/datasciencebowl/forums/t/13166/happy-lantern-festival-report-and-code This does not yet take into consideration feature pooling, padding, striding and similar gimmicks.
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dnouri/nolearn
nolearn/lasagne/util.py
get_receptive_field
def get_receptive_field(layers, img_size): """Get the real filter sizes of each layer involved in convoluation. See Xudong Cao: https://www.kaggle.com/c/datasciencebowl/forums/t/13166/happy-lantern-festival-report-and-code This does not yet take into consideration feature pooling, padding, striding ...
python
def get_receptive_field(layers, img_size): """Get the real filter sizes of each layer involved in convoluation. See Xudong Cao: https://www.kaggle.com/c/datasciencebowl/forums/t/13166/happy-lantern-festival-report-and-code This does not yet take into consideration feature pooling, padding, striding ...
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dnouri/nolearn
nolearn/decaf.py
ConvNetFeatures.prepare_image
def prepare_image(self, image): """Returns image of shape `(256, 256, 3)`, as expected by `transform` when `classify_direct = True`. """ from decaf.util import transform # soft dep _JEFFNET_FLIP = True # first, extract the 256x256 center. image = transform.scale...
python
def prepare_image(self, image): """Returns image of shape `(256, 256, 3)`, as expected by `transform` when `classify_direct = True`. """ from decaf.util import transform # soft dep _JEFFNET_FLIP = True # first, extract the 256x256 center. image = transform.scale...
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Returns image of shape `(256, 256, 3)`, as expected by `transform` when `classify_direct = True`.
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dnouri/nolearn
nolearn/metrics.py
multiclass_logloss
def multiclass_logloss(actual, predicted, eps=1e-15): """Multi class version of Logarithmic Loss metric. :param actual: Array containing the actual target classes :param predicted: Matrix with class predictions, one probability per class """ # Convert 'actual' to a binary array if it's not already:...
python
def multiclass_logloss(actual, predicted, eps=1e-15): """Multi class version of Logarithmic Loss metric. :param actual: Array containing the actual target classes :param predicted: Matrix with class predictions, one probability per class """ # Convert 'actual' to a binary array if it's not already:...
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Multi class version of Logarithmic Loss metric. :param actual: Array containing the actual target classes :param predicted: Matrix with class predictions, one probability per class
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dnouri/nolearn
nolearn/lasagne/base.py
objective
def objective(layers, loss_function, target, aggregate=aggregate, deterministic=False, l1=0, l2=0, get_output_kw=None): """ Default implementation of the NeuralNet objective. :param layers: The underlying laye...
python
def objective(layers, loss_function, target, aggregate=aggregate, deterministic=False, l1=0, l2=0, get_output_kw=None): """ Default implementation of the NeuralNet objective. :param layers: The underlying laye...
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dnouri/nolearn
nolearn/lasagne/base.py
NeuralNet.initialize
def initialize(self): """Initializes the network. Checks that no extra kwargs were passed to the constructor, and compiles the train, predict, and evaluation functions. Subsequent calls to this function will return without any action. """ if getattr(self, '_initialized'...
python
def initialize(self): """Initializes the network. Checks that no extra kwargs were passed to the constructor, and compiles the train, predict, and evaluation functions. Subsequent calls to this function will return without any action. """ if getattr(self, '_initialized'...
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dnouri/nolearn
nolearn/lasagne/base.py
NeuralNet.initialize_layers
def initialize_layers(self, layers=None): """Sets up the Lasagne layers :param layers: The dictionary of layers, or a :class:`lasagne.Layers` instance, describing the underlying network :return: the output layer of the underlying lasagne network. :seealso: :ref:`layer-...
python
def initialize_layers(self, layers=None): """Sets up the Lasagne layers :param layers: The dictionary of layers, or a :class:`lasagne.Layers` instance, describing the underlying network :return: the output layer of the underlying lasagne network. :seealso: :ref:`layer-...
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dnouri/nolearn
nolearn/lasagne/base.py
NeuralNet.fit
def fit(self, X, y, epochs=None): """ Runs the training loop for a given number of epochs :param X: The input data :param y: The ground truth :param epochs: The number of epochs to run, if `None` runs for the network's :attr:`max_epochs` :return:...
python
def fit(self, X, y, epochs=None): """ Runs the training loop for a given number of epochs :param X: The input data :param y: The ground truth :param epochs: The number of epochs to run, if `None` runs for the network's :attr:`max_epochs` :return:...
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Runs the training loop for a given number of epochs :param X: The input data :param y: The ground truth :param epochs: The number of epochs to run, if `None` runs for the network's :attr:`max_epochs` :return: This instance
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dnouri/nolearn
nolearn/lasagne/base.py
NeuralNet.partial_fit
def partial_fit(self, X, y, classes=None): """ Runs a single epoch using the provided data :return: This instance """ return self.fit(X, y, epochs=1)
python
def partial_fit(self, X, y, classes=None): """ Runs a single epoch using the provided data :return: This instance """ return self.fit(X, y, epochs=1)
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pennersr/django-trackstats
trackstats/models.py
RegisterLazilyManagerMixin._register
def _register(self, defaults=None, **kwargs): """Fetch (update or create) an instance, lazily. We're doing this lazily, so that it becomes possible to define custom enums in your code, even before the Django ORM is fully initialized. Domain.objects.SHOPPING = Domain.objects.re...
python
def _register(self, defaults=None, **kwargs): """Fetch (update or create) an instance, lazily. We're doing this lazily, so that it becomes possible to define custom enums in your code, even before the Django ORM is fully initialized. Domain.objects.SHOPPING = Domain.objects.re...
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pennersr/django-trackstats
trackstats/models.py
ByDateQuerySetMixin.narrow
def narrow(self, **kwargs): """Up-to including""" from_date = kwargs.pop('from_date', None) to_date = kwargs.pop('to_date', None) date = kwargs.pop('date', None) qs = self if from_date: qs = qs.filter(date__gte=from_date) if to_date: qs = q...
python
def narrow(self, **kwargs): """Up-to including""" from_date = kwargs.pop('from_date', None) to_date = kwargs.pop('to_date', None) date = kwargs.pop('date', None) qs = self if from_date: qs = qs.filter(date__gte=from_date) if to_date: qs = q...
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Up-to including
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https://github.com/pennersr/django-trackstats/blob/4c36e769cb02017675a86de405afcd4e10ed3356/trackstats/models.py#L230-L242
HDE/python-lambda-local
lambda_local/environment_variables.py
set_environment_variables
def set_environment_variables(json_file_path): """ Read and set environment variables from a flat json file. Bear in mind that env vars set this way and later on read using `os.getenv` function will be strings since after all env vars are just that - plain strings. Json file example: ``` ...
python
def set_environment_variables(json_file_path): """ Read and set environment variables from a flat json file. Bear in mind that env vars set this way and later on read using `os.getenv` function will be strings since after all env vars are just that - plain strings. Json file example: ``` ...
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Read and set environment variables from a flat json file. Bear in mind that env vars set this way and later on read using `os.getenv` function will be strings since after all env vars are just that - plain strings. Json file example: ``` { "FOO": "bar", "BAZ": true } ``...
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train
https://github.com/HDE/python-lambda-local/blob/49ad011a039974f1d8f904435eb8db895558d2d9/lambda_local/environment_variables.py#L10-L33
HDE/python-lambda-local
lambda_local/context.py
millis_interval
def millis_interval(start, end): """start and end are datetime instances""" diff = end - start millis = diff.days * 24 * 60 * 60 * 1000 millis += diff.seconds * 1000 millis += diff.microseconds / 1000 return millis
python
def millis_interval(start, end): """start and end are datetime instances""" diff = end - start millis = diff.days * 24 * 60 * 60 * 1000 millis += diff.seconds * 1000 millis += diff.microseconds / 1000 return millis
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start and end are datetime instances
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train
https://github.com/HDE/python-lambda-local/blob/49ad011a039974f1d8f904435eb8db895558d2d9/lambda_local/context.py#L49-L55
locationlabs/mockredis
mockredis/script.py
Script._execute_lua
def _execute_lua(self, keys, args, client): """ Sets KEYS and ARGV alongwith redis.call() function in lua globals and executes the lua redis script """ lua, lua_globals = Script._import_lua(self.load_dependencies) lua_globals.KEYS = self._python_to_lua(keys) lua_g...
python
def _execute_lua(self, keys, args, client): """ Sets KEYS and ARGV alongwith redis.call() function in lua globals and executes the lua redis script """ lua, lua_globals = Script._import_lua(self.load_dependencies) lua_globals.KEYS = self._python_to_lua(keys) lua_g...
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Sets KEYS and ARGV alongwith redis.call() function in lua globals and executes the lua redis script
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/script.py#L29-L51
locationlabs/mockredis
mockredis/script.py
Script._import_lua
def _import_lua(load_dependencies=True): """ Import lua and dependencies. :param load_dependencies: should Lua library dependencies be loaded? :raises: RuntimeError if Lua is not available """ try: import lua except ImportError: raise Runt...
python
def _import_lua(load_dependencies=True): """ Import lua and dependencies. :param load_dependencies: should Lua library dependencies be loaded? :raises: RuntimeError if Lua is not available """ try: import lua except ImportError: raise Runt...
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Import lua and dependencies. :param load_dependencies: should Lua library dependencies be loaded? :raises: RuntimeError if Lua is not available
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/script.py#L54-L69
locationlabs/mockredis
mockredis/script.py
Script._import_lua_dependencies
def _import_lua_dependencies(lua, lua_globals): """ Imports lua dependencies that are supported by redis lua scripts. The current implementation is fragile to the target platform and lua version and may be disabled if these imports are not needed. Included: - cjson ...
python
def _import_lua_dependencies(lua, lua_globals): """ Imports lua dependencies that are supported by redis lua scripts. The current implementation is fragile to the target platform and lua version and may be disabled if these imports are not needed. Included: - cjson ...
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/script.py#L72-L96
locationlabs/mockredis
mockredis/script.py
Script._lua_to_python
def _lua_to_python(lval, return_status=False): """ Convert Lua object(s) into Python object(s), as at times Lua object(s) are not compatible with Python functions """ import lua lua_globals = lua.globals() if lval is None: # Lua None --> Python None ...
python
def _lua_to_python(lval, return_status=False): """ Convert Lua object(s) into Python object(s), as at times Lua object(s) are not compatible with Python functions """ import lua lua_globals = lua.globals() if lval is None: # Lua None --> Python None ...
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Convert Lua object(s) into Python object(s), as at times Lua object(s) are not compatible with Python functions
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/script.py#L99-L135
locationlabs/mockredis
mockredis/script.py
Script._python_to_lua
def _python_to_lua(pval): """ Convert Python object(s) into Lua object(s), as at times Python object(s) are not compatible with Lua functions """ import lua if pval is None: # Python None --> Lua None return lua.eval("") if isinstance(pval,...
python
def _python_to_lua(pval): """ Convert Python object(s) into Lua object(s), as at times Python object(s) are not compatible with Lua functions """ import lua if pval is None: # Python None --> Lua None return lua.eval("") if isinstance(pval,...
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Convert Python object(s) into Lua object(s), as at times Python object(s) are not compatible with Lua functions
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/script.py#L138-L179
locationlabs/mockredis
mockredis/client.py
MockRedis.lock
def lock(self, key, timeout=0, sleep=0): """Emulate lock.""" return MockRedisLock(self, key, timeout, sleep)
python
def lock(self, key, timeout=0, sleep=0): """Emulate lock.""" return MockRedisLock(self, key, timeout, sleep)
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Emulate lock.
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L77-L79
locationlabs/mockredis
mockredis/client.py
MockRedis.keys
def keys(self, pattern='*'): """Emulate keys.""" # making sure the pattern is unicode/str. try: pattern = pattern.decode('utf-8') # This throws an AttributeError in python 3, or an # UnicodeEncodeError in python 2 except (AttributeError, UnicodeEncodeE...
python
def keys(self, pattern='*'): """Emulate keys.""" # making sure the pattern is unicode/str. try: pattern = pattern.decode('utf-8') # This throws an AttributeError in python 3, or an # UnicodeEncodeError in python 2 except (AttributeError, UnicodeEncodeE...
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Emulate keys.
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L154-L169
locationlabs/mockredis
mockredis/client.py
MockRedis.delete
def delete(self, *keys): """Emulate delete.""" key_counter = 0 for key in map(self._encode, keys): if key in self.redis: del self.redis[key] key_counter += 1 if key in self.timeouts: del self.timeouts[key] return key...
python
def delete(self, *keys): """Emulate delete.""" key_counter = 0 for key in map(self._encode, keys): if key in self.redis: del self.redis[key] key_counter += 1 if key in self.timeouts: del self.timeouts[key] return key...
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Emulate delete.
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L171-L180
locationlabs/mockredis
mockredis/client.py
MockRedis.expire
def expire(self, key, delta): """Emulate expire""" delta = delta if isinstance(delta, timedelta) else timedelta(seconds=delta) return self._expire(self._encode(key), delta)
python
def expire(self, key, delta): """Emulate expire""" delta = delta if isinstance(delta, timedelta) else timedelta(seconds=delta) return self._expire(self._encode(key), delta)
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Emulate expire
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L199-L202
locationlabs/mockredis
mockredis/client.py
MockRedis.pexpire
def pexpire(self, key, milliseconds): """Emulate pexpire""" return self._expire(self._encode(key), timedelta(milliseconds=milliseconds))
python
def pexpire(self, key, milliseconds): """Emulate pexpire""" return self._expire(self._encode(key), timedelta(milliseconds=milliseconds))
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Emulate pexpire
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L204-L206
locationlabs/mockredis
mockredis/client.py
MockRedis.expireat
def expireat(self, key, when): """Emulate expireat""" expire_time = datetime.fromtimestamp(when) key = self._encode(key) if key in self.redis: self.timeouts[key] = expire_time return True return False
python
def expireat(self, key, when): """Emulate expireat""" expire_time = datetime.fromtimestamp(when) key = self._encode(key) if key in self.redis: self.timeouts[key] = expire_time return True return False
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Emulate expireat
[ "Emulate", "expireat" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L208-L215
locationlabs/mockredis
mockredis/client.py
MockRedis.ttl
def ttl(self, key): """ Emulate ttl Even though the official redis commands documentation at http://redis.io/commands/ttl states "Return value: Integer reply: TTL in seconds, -2 when key does not exist or -1 when key does not have a timeout." the redis-py lib returns None for bo...
python
def ttl(self, key): """ Emulate ttl Even though the official redis commands documentation at http://redis.io/commands/ttl states "Return value: Integer reply: TTL in seconds, -2 when key does not exist or -1 when key does not have a timeout." the redis-py lib returns None for bo...
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Emulate ttl Even though the official redis commands documentation at http://redis.io/commands/ttl states "Return value: Integer reply: TTL in seconds, -2 when key does not exist or -1 when key does not have a timeout." the redis-py lib returns None for both these cases. The lib behavior...
[ "Emulate", "ttl" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L217-L233
locationlabs/mockredis
mockredis/client.py
MockRedis.pttl
def pttl(self, key): """ Emulate pttl :param key: key for which pttl is requested. :returns: the number of milliseconds till timeout, None if the key does not exist or if the key has no timeout(as per the redis-py lib behavior). """ """ Returns ...
python
def pttl(self, key): """ Emulate pttl :param key: key for which pttl is requested. :returns: the number of milliseconds till timeout, None if the key does not exist or if the key has no timeout(as per the redis-py lib behavior). """ """ Returns ...
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Emulate pttl :param key: key for which pttl is requested. :returns: the number of milliseconds till timeout, None if the key does not exist or if the key has no timeout(as per the redis-py lib behavior).
[ "Emulate", "pttl" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L235-L256
locationlabs/mockredis
mockredis/client.py
MockRedis.do_expire
def do_expire(self): """ Expire objects assuming now == time """ # Deep copy to avoid RuntimeError: dictionary changed size during iteration _timeouts = deepcopy(self.timeouts) for key, value in _timeouts.items(): if value - self.clock.now() < timedelta(0): ...
python
def do_expire(self): """ Expire objects assuming now == time """ # Deep copy to avoid RuntimeError: dictionary changed size during iteration _timeouts = deepcopy(self.timeouts) for key, value in _timeouts.items(): if value - self.clock.now() < timedelta(0): ...
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Expire objects assuming now == time
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L258-L269
locationlabs/mockredis
mockredis/client.py
MockRedis.set
def set(self, key, value, ex=None, px=None, nx=False, xx=False): """ Set the ``value`` for the ``key`` in the context of the provided kwargs. As per the behavior of the redis-py lib: If nx and xx are both set, the function does nothing and None is returned. If px and ex are both...
python
def set(self, key, value, ex=None, px=None, nx=False, xx=False): """ Set the ``value`` for the ``key`` in the context of the provided kwargs. As per the behavior of the redis-py lib: If nx and xx are both set, the function does nothing and None is returned. If px and ex are both...
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Set the ``value`` for the ``key`` in the context of the provided kwargs. As per the behavior of the redis-py lib: If nx and xx are both set, the function does nothing and None is returned. If px and ex are both set, the preference is given to px. If the key is not set for some reason, t...
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L313-L342
locationlabs/mockredis
mockredis/client.py
MockRedis._should_set
def _should_set(self, key, mode): """ Determine if it is okay to set a key. If the mode is None, returns True, otherwise, returns True of false based on the value of ``key`` and the ``mode`` (nx | xx). """ if mode is None or mode not in ["nx", "xx"]: return ...
python
def _should_set(self, key, mode): """ Determine if it is okay to set a key. If the mode is None, returns True, otherwise, returns True of false based on the value of ``key`` and the ``mode`` (nx | xx). """ if mode is None or mode not in ["nx", "xx"]: return ...
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L359-L381
locationlabs/mockredis
mockredis/client.py
MockRedis.setex
def setex(self, name, time, value): """ Set the value of ``name`` to ``value`` that expires in ``time`` seconds. ``time`` can be represented by an integer or a Python timedelta object. """ if not self.strict: # when not strict mode swap value and time args ord...
python
def setex(self, name, time, value): """ Set the value of ``name`` to ``value`` that expires in ``time`` seconds. ``time`` can be represented by an integer or a Python timedelta object. """ if not self.strict: # when not strict mode swap value and time args ord...
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L383-L392
locationlabs/mockredis
mockredis/client.py
MockRedis.psetex
def psetex(self, key, time, value): """ Set the value of ``key`` to ``value`` that expires in ``time`` milliseconds. ``time`` can be represented by an integer or a Python timedelta object. """ return self.set(key, value, px=time)
python
def psetex(self, key, time, value): """ Set the value of ``key`` to ``value`` that expires in ``time`` milliseconds. ``time`` can be represented by an integer or a Python timedelta object. """ return self.set(key, value, px=time)
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Set the value of ``key`` to ``value`` that expires in ``time`` milliseconds. ``time`` can be represented by an integer or a Python timedelta object.
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L394-L400
locationlabs/mockredis
mockredis/client.py
MockRedis.setnx
def setnx(self, key, value): """Set the value of ``key`` to ``value`` if key doesn't exist""" return self.set(key, value, nx=True)
python
def setnx(self, key, value): """Set the value of ``key`` to ``value`` if key doesn't exist""" return self.set(key, value, nx=True)
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L402-L404
locationlabs/mockredis
mockredis/client.py
MockRedis.mset
def mset(self, *args, **kwargs): """ Sets key/values based on a mapping. Mapping can be supplied as a single dictionary argument or as kwargs. """ mapping = kwargs if args: if len(args) != 1 or not isinstance(args[0], dict): raise RedisError('M...
python
def mset(self, *args, **kwargs): """ Sets key/values based on a mapping. Mapping can be supplied as a single dictionary argument or as kwargs. """ mapping = kwargs if args: if len(args) != 1 or not isinstance(args[0], dict): raise RedisError('M...
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Sets key/values based on a mapping. Mapping can be supplied as a single dictionary argument or as kwargs.
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L406-L422
locationlabs/mockredis
mockredis/client.py
MockRedis.msetnx
def msetnx(self, *args, **kwargs): """ Sets key/values based on a mapping if none of the keys are already set. Mapping can be supplied as a single dictionary argument or as kwargs. Returns a boolean indicating if the operation was successful. """ if args: if l...
python
def msetnx(self, *args, **kwargs): """ Sets key/values based on a mapping if none of the keys are already set. Mapping can be supplied as a single dictionary argument or as kwargs. Returns a boolean indicating if the operation was successful. """ if args: if l...
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Sets key/values based on a mapping if none of the keys are already set. Mapping can be supplied as a single dictionary argument or as kwargs. Returns a boolean indicating if the operation was successful.
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train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L424-L446
locationlabs/mockredis
mockredis/client.py
MockRedis.setbit
def setbit(self, key, offset, value): """ Set the bit at ``offset`` in ``key`` to ``value``. """ key = self._encode(key) index, bits, mask = self._get_bits_and_offset(key, offset) if index >= len(bits): bits.extend(b"\x00" * (index + 1 - len(bits))) ...
python
def setbit(self, key, offset, value): """ Set the bit at ``offset`` in ``key`` to ``value``. """ key = self._encode(key) index, bits, mask = self._get_bits_and_offset(key, offset) if index >= len(bits): bits.extend(b"\x00" * (index + 1 - len(bits))) ...
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Set the bit at ``offset`` in ``key`` to ``value``.
[ "Set", "the", "bit", "at", "offset", "in", "key", "to", "value", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L465-L484
locationlabs/mockredis
mockredis/client.py
MockRedis.getbit
def getbit(self, key, offset): """ Returns the bit value at ``offset`` in ``key``. """ key = self._encode(key) index, bits, mask = self._get_bits_and_offset(key, offset) if index >= len(bits): return 0 return 1 if (bits[index] & mask) else 0
python
def getbit(self, key, offset): """ Returns the bit value at ``offset`` in ``key``. """ key = self._encode(key) index, bits, mask = self._get_bits_and_offset(key, offset) if index >= len(bits): return 0 return 1 if (bits[index] & mask) else 0
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Returns the bit value at ``offset`` in ``key``.
[ "Returns", "the", "bit", "value", "at", "offset", "in", "key", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L486-L496
locationlabs/mockredis
mockredis/client.py
MockRedis.hexists
def hexists(self, hashkey, attribute): """Emulate hexists.""" redis_hash = self._get_hash(hashkey, 'HEXISTS') return self._encode(attribute) in redis_hash
python
def hexists(self, hashkey, attribute): """Emulate hexists.""" redis_hash = self._get_hash(hashkey, 'HEXISTS') return self._encode(attribute) in redis_hash
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Emulate hexists.
[ "Emulate", "hexists", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L506-L510
locationlabs/mockredis
mockredis/client.py
MockRedis.hget
def hget(self, hashkey, attribute): """Emulate hget.""" redis_hash = self._get_hash(hashkey, 'HGET') return redis_hash.get(self._encode(attribute))
python
def hget(self, hashkey, attribute): """Emulate hget.""" redis_hash = self._get_hash(hashkey, 'HGET') return redis_hash.get(self._encode(attribute))
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Emulate hget.
[ "Emulate", "hget", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L512-L516
locationlabs/mockredis
mockredis/client.py
MockRedis.hdel
def hdel(self, hashkey, *keys): """Emulate hdel""" redis_hash = self._get_hash(hashkey, 'HDEL') count = 0 for key in keys: attribute = self._encode(key) if attribute in redis_hash: count += 1 del redis_hash[attribute] ...
python
def hdel(self, hashkey, *keys): """Emulate hdel""" redis_hash = self._get_hash(hashkey, 'HDEL') count = 0 for key in keys: attribute = self._encode(key) if attribute in redis_hash: count += 1 del redis_hash[attribute] ...
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Emulate hdel
[ "Emulate", "hdel" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L524-L536
locationlabs/mockredis
mockredis/client.py
MockRedis.hmset
def hmset(self, hashkey, value): """Emulate hmset.""" redis_hash = self._get_hash(hashkey, 'HMSET', create=True) for key, value in value.items(): attribute = self._encode(key) redis_hash[attribute] = self._encode(value) return True
python
def hmset(self, hashkey, value): """Emulate hmset.""" redis_hash = self._get_hash(hashkey, 'HMSET', create=True) for key, value in value.items(): attribute = self._encode(key) redis_hash[attribute] = self._encode(value) return True
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Emulate hmset.
[ "Emulate", "hmset", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L543-L550
locationlabs/mockredis
mockredis/client.py
MockRedis.hmget
def hmget(self, hashkey, keys, *args): """Emulate hmget.""" redis_hash = self._get_hash(hashkey, 'HMGET') attributes = self._list_or_args(keys, args) return [redis_hash.get(self._encode(attribute)) for attribute in attributes]
python
def hmget(self, hashkey, keys, *args): """Emulate hmget.""" redis_hash = self._get_hash(hashkey, 'HMGET') attributes = self._list_or_args(keys, args) return [redis_hash.get(self._encode(attribute)) for attribute in attributes]
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Emulate hmget.
[ "Emulate", "hmget", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L552-L557
locationlabs/mockredis
mockredis/client.py
MockRedis.hset
def hset(self, hashkey, attribute, value): """Emulate hset.""" redis_hash = self._get_hash(hashkey, 'HSET', create=True) attribute = self._encode(attribute) attribute_present = attribute in redis_hash redis_hash[attribute] = self._encode(value) return long(0) if attribut...
python
def hset(self, hashkey, attribute, value): """Emulate hset.""" redis_hash = self._get_hash(hashkey, 'HSET', create=True) attribute = self._encode(attribute) attribute_present = attribute in redis_hash redis_hash[attribute] = self._encode(value) return long(0) if attribut...
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Emulate hset.
[ "Emulate", "hset", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L559-L566
locationlabs/mockredis
mockredis/client.py
MockRedis.hsetnx
def hsetnx(self, hashkey, attribute, value): """Emulate hsetnx.""" redis_hash = self._get_hash(hashkey, 'HSETNX', create=True) attribute = self._encode(attribute) if attribute in redis_hash: return long(0) else: redis_hash[attribute] = self._encode(value)...
python
def hsetnx(self, hashkey, attribute, value): """Emulate hsetnx.""" redis_hash = self._get_hash(hashkey, 'HSETNX', create=True) attribute = self._encode(attribute) if attribute in redis_hash: return long(0) else: redis_hash[attribute] = self._encode(value)...
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Emulate hsetnx.
[ "Emulate", "hsetnx", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L568-L577
locationlabs/mockredis
mockredis/client.py
MockRedis.hincrby
def hincrby(self, hashkey, attribute, increment=1): """Emulate hincrby.""" return self._hincrby(hashkey, attribute, 'HINCRBY', long, increment)
python
def hincrby(self, hashkey, attribute, increment=1): """Emulate hincrby.""" return self._hincrby(hashkey, attribute, 'HINCRBY', long, increment)
[ "def", "hincrby", "(", "self", ",", "hashkey", ",", "attribute", ",", "increment", "=", "1", ")", ":", "return", "self", ".", "_hincrby", "(", "hashkey", ",", "attribute", ",", "'HINCRBY'", ",", "long", ",", "increment", ")" ]
Emulate hincrby.
[ "Emulate", "hincrby", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L579-L582
locationlabs/mockredis
mockredis/client.py
MockRedis.hincrbyfloat
def hincrbyfloat(self, hashkey, attribute, increment=1.0): """Emulate hincrbyfloat.""" return self._hincrby(hashkey, attribute, 'HINCRBYFLOAT', float, increment)
python
def hincrbyfloat(self, hashkey, attribute, increment=1.0): """Emulate hincrbyfloat.""" return self._hincrby(hashkey, attribute, 'HINCRBYFLOAT', float, increment)
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Emulate hincrbyfloat.
[ "Emulate", "hincrbyfloat", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L584-L587
locationlabs/mockredis
mockredis/client.py
MockRedis._hincrby
def _hincrby(self, hashkey, attribute, command, type_, increment): """Shared hincrby and hincrbyfloat routine""" redis_hash = self._get_hash(hashkey, command, create=True) attribute = self._encode(attribute) previous_value = type_(redis_hash.get(attribute, '0')) redis_hash[attrib...
python
def _hincrby(self, hashkey, attribute, command, type_, increment): """Shared hincrby and hincrbyfloat routine""" redis_hash = self._get_hash(hashkey, command, create=True) attribute = self._encode(attribute) previous_value = type_(redis_hash.get(attribute, '0')) redis_hash[attrib...
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Shared hincrby and hincrbyfloat routine
[ "Shared", "hincrby", "and", "hincrbyfloat", "routine" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L589-L595
locationlabs/mockredis
mockredis/client.py
MockRedis.lrange
def lrange(self, key, start, stop): """Emulate lrange.""" redis_list = self._get_list(key, 'LRANGE') start, stop = self._translate_range(len(redis_list), start, stop) return redis_list[start:stop + 1]
python
def lrange(self, key, start, stop): """Emulate lrange.""" redis_list = self._get_list(key, 'LRANGE') start, stop = self._translate_range(len(redis_list), start, stop) return redis_list[start:stop + 1]
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Emulate lrange.
[ "Emulate", "lrange", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L611-L615
locationlabs/mockredis
mockredis/client.py
MockRedis.lindex
def lindex(self, key, index): """Emulate lindex.""" redis_list = self._get_list(key, 'LINDEX') if self._encode(key) not in self.redis: return None try: return redis_list[index] except (IndexError): # Redis returns nil if the index doesn't ex...
python
def lindex(self, key, index): """Emulate lindex.""" redis_list = self._get_list(key, 'LINDEX') if self._encode(key) not in self.redis: return None try: return redis_list[index] except (IndexError): # Redis returns nil if the index doesn't ex...
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Emulate lindex.
[ "Emulate", "lindex", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L617-L629
locationlabs/mockredis
mockredis/client.py
MockRedis._blocking_pop
def _blocking_pop(self, pop_func, keys, timeout): """Emulate blocking pop functionality""" if not isinstance(timeout, (int, long)): raise RuntimeError('timeout is not an integer or out of range') if timeout is None or timeout == 0: timeout = self.blocking_timeout ...
python
def _blocking_pop(self, pop_func, keys, timeout): """Emulate blocking pop functionality""" if not isinstance(timeout, (int, long)): raise RuntimeError('timeout is not an integer or out of range') if timeout is None or timeout == 0: timeout = self.blocking_timeout ...
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Emulate blocking pop functionality
[ "Emulate", "blocking", "pop", "functionality" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L638-L660
locationlabs/mockredis
mockredis/client.py
MockRedis.blpop
def blpop(self, keys, timeout=0): """Emulate blpop""" return self._blocking_pop(self.lpop, keys, timeout)
python
def blpop(self, keys, timeout=0): """Emulate blpop""" return self._blocking_pop(self.lpop, keys, timeout)
[ "def", "blpop", "(", "self", ",", "keys", ",", "timeout", "=", "0", ")", ":", "return", "self", ".", "_blocking_pop", "(", "self", ".", "lpop", ",", "keys", ",", "timeout", ")" ]
Emulate blpop
[ "Emulate", "blpop" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L669-L671
locationlabs/mockredis
mockredis/client.py
MockRedis.brpop
def brpop(self, keys, timeout=0): """Emulate brpop""" return self._blocking_pop(self.rpop, keys, timeout)
python
def brpop(self, keys, timeout=0): """Emulate brpop""" return self._blocking_pop(self.rpop, keys, timeout)
[ "def", "brpop", "(", "self", ",", "keys", ",", "timeout", "=", "0", ")", ":", "return", "self", ".", "_blocking_pop", "(", "self", ".", "rpop", ",", "keys", ",", "timeout", ")" ]
Emulate brpop
[ "Emulate", "brpop" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L673-L675
locationlabs/mockredis
mockredis/client.py
MockRedis.lpush
def lpush(self, key, *args): """Emulate lpush.""" redis_list = self._get_list(key, 'LPUSH', create=True) # Creates the list at this key if it doesn't exist, and appends args to its beginning args_reversed = [self._encode(arg) for arg in args] args_reversed.reverse() upda...
python
def lpush(self, key, *args): """Emulate lpush.""" redis_list = self._get_list(key, 'LPUSH', create=True) # Creates the list at this key if it doesn't exist, and appends args to its beginning args_reversed = [self._encode(arg) for arg in args] args_reversed.reverse() upda...
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Emulate lpush.
[ "Emulate", "lpush", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L693-L704
locationlabs/mockredis
mockredis/client.py
MockRedis.rpop
def rpop(self, key): """Emulate lpop.""" redis_list = self._get_list(key, 'RPOP') if self._encode(key) not in self.redis: return None try: value = redis_list.pop() if len(redis_list) == 0: self.delete(key) return value ...
python
def rpop(self, key): """Emulate lpop.""" redis_list = self._get_list(key, 'RPOP') if self._encode(key) not in self.redis: return None try: value = redis_list.pop() if len(redis_list) == 0: self.delete(key) return value ...
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Emulate lpop.
[ "Emulate", "lpop", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L706-L720
locationlabs/mockredis
mockredis/client.py
MockRedis.rpush
def rpush(self, key, *args): """Emulate rpush.""" redis_list = self._get_list(key, 'RPUSH', create=True) # Creates the list at this key if it doesn't exist, and appends args to it redis_list.extend(map(self._encode, args)) # Return the length of the list after the push operatio...
python
def rpush(self, key, *args): """Emulate rpush.""" redis_list = self._get_list(key, 'RPUSH', create=True) # Creates the list at this key if it doesn't exist, and appends args to it redis_list.extend(map(self._encode, args)) # Return the length of the list after the push operatio...
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Emulate rpush.
[ "Emulate", "rpush", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L722-L730
locationlabs/mockredis
mockredis/client.py
MockRedis.lrem
def lrem(self, key, value, count=0): """Emulate lrem.""" value = self._encode(value) redis_list = self._get_list(key, 'LREM') removed_count = 0 if self._encode(key) in self.redis: if count == 0: # Remove all ocurrences while redis_list....
python
def lrem(self, key, value, count=0): """Emulate lrem.""" value = self._encode(value) redis_list = self._get_list(key, 'LREM') removed_count = 0 if self._encode(key) in self.redis: if count == 0: # Remove all ocurrences while redis_list....
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Emulate lrem.
[ "Emulate", "lrem", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L732-L765
locationlabs/mockredis
mockredis/client.py
MockRedis.ltrim
def ltrim(self, key, start, stop): """Emulate ltrim.""" redis_list = self._get_list(key, 'LTRIM') if redis_list: start, stop = self._translate_range(len(redis_list), start, stop) self.redis[self._encode(key)] = redis_list[start:stop + 1] return True
python
def ltrim(self, key, start, stop): """Emulate ltrim.""" redis_list = self._get_list(key, 'LTRIM') if redis_list: start, stop = self._translate_range(len(redis_list), start, stop) self.redis[self._encode(key)] = redis_list[start:stop + 1] return True
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Emulate ltrim.
[ "Emulate", "ltrim", "." ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L767-L773
locationlabs/mockredis
mockredis/client.py
MockRedis.rpoplpush
def rpoplpush(self, source, destination): """Emulate rpoplpush""" transfer_item = self.rpop(source) if transfer_item is not None: self.lpush(destination, transfer_item) return transfer_item
python
def rpoplpush(self, source, destination): """Emulate rpoplpush""" transfer_item = self.rpop(source) if transfer_item is not None: self.lpush(destination, transfer_item) return transfer_item
[ "def", "rpoplpush", "(", "self", ",", "source", ",", "destination", ")", ":", "transfer_item", "=", "self", ".", "rpop", "(", "source", ")", "if", "transfer_item", "is", "not", "None", ":", "self", ".", "lpush", "(", "destination", ",", "transfer_item", ...
Emulate rpoplpush
[ "Emulate", "rpoplpush" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L775-L780
locationlabs/mockredis
mockredis/client.py
MockRedis.brpoplpush
def brpoplpush(self, source, destination, timeout=0): """Emulate brpoplpush""" transfer_item = self.brpop(source, timeout) if transfer_item is None: return None key, val = transfer_item self.lpush(destination, val) return val
python
def brpoplpush(self, source, destination, timeout=0): """Emulate brpoplpush""" transfer_item = self.brpop(source, timeout) if transfer_item is None: return None key, val = transfer_item self.lpush(destination, val) return val
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Emulate brpoplpush
[ "Emulate", "brpoplpush" ]
train
https://github.com/locationlabs/mockredis/blob/fd4e3117066ff0c24e86ebca007853a8092e3254/mockredis/client.py#L782-L790