benjamintli/cosqa-llm-filtered-hard-negatives huggingface dataset:
Query: python lambda takes a tuple

Relevant code:
def lambda_tuple_converter(func):
    """
    Converts a Python 2 function as
      lambda (x,y): x + y
    In the Python 3 format:
      lambda x,y : x + y
    """
    if func is not None and func.__code__.co_argcount == 1:
        return lambda *args: func(args[0] if len(args) == 1 else args)
    else:
        return func

Similar but not relevant code:
def tuple(self, var, cast=None, default=NOTSET):
        """
        :rtype: tuple
        """
        return self.get_value(var, cast=tuple if not cast else (cast,), default=default)

Similar but not relevant code:
def ensure_tuple(obj):
    """Try and make the given argument into a tuple."""
    if obj is None:
        return tuple()
    if isinstance(obj, Iterable) and not isinstance(obj, six.string_types):
        return tuple(obj)
    return obj,

Similar but not relevant code:
def _get_tuple(self, fields):
    """
    :param fields: a list which contains either 0,1,or 2 values
    :return: a tuple with default values of '';
    """
    v1 = ''
    v2 = ''
    if len(fields) > 0:
      v1 = fields[0]
    if len(fields) > 1:
      v2 = fields[1]
    return v1, v2

Similar but not relevant code:
def _parse_tuple_string(argument):
        """ Return a tuple from parsing 'a,b,c,d' -> (a,b,c,d) """
        if isinstance(argument, str):
            return tuple(int(p.strip()) for p in argument.split(','))
        return argument

Similar but not relevant code:
def as_tuple(self, value):
        """Utility function which converts lists to tuples."""
        if isinstance(value, list):
            value = tuple(value)
        return value
Query: how to allivate permission in python

Relevant code:
def has_edit_permission(self, request):
        """ Can edit this object """
        return request.user.is_authenticated and request.user.is_active and request.user.is_staff

Similar but not relevant code:
def perform_permissions_check(self, user, obj, perms):
        """ Performs the permission check. """
        return self.request.forum_permission_handler.can_download_files(obj, user)

Similar but not relevant code:
def make_file_read_only(file_path):
    """
    Removes the write permissions for the given file for owner, groups and others.

    :param file_path: The file whose privileges are revoked.
    :raise FileNotFoundError: If the given file does not exist.
    """
    old_permissions = os.stat(file_path).st_mode
    os.chmod(file_path, old_permissions & ~WRITE_PERMISSIONS)
Query: python latex to png

Relevant code:
def print_display_png(o):
    """
    A function to display sympy expression using display style LaTeX in PNG.
    """
    s = latex(o, mode='plain')
    s = s.strip('$')
    # As matplotlib does not support display style, dvipng backend is
    # used here.
    png = latex_to_png('$$%s$$' % s, backend='dvipng')
    return png

Similar but not relevant code:
def file_to_png(fp):
	"""Convert an image to PNG format with Pillow.
	
	:arg file-like fp: The image file.
	:rtype: bytes
	"""
	import PIL.Image # pylint: disable=import-error
	with io.BytesIO() as dest:
		PIL.Image.open(fp).save(dest, "PNG", optimize=True)
		return dest.getvalue()

Similar but not relevant code:
def _convert(self, image, output=None):
        """Private method for converting a single PNG image to a PDF."""
        with Image.open(image) as im:
            width, height = im.size

            co = CanvasObjects()
            co.add(CanvasImg(image, 1.0, w=width, h=height))

            return WatermarkDraw(co, tempdir=self.tempdir, pagesize=(width, height)).write(output)

Similar but not relevant code:
def save_pdf(path):
  """
  Saves a pdf of the current matplotlib figure.

  :param path: str, filepath to save to
  """

  pp = PdfPages(path)
  pp.savefig(pyplot.gcf())
  pp.close()

Similar but not relevant code:
def save_as_png(self, filename, width=300, height=250, render_time=1):
        """Open saved html file in an virtual browser and save a screen shot to PNG format."""
        self.driver.set_window_size(width, height)
        self.driver.get('file://{path}/{filename}'.format(
            path=os.getcwd(), filename=filename + ".html"))
        time.sleep(render_time)
        self.driver.save_screenshot(filename + ".png")
Query: how to apply bin function to elements in a list or array in python

Relevant code:
def lazy_reverse_binmap(f, xs):
    """
    Same as lazy_binmap, except the parameters are flipped for the binary function
    """
    return (f(y, x) for x, y in zip(xs, xs[1:]))

Similar but not relevant code:
def _fill_array_from_list(the_list, the_array):
        """Fill an `array` from a `list`"""
        for i, val in enumerate(the_list):
            the_array[i] = val
        return the_array

Similar but not relevant code:
def multiply(self, number):
        """Return a Vector as the product of the vector and a real number."""
        return self.from_list([x * number for x in self.to_list()])

Similar but not relevant code:
def splitBy(data, num):
    """ Turn a list to list of list """
    return [data[i:i + num] for i in range(0, len(data), num)]

Similar but not relevant code:
def apply(f, obj, *args, **kwargs):
    """Apply a function in parallel to each element of the input"""
    return vectorize(f)(obj, *args, **kwargs)

Similar but not relevant code:
def inh(table):
    """
    inverse hyperbolic sine transformation
    """
    t = []
    for i in table:
        t.append(np.ndarray.tolist(np.arcsinh(i)))
    return t
Query: python left right mid string

Relevant code:
def _mid(string, start, end=None):
    """
    Returns a substring delimited by start and end position.
    """
    if end is None:
        end = len(string)
    return string[start:start + end]

Similar but not relevant code:
def _mid(pt1, pt2):
    """
    (Point, Point) -> Point
    Return the point that lies in between the two input points.
    """
    (x0, y0), (x1, y1) = pt1, pt2
    return 0.5 * (x0 + x1), 0.5 * (y0 + y1)

Similar but not relevant code:
def findLastCharIndexMatching(text, func):
    """ Return index of last character in string for which func(char) evaluates to True. """
    for i in range(len(text) - 1, -1, -1):
      if func(text[i]):
        return i

Similar but not relevant code:
def get_bottomrect_idx(self, pos):
        """ Determine if cursor is on bottom right corner of a hot spot."""
        for i, r in enumerate(self.link_bottom_rects):
            if r.Contains(pos):
                return i
        return -1

Similar but not relevant code:
def text_alignment(x, y):
    """
    Align text labels based on the x- and y-axis coordinate values.

    This function is used for computing the appropriate alignment of the text
    label.

    For example, if the text is on the "right" side of the plot, we want it to
    be left-aligned. If the text is on the "top" side of the plot, we want it
    to be bottom-aligned.

    :param x, y: (`int` or `float`) x- and y-axis coordinate respectively.
    :returns: A 2-tuple of strings, the horizontal and vertical alignments
        respectively.
    """
    if x == 0:
        ha = "center"
    elif x > 0:
        ha = "left"
    else:
        ha = "right"
    if y == 0:
        va = "center"
    elif y > 0:
        va = "bottom"
    else:
        va = "top"

    return ha, va
Query: how to apply log transformation to a column in python

Relevant code:
def log_normalize(data):
    """Perform log transform log(x + 1).
    
    Parameters
    ----------
    data : array_like
    
    """
    if sp.issparse(data):
        data = data.copy()
        data.data = np.log2(data.data + 1)
        return data

    return np.log2(data.astype(np.float64) + 1)

Similar but not relevant code:
def _transform_col(self, x, i):
        """Encode one categorical column into labels.

        Args:
            x (pandas.Series): a categorical column to encode
            i (int): column index

        Returns:
            x (pandas.Series): a column with labels.
        """
        return x.fillna(NAN_INT).map(self.label_encoders[i]).fillna(0)

Similar but not relevant code:
def reverse_transform(self, col):
        """Converts data back into original format.

        Args:
            col(pandas.DataFrame): Data to transform.

        Returns:
            pandas.DataFrame
        """

        output = pd.DataFrame()
        output[self.col_name] = self.get_category(col[self.col_name])

        return output

Similar but not relevant code:
def log_to_json(log):
    """Convert a log record into a list of strings"""
    return [log.timestamp.isoformat()[:22],
            log.level, log.process, log.message]

Similar but not relevant code:
def _get_log_prior_cl_func(self):
        """Get the CL log prior compute function.

        Returns:
            str: the compute function for computing the log prior.
        """
        return SimpleCLFunction.from_string('''
            mot_float_type _computeLogPrior(local const mot_float_type* x, void* data){
                return ''' + self._log_prior_func.get_cl_function_name() + '''(x, data);
            }
        ''', dependencies=[self._log_prior_func])
Query: python len function complexity

Relevant code:
def size(self):
        """
        Recursively find size of a tree. Slow.
        """

        if self is NULL:
            return 0
        return 1 + self.left.size() + self.right.size()

Similar but not relevant code:
def compute_number_edges(function):
    """
    Compute the number of edges of the CFG
    Args:
        function (core.declarations.function.Function)
    Returns:
        int
    """
    n = 0
    for node in function.nodes:
        n += len(node.sons)
    return n

Similar but not relevant code:
def hstrlen(self, name, key):
        """
        Return the number of bytes stored in the value of ``key``
        within hash ``name``
        """
        with self.pipe as pipe:
            return pipe.hstrlen(self.redis_key(name), key)

Similar but not relevant code:
def estimate_complexity(self, x,y,z,n):
        """ 
        calculates a rough guess of runtime based on product of parameters 
        """
        num_calculations = x * y * z * n
        run_time = num_calculations / 100000  # a 2014 PC does about 100k calcs in a second (guess based on prior logs)
        return self.show_time_as_short_string(run_time)

Similar but not relevant code:
def codes_get_size(handle, key):
    # type: (cffi.FFI.CData, str) -> int
    """
    Get the number of coded value from a key.
    If several keys of the same name are present, the total sum is returned.

    :param bytes key: the keyword to get the size of

    :rtype: int
    """
    size = ffi.new('size_t *')
    _codes_get_size(handle, key.encode(ENC), size)
    return size[0]
Query: how to ask question in python then pick formula based on answer

Relevant code:
def confirm(question, default=True):
    """Ask a yes/no question interactively.

    :param question: The text of the question to ask.
    :returns: True if the answer was "yes", False otherwise.
    """
    valid = {"": default, "yes": True, "y": True, "no": False, "n": False}
    while 1:
        choice = input(question + (" [Y/n] " if default else " [y/N] ")).lower()
        if choice in valid:
            return valid[choice]
        print("Please respond with 'y' or 'n' ")

Similar but not relevant code:
def parse_querystring(self, req, name, field):
        """Pull a querystring value from the request."""
        return core.get_value(req.args, name, field)

Similar but not relevant code:
def find_unit_clause(clauses, model):
    """Find a forced assignment if possible from a clause with only 1
    variable not bound in the model.
    >>> find_unit_clause([A|B|C, B|~C, ~A|~B], {A:True})
    (B, False)
    """
    for clause in clauses:
        P, value = unit_clause_assign(clause, model)
        if P: return P, value
    return None, None

Similar but not relevant code:
def returns(self) -> T.Optional[DocstringReturns]:
        """Return return information indicated in docstring."""
        try:
            return next(
                DocstringReturns.from_meta(meta)
                for meta in self.meta
                if meta.args[0] in {"return", "returns", "yield", "yields"}
            )
        except StopIteration:
            return None
Query: python levenshtein distance algorithm

Relevant code:
def levenshtein_distance_metric(a, b):
    """ 1 - farthest apart (same number of words, all diff). 0 - same"""
    return (levenshtein_distance(a, b) / (2.0 * max(len(a), len(b), 1)))

Similar but not relevant code:
def _manhattan_distance(vec_a, vec_b):
    """Return manhattan distance between two lists of numbers."""
    if len(vec_a) != len(vec_b):
        raise ValueError('len(vec_a) must equal len(vec_b)')
    return sum(map(lambda a, b: abs(a - b), vec_a, vec_b))

Similar but not relevant code:
def distL1(x1,y1,x2,y2):
    """Compute the L1-norm (Manhattan) distance between two points.

    The distance is rounded to the closest integer, for compatibility
    with the TSPLIB convention.

    The two points are located on coordinates (x1,y1) and (x2,y2),
    sent as parameters"""
    return int(abs(x2-x1) + abs(y2-y1)+.5)

Similar but not relevant code:
def hamming_distance(str1, str2):
    """Calculate the Hamming distance between two bit strings

    Args:
        str1 (str): First string.
        str2 (str): Second string.
    Returns:
        int: Distance between strings.
    Raises:
        VisualizationError: Strings not same length
    """
    if len(str1) != len(str2):
        raise VisualizationError('Strings not same length.')
    return sum(s1 != s2 for s1, s2 in zip(str1, str2))

Similar but not relevant code:
def manhattan(h1, h2): # # 7 us @array, 31 us @list \w 100 bins
    r"""
    Equal to Minowski distance with :math:`p=1`.
    
    See also
    --------
    minowski
    """
    h1, h2 = __prepare_histogram(h1, h2)
    return scipy.sum(scipy.absolute(h1 - h2))

Similar but not relevant code:
def jaccard(c_1, c_2):
    """
    Calculates the Jaccard similarity between two sets of nodes. Called by mroc.

    Inputs:  - c_1: Community (set of nodes) 1.
             - c_2: Community (set of nodes) 2.

    Outputs: - jaccard_similarity: The Jaccard similarity of these two communities.
    """
    nom = np.intersect1d(c_1, c_2).size
    denom = np.union1d(c_1, c_2).size
    return nom/denom
Query: how to bold the text in print in python

Relevant code:
def good(txt):
    """Print, emphasized 'good', the given 'txt' message"""

    print("%s# %s%s%s" % (PR_GOOD_CC, get_time_stamp(), txt, PR_NC))
    sys.stdout.flush()

Similar but not relevant code:
def info(txt):
    """Print, emphasized 'neutral', the given 'txt' message"""

    print("%s# %s%s%s" % (PR_EMPH_CC, get_time_stamp(), txt, PR_NC))
    sys.stdout.flush()

Similar but not relevant code:
def _update_font_style(self, font_style):
        """Updates font style widget

        Parameters
        ----------

        font_style: Integer
        \tButton down iif font_style == wx.FONTSTYLE_ITALIC

        """

        toggle_state = font_style & wx.FONTSTYLE_ITALIC == wx.FONTSTYLE_ITALIC

        self.ToggleTool(wx.FONTFLAG_ITALIC, toggle_state)
Query: python linked list implementation with head and tail

Relevant code:
def get_tail(self):
        """Gets tail

        :return: Tail of linked list
        """
        node = self.head
        last_node = self.head

        while node is not None:
            last_node = node
            node = node.next_node

        return last_node

Similar but not relevant code:
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()
        updated_list = args_reversed + redis_list
        self.redis[self._encode(key)] = updated_list

        # Return the length of the list after the push operation
        return len(updated_list)

Similar but not relevant code:
def _listify(collection):
        """This is a workaround where Collections are no longer iterable
        when using JPype."""
        new_list = []
        for index in range(len(collection)):
            new_list.append(collection[index])
        return new_list

Similar but not relevant code:
def head(self) -> Any:
        """Retrive first element in List."""

        lambda_list = self._get_value()
        return lambda_list(lambda head, _: head)

Similar but not relevant code:
def tail(self, n=10):
        """
        Get an SArray that contains the last n elements in the SArray.

        Parameters
        ----------
        n : int
            The number of elements to fetch

        Returns
        -------
        out : SArray
            A new SArray which contains the last n rows of the current SArray.
        """
        with cython_context():
            return SArray(_proxy=self.__proxy__.tail(n))

Similar but not relevant code:
def push(self, el):
        """ Put a new element in the queue. """
        count = next(self.counter)
        heapq.heappush(self._queue, (el, count))
Query: how to byte align in python

Relevant code:
def be_array_from_bytes(fmt, data):
    """
    Reads an array from bytestring with big-endian data.
    """
    arr = array.array(str(fmt), data)
    return fix_byteorder(arr)

Similar but not relevant code:
def bytes_to_bits(bytes_):
    """Convert bytes to a list of bits
    """
    res = []
    for x in bytes_:
        if not isinstance(x, int):
            x = ord(x)
        res += byte_to_bits(x)
    return res
Query: python list combine to string with delimiter

Relevant code:
def list2string (inlist,delimit=' '):
    """
Converts a 1D list to a single long string for file output, using
the string.join function.

Usage:   list2string (inlist,delimit=' ')
Returns: the string created from inlist
"""
    stringlist = [makestr(_) for _ in inlist]
    return string.join(stringlist,delimit)

Similar but not relevant code:
def split_elements(value):
    """Split a string with comma or space-separated elements into a list."""
    l = [v.strip() for v in value.split(',')]
    if len(l) == 1:
        l = value.split()
    return l
Query: how to calculate covariance python

Relevant code:
def empirical(X):
    """Compute empirical covariance as baseline estimator.
    """
    print("Empirical")
    cov = np.dot(X.T, X) / n_samples
    return cov, np.linalg.inv(cov)

Similar but not relevant code:
def _covariance_matrix(self, type='noise'):
        """
        Constructs the covariance matrix from PCA
        residuals
        """
        if type == 'sampling':
            return self.sigma**2/(self.n-1)
        elif type == 'noise':
            return 4*self.sigma*N.var(self.rotated(), axis=0)

Similar but not relevant code:
def Cinv(self):
        """Inverse of the noise covariance."""
        try:
            return np.linalg.inv(self.c)
        except np.linalg.linalg.LinAlgError:
            print('Warning: non-invertible noise covariance matrix c.')
            return np.eye(self.c.shape[0])
Query: python list dedup in order

Relevant code:
def dedup(seq):
    """Remove duplicates from a list while keeping order."""
    seen = set()
    for item in seq:
        if item not in seen:
            seen.add(item)
            yield item

Similar but not relevant code:
def partition_all(n, iterable):
    """Partition a list into equally sized pieces, including last smaller parts
    http://stackoverflow.com/questions/5129102/python-equivalent-to-clojures-partition-all
    """
    it = iter(iterable)
    while True:
        chunk = list(itertools.islice(it, n))
        if not chunk:
            break
        yield chunk

Similar but not relevant code:
def strip_head(sequence, values):
    """Strips elements of `values` from the beginning of `sequence`."""
    values = set(values)
    return list(itertools.dropwhile(lambda x: x in values, sequence))

Similar but not relevant code:
def inverse(d):
    """
    reverse the k:v pairs
    """
    output = {}
    for k, v in unwrap(d).items():
        output[v] = output.get(v, [])
        output[v].append(k)
    return output

Similar but not relevant code:
def sorted_chain(*ranges: Iterable[Tuple[int, int]]) -> List[Tuple[int, int]]:
    """Chain & sort ranges."""
    return sorted(itertools.chain(*ranges))
Query: how to calculate standard deviation or missing percentage of a variable in python

Relevant code:
def stddev(values, meanval=None):  #from AI: A Modern Appproach
    """The standard deviation of a set of values.
    Pass in the mean if you already know it."""
    if meanval == None: meanval = mean(values)
    return math.sqrt( sum([(x - meanval)**2 for x in values]) / (len(values)-1) )

Similar but not relevant code:
def mad(v):
    """MAD -- Median absolute deviation. More robust than standard deviation.
    """
    return np.median(np.abs(v - np.median(v)))

Similar but not relevant code:
def explained_variance(returns, values):
    """ Calculate how much variance in returns do the values explain """
    exp_var = 1 - torch.var(returns - values) / torch.var(returns)
    return exp_var.item()
Query: python list fill between values

Relevant code:
def _fill_array_from_list(the_list, the_array):
        """Fill an `array` from a `list`"""
        for i, val in enumerate(the_list):
            the_array[i] = val
        return the_array

Similar but not relevant code:
def _maybe_fill(arr, fill_value=np.nan):
    """
    if we have a compatible fill_value and arr dtype, then fill
    """
    if _isna_compat(arr, fill_value):
        arr.fill(fill_value)
    return arr

Similar but not relevant code:
def flatten_list(l: List[list]) -> list:
    """ takes a list of lists, l and returns a flat list
    """
    return [v for inner_l in l for v in inner_l]

Similar but not relevant code:
def flatten_list(l):
    """ Nested lists to single-level list, does not split strings"""
    return list(chain.from_iterable(repeat(x,1) if isinstance(x,str) else x for x in l))

Similar but not relevant code:
def flatten(l, types=(list, float)):
    """
    Flat nested list of lists into a single list.
    """
    l = [item if isinstance(item, types) else [item] for item in l]
    return [item for sublist in l for item in sublist]

Similar but not relevant code:
def from_pairs_to_array_values(pairs):
    """
        Like from pairs but combines duplicate key values into arrays
    :param pairs:
    :return:
    """
    result = {}
    for pair in pairs:
        result[pair[0]] = concat(prop_or([], pair[0], result), [pair[1]])
    return result
Query: python list median calculations

Relevant code:
def median(data):
    """Calculate the median of a list."""
    data.sort()
    num_values = len(data)
    half = num_values // 2
    if num_values % 2:
        return data[half]
    return 0.5 * (data[half-1] + data[half])

Similar but not relevant code:
def median(self):
        """Computes the median of a log-normal distribution built with the stats data."""
        mu = self.mean()
        ret_val = math.exp(mu)
        if math.isnan(ret_val):
            ret_val = float("inf")
        return ret_val
Query: how to call the header of columns in python

Relevant code:
def printheader(h=None):
    """Print the header for the CSV table."""
    writer = csv.writer(sys.stdout)
    writer.writerow(header_fields(h))

Similar but not relevant code:
def generate_header(headerfields, oldheader, group_by_field):
    """Returns a header as a list, ready to write to TSV file"""
    fieldtypes = ['peptidefdr', 'peptidepep', 'nopsms', 'proteindata',
                  'precursorquant', 'isoquant']
    return generate_general_header(headerfields, fieldtypes,
                                   peptabledata.HEADER_PEPTIDE, oldheader,
                                   group_by_field)