benjamintli/cosqa-llm-filtered-hard-negatives huggingface dataset:
Query: scope of variables in same function in python

Relevant code:
def extract_vars_above(*names):
    """Extract a set of variables by name from another frame.

    Similar to extractVars(), but with a specified depth of 1, so that names
    are exctracted exactly from above the caller.

    This is simply a convenience function so that the very common case (for us)
    of skipping exactly 1 frame doesn't have to construct a special dict for
    keyword passing."""

    callerNS = sys._getframe(2).f_locals
    return dict((k,callerNS[k]) for k in names)

Similar but not relevant code:
def scopes_as(self, new_scopes):
        """Replace my :attr:`scopes` for the duration of the with block.

        My global scope is not replaced.

        Args:
            new_scopes (list of dict-likes): The new :attr:`scopes` to use.
        """
        old_scopes, self.scopes = self.scopes, new_scopes
        yield
        self.scopes = old_scopes

Similar but not relevant code:
def append_scope(self):
        """Create a new scope in the current frame."""
        self.stack.current.append(Scope(self.stack.current.current))
Query: python boto3 create containor

Relevant code:
def __init__(self, name, contained_key):
        """Instantiate an anonymous file-based Bucket around a single key.
        """
        self.name = name
        self.contained_key = contained_key

Similar but not relevant code:
def get_boto_session(
        region,
        aws_access_key_id=None,
        aws_secret_access_key=None,
        aws_session_token=None
        ):
    """Get a boto3 session."""
    return boto3.session.Session(
        region_name=region,
        aws_secret_access_key=aws_secret_access_key,
        aws_access_key_id=aws_access_key_id,
        aws_session_token=aws_session_token
    )

Similar but not relevant code:
def s3(ctx, bucket_name, data_file, region):
    """Use the S3 SWAG backend."""
    if not ctx.data_file:
        ctx.data_file = data_file

    if not ctx.bucket_name:
        ctx.bucket_name = bucket_name

    if not ctx.region:
        ctx.region = region

    ctx.type = 's3'

Similar but not relevant code:
def get_key(self, key, bucket_name=None):
        """
        Returns a boto3.s3.Object

        :param key: the path to the key
        :type key: str
        :param bucket_name: the name of the bucket
        :type bucket_name: str
        """
        if not bucket_name:
            (bucket_name, key) = self.parse_s3_url(key)

        obj = self.get_resource_type('s3').Object(bucket_name, key)
        obj.load()
        return obj

Similar but not relevant code:
def _aws_get_instance_by_tag(region, name, tag, raw):
    """Get all instances matching a tag."""
    client = boto3.session.Session().client('ec2', region)
    matching_reservations = client.describe_instances(Filters=[{'Name': tag, 'Values': [name]}]).get('Reservations', [])
    instances = []
    [[instances.append(_aws_instance_from_dict(region, instance, raw))  # pylint: disable=expression-not-assigned
      for instance in reservation.get('Instances')] for reservation in matching_reservations if reservation]
    return instances

Similar but not relevant code:
def connect_rds(aws_access_key_id=None, aws_secret_access_key=None, **kwargs):
    """
    :type aws_access_key_id: string
    :param aws_access_key_id: Your AWS Access Key ID

    :type aws_secret_access_key: string
    :param aws_secret_access_key: Your AWS Secret Access Key

    :rtype: :class:`boto.rds.RDSConnection`
    :return: A connection to RDS
    """
    from boto.rds import RDSConnection
    return RDSConnection(aws_access_key_id, aws_secret_access_key, **kwargs)
Query: see if a list is null in python

Relevant code:
def is_nullable_list(val, vtype):
    """Return True if list contains either values of type `vtype` or None."""
    return (isinstance(val, list) and
            any(isinstance(v, vtype) for v in val) and
            all((isinstance(v, vtype) or v is None) for v in val))

Similar but not relevant code:
def is_list_of_list(item):
    """
    check whether the item is list (tuple)
    and consist of list (tuple) elements
    """
    if (
        type(item) in (list, tuple)
        and len(item)
        and isinstance(item[0], (list, tuple))
    ):
        return True
    return False

Similar but not relevant code:
def is_iter_non_string(obj):
    """test if object is a list or tuple"""
    if isinstance(obj, list) or isinstance(obj, tuple):
        return True
    return False

Similar but not relevant code:
def list_of(cls):
    """
    Returns a function that checks that each element in a
    list is of a specific type.
    """
    return lambda l: isinstance(l, list) and all(isinstance(x, cls) for x in l)

Similar but not relevant code:
def is_listish(obj):
    """Check if something quacks like a list."""
    if isinstance(obj, (list, tuple, set)):
        return True
    return is_sequence(obj)
Query: python box plot value

Relevant code:
def compute_boxplot(self, series):
        """
        Compute boxplot for given pandas Series.
        """
        from matplotlib.cbook import boxplot_stats
        series = series[series.notnull()]
        if len(series.values) == 0:
            return {}
        elif not is_numeric_dtype(series):
            return self.non_numeric_stats(series)
        stats = boxplot_stats(list(series.values))[0]
        stats['count'] = len(series.values)
        stats['fliers'] = "|".join(map(str, stats['fliers']))
        return stats

Similar but not relevant code:
def oplot(self, x, y, **kw):
        """generic plotting method, overplotting any existing plot """
        self.panel.oplot(x, y, **kw)

Similar but not relevant code:
def add_plot(x, y, xl, yl, fig, ax, LATEX=False, linestyle=None, **kwargs):
    """Add plots to an existing plot"""
    if LATEX:
        xl_data = xl[1]  # NOQA
        yl_data = yl[1]
    else:
        xl_data = xl[0]  # NOQA
        yl_data = yl[0]

    for idx in range(len(y)):
        ax.plot(x, y[idx], label=yl_data[idx], linestyle=linestyle)

    ax.legend(loc='upper right')
    ax.set_ylim(auto=True)

Similar but not relevant code:
def plot_target(target, ax):
    """Ajoute la target au plot"""
    ax.scatter(target[0], target[1], target[2], c="red", s=80)

Similar but not relevant code:
def finish_plot():
    """Helper for plotting."""
    plt.legend()
    plt.grid(color='0.7')
    plt.xlabel('x')
    plt.ylabel('y')
    plt.show()

Similar but not relevant code:
def scatter(self, *args, **kwargs):
        """Add a scatter plot."""
        cls = _make_class(ScatterVisual,
                          _default_marker=kwargs.pop('marker', None),
                          )
        return self._add_item(cls, *args, **kwargs)
Query: select all components in array python numpy

Relevant code:
def Any(a, axis, keep_dims):
    """
    Any reduction op.
    """
    return np.any(a, axis=axis if not isinstance(axis, np.ndarray) else tuple(axis),
                  keepdims=keep_dims),

Similar but not relevant code:
def array(self):
        """
        The underlying array of shape (N, L, I)
        """
        return numpy.array([self[sid].array for sid in sorted(self)])

Similar but not relevant code:
def _indexes(arr):
    """ Returns the list of all indexes of the given array.

    Currently works for one and two-dimensional arrays

    """
    myarr = np.array(arr)
    if myarr.ndim == 1:
        return list(range(len(myarr)))
    elif myarr.ndim == 2:
        return tuple(itertools.product(list(range(arr.shape[0])),
                                       list(range(arr.shape[1]))))
    else:
        raise NotImplementedError('Only supporting arrays of dimension 1 and 2 as yet.')

Similar but not relevant code:
def remove_nans_1D(*args) -> tuple:
    """Remove nans in a set of 1D arrays.

    Removes indicies in all arrays if any array is nan at that index.
    All input arrays must have the same size.

    Parameters
    ----------
    args : 1D arrays

    Returns
    -------
    tuple
        Tuple of 1D arrays in same order as given, with nan indicies removed.
    """
    vals = np.isnan(args[0])
    for a in args:
        vals |= np.isnan(a)
    return tuple(np.array(a)[~vals] for a in args)

Similar but not relevant code:
def feature_subset(self, indices):
        """ Returns some subset of the features.
        
        Parameters
        ----------
        indices : :obj:`list` of :obj:`int`
            indices of the features in the list

        Returns
        -------
        :obj:`list` of :obj:`Feature`
        """
        if isinstance(indices, np.ndarray):
            indices = indices.tolist()
        if not isinstance(indices, list):
            raise ValueError('Can only index with lists')
        return [self.features_[i] for i in indices]
Query: python boxplot min max q1 median to number summary

Relevant code:
def compute_boxplot(self, series):
        """
        Compute boxplot for given pandas Series.
        """
        from matplotlib.cbook import boxplot_stats
        series = series[series.notnull()]
        if len(series.values) == 0:
            return {}
        elif not is_numeric_dtype(series):
            return self.non_numeric_stats(series)
        stats = boxplot_stats(list(series.values))[0]
        stats['count'] = len(series.values)
        stats['fliers'] = "|".join(map(str, stats['fliers']))
        return stats

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

Similar but not relevant code:
def _histplot_bins(column, bins=100):
    """Helper to get bins for histplot."""
    col_min = np.min(column)
    col_max = np.max(column)
    return range(col_min, col_max + 2, max((col_max - col_min) // bins, 1))

Similar but not relevant code:
def inverseHistogram(hist, bin_range):
    """sample data from given histogram and min, max values within range

    Returns:
        np.array: data that would create the same histogram as given
    """
    data = hist.astype(float) / np.min(hist[np.nonzero(hist)])
    new_data = np.empty(shape=np.sum(data, dtype=int))
    i = 0
    xvals = np.linspace(bin_range[0], bin_range[1], len(data))
    for d, x in zip(data, xvals):
        new_data[i:i + d] = x
        i += int(d)
    return new_data

Similar but not relevant code:
def median_high(data):
    """Return the high median of data.

    When the number of data points is odd, the middle value is returned.
    When it is even, the larger of the two middle values is returned.

    """
    data = sorted(data)
    n = len(data)
    if n == 0:
        raise StatisticsError("no median for empty data")
    return data[n // 2]

Similar but not relevant code:
def plot_kde(data, ax, title=None, color='r', fill_bt=True):
    """
    Plot a smoothed (by kernel density estimate) histogram.
    :type data: numpy array
    :param data: An array containing the data to be plotted

    :type ax: matplotlib.Axes
    :param ax: The Axes object to draw to

    :type title: str
    :param title: The plot title

    :type color: str
    :param color: The color of the histogram line and fill. Note that the fill
                  will be plotted with an alpha of 0.35.

    :type fill_bt: bool
    :param fill_bt: Specify whether to fill the area beneath the histogram line
    """
    if isinstance(data, list):
        data = np.asarray(data)
    e = kde.KDEUnivariate(data.astype(np.float))
    e.fit()
    ax.plot(e.support, e.density, color=color, alpha=0.9, linewidth=2.25)
    if fill_bt:
        ax.fill_between(e.support, e.density, alpha=.35, zorder=1,
                        antialiased=True, color=color)
    if title is not None:
        t = ax.set_title(title)
        t.set_y(1.05)
Query: select rows isin python notin

Relevant code:
def selectin(table, field, value, complement=False):
    """Select rows where the given field is a member of the given value."""

    return select(table, field, lambda v: v in value,
                  complement=complement)

Similar but not relevant code:
def selecttrue(table, field, complement=False):
    """Select rows where the given field evaluates `True`."""

    return select(table, field, lambda v: bool(v), complement=complement)

Similar but not relevant code:
def selectnotnone(table, field, complement=False):
    """Select rows where the given field is not `None`."""

    return select(table, field, lambda v: v is not None,
                  complement=complement)

Similar but not relevant code:
def selectnone(table, field, complement=False):
    """Select rows where the given field is `None`."""

    return select(table, field, lambda v: v is None, complement=complement)

Similar but not relevant code:
def select_if(df, fun):
    """Selects columns where fun(ction) is true
    Args:
        fun: a function that will be applied to columns
    """

    def _filter_f(col):
        try:
            return fun(df[col])
        except:
            return False

    cols = list(filter(_filter_f, df.columns))
    return df[cols]
Query: python boxplot not working

Relevant code:
def compute_boxplot(self, series):
        """
        Compute boxplot for given pandas Series.
        """
        from matplotlib.cbook import boxplot_stats
        series = series[series.notnull()]
        if len(series.values) == 0:
            return {}
        elif not is_numeric_dtype(series):
            return self.non_numeric_stats(series)
        stats = boxplot_stats(list(series.values))[0]
        stats['count'] = len(series.values)
        stats['fliers'] = "|".join(map(str, stats['fliers']))
        return stats

Similar but not relevant code:
def oplot(self, x, y, **kw):
        """generic plotting method, overplotting any existing plot """
        self.panel.oplot(x, y, **kw)

Similar but not relevant code:
def finish_plot():
    """Helper for plotting."""
    plt.legend()
    plt.grid(color='0.7')
    plt.xlabel('x')
    plt.ylabel('y')
    plt.show()

Similar but not relevant code:
def add_plot(x, y, xl, yl, fig, ax, LATEX=False, linestyle=None, **kwargs):
    """Add plots to an existing plot"""
    if LATEX:
        xl_data = xl[1]  # NOQA
        yl_data = yl[1]
    else:
        xl_data = xl[0]  # NOQA
        yl_data = yl[0]

    for idx in range(len(y)):
        ax.plot(x, y[idx], label=yl_data[idx], linestyle=linestyle)

    ax.legend(loc='upper right')
    ax.set_ylim(auto=True)

Similar but not relevant code:
def plot_target(target, ax):
    """Ajoute la target au plot"""
    ax.scatter(target[0], target[1], target[2], c="red", s=80)

Similar but not relevant code:
def activate_subplot(numPlot):
    """Make subplot *numPlot* active on the canvas.

    Use this if a simple ``subplot(numRows, numCols, numPlot)``
    overwrites the subplot instead of activating it.
    """
    # see http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg07156.html
    from pylab import gcf, axes
    numPlot -= 1  # index is 0-based, plots are 1-based
    return axes(gcf().get_axes()[numPlot])
Query: selenim uncheck box python

Relevant code:
def uncheck(self, locator=None, allow_label_click=None, **kwargs):
        """
        Find a check box and uncheck it. The check box can be found via name, id, or label text. ::

            page.uncheck("German")

        Args:
            locator (str, optional): Which check box to uncheck.
            allow_label_click (bool, optional): Attempt to click the label to toggle state if
                element is non-visible. Defaults to :data:`capybara.automatic_label_click`.
            **kwargs: Arbitrary keyword arguments for :class:`SelectorQuery`.
        """

        self._check_with_label(
            "checkbox", False, locator=locator, allow_label_click=allow_label_click, **kwargs)

Similar but not relevant code:
def alert(text='', title='', button=OK_TEXT, root=None, timeout=None):
    """Displays a simple message box with text and a single OK button. Returns the text of the button clicked on."""
    assert TKINTER_IMPORT_SUCCEEDED, 'Tkinter is required for pymsgbox'
    return _buttonbox(msg=text, title=title, choices=[str(button)], root=root, timeout=timeout)
Query: send python list as json django

Relevant code:
def upload_as_json(name, mylist):
    """
    Upload the IPList as json payload. 

    :param str name: name of IPList
    :param list: list of IPList entries
    :return: None
    """
    location = list(IPList.objects.filter(name))
    if location:
        iplist = location[0]
        return iplist.upload(json=mylist, as_type='json')

Similar but not relevant code:
def __as_list(value: List[JsonObjTypes]) -> List[JsonTypes]:
        """ Return a json array as a list

        :param value: array
        :return: array with JsonObj instances removed
        """
        return [e._as_dict if isinstance(e, JsonObj) else e for e in value]

Similar but not relevant code:
def from_json_list(cls, api_client, data):
        """Convert a list of JSON values to a list of models
        """
        return [cls.from_json(api_client, item) for item in data]

Similar but not relevant code:
def encode_list(dynamizer, value):
    """ Encode a list for the DynamoDB format """
    encoded_list = []
    dict(map(dynamizer.raw_encode, value))
    for v in value:
        encoded_type, encoded_value = dynamizer.raw_encode(v)
        encoded_list.append({
            encoded_type: encoded_value,
        })
    return 'L', encoded_list

Similar but not relevant code:
def _make_cmd_list(cmd_list):
    """
    Helper function to easily create the proper json formated string from a list of strs
    :param cmd_list: list of strings
    :return: str json formatted
    """
    cmd = ''
    for i in cmd_list:
        cmd = cmd + '"' + i + '",'
    cmd = cmd[:-1]
    return cmd
Query: python byte array slicing

Relevant code:
def getbyteslice(self, start, end):
        """Direct access to byte data."""
        c = self._rawarray[start:end]
        return c

Similar but not 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 to_bytes(data: Any) -> bytearray:
    """
    Convert anything to a ``bytearray``.
    
    See
    
    - http://stackoverflow.com/questions/7585435/best-way-to-convert-string-to-bytes-in-python-3
    - http://stackoverflow.com/questions/10459067/how-to-convert-my-bytearrayb-x9e-x18k-x9a-to-something-like-this-x9e-x1
    """  # noqa
    if isinstance(data, int):
        return bytearray([data])
    return bytearray(data, encoding='latin-1')

Similar but not relevant code:
def __init__(self, ba=None):
        """Constructor."""
        self.bytearray = ba or (bytearray(b'\0') * self.SIZEOF)

Similar but not relevant code:
def c_array(ctype, values):
    """Convert a python string to c array."""
    if isinstance(values, np.ndarray) and values.dtype.itemsize == ctypes.sizeof(ctype):
        return (ctype * len(values)).from_buffer_copy(values)
    return (ctype * len(values))(*values)
Query: serializer database model python model relation

Relevant code:
def get_serializable_data_for_fields(model):
    """
    Return a serialised version of the model's fields which exist as local database
    columns (i.e. excluding m2m and incoming foreign key relations)
    """
    pk_field = model._meta.pk
    # If model is a child via multitable inheritance, use parent's pk
    while pk_field.remote_field and pk_field.remote_field.parent_link:
        pk_field = pk_field.remote_field.model._meta.pk

    obj = {'pk': get_field_value(pk_field, model)}

    for field in model._meta.fields:
        if field.serialize:
            obj[field.name] = get_field_value(field, model)

    return obj

Similar but not relevant code:
def find_model_by_table_name(name):
    """Find a model reference by its table name"""

    for model in ModelBase._decl_class_registry.values():
        if hasattr(model, '__table__') and model.__table__.fullname == name:
            return model
    return None

Similar but not relevant code:
def get_table_names_from_metadata(metadata: MetaData) -> List[str]:
    """
    Returns all database table names found in an SQLAlchemy :class:`MetaData`
    object.
    """
    return [table.name for table in metadata.tables.values()]

Similar but not relevant code:
def serialize(self):
        """Serialize the query to a structure using the query DSL."""
        data = {'doc': self.doc}
        if isinstance(self.query, Query):
            data['query'] = self.query.serialize()
        return data
Query: python bytearray no init

Relevant code:
def __init__(self, ba=None):
        """Constructor."""
        self.bytearray = ba or (bytearray(b'\0') * self.SIZEOF)

Similar but not relevant code:
def getBuffer(x):
    """
    Copy @x into a (modifiable) ctypes byte array
    """
    b = bytes(x)
    return (c_ubyte * len(b)).from_buffer_copy(bytes(x))

Similar but not relevant code:
def cint8_array_to_numpy(cptr, length):
    """Convert a ctypes int pointer array to a numpy array."""
    if isinstance(cptr, ctypes.POINTER(ctypes.c_int8)):
        return np.fromiter(cptr, dtype=np.int8, count=length)
    else:
        raise RuntimeError('Expected int pointer')

Similar but not relevant code:
def decode(self, bytes, raw=False):
        """decode(bytearray, raw=False) -> value

        Decodes the given bytearray according to this PrimitiveType
        definition.

        NOTE: The parameter ``raw`` is present to adhere to the
        ``decode()`` inteface, but has no effect for PrimitiveType
        definitions.
        """
        return struct.unpack(self.format, buffer(bytes))[0]

Similar but not 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 to_bytes_or_none(value):
    """Converts C char arrays to bytes and C NULL values to None."""
    if value == ffi.NULL:
        return None
    elif isinstance(value, ffi.CData):
        return ffi.string(value)
    else:
        raise ValueError('Value must be char[] or NULL')
Query: set color for scatter plot in python

Relevant code:
def plot_target(target, ax):
    """Ajoute la target au plot"""
    ax.scatter(target[0], target[1], target[2], c="red", s=80)

Similar but not relevant code:
def scatter(self, *args, **kwargs):
        """Add a scatter plot."""
        cls = _make_class(ScatterVisual,
                          _default_marker=kwargs.pop('marker', None),
                          )
        return self._add_item(cls, *args, **kwargs)

Similar but not relevant code:
def add_plot(x, y, xl, yl, fig, ax, LATEX=False, linestyle=None, **kwargs):
    """Add plots to an existing plot"""
    if LATEX:
        xl_data = xl[1]  # NOQA
        yl_data = yl[1]
    else:
        xl_data = xl[0]  # NOQA
        yl_data = yl[0]

    for idx in range(len(y)):
        ax.plot(x, y[idx], label=yl_data[idx], linestyle=linestyle)

    ax.legend(loc='upper right')
    ax.set_ylim(auto=True)

Similar but not relevant code:
def colorbar(height, length, colormap):
    """Return the channels of a colorbar.
    """
    cbar = np.tile(np.arange(length) * 1.0 / (length - 1), (height, 1))
    cbar = (cbar * (colormap.values.max() - colormap.values.min())
            + colormap.values.min())

    return colormap.colorize(cbar)

Similar but not relevant code:
def oplot(self, x, y, **kw):
        """generic plotting method, overplotting any existing plot """
        self.panel.oplot(x, y, **kw)

Similar but not relevant code:
def sample_colormap(cmap_name, n_samples):
    """
    Sample a colormap from matplotlib
    """
    colors = []
    colormap = cm.cmap_d[cmap_name]
    for i in np.linspace(0, 1, n_samples):
        colors.append(colormap(i))

    return colors