benjamintli/cosqa-llm-filtered-hard-negatives huggingface dataset:
Query: example python bokeh customjs

Relevant code:
def get_code_language(self):
        """
        This is largely copied from bokeh.sphinxext.bokeh_plot.run
        """
        js_source = self.get_js_source()
        if self.options.get("include_html", False):
            resources = get_sphinx_resources(include_bokehjs_api=True)
            html_source = BJS_HTML.render(
                css_files=resources.css_files,
                js_files=resources.js_files,
                bjs_script=js_source)
            return [html_source, "html"]
        else:
            return [js_source, "javascript"]

Similar but not relevant code:
def import_js(path, lib_name, globals):
    """Imports from javascript source file.
      globals is your globals()"""
    with codecs.open(path_as_local(path), "r", "utf-8") as f:
        js = f.read()
    e = EvalJs()
    e.execute(js)
    var = e.context['var']
    globals[lib_name] = var.to_python()

Similar but not relevant code:
def typescript_compile(source):
    """Compiles the given ``source`` from TypeScript to ES5 using TypescriptServices.js"""
    with open(TS_COMPILER, 'r') as tsservices_js:
        return evaljs(
            (tsservices_js.read(),
             'ts.transpile(dukpy.tscode, {options});'.format(options=TSC_OPTIONS)),
            tscode=source
        )

Similar but not relevant code:
def generate_swagger_html(swagger_static_root, swagger_json_url):
    """
    given a root directory for the swagger statics, and
    a swagger json path, return back a swagger html designed
    to use those values.
    """
    tmpl = _get_template("swagger.html")
    return tmpl.render(
        swagger_root=swagger_static_root, swagger_json_url=swagger_json_url
    )

Similar but not relevant code:
def add_swagger(app, json_route, html_route):
    """
    a convenience method for both adding a swagger.json route,
    as well as adding a page showing the html documentation
    """
    app.router.add_route('GET', json_route, create_swagger_json_handler(app))
    add_swagger_api_route(app, html_route, json_route)

Similar but not relevant code:
def json_template(data, template_name, template_context):
    """Old style, use JSONTemplateResponse instead of this.
    """
    html = render_to_string(template_name, template_context)
    data = data or {}
    data['html'] = html
    return HttpResponse(json_encode(data), content_type='application/json')
Query: extract numbers from tuple python

Relevant code:
def version_triple(tag):
    """
    returns: a triple of integers from a version tag
    """
    groups = re.match(r'v?(\d+)\.(\d+)\.(\d+)', tag).groups()
    return tuple(int(n) for n in groups)

Similar but not relevant code:
def option2tuple(opt):
    """Return a tuple of option, taking possible presence of level into account"""

    if isinstance(opt[0], int):
        tup = opt[1], opt[2:]
    else:
        tup = opt[0], opt[1:]

    return tup

Similar but not relevant code:
def get_numbers(s):
    """Extracts all integers from a string an return them in a list"""

    result = map(int, re.findall(r'[0-9]+', unicode(s)))
    return result + [1] * (2 - len(result))
Query: python gnereating a md5 checksum for a file

Relevant code:
def get_file_md5sum(path):
    """Calculate the MD5 hash for a file."""
    with open(path, 'rb') as fh:
        h = str(hashlib.md5(fh.read()).hexdigest())
    return h

Similar but not relevant code:
def checksum(path):
    """Calculcate checksum for a file."""
    hasher = hashlib.sha1()
    with open(path, 'rb') as stream:
        buf = stream.read(BLOCKSIZE)
        while len(buf) > 0:
            hasher.update(buf)
            buf = stream.read(BLOCKSIZE)
    return hasher.hexdigest()
Query: python go to end of line python

Relevant code:
def erase_lines(n=1):
    """ Erases n lines from the screen and moves the cursor up to follow
    """
    for _ in range(n):
        print(codes.cursor["up"], end="")
        print(codes.cursor["eol"], end="")

Similar but not relevant code:
def readline(self):
        """Get the next line including the newline or '' on EOF."""
        self.lineno += 1
        if self._buffer:
            return self._buffer.pop()
        else:
            return self.input.readline()

Similar but not relevant code:
def advance_one_line(self):
    """Advances to next line."""

    current_line = self._current_token.line_number
    while current_line == self._current_token.line_number:
      self._current_token = ConfigParser.Token(*next(self._token_generator))

Similar but not relevant code:
def next(self):
        """Provides hook for Python2 iterator functionality."""
        _LOGGER.debug("reading next")
        if self.closed:
            _LOGGER.debug("stream is closed")
            raise StopIteration()

        line = self.readline()
        if not line:
            _LOGGER.debug("nothing more to read")
            raise StopIteration()

        return line

Similar but not relevant code:
def step_next_line(self):
        """Sets cursor as beginning of next line."""
        self._eol.append(self.position)
        self._lineno += 1
        self._col_offset = 0
Query: fastest way to make a list python

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 ensure_list(iterable: Iterable[A]) -> List[A]:
    """
    An Iterable may be a list or a generator.
    This ensures we get a list without making an unnecessary copy.
    """
    if isinstance(iterable, list):
        return iterable
    else:
        return list(iterable)

Similar but not relevant code:
def listify(a):
    """
    Convert a scalar ``a`` to a list and all iterables to list as well.

    Examples
    --------
    >>> listify(0)
    [0]

    >>> listify([1,2,3])
    [1, 2, 3]

    >>> listify('a')
    ['a']

    >>> listify(np.array([1,2,3]))
    [1, 2, 3]

    >>> listify('string')
    ['string']
    """
    if a is None:
        return []
    elif not isinstance(a, (tuple, list, np.ndarray)):
        return [a]
    return list(a)

Similar but not relevant code:
def chunk_list(l, n):
    """Return `n` size lists from a given list `l`"""
    return [l[i:i + n] for i in range(0, len(l), n)]

Similar but not relevant code:
def pool_args(function, sequence, kwargs):
    """Return a single iterator of n elements of lists of length 3, given a sequence of len n."""
    return zip(itertools.repeat(function), sequence, itertools.repeat(kwargs))

Similar but not relevant code:
async def list(source):
    """Generate a single list from an asynchronous sequence."""
    result = []
    async with streamcontext(source) as streamer:
        async for item in streamer:
            result.append(item)
    yield result
Query: python goodness of fit plot

Relevant code:
def plot(self):
        """Plot the empirical histogram versus best-fit distribution's PDF."""
        plt.plot(self.bin_edges, self.hist, self.bin_edges, self.best_pdf)

Similar but not relevant code:
def linear_variogram_model(m, d):
    """Linear model, m is [slope, nugget]"""
    slope = float(m[0])
    nugget = float(m[1])
    return slope * d + nugget

Similar but not relevant code:
def plot_epsilon_residuals(self):
        """Plots the epsilon residuals for the variogram fit."""
        fig = plt.figure()
        ax = fig.add_subplot(111)
        ax.scatter(range(self.epsilon.size), self.epsilon, c='k', marker='*')
        ax.axhline(y=0.0)
        plt.show()

Similar but not relevant code:
def _precision_recall(y_true, y_score, ax=None):
    """
    Plot precision-recall curve.

    Parameters
    ----------
    y_true : array-like, shape = [n_samples]
        Correct target values (ground truth).
    y_score : array-like, shape = [n_samples]
        Target scores (estimator predictions).
    ax : matplotlib Axes
        Axes object to draw the plot onto, otherwise uses current Axes

    Returns
    -------
    ax: matplotlib Axes
        Axes containing the plot

    """
    precision, recall, _ = precision_recall_curve(y_true, y_score)
    average_precision = average_precision_score(y_true, y_score)

    if ax is None:
        ax = plt.gca()

    ax.plot(recall, precision, label=('Precision-Recall curve: AUC={0:0.2f}'
                                      .format(average_precision)))
    _set_ax_settings(ax)
    return ax

Similar but not relevant code:
def _root_mean_square_error(y, y_pred, w):
    """Calculate the root mean square error."""
    return np.sqrt(np.average(((y_pred - y) ** 2), weights=w))

Similar but not relevant code:
def roc_auc(y_true, y_score):
    """
    Returns are under the ROC curve
    """
    notnull = ~np.isnan(y_true)
    fpr, tpr, thresholds = sklearn.metrics.roc_curve(y_true[notnull], y_score[notnull])
    return sklearn.metrics.auc(fpr, tpr)
Query: fetch a single column from an ndarray python\

Relevant code:
def get_column(self, X, column):
        """Return a column of the given matrix.

        Args:
            X: `numpy.ndarray` or `pandas.DataFrame`.
            column: `int` or `str`.

        Returns:
            np.ndarray: Selected column.
        """
        if isinstance(X, pd.DataFrame):
            return X[column].values

        return X[:, column]

Similar but not relevant code:
def _first_and_last_element(arr):
    """Returns first and last element of numpy array or sparse matrix."""
    if isinstance(arr, np.ndarray) or hasattr(arr, 'data'):
        # numpy array or sparse matrix with .data attribute
        data = arr.data if sparse.issparse(arr) else arr
        return data.flat[0], data.flat[-1]
    else:
        # Sparse matrices without .data attribute. Only dok_matrix at
        # the time of writing, in this case indexing is fast
        return arr[0, 0], arr[-1, -1]

Similar but not relevant code:
def extract(self):
        """
        Creates a copy of this tabarray in the form of a numpy ndarray.

        Useful if you want to do math on array elements, e.g. if you have a 
        subset of the columns that are all numerical, you can construct a 
        numerical matrix and do matrix operations.

        """
        return np.vstack([self[r] for r in self.dtype.names]).T.squeeze()

Similar but not relevant code:
def load_data(filename):
    """
    :rtype : numpy matrix
    """
    data = pandas.read_csv(filename, header=None, delimiter='\t', skiprows=9)
    return data.as_matrix()

Similar but not relevant code:
def get_X0(X):
    """ Return zero-th element of a one-element data container.
    """
    if pandas_available and isinstance(X, pd.DataFrame):
        assert len(X) == 1
        x = np.array(X.iloc[0])
    else:
        x, = X
    return x
Query: python grab image from url

Relevant code:
def url_to_image(url):
    """
    Fetch an image from url and convert it into a Pillow Image object
    """
    r = requests.get(url)
    image = StringIO(r.content)
    return image

Similar but not relevant code:
def get_image(self, source):
        """
        Given a file-like object, loads it up into a PIL.Image object
        and returns it.

        :param file source: A file-like object to load the image from.
        :rtype: PIL.Image
        :returns: The loaded image.
        """
        buf = StringIO(source.read())
        return Image.open(buf)

Similar but not relevant code:
def get_url_file_name(url):
    """Get the file name from an url
    
    Parameters
    ----------
    url : str

    Returns
    -------
    str
        The file name 
    """

    assert isinstance(url, (str, _oldstr))
    return urlparse.urlparse(url).path.split('/')[-1]

Similar but not relevant code:
def url_read_text(url, verbose=True):
    r"""
    Directly reads text data from url
    """
    data = url_read(url, verbose)
    text = data.decode('utf8')
    return text

Similar but not relevant code:
def from_file_url(url):
    """ Convert from file:// url to file path
    """
    if url.startswith('file://'):
        url = url[len('file://'):].replace('/', os.path.sep)

    return url

Similar but not relevant code:
def load_image(fname):
    """ read an image from file - PIL doesnt close nicely """
    with open(fname, "rb") as f:
        i = Image.open(fname)
        #i.load()
        return i
Query: python grabbing a file from the internet

Relevant code:
def wget(url):
    """
    Download the page into a string
    """
    import urllib.parse
    request = urllib.request.urlopen(url)
    filestring = request.read()
    return filestring

Similar but not relevant code:
def read(fname):
    """Quick way to read a file content."""
    content = None
    with open(os.path.join(here, fname)) as f:
        content = f.read()
    return content
Query: fill a column with null in python

Relevant code:
def fill_nulls(self, col: str):
        """
        Fill all null values with NaN values in a column.
        Null values are ``None`` or en empty string

        :param col: column name
        :type col: str

        :example: ``ds.fill_nulls("mycol")``
        """
        n = [None, ""]
        try:
            self.df[col] = self.df[col].replace(n, nan)
        except Exception as e:
            self.err(e)

Similar but not relevant code:
def count_nulls(self, field):
        """
        Count the number of null values in a column
        """
        try:
            n = self.df[field].isnull().sum()
        except KeyError:
            self.warning("Can not find column", field)
            return
        except Exception as e:
            self.err(e, "Can not count nulls")
            return
        self.ok("Found", n, "nulls in column", field)

Similar but not relevant code:
def is_not_null(df: DataFrame, col_name: str) -> bool:
    """
    Return ``True`` if the given DataFrame has a column of the given
    name (string), and there exists at least one non-NaN value in that
    column; return ``False`` otherwise.
    """
    if (
        isinstance(df, pd.DataFrame)
        and col_name in df.columns
        and df[col_name].notnull().any()
    ):
        return True
    else:
        return False

Similar but not relevant code:
def dropna(self):
        """Returns MultiIndex without any rows containing null values according to Baloo's convention.

        Returns
        -------
        MultiIndex
            MultiIndex with no null values.

        """
        not_nas = [v.notna() for v in self.values]
        and_filter = reduce(lambda x, y: x & y, not_nas)

        return self[and_filter]

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)
Query: python group by multiple keys itertools

Relevant code:
def group_by(iterable, key_func):
    """Wrap itertools.groupby to make life easier."""
    groups = (
        list(sub) for key, sub in groupby(iterable, key_func)
    )
    return zip(groups, groups)

Similar but not relevant code:
def _Members(self, group):
    """Unify members of a group and accounts with the group as primary gid."""
    group.members = set(group.members).union(self.gids.get(group.gid, []))
    return group

Similar but not relevant code:
def union(cls, *sets):
        """
        >>> from utool.util_set import *  # NOQA
        """
        import utool as ut
        lists_ = ut.flatten([list(s) for s in sets])
        return cls(lists_)

Similar but not relevant code:
def combinations(l):
    """Pure-Python implementation of itertools.combinations(l, 2)."""
    result = []
    for x in xrange(len(l) - 1):
        ls = l[x + 1:]
        for y in ls:
            result.append((l[x], y))
    return result

Similar but not relevant code:
def get_groups(self, username):
        """Get all groups of a user"""
        username = ldap.filter.escape_filter_chars(self._byte_p2(username))
        userdn = self._get_user(username, NO_ATTR)

        searchfilter = self.group_filter_tmpl % {
            'userdn': userdn,
            'username': username
        }

        groups = self._search(searchfilter, NO_ATTR, self.groupdn)
        ret = []
        for entry in groups:
            ret.append(self._uni(entry[0]))
        return ret

Similar but not relevant code:
def _iter_keys(key):
    """! Iterate over subkeys of a key
    """
    for i in range(winreg.QueryInfoKey(key)[0]):
        yield winreg.OpenKey(key, winreg.EnumKey(key, i))
Query: filling out a pdf with python

Relevant code:
def append_pdf(input_pdf: bytes, output_writer: PdfFileWriter):
    """
    Appends a PDF to a pyPDF writer. Legacy interface.
    """
    append_memory_pdf_to_writer(input_pdf=input_pdf,
                                writer=output_writer)

Similar but not relevant code:
def _put_header(self):
        """ Standard first line in a PDF. """
        self.session._out('%%PDF-%s' % self.pdf_version)
        if self.session.compression:
            self.session.buffer += '%' + chr(235) + chr(236) + chr(237) + chr(238) + "\n"

Similar but not relevant code:
def availability_pdf() -> bool:
    """
    Is a PDF-to-text tool available?
    """
    pdftotext = tools['pdftotext']
    if pdftotext:
        return True
    elif pdfminer:
        log.warning("PDF conversion: pdftotext missing; "
                    "using pdfminer (less efficient)")
        return True
    else:
        return False
Query: python gui change title window

Relevant code:
def title(msg):
    """Sets the title of the console window."""
    if sys.platform.startswith("win"):
        ctypes.windll.kernel32.SetConsoleTitleW(tounicode(msg))

Similar but not relevant code:
def inFocus(self):
        """Set GUI on-top flag"""
        previous_flags = self.window.flags()
        self.window.setFlags(previous_flags |
                             QtCore.Qt.WindowStaysOnTopHint)

Similar but not relevant code:
def getFileDialogTitle(msg, title):
    """
    Create nicely-formatted string based on arguments msg and title
    :param msg: the msg to be displayed
    :param title: the window title
    :return: None
    """
    if msg and title:
        return "%s - %s" % (title, msg)
    if msg and not title:
        return str(msg)
    if title and not msg:
        return str(title)
    return None

Similar but not relevant code:
def show_tip(self, tip=""):
        """Show tip"""
        QToolTip.showText(self.mapToGlobal(self.pos()), tip, self)

Similar but not relevant code:
def set_icon(self, bmp):
        """Sets main window icon to given wx.Bitmap"""

        _icon = wx.EmptyIcon()
        _icon.CopyFromBitmap(bmp)
        self.SetIcon(_icon)
Query: fillna python specific columns

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 add_blank_row(self, label):
        """
        Add a blank row with only an index value to self.df.
        This is done inplace.
        """
        col_labels = self.df.columns
        blank_item = pd.Series({}, index=col_labels, name=label)
        # use .loc to add in place (append won't do that)
        self.df.loc[blank_item.name] = blank_item
        return self.df
Query: python hamming distance script

Relevant code:
def hamming(s, t):
    """
    Calculate the Hamming distance between two strings. From Wikipedia article: Iterative with two matrix rows.

    :param s: string 1
    :type s: str
    :param t: string 2
    :type s: str
    :return: Hamming distance
    :rtype: float
    """
    if len(s) != len(t):
        raise ValueError('Hamming distance needs strings of equal length.')
    return sum(s_ != t_ for s_, t_ in zip(s, t))

Similar but not relevant code:
def get_distance(F, x):
    """Helper function for margin-based loss. Return a distance matrix given a matrix."""
    n = x.shape[0]

    square = F.sum(x ** 2.0, axis=1, keepdims=True)
    distance_square = square + square.transpose() - (2.0 * F.dot(x, x.transpose()))

    # Adding identity to make sqrt work.
    return F.sqrt(distance_square + F.array(np.identity(n)))

Similar but not relevant code:
def _hess_two_param(self, funct, p0, p1, dl=2e-5, rts=False, **kwargs):
        """
        Hessian of `func` wrt two parameters `p0` and `p1`. (see _graddoc)
        """
        vals0 = self.get_values(p0)
        vals1 = self.get_values(p1)

        f00 = funct(**kwargs)

        self.update(p0, vals0+dl)
        f10 = funct(**kwargs)

        self.update(p1, vals1+dl)
        f11 = funct(**kwargs)

        self.update(p0, vals0)
        f01 = funct(**kwargs)

        if rts:
            self.update(p0, vals0)
            self.update(p1, vals1)
        return (f11 - f10 - f01 + f00) / (dl**2)

Similar but not relevant code:
def get_distance_matrix(x):
    """Get distance matrix given a matrix. Used in testing."""
    square = nd.sum(x ** 2.0, axis=1, keepdims=True)
    distance_square = square + square.transpose() - (2.0 * nd.dot(x, x.transpose()))
    return nd.sqrt(distance_square)

Similar but not relevant code:
def signed_distance(mesh, points):
    """
    Find the signed distance from a mesh to a list of points.

    * Points OUTSIDE the mesh will have NEGATIVE distance
    * Points within tol.merge of the surface will have POSITIVE distance
    * Points INSIDE the mesh will have POSITIVE distance

    Parameters
    -----------
    mesh   : Trimesh object
    points : (n,3) float, list of points in space

    Returns
    ----------
    signed_distance : (n,3) float, signed distance from point to mesh
    """
    # make sure we have a numpy array
    points = np.asanyarray(points, dtype=np.float64)

    # find the closest point on the mesh to the queried points
    closest, distance, triangle_id = closest_point(mesh, points)

    # we only care about nonzero distances
    nonzero = distance > tol.merge

    if not nonzero.any():
        return distance

    inside = mesh.ray.contains_points(points[nonzero])
    sign = (inside.astype(int) * 2) - 1

    # apply sign to previously computed distance
    distance[nonzero] *= sign

    return distance
Query: python hash function crash

Relevant code:
def double_sha256(data):
    """A standard compound hash."""
    return bytes_as_revhex(hashlib.sha256(hashlib.sha256(data).digest()).digest())

Similar but not relevant code:
def __hash__(self):
        """Return ``hash(self)``."""
        return hash((type(self), self.domain, self.range, self.partition))

Similar but not relevant code:
def _my_hash(arg_list):
    # type: (List[Any]) -> int
    """Simple helper hash function"""
    res = 0
    for arg in arg_list:
        res = res * 31 + hash(arg)
    return res

Similar but not relevant code:
def _hash_the_file(hasher, filename):
    """Helper function for creating hash functions.

    See implementation of :func:`dtoolcore.filehasher.shasum`
    for more usage details.
    """
    BUF_SIZE = 65536
    with open(filename, 'rb') as f:
        buf = f.read(BUF_SIZE)
        while len(buf) > 0:
            hasher.update(buf)
            buf = f.read(BUF_SIZE)
    return hasher