Instruction:
Create a Python 3 function to
extract the set of configuration parameters from the properties attached to the schedule

Response:
def get_config_params(properties):
    '''Extract the set of configuration parameters from the properties attached
    to the schedule
    '''
    param = []
    wdef = ''
    for prop in properties.split('\n'):
        if prop.startswith('org.opencastproject.workflow.config'):
            key, val = prop.split('=', 1)
            key = key.split('.')[-1]
            param.append((key, val))
        elif prop.startswith('org.opencastproject.workflow.definition'):
            wdef = prop.split('=', 1)[-1]
    return wdef, param


Instruction:
Explain what the following Python 3 code does
def ingest(event):
    '''Ingest a finished recording to the Opencast server.
    '''
    # Update status
    set_service_status(Service.INGEST, ServiceStatus.BUSY)
    notify.notify('STATUS=Uploading')
    recording_state(event.uid, 'uploading')
    update_event_status(event, Status.UPLOADING)

    # Select ingest service
    # The ingest service to use is selected at random from the available
    # ingest services to ensure that not every capture agent uses the same
    # service at the same time
    service = config('service-ingest')
    service = service[randrange(0, len(service))]
    logger.info('Selecting ingest service to use: ' + service)

    # create mediapackage
    logger.info('Creating new mediapackage')
    mediapackage = http_request(service + '/createMediaPackage')

    # extract workflow_def, workflow_config and add DC catalogs
    prop = 'org.opencastproject.capture.agent.properties'
    dcns = 'http://www.opencastproject.org/xsd/1.0/dublincore/'
    for attachment in event.get_data().get('attach'):
        data = attachment.get('data')
        if attachment.get('x-apple-filename') == prop:
            workflow_def, workflow_config = get_config_params(data)

        # Check for dublincore catalogs
        elif attachment.get('fmttype') == 'application/xml' and dcns in data:
            name = attachment.get('x-apple-filename', '').rsplit('.', 1)[0]
            logger.info('Adding %s DC catalog' % name)
            fields = [('mediaPackage', mediapackage),
                      ('flavor', 'dublincore/%s' % name),
                      ('dublinCore', data.encode('utf-8'))]
            mediapackage = http_request(service + '/addDCCatalog', fields)

    # add track
    for (flavor, track) in event.get_tracks():
        logger.info('Adding track ({0} -> {1})'.format(flavor, track))
        track = track.encode('ascii', 'ignore')
        fields = [('mediaPackage', mediapackage), ('flavor', flavor),
                  ('BODY1', (pycurl.FORM_FILE, track))]
        mediapackage = http_request(service + '/addTrack', fields)

    # ingest
    logger.info('Ingest recording')
    fields = [('mediaPackage', mediapackage)]
    if workflow_def:
        fields.append(('workflowDefinitionId', workflow_def))
    if event.uid:
        fields.append(('workflowInstanceId',
                       event.uid.encode('ascii', 'ignore')))
    fields += workflow_config
    mediapackage = http_request(service + '/ingest', fields)

    # Update status
    recording_state(event.uid, 'upload_finished')
    update_event_status(event, Status.FINISHED_UPLOADING)
    notify.notify('STATUS=Running')
    set_service_status_immediate(Service.INGEST, ServiceStatus.IDLE)

    logger.info('Finished ingest')

Response: Ingest a finished recording to the Opencast server.


Instruction:
Explain what the following Python 3 code does
def safe_start_ingest(event):
    '''Start a capture process but make sure to catch any errors during this
    process, log them but otherwise ignore them.
    '''
    try:
        ingest(event)
    except Exception:
        logger.error('Something went wrong during the upload')
        logger.error(traceback.format_exc())
        # Update state if something went wrong
        recording_state(event.uid, 'upload_error')
        update_event_status(event, Status.FAILED_UPLOADING)
        set_service_status_immediate(Service.INGEST, ServiceStatus.IDLE)

Response:
Start a capture process but make sure to catch any errors during this
    log them but otherwise ignore them.


Instruction:
Implement a function in Python 3 to
intercept sigterm and terminate all processes.

Response:
def sigterm_handler(signum, frame):
    '''Intercept sigterm and terminate all processes.
    '''
    if captureproc and captureproc.poll() is None:
        captureproc.terminate()
    terminate(True)
    sys.exit(0)


Instruction:
Write a Python 3 function for
starting the capture process creating all necessary files and directories as well as ingesting the captured files if no backup mode is configured.

Response:
def start_capture(upcoming_event):
    '''Start the capture process, creating all necessary files and directories
    as well as ingesting the captured files if no backup mode is configured.
    '''
    logger.info('Start recording')

    # First move event to recording_event table
    db = get_session()
    event = db.query(RecordedEvent)\
              .filter(RecordedEvent.uid == upcoming_event.uid)\
              .filter(RecordedEvent.start == upcoming_event.start)\
              .first()
    if not event:
        event = RecordedEvent(upcoming_event)
        db.add(event)
        db.commit()

    try_mkdir(config()['capture']['directory'])
    os.mkdir(event.directory())

    # Set state
    update_event_status(event, Status.RECORDING)
    recording_state(event.uid, 'capturing')
    set_service_status_immediate(Service.CAPTURE, ServiceStatus.BUSY)

    # Recording
    tracks = recording_command(event)
    event.set_tracks(tracks)
    db.commit()

    # Set status
    update_event_status(event, Status.FINISHED_RECORDING)
    recording_state(event.uid, 'capture_finished')
    set_service_status_immediate(Service.CAPTURE, ServiceStatus.IDLE)

    logger.info('Finished recording')


Instruction:
Can you write a function in Python 3 where it
starts a capture process but make sure to catch any errors during this log them but otherwise ignore them.

Response:
def safe_start_capture(event):
    '''Start a capture process but make sure to catch any errors during this
    process, log them but otherwise ignore them.
    '''
    try:
        start_capture(event)
    except Exception:
        logger.error('Recording failed')
        logger.error(traceback.format_exc())
        # Update state
        recording_state(event.uid, 'capture_error')
        update_event_status(event, Status.FAILED_RECORDING)
        set_service_status_immediate(Service.CAPTURE, ServiceStatus.IDLE)


Instruction:
Can you generate a brief explanation for the following Python 3 code
def recording_command(event):
    '''Run the actual command to record the a/v material.
    '''
    conf = config('capture')
    # Prepare command line
    cmd = conf['command']
    cmd = cmd.replace('{{time}}', str(event.remaining_duration(timestamp())))
    cmd = cmd.replace('{{dir}}', event.directory())
    cmd = cmd.replace('{{name}}', event.name())
    cmd = cmd.replace('{{previewdir}}', conf['preview_dir'])

    # Signal configuration
    sigterm_time = conf['sigterm_time']
    sigkill_time = conf['sigkill_time']
    sigcustom_time = conf['sigcustom_time']
    sigcustom_time = 0 if sigcustom_time < 0 else event.end + sigcustom_time
    sigterm_time = 0 if sigterm_time < 0 else event.end + sigterm_time
    sigkill_time = 0 if sigkill_time < 0 else event.end + sigkill_time

    # Launch capture command
    logger.info(cmd)
    args = shlex.split(cmd)
    DEVNULL = getattr(subprocess, 'DEVNULL', os.open(os.devnull, os.O_RDWR))
    captureproc = subprocess.Popen(args, stdin=DEVNULL)
    hasattr(subprocess, 'DEVNULL') or os.close(DEVNULL)

    # Set systemd status
    notify.notify('STATUS=Capturing')

    # Check process
    while captureproc.poll() is None:
        notify.notify('WATCHDOG=1')
        if sigcustom_time and timestamp() > sigcustom_time:
            logger.info("Sending custom signal to capture process")
            captureproc.send_signal(conf['sigcustom'])
            sigcustom_time = 0  # send only once
        if sigterm_time and timestamp() > sigterm_time:
            logger.info("Terminating capture process")
            captureproc.terminate()
            sigterm_time = 0  # send only once
        elif sigkill_time and timestamp() > sigkill_time:
            logger.warning("Killing capture process")
            captureproc.kill()
            sigkill_time = 0  # send only once
        time.sleep(0.1)

    # Remove preview files:
    for preview in conf['preview']:
        try:
            os.remove(preview.replace('{{previewdir}}', conf['preview_dir']))
        except OSError:
            logger.warning('Could not remove preview files')
            logger.warning(traceback.format_exc())

    # Check process for errors
    exitcode = config()['capture']['exit_code']
    if captureproc.poll() > 0 and captureproc.returncode != exitcode:
        raise RuntimeError('Recording failed (%i)' % captureproc.returncode)

    # Reset systemd status
    notify.notify('STATUS=Waiting')

    # Return [(flavor,path),…]
    files = (f.replace('{{dir}}', event.directory()) for f in conf['files'])
    files = (f.replace('{{name}}', event.name()) for f in files)
    return list(zip(conf['flavors'], files))

Response: Run the actual command to record the a / v material.


Instruction:
Can you tell what is the following Python 3 function doing
def control_loop():
    '''Main loop of the capture agent, retrieving and checking the schedule as
    well as starting the capture process if necessry.
    '''
    set_service_status(Service.CAPTURE, ServiceStatus.IDLE)
    notify.notify('READY=1')
    notify.notify('STATUS=Waiting')
    while not terminate():
        notify.notify('WATCHDOG=1')
        # Get next recording
        event = get_session().query(UpcomingEvent)\
                             .filter(UpcomingEvent.start <= timestamp())\
                             .filter(UpcomingEvent.end > timestamp())\
                             .first()
        if event:
            safe_start_capture(event)
        time.sleep(1.0)
    logger.info('Shutting down capture service')
    set_service_status(Service.CAPTURE, ServiceStatus.STOPPED)

Response: Main loop of the capture agent.


Instruction:
Explain what the following Python 3 code does
def render_to_fragment(self, request, **kwargs):
        fragment = Fragment(TEST_HTML)
        fragment.add_javascript(TEST_JS)
        fragment.add_css(TEST_CSS)
        return fragment

Response: Returns a simple fragment that can be used to render the page.


Instruction:
Explain what the following Python 3 code does
def resources(self):
        seen = set()
        # seen.add always returns None, so 'not seen.add(x)' is always True,
        # but will only be called if the value is not already in seen (because
        # 'and' short-circuits)
        return [x for x in self._resources if x not in seen and not seen.add(x)]

Response: Returns list of unique FragmentResource s by order of first appearance.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def to_dict(self):
        return {
            'content': self.content,
            'resources': [r._asdict() for r in self.resources],  # pylint: disable=W0212
            'js_init_fn': self.js_init_fn,
            'js_init_version': self.js_init_version,
            'json_init_args': self.json_init_args
        }

Response: Returns the fragment in a dictionary representation.


Instruction:
Make a summary of the following Python 3 code
def from_dict(cls, pods):
        frag = cls()
        frag.content = pods['content']
        frag._resources = [FragmentResource(**d) for d in pods['resources']]  # pylint: disable=protected-access
        frag.js_init_fn = pods['js_init_fn']
        frag.js_init_version = pods['js_init_version']
        frag.json_init_args = pods['json_init_args']
        return frag

Response: Returns a new Fragment from a dictionary representation.


Instruction:
Can you generate the documentation for the following Python 3 function
def add_content(self, content):
        assert isinstance(content, six.text_type)
        self.content += content

Response: Add content to the content of the current tag.


Instruction:
Write a Python 3 function for
adding a resource needed by this Fragment.

Response:
def add_resource(self, text, mimetype, placement=None):
        """
        Add a resource needed by this Fragment.

        Other helpers, such as :func:`add_css` or :func:`add_javascript` are
        more convenient for those common types of resource.

        `text`: the actual text of this resource, as a unicode string.

        `mimetype`: the MIME type of the resource.

        `placement`: where on the page the resource should be placed:

            None: let the Fragment choose based on the MIME type.

            "head": put this resource in the ``<head>`` of the page.

            "foot": put this resource at the end of the ``<body>`` of the
            page.

        """
        if not placement:
            placement = self._default_placement(mimetype)
        res = FragmentResource('text', text, mimetype, placement)
        self._resources.append(res)


Instruction:
Write a Python 3 function that can
add a resource by URL needed by this Fragment.

Response:
def add_resource_url(self, url, mimetype, placement=None):
        """
        Add a resource by URL needed by this Fragment.

        Other helpers, such as :func:`add_css_url` or
        :func:`add_javascript_url` are more convenent for those common types of
        resource.

        `url`: the URL to the resource.

        Other parameters are as defined for :func:`add_resource`.
        """
        if not placement:
            placement = self._default_placement(mimetype)
        self._resources.append(FragmentResource('url', url, mimetype, placement))


Instruction:
Write a Python 3 function for
registering a Javascript function to initialize the Javascript resources.

Response:
def initialize_js(self, js_func, json_args=None):
        """
        Register a Javascript function to initialize the Javascript resources.

        `js_func` is the name of a Javascript function defined by one of the
        Javascript resources.  As part of setting up the browser's runtime
        environment, the function will be invoked, passing a runtime object
        and a DOM element.
        """
        self.js_init_fn = js_func
        self.js_init_version = JS_API_VERSION
        if json_args:
            self.json_init_args = json_args


Instruction:
Write a Python 3 function for
getting some resource HTML for this Fragment. placement is head or foot.

Response:
def resources_to_html(self, placement):
        """
        Get some resource HTML for this Fragment.

        `placement` is "head" or "foot".

        Returns a unicode string, the HTML for the head or foot of the page.
        """
        # - non url js could be wrapped in an anonymous function
        # - non url css could be rewritten to match the wrapper tag

        return '\n'.join(
            self.resource_to_html(resource)
            for resource in self.resources
            if resource.placement == placement
        )


Instruction:
Can you tell what is the following Python 3 function doing
def resource_to_html(resource):
        if resource.mimetype == "text/css":
            if resource.kind == "text":
                return u"<style type='text/css'>\n%s\n</style>" % resource.data
            elif resource.kind == "url":
                return u"<link rel='stylesheet' href='%s' type='text/css'>" % resource.data
            else:
                raise Exception("Unrecognized resource kind %r" % resource.kind)

        elif resource.mimetype == "application/javascript":
            if resource.kind == "text":
                return u"<script>\n%s\n</script>" % resource.data
            elif resource.kind == "url":
                return u"<script src='%s' type='application/javascript'></script>" % resource.data
            else:
                raise Exception("Unrecognized resource kind %r" % resource.kind)

        elif resource.mimetype == "text/html":
            assert resource.kind == "text"
            return resource.data

        else:
            raise Exception("Unrecognized mimetype %r" % resource.mimetype)

Response: Converts a resource into an html tag.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def get(self, request, *args, **kwargs):
        fragment = self.render_to_fragment(request, **kwargs)
        response_format = request.GET.get('format') or request.POST.get('format') or 'html'
        if response_format == 'json' or WEB_FRAGMENT_RESPONSE_TYPE in request.META.get('HTTP_ACCEPT', 'text/html'):
            return JsonResponse(fragment.to_dict())
        else:
            return self.render_standalone_response(request, fragment, **kwargs)

Response: Render a fragment to HTML or return JSON describing it based on the request.


Instruction:
Here you have a function in Python 3, explain what it does
def render_standalone_response(self, request, fragment, **kwargs):  # pylint: disable=unused-argument
        if fragment is None:
            return HttpResponse(status=204)

        html = self.render_to_standalone_html(request, fragment, **kwargs)
        return HttpResponse(html)

Response: Renders a standalone page as a response for the specified fragment.


Instruction:
Write a Python 3 function that can
render the specified fragment to HTML for a standalone page.

Response:
def render_to_standalone_html(self, request, fragment, **kwargs):  # pylint: disable=unused-argument
        """
        Render the specified fragment to HTML for a standalone page.
        """
        template = get_template(STANDALONE_TEMPLATE_NAME)
        context = {
            'head_html': fragment.head_html(),
            'body_html': fragment.body_html(),
            'foot_html': fragment.foot_html(),
        }
        return template.render(context)


Instruction:
How would you explain what the following Python 3 function does
def calc(pvalues, lamb):

    m = len(pvalues)
    pi0 = (pvalues > lamb).sum() / ((1 - lamb)*m)

    pFDR = np.ones(m)
    print("pFDR    y        Pr     fastPow")
    for i in range(m):
        y = pvalues[i]
        Pr = max(1, m - i) / float(m)
        pFDR[i] = (pi0 * y) / (Pr * (1 - math.pow(1-y, m)))
        print(i, pFDR[i], y, Pr, 1.0 - math.pow(1-y, m))

    num_null = pi0*m
    num_alt = m - num_null
    num_negs = np.array(range(m))
    num_pos = m - num_negs
    pp = num_pos / float(m)

    qvalues = np.ones(m)
    qvalues[0] = pFDR[0]
    for i in range(m-1):
        qvalues[i+1] = min(qvalues[i], pFDR[i+1])

    sens = ((1.0 - qvalues) * num_pos) / num_alt
    sens[sens > 1.0] = 1.0

    df = pd.DataFrame(dict(
        pvalue=pvalues,
        qvalue=qvalues,
        FDR=pFDR,
        percentile_positive=pp,
        sens=sens
    ))

    df["svalue"] = df.sens[::-1].cummax()[::-1]

    return df, num_null, m

Response: calculate the fastPow of a set of pvalues


Instruction:
Can you generate the documentation for the following Python 3 function
def unwrap_self_for_multiprocessing(arg):
    (inst, method_name, args) = arg
    return getattr(inst, method_name)(*args)

Response: Unwrap the object with the given method.


Instruction:
Write a Python 3 script for
converting list or flattens n - dim array to 1 - dim array if possible

Response:
def to_one_dim_array(values, as_type=None):
    """ Converts list or flattens n-dim array to 1-dim array if possible """

    if isinstance(values, (list, tuple)):
        values = np.array(values, dtype=np.float32)
    elif isinstance(values, pd.Series):
        values = values.values
    values = values.flatten()
    assert values.ndim == 1, "values has wrong dimension"
    if as_type is not None:
        return values.astype(as_type)
    return values


Instruction:
How would you explain what the following Python 3 function does
def lookup_values_from_error_table(scores, err_df):
    ix = find_nearest_matches(np.float32(err_df.cutoff.values), np.float32(scores))
    return err_df.pvalue.iloc[ix].values, err_df.svalue.iloc[ix].values, err_df.pep.iloc[ix].values, err_df.qvalue.iloc[ix].values

Response: Find matching p - value s - value pep - value and q - value for each score in scores


Instruction:
How would you explain what the following Python 3 function does
def posterior_chromatogram_hypotheses_fast(experiment, prior_chrom_null):

    tg_ids = experiment.df.tg_num_id.values
    pp_values = 1-experiment.df["pep"].values

    current_tg_id = tg_ids[0]
    scores = []
    final_result = []
    final_result_h0 = []
    for i in range(tg_ids.shape[0]):

        id_ = tg_ids[i]
        if id_ != current_tg_id:

            # Actual computation for a single transition group (chromatogram)
            prior_pg_true = (1.0 - prior_chrom_null) / len(scores)
            rr = single_chromatogram_hypothesis_fast(
                np.array(scores), prior_chrom_null, prior_pg_true)
            final_result.extend(rr[1:])
            final_result_h0.extend(rr[0] for i in range(len(scores)))

            # Reset for next cycle
            scores = []
            current_tg_id = id_

        scores.append(1.0 - pp_values[i])

    # Last cycle
    prior_pg_true = (1.0 - prior_chrom_null) / len(scores)
    rr = single_chromatogram_hypothesis_fast(np.array(scores), prior_chrom_null, prior_pg_true)
    final_result.extend(rr[1:])
    final_result_h0.extend([rr[0]] * len(scores))

    return final_result, final_result_h0

Response: Compute the posterior probabilities for each chromatogram and each peak in the cluster.


Instruction:
Can you implement a function in Python 3 that
computes empirical values identically to bioconductor or qvalue empPvals

Response:
def pemp(stat, stat0):
    """ Computes empirical values identically to bioconductor/qvalue empPvals """

    assert len(stat0) > 0
    assert len(stat) > 0

    stat = np.array(stat)
    stat0 = np.array(stat0)

    m = len(stat)
    m0 = len(stat0)

    statc = np.concatenate((stat, stat0))
    v = np.array([True] * m + [False] * m0)
    perm = np.argsort(-statc, kind="mergesort")  # reversed sort, mergesort is stable
    v = v[perm]

    u = np.where(v)[0]
    p = (u - np.arange(m)) / float(m0)

    # ranks can be fractional, we round down to the next integer, ranking returns values starting
    # with 1, not 0:
    ranks = np.floor(scipy.stats.rankdata(-stat)).astype(int) - 1
    p = p[ranks]
    p[p <= 1.0 / m0] = 1.0 / m0

    return p


Instruction:
Implement a function in Python 3 to
estimate the pi0 according to bioconductor or qvalue reference implementation.

Response:
def pi0est(p_values, lambda_ = np.arange(0.05,1.0,0.05), pi0_method = "smoother", smooth_df = 3, smooth_log_pi0 = False):
    """ Estimate pi0 according to bioconductor/qvalue """

    # Compare to bioconductor/qvalue reference implementation
    # import rpy2
    # import rpy2.robjects as robjects
    # from rpy2.robjects import pandas2ri
    # pandas2ri.activate()

    # smoothspline=robjects.r('smooth.spline')
    # predict=robjects.r('predict')

    p = np.array(p_values)

    rm_na = np.isfinite(p)
    p = p[rm_na]
    m = len(p)
    ll = 1
    if isinstance(lambda_, np.ndarray ):
        ll = len(lambda_)
        lambda_ = np.sort(lambda_)

    if (min(p) < 0 or max(p) > 1):
        raise click.ClickException("p-values not in valid range [0,1].")
    elif (ll > 1 and ll < 4):
        raise click.ClickException("If lambda_ is not predefined (one value), at least four data points are required.")
    elif (np.min(lambda_) < 0 or np.max(lambda_) >= 1):
        raise click.ClickException("Lambda must be within [0,1)")

    if (ll == 1):
        pi0 = np.mean(p >= lambda_)/(1 - lambda_)
        pi0_lambda = pi0
        pi0 = np.minimum(pi0, 1)
        pi0Smooth = False
    else:
        pi0 = []
        for l in lambda_:
            pi0.append(np.mean(p >= l)/(1 - l))
        pi0_lambda = pi0

        if (pi0_method == "smoother"):
            if smooth_log_pi0:
                pi0 = np.log(pi0)
                spi0 = sp.interpolate.UnivariateSpline(lambda_, pi0, k=smooth_df)
                pi0Smooth = np.exp(spi0(lambda_))
                # spi0 = smoothspline(lambda_, pi0, df = smooth_df) # R reference function
                # pi0Smooth = np.exp(predict(spi0, x = lambda_).rx2('y')) # R reference function
            else:
                spi0 = sp.interpolate.UnivariateSpline(lambda_, pi0, k=smooth_df)
                pi0Smooth = spi0(lambda_)
                # spi0 = smoothspline(lambda_, pi0, df = smooth_df) # R reference function
                # pi0Smooth = predict(spi0, x = lambda_).rx2('y')  # R reference function
            pi0 = np.minimum(pi0Smooth[ll-1],1)
        elif (pi0_method == "bootstrap"):
            minpi0 = np.percentile(pi0,0.1)
            W = []
            for l in lambda_:
                W.append(np.sum(p >= l))
            mse = (np.array(W) / (np.power(m,2) * np.power((1 - lambda_),2))) * (1 - np.array(W) / m) + np.power((pi0 - minpi0),2)
            pi0 = np.minimum(pi0[np.argmin(mse)],1)
            pi0Smooth = False
        else:
            raise click.ClickException("pi0_method must be one of 'smoother' or 'bootstrap'.")
    if (pi0<=0):
        raise click.ClickException("The estimated pi0 <= 0. Check that you have valid p-values or use a different range of lambda.")

    return {'pi0': pi0, 'pi0_lambda': pi0_lambda, 'lambda_': lambda_, 'pi0_smooth': pi0Smooth}


Instruction:
Can you write a function in Python 3 where it
estimates local FDR for a given set of p - values.

Response:
def lfdr(p_values, pi0, trunc = True, monotone = True, transf = "probit", adj = 1.5, eps = np.power(10.0,-8)):
    """ Estimate local FDR / posterior error probability from p-values according to bioconductor/qvalue """
    p = np.array(p_values)

    # Compare to bioconductor/qvalue reference implementation
    # import rpy2
    # import rpy2.robjects as robjects
    # from rpy2.robjects import pandas2ri
    # pandas2ri.activate()

    # density=robjects.r('density')
    # smoothspline=robjects.r('smooth.spline')
    # predict=robjects.r('predict')

    # Check inputs
    lfdr_out = p
    rm_na = np.isfinite(p)
    p = p[rm_na]

    if (min(p) < 0 or max(p) > 1):
        raise click.ClickException("p-values not in valid range [0,1].")
    elif (pi0 < 0 or pi0 > 1):
        raise click.ClickException("pi0 not in valid range [0,1].")

    # Local FDR method for both probit and logit transformations
    if (transf == "probit"):
        p = np.maximum(p, eps)
        p = np.minimum(p, 1-eps)
        x = scipy.stats.norm.ppf(p, loc=0, scale=1)

        # R-like implementation
        bw = bw_nrd0(x)
        myd = KDEUnivariate(x)
        myd.fit(bw=adj*bw, gridsize = 512)
        splinefit = sp.interpolate.splrep(myd.support, myd.density)
        y = sp.interpolate.splev(x, splinefit)
        # myd = density(x, adjust = 1.5) # R reference function
        # mys = smoothspline(x = myd.rx2('x'), y = myd.rx2('y')) # R reference function
        # y = predict(mys, x).rx2('y') # R reference function

        lfdr = pi0 * scipy.stats.norm.pdf(x) / y
    elif (transf == "logit"):
        x = np.log((p + eps) / (1 - p + eps))

        # R-like implementation
        bw = bw_nrd0(x)
        myd = KDEUnivariate(x)
        myd.fit(bw=adj*bw, gridsize = 512)

        splinefit = sp.interpolate.splrep(myd.support, myd.density)
        y = sp.interpolate.splev(x, splinefit)
        # myd = density(x, adjust = 1.5) # R reference function
        # mys = smoothspline(x = myd.rx2('x'), y = myd.rx2('y')) # R reference function
        # y = predict(mys, x).rx2('y') # R reference function

        dx = np.exp(x) / np.power((1 + np.exp(x)),2)
        lfdr = (pi0 * dx) / y
    else:
        raise click.ClickException("Invalid local FDR method.")

    if (trunc):
        lfdr[lfdr > 1] = 1
    if (monotone):
        lfdr = lfdr[p.ravel().argsort()]
        for i in range(1,len(x)):
            if (lfdr[i] < lfdr[i - 1]):
                lfdr[i] = lfdr[i - 1]
        lfdr = lfdr[scipy.stats.rankdata(p,"min")-1]

    lfdr_out[rm_na] = lfdr
    return lfdr_out


Instruction:
Can you write a function in Python 3 where it
creates artificial cutoff sample points from given range of cutoff values in df

Response:
def final_err_table(df, num_cut_offs=51):
    """ Create artificial cutoff sample points from given range of cutoff
    values in df, number of sample points is 'num_cut_offs' """

    cutoffs = df.cutoff.values
    min_ = min(cutoffs)
    max_ = max(cutoffs)
    # extend max_ and min_ by 5 % of full range
    margin = (max_ - min_) * 0.05
    sampled_cutoffs = np.linspace(min_ - margin, max_ + margin, num_cut_offs, dtype=np.float32)

    # find best matching row index for each sampled cut off:
    ix = find_nearest_matches(np.float32(df.cutoff.values), sampled_cutoffs)

    # create sub dataframe:
    sampled_df = df.iloc[ix].copy()
    sampled_df.cutoff = sampled_cutoffs
    # remove 'old' index from input df:
    sampled_df.reset_index(inplace=True, drop=True)

    return sampled_df


Instruction:
Can you generate the documentation for the following Python 3 function
def summary_err_table(df, qvalues=[0, 0.01, 0.02, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5]):

    qvalues = to_one_dim_array(qvalues)
    # find best matching fows in df for given qvalues:
    ix = find_nearest_matches(np.float32(df.qvalue.values), qvalues)
    # extract sub table
    df_sub = df.iloc[ix].copy()
    # remove duplicate hits, mark them with None / NAN:
    for i_sub, (i0, i1) in enumerate(zip(ix, ix[1:])):
        if i1 == i0:
            df_sub.iloc[i_sub + 1, :] = None
    # attach q values column
    df_sub.qvalue = qvalues
    # remove old index from original df:
    df_sub.reset_index(inplace=True, drop=True)
    return df_sub[['qvalue','pvalue','svalue','pep','fdr','fnr','fpr','tp','tn','fp','fn','cutoff']]

Response: Summary error table for some typical q - values


Instruction:
Make a summary of the following Python 3 code
def error_statistics(target_scores, decoy_scores, parametric, pfdr, pi0_lambda, pi0_method = "smoother", pi0_smooth_df = 3, pi0_smooth_log_pi0 = False, compute_lfdr = False, lfdr_trunc = True, lfdr_monotone = True, lfdr_transf = "probit", lfdr_adj = 1.5, lfdr_eps = np.power(10.0,-8)):

    target_scores = to_one_dim_array(target_scores)
    target_scores = np.sort(target_scores[~np.isnan(target_scores)])

    decoy_scores = to_one_dim_array(decoy_scores)
    decoy_scores = np.sort(decoy_scores[~np.isnan(decoy_scores)])

    # compute p-values using decoy scores
    if parametric:
        # parametric
        target_pvalues = pnorm(target_scores, decoy_scores)
    else:
        # non-parametric
        target_pvalues = pemp(target_scores, decoy_scores)

    # estimate pi0
    pi0 = pi0est(target_pvalues, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0)

    # compute q-value
    target_qvalues = qvalue(target_pvalues, pi0['pi0'], pfdr)

    # compute other metrics
    metrics = stat_metrics(target_pvalues, pi0['pi0'], pfdr)

    # generate main statistics table
    error_stat = pd.DataFrame({'cutoff': target_scores, 'pvalue': target_pvalues, 'qvalue': target_qvalues, 'svalue': metrics['svalue'], 'tp': metrics['tp'], 'fp': metrics['fp'], 'tn': metrics['tn'], 'fn': metrics['fn'], 'fpr': metrics['fpr'], 'fdr': metrics['fdr'], 'fnr': metrics['fnr']})

    # compute lfdr / PEP
    if compute_lfdr:
        error_stat['pep'] = lfdr(target_pvalues, pi0['pi0'], lfdr_trunc, lfdr_monotone, lfdr_transf, lfdr_adj, lfdr_eps)

    return error_stat, pi0

Response: Generates a dataframe of error statistics for a set of target scores and decoy scores.


Instruction:
Explain what the following Python 3 code does
def find_cutoff(tt_scores, td_scores, cutoff_fdr, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0):

    error_stat, pi0 = error_statistics(tt_scores, td_scores, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, False)
    if not len(error_stat):
        raise click.ClickException("Too little data for calculating error statistcs.")
    i0 = (error_stat.qvalue - cutoff_fdr).abs().idxmin()
    cutoff = error_stat.iloc[i0]["cutoff"]
    return cutoff

Response: Find the cutoff target score for specified false discovery rate fdr.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def score(infile, outfile, classifier, xgb_autotune, apply_weights, xeval_fraction, xeval_num_iter, ss_initial_fdr, ss_iteration_fdr, ss_num_iter, ss_main_score, group_id, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps, level, ipf_max_peakgroup_rank, ipf_max_peakgroup_pep, ipf_max_transition_isotope_overlap, ipf_min_transition_sn, tric_chromprob, threads, test):

    if outfile is None:
        outfile = infile
    else:
        outfile = outfile

    # Prepare XGBoost-specific parameters
    xgb_hyperparams = {'autotune': xgb_autotune, 'autotune_num_rounds': 10, 'num_boost_round': 100, 'early_stopping_rounds': 10, 'test_size': 0.33}

    xgb_params = {'eta': 0.3, 'gamma': 0, 'max_depth': 6, 'min_child_weight': 1, 'subsample': 1, 'colsample_bytree': 1, 'colsample_bylevel': 1, 'colsample_bynode': 1, 'lambda': 1, 'alpha': 0, 'scale_pos_weight': 1, 'silent': 1, 'objective': 'binary:logitraw', 'nthread': 1, 'eval_metric': 'auc'}

    xgb_params_space = {'eta': hp.uniform('eta', 0.0, 0.3), 'gamma': hp.uniform('gamma', 0.0, 0.5), 'max_depth': hp.quniform('max_depth', 2, 8, 1), 'min_child_weight': hp.quniform('min_child_weight', 1, 5, 1), 'subsample': 1, 'colsample_bytree': 1, 'colsample_bylevel': 1, 'colsample_bynode': 1, 'lambda': hp.uniform('lambda', 0.0, 1.0), 'alpha': hp.uniform('alpha', 0.0, 1.0), 'scale_pos_weight': 1.0, 'silent': 1, 'objective': 'binary:logitraw', 'nthread': 1, 'eval_metric': 'auc'}

    if not apply_weights:
        PyProphetLearner(infile, outfile, classifier, xgb_hyperparams, xgb_params, xgb_params_space, xeval_fraction, xeval_num_iter, ss_initial_fdr, ss_iteration_fdr, ss_num_iter, ss_main_score, group_id, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps, level, ipf_max_peakgroup_rank, ipf_max_peakgroup_pep, ipf_max_transition_isotope_overlap, ipf_min_transition_sn, tric_chromprob, threads, test).run()
    else:
        PyProphetWeightApplier(infile, outfile, classifier, xgb_hyperparams, xgb_params, xgb_params_space, xeval_fraction, xeval_num_iter, ss_initial_fdr, ss_iteration_fdr, ss_num_iter, ss_main_score, group_id, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps, level, ipf_max_peakgroup_rank, ipf_max_peakgroup_pep, ipf_max_transition_isotope_overlap, ipf_min_transition_sn, tric_chromprob, threads, test, apply_weights).run()

Response: Score a file using semi - supervised learning and error - rate estimation.


Instruction:
Can you implement a function in Python 3 that
infers peptidoforms after scoring of MS1 MS2 and transition - level data.

Response:
def ipf(infile, outfile, ipf_ms1_scoring, ipf_ms2_scoring, ipf_h0, ipf_grouped_fdr, ipf_max_precursor_pep, ipf_max_peakgroup_pep, ipf_max_precursor_peakgroup_pep, ipf_max_transition_pep):
    """
    Infer peptidoforms after scoring of MS1, MS2 and transition-level data.
    """

    if outfile is None:
        outfile = infile
    else:
        outfile = outfile

    infer_peptidoforms(infile, outfile, ipf_ms1_scoring, ipf_ms2_scoring, ipf_h0, ipf_grouped_fdr, ipf_max_precursor_pep, ipf_max_peakgroup_pep, ipf_max_precursor_peakgroup_pep, ipf_max_transition_pep)


Instruction:
Can you generate a brief explanation for the following Python 3 code
def peptide(infile, outfile, context, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps):

    if outfile is None:
        outfile = infile
    else:
        outfile = outfile

    infer_peptides(infile, outfile, context, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps)

Response: Infer peptides and conduct error - rate estimation in different contexts.


Instruction:
Here you have a function in Python 3, explain what it does
def protein(infile, outfile, context, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps):

    if outfile is None:
        outfile = infile
    else:
        outfile = outfile

    infer_proteins(infile, outfile, context, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps)

Response: Infer proteins and conduct error - rate estimation in different contexts.


Instruction:
Write a Python 3 function for
reducing the file to minimum for global scoring

Response:
def reduce(infile, outfile):
    """
    Reduce scored PyProphet file to minimum for global scoring
    """

    if outfile is None:
        outfile = infile
    else:
        outfile = outfile

    reduce_osw(infile, outfile)


Instruction:
Can you create a Python 3 function that
merges multiple OSW files and output the result.

Response:
def merge(infiles, outfile, same_run, templatefile):
    """
    Merge multiple OSW files and (for large experiments, it is recommended to subsample first).
    """

    if len(infiles) < 1:
        raise click.ClickException("At least one PyProphet input file needs to be provided.")

    merge_osw(infiles, outfile, templatefile, same_run)


Instruction:
Explain what the following Python 3 code does
def backpropagate(infile, outfile, apply_scores):

    if outfile is None:
        outfile = infile
    else:
        outfile = outfile

    backpropagate_oswr(infile, outfile, apply_scores)

Response: Backpropagate multi - run peptide and protein scores to single files.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def export(infile, outfile, format, outcsv, transition_quantification, max_transition_pep, ipf, ipf_max_peptidoform_pep, max_rs_peakgroup_qvalue, peptide, max_global_peptide_qvalue, protein, max_global_protein_qvalue):
    if format == "score_plots":
        export_score_plots(infile)
    else:
        if outfile is None:
            if outcsv:
                outfile = infile.split(".osw")[0] + ".csv"
            else:
                outfile = infile.split(".osw")[0] + ".tsv"
        else:
            outfile = outfile

        export_tsv(infile, outfile, format, outcsv, transition_quantification, max_transition_pep, ipf, ipf_max_peptidoform_pep, max_rs_peakgroup_qvalue, peptide, max_global_peptide_qvalue, protein, max_global_protein_qvalue)

Response: Export the ISA - specific data to a file.


Instruction:
How would you implement a function in Python 3 that
exports Compound TSV or CSV tables

Response:
def export_compound(infile, outfile, format, outcsv, max_rs_peakgroup_qvalue):
    """
    Export Compound TSV/CSV tables
    """
    if format == "score_plots":
        export_score_plots(infile)
    else:
        if outfile is None:
            if outcsv:
                outfile = infile.split(".osw")[0] + ".csv"
            else:
                outfile = infile.split(".osw")[0] + ".tsv"
        else:
            outfile = outfile

        export_compound_tsv(infile, outfile, format, outcsv, max_rs_peakgroup_qvalue)


Instruction:
How would you implement a function in Python 3 that
searches for groups in the specified set of parameters.

Response:
def search_groups(self, **kwargs):
        """
        Returns a list of restclients.GroupReference objects matching the
        passed parameters. Valid parameters are:
            name: parts_of_name
                name may include the wild-card (*) character.
            stem: group_stem
            member: member netid
            owner: admin netid
            instructor: instructor netid
                stem="course" will be set when this parameter is passed.
            student: student netid
                stem="course" will be set when this parameter is passed.
            affiliate: affiliate_name
            type: search_type
                Values are 'direct' to search for direct membership and
                'effective' to search for effective memberships. Default is
                direct membership.
            scope: search_scope
                Values are 'one' to limit results to one level of stem name
                and 'all' to return all groups.
        """
        kwargs = dict((k.lower(), kwargs[k].lower()) for k in kwargs)
        if 'type' in kwargs and (
                kwargs['type'] != 'direct' and kwargs['type'] != 'effective'):
            del(kwargs['type'])

        if 'scope' in kwargs and (
                kwargs['scope'] != 'one' and kwargs['scope'] != 'all'):
            del(kwargs['scope'])

        if "instructor" in kwargs or "student" in kwargs:
            kwargs["stem"] = "course"

        url = "{}/search?{}".format(self.API, urlencode(kwargs))

        data = self._get_resource(url)

        groups = []
        for datum in data.get('data', []):
            group = GroupReference()
            group.uwregid = datum.get('regid')
            group.display_name = datum.get('displayName')
            group.name = datum.get('id')
            group.url = datum.get('url')
            groups.append(group)

        return groups


Instruction:
Can you generate a brief explanation for the following Python 3 code
def get_group_by_id(self, group_id):
        self._valid_group_id(group_id)

        url = "{}/group/{}".format(self.API, group_id)

        data = self._get_resource(url)

        return self._group_from_json(data.get("data"))

Response: Returns a restclients. Group object for the group identified by the passed group ID.


Instruction:
Can you generate the documentation for the following Python 3 function
def create_group(self, group):
        self._valid_group_id(group.id)

        body = {"data": group.json_data()}
        url = "{}/group/{}".format(self.API, group.name)

        data = self._put_resource(url, headers={}, body=body)

        return self._group_from_json(data.get("data"))

Response: Creates a group from the passed restclients. Group object.


Instruction:
Implement a Python 3 function for
deleting the group identified by the passed group ID.

Response:
def delete_group(self, group_id):
        """
        Deletes the group identified by the passed group ID.
        """
        self._valid_group_id(group_id)

        url = "{}/group/{}".format(self.API, group_id)

        self._delete_resource(url)

        return True


Instruction:
Can you implement a function in Python 3 that
returns a list of restclients. GroupMember objects for the passed group ID.

Response:
def get_members(self, group_id):
        """
        Returns a list of restclients.GroupMember objects for the group
        identified by the passed group ID.
        """
        self._valid_group_id(group_id)

        url = "{}/group/{}/member".format(self.API, group_id)

        data = self._get_resource(url)

        members = []
        for datum in data.get("data"):
            members.append(self._group_member_from_json(datum))
        return members


Instruction:
Can you generate the documentation for the following Python 3 function
def update_members(self, group_id, members):
        self._valid_group_id(group_id)

        body = {"data": [m.json_data() for m in members]}
        headers = {"If-Match": "*"}
        url = "{}/group/{}/member".format(self.API, group_id)

        data = self._put_resource(url, headers, body)

        errors = data.get("errors", [])
        if len(errors):
            return errors[0].get("notFound", [])
        return []

Response: Updates the membership of the group represented by the passed group id. Returns a list of members not found.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def get_effective_member_count(self, group_id):
        self._valid_group_id(group_id)

        url = "{}/group/{}/effective_member?view=count".format(self.API,
                                                               group_id)

        data = self._get_resource(url)

        count = data.get("data").get("count")
        return int(count)

Response: Returns a count of effective members for the group identified by the passed group ID.


Instruction:
Here you have a function in Python 3, explain what it does
def is_effective_member(self, group_id, netid):
        self._valid_group_id(group_id)

        # GWS doesn't accept EPPNs on effective member checks, for UW users
        netid = re.sub('@washington.edu', '', netid)

        url = "{}/group/{}/effective_member/{}".format(self.API,
                                                       group_id,
                                                       netid)

        try:
            data = self._get_resource(url)
            return True  # 200
        except DataFailureException as ex:
            if ex.status == 404:
                return False
            else:
                raise

Response: Returns True if the netid is in the group False otherwise.


Instruction:
Write a Python 3 script to
modify the conf. py file to include the necessary documentation.

Response:
def modify_conf():
    """
    pip install redbaron
    """
    import redbaron
    import ubelt as ub
    conf_path = 'docs/conf.py'

    source = ub.readfrom(conf_path)
    red = redbaron.RedBaron(source)

    # Insert custom extensions
    extra_extensions = [
        '"sphinxcontrib.napoleon"'
    ]

    ext_node = red.find('name', value='extensions').parent
    ext_node.value.value.extend(extra_extensions)

    # Overwrite theme to read-the-docs
    theme_node = red.find('name', value='html_theme').parent
    theme_node.value.value = '"sphinx_rtd_theme"'

    ub.writeto(conf_path, red.dumps())


Instruction:
Can you generate a brief explanation for the following Python 3 code
def parse_version():
    from os.path import dirname, join
    import ast
    modname = setupkw['name']
    init_fpath = join(dirname(__file__), modname, '__init__.py')
    with open(init_fpath) as file_:
        sourcecode = file_.read()
    pt = ast.parse(sourcecode)
    class VersionVisitor(ast.NodeVisitor):
        def visit_Assign(self, node):
            for target in node.targets:
                if target.id == '__version__':
                    self.version = node.value.s
    visitor = VersionVisitor()
    visitor.visit(pt)
    return visitor.version

Response: Statically parse the version number from the __init__. py file


Instruction:
Create a Python 3 function for
creating a 3D array in a group.

Response:
def create_dataset(self, name, shape=None, dtype=None, data=None,
                       sparse_format=None, indptr_dtype=np.int64, indices_dtype=np.int32,
                       **kwargs):
        """Create 3 datasets in a group to represent the sparse array.

        Parameters
        ----------
        sparse_format:
        """
        if isinstance(data, Dataset):
            assert sparse_format is None
            group = self.create_group(name)
            group.attrs['h5sparse_format'] = data.attrs['h5sparse_format']
            group.attrs['h5sparse_shape'] = data.attrs['h5sparse_shape']
            group.create_dataset('data', data=data.h5py_group['data'],
                                 dtype=dtype, **kwargs)
            group.create_dataset('indices', data=data.h5py_group['indices'],
                                 dtype=indices_dtype, **kwargs)
            group.create_dataset('indptr', data=data.h5py_group['indptr'],
                                 dtype=indptr_dtype, **kwargs)
        elif ss.issparse(data):
            if sparse_format is not None:
                format_class = get_format_class(sparse_format)
                data = format_class(data)
            group = self.create_group(name)
            group.attrs['h5sparse_format'] = get_format_str(data)
            group.attrs['h5sparse_shape'] = data.shape
            group.create_dataset('data', data=data.data, dtype=dtype, **kwargs)
            group.create_dataset('indices', data=data.indices, dtype=indices_dtype, **kwargs)
            group.create_dataset('indptr', data=data.indptr, dtype=indptr_dtype, **kwargs)
        elif data is None and sparse_format is not None:
            format_class = get_format_class(sparse_format)
            if dtype is None:
                dtype = np.float64
            if shape is None:
                shape = (0, 0)
            data = format_class(shape, dtype=dtype)
            group = self.create_group(name)
            group.attrs['h5sparse_format'] = get_format_str(data)
            group.attrs['h5sparse_shape'] = data.shape
            group.create_dataset('data', data=data.data, dtype=dtype, **kwargs)
            group.create_dataset('indices', data=data.indices, dtype=indices_dtype, **kwargs)
            group.create_dataset('indptr', data=data.indptr, dtype=indptr_dtype, **kwargs)
        else:
            # forward the arguments to h5py
            assert sparse_format is None
            return super(Group, self).create_dataset(
                name, data=data, shape=shape, dtype=dtype, **kwargs)
        return Dataset(group)


Instruction:
Can you generate a brief explanation for the following Python 3 code
def cli_decrypt(context, key):
    with context.io_manager.with_stdout() as stdout:
        with context.io_manager.with_stdin() as stdin:
            crypt_type = stdin.read(1)
            if crypt_type == AES256CBC:
                for chunk in aes_decrypt(key, stdin):
                    stdout.write(chunk)
                stdout.flush()
            else:
                raise ReturnCode(
                    'contents encrypted with unsupported type %r' % crypt_type)

Response:
Decrypt a single element of a context. io_manager s stdin and sends that to
AGEREA.


Instruction:
Can you generate the documentation for the following Python 3 function
def spawn(self, ident, func, *args, **kwargs):
        if self._pool:
            self._pool.spawn_n(self._spawner, ident, func, *args, **kwargs)
            sleep()
        else:
            self._spawner(ident, func, *args, **kwargs)

Response: Spawns a new entry in the cache.


Instruction:
Given the following Python 3 function, write the documentation
def get_results(self):
        try:
            while True:
                ident, value = self._queue.get(block=False)
                self._results[ident] = value
        except queue.Empty:
            pass
        return self._results

Response: Returns a dict of the results currently available.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def client_path_to_os_path(self, client_path):
        if os.path.sep == '/':
            return client_path
        return client_path.replace(os.path.sep, '-').replace('/', os.path.sep)

Response: Converts a client path into the operating system s path by replacing any instances of '/' with '-'.


Instruction:
Write a Python 3 function that can
convert an operating system path into a client path by replacing any instances of os. path. sep with -.

Response:
def os_path_to_client_path(self, os_path):
        """
        Converts an operating system path into a client path by
        replacing instances of os.path.sep with '/'.

        Note: If the client path contains any instances of '/'
        already, they will be replaced with '-'.
        """
        if os.path.sep == '/':
            return os_path
        return os_path.replace('/', '-').replace(os.path.sep, '/')


Instruction:
Write a Python 3 script to
return a file - like object based on the s stdin and the stdin - root.

Response:
def get_stdin(self, os_path=None, skip_sub_command=False):
        """
        Returns a stdin-suitable file-like object based on the
        optional os_path and optionally skipping any configured
        sub-command.
        """
        sub_command = None if skip_sub_command else self.stdin_sub_command
        inn, path = self._get_in_and_path(
            self.stdin, self.stdin_root, sub_command, os_path)
        if hasattr(inn, 'stdout'):
            return inn.stdout
        return inn


Instruction:
Can you write a function in Python 3 where it
returns a file - like object based on the stdout - suitable file - like object based on the os_path.

Response:
def get_stdout(self, os_path=None, skip_sub_command=False):
        """
        Returns a stdout-suitable file-like object based on the
        optional os_path and optionally skipping any configured
        sub-command.
        """
        sub_command = None if skip_sub_command else self.stdout_sub_command
        out, path = self._get_out_and_path(
            self.stdout, self.stdout_root, sub_command, os_path)
        if hasattr(out, 'stdin'):
            return out.stdin
        return out


Instruction:
Can you tell what is the following Python 3 function doing
def get_stderr(self, os_path=None, skip_sub_command=False):
        sub_command = None if skip_sub_command else self.stderr_sub_command
        out, path = self._get_out_and_path(
            self.stderr, self.stderr_root, sub_command, os_path)
        if hasattr(out, 'stdin'):
            return out.stdin
        return out

Response: Returns a file - like object based on the stderr - root and stderr - sub - command.


Instruction:
Write a Python 3 script for
returning a debug - output - suitable file - like object based on the optional os_path optional skip_sub_command.

Response:
def get_debug(self, os_path=None, skip_sub_command=False):
        """
        Returns a debug-output-suitable file-like object based on the
        optional os_path and optionally skipping any configured
        sub-command.
        """
        sub_command = None if skip_sub_command else self.debug_sub_command
        out, path = self._get_out_and_path(
            self.debug, self.debug_root, sub_command, os_path)
        if hasattr(out, 'stdin'):
            return out.stdin
        return out


Instruction:
Explain what the following Python 3 code does
def with_stdin(self, os_path=None, skip_sub_command=False,
                   disk_closed_callback=None):
        """
        A context manager yielding a stdin-suitable file-like object
        based on the optional os_path and optionally skipping any
        configured sub-command.

        :param os_path: Optional path to base the file-like object
            on.
        :param skip_sub_command: Set True to skip any configured
            sub-command filter.
        :param disk_closed_callback: If the backing of the file-like
            object is an actual file that will be closed,
            disk_closed_callback (if set) will be called with the
            on-disk path just after closing it.
        """
        sub_command = None if skip_sub_command else self.stdin_sub_command
        inn, path = self._get_in_and_path(
            self.stdin, self.stdin_root, sub_command, os_path)
        try:
            if hasattr(inn, 'stdout'):
                yield inn.stdout
            else:
                yield inn
        finally:
            if hasattr(inn, 'stdout'):
                self._close(inn.stdout)
            self._wait(inn, path)
            self._close(inn)
            if disk_closed_callback and path:
                disk_closed_callback(path)

Response: A context manager that yields a file - like object that can be read from stdin.


Instruction:
Given the following Python 3 function, write the documentation
def with_stderr(self, os_path=None, skip_sub_command=False,
                    disk_closed_callback=None):
        """
        A context manager yielding a stderr-suitable file-like object
        based on the optional os_path and optionally skipping any
        configured sub-command.

        :param os_path: Optional path to base the file-like object
            on.
        :param skip_sub_command: Set True to skip any configured
            sub-command filter.
        :param disk_closed_callback: If the backing of the file-like
            object is an actual file that will be closed,
            disk_closed_callback (if set) will be called with the
            on-disk path just after closing it.
        """
        sub_command = None if skip_sub_command else self.stderr_sub_command
        out, path = self._get_out_and_path(
            self.stderr, self.stderr_root, sub_command, os_path)
        try:
            if hasattr(out, 'stdin'):
                yield out.stdin
            else:
                yield out
        finally:
            if hasattr(out, 'stdin'):
                self._close(out.stdin)
            self._wait(out, path)
            self._close(out)
            if disk_closed_callback and path:
                disk_closed_callback(path)

Response: A context manager that yields a file - like object that will be written to stderr.


Instruction:
How would you explain what the following Python 3 function does
def with_debug(self, os_path=None, skip_sub_command=False,
                   disk_closed_callback=None):
        """
        A context manager yielding a debug-output-suitable file-like
        object based on the optional os_path and optionally skipping
        any configured sub-command.

        :param os_path: Optional path to base the file-like object
            on.
        :param skip_sub_command: Set True to skip any configured
            sub-command filter.
        :param disk_closed_callback: If the backing of the file-like
            object is an actual file that will be closed,
            disk_closed_callback (if set) will be called with the
            on-disk path just after closing it.
        """
        sub_command = None if skip_sub_command else self.debug_sub_command
        out, path = self._get_out_and_path(
            self.debug, self.debug_root, sub_command, os_path)
        try:
            if hasattr(out, 'stdin'):
                yield out.stdin
            else:
                yield out
        finally:
            if hasattr(out, 'stdin'):
                self._close(out.stdin)
            self._wait(out, path)
            self._close(out)
            if disk_closed_callback and path:
                disk_closed_callback(path)

Response: A context manager that yields a debug - output suitable file - like object.


Instruction:
Given the following Python 3 function, write the documentation
def cli_empty_account(context, yes_empty_account=False, until_empty=False):
    if not yes_empty_account:
        raise ReturnCode(
            'called cli_empty_account without setting yes_empty_account=True')
    marker = None
    while True:
        with context.client_manager.with_client() as client:
            status, reason, headers, contents = client.get_account(
                marker=marker, headers=context.headers, query=context.query,
                cdn=context.cdn)
        if status // 100 != 2:
            if status == 404 and context.ignore_404:
                return
            raise ReturnCode('listing account: %s %s' % (status, reason))
        if not contents:
            if until_empty and marker:
                marker = None
                continue
            break
        for item in contents:
            cli_delete(
                context, item['name'], context.headers, recursive=True)
        marker = item['name']

Response: Delete all objects and containers in an account.


Instruction:
Make a summary of the following Python 3 code
def cli_empty_container(context, path, until_empty=False):
    path = path.rstrip('/').decode('utf8')
    conc = Concurrency(context.concurrency)

    def check_conc():
        for (exc_type, exc_value, exc_tb, result) in \
                six.itervalues(conc.get_results()):
            if exc_value:
                with context.io_manager.with_stderr() as fp:
                    fp.write(str(exc_value))
                    fp.write('\n')
                    fp.flush()

    marker = None
    while True:
        with context.client_manager.with_client() as client:
            status, reason, headers, contents = client.get_container(
                path, marker=marker, headers=context.headers,
                query=context.query, cdn=context.cdn)
        if status // 100 != 2:
            if status == 404 and context.ignore_404:
                return
            raise ReturnCode(
                'listing container %r: %s %s' % (path, status, reason))
        if not contents:
            if until_empty and marker:
                marker = None
                continue
            break
        for item in contents:
            newpath = '%s/%s' % (path, item['name'])
            new_context = context.copy()
            new_context.ignore_404 = True
            check_conc()
            conc.spawn(newpath, cli_delete, new_context, newpath)
        marker = item['name']
        conc.join()
        check_conc()

Response: Deletes all objects in the specified container.


Instruction:
Write a Python 3 script to
delete the item at the given path.

Response:
def cli_delete(context, path, body=None, recursive=False,
               yes_empty_account=False, yes_delete_account=False,
               until_empty=False):
    """
    Deletes the item (account, container, or object) at the path.

    See :py:mod:`swiftly.cli.delete` for context usage information.

    See :py:class:`CLIDelete` for more information.

    :param context: The :py:class:`swiftly.cli.context.CLIContext` to
        use.
    :param path: The path of the item (acount, container, or object)
        to delete.
    :param body: The body to send with the DELETE request. Bodies are
        not normally sent with DELETE requests, but this can be
        useful with bulk deletes for instance.
    :param recursive: If True and the item is an account or
        container, deletes will be issued for any containing items as
        well. This does one pass at the deletion; so if objects revert
        to previous versions or if new objects otherwise arise during
        the process, the container(s) may not be empty once done. Set
        `until_empty` to True if you want multiple passes to keep trying
        to fully empty the containers.
    :param until_empty: If True and recursive is True, this will cause
        Swiftly to keep looping through the deletes until the containers
        are completely empty. Useful if you have object versioning
        turned on or otherwise have objects that seemingly reappear
        after being deleted. It could also run forever if you have
        something that's uploading objects at a faster rate than they
        are deleted.
    :param yes_empty_account: This must be set to True for
        verification when the item is an account and recursive is
        True.
    :param yes_delete_account: This must be set to True for
        verification when the item is an account and you really wish
        a delete to be issued for the account itself.
    """
    path = path.lstrip('/') if path else ''
    if not path:
        if yes_empty_account:
            cli_empty_account(
                context, yes_empty_account=yes_empty_account,
                until_empty=until_empty)
        if yes_delete_account:
            with context.client_manager.with_client() as client:
                status, reason, headers, contents = client.delete_account(
                    headers=context.headers, query=context.query,
                    cdn=context.cdn, body=body,
                    yes_i_mean_delete_the_account=yes_delete_account)
                if status // 100 != 2:
                    if status == 404 and context.ignore_404:
                        return
                    raise ReturnCode(
                        'deleting account: %s %s' % (status, reason))
    elif '/' not in path.rstrip('/'):
        path = path.rstrip('/')
        if recursive:
            cli_empty_container(context, path, until_empty=until_empty)
        with context.client_manager.with_client() as client:
            status, reason, headers, contents = client.delete_container(
                path, headers=context.headers,
                query=context.query, cdn=context.cdn, body=body)
            if status // 100 != 2:
                if status == 404 and context.ignore_404:
                    return
                raise ReturnCode(
                    'deleting container %r: %s %s' % (path, status, reason))
    else:
        with context.client_manager.with_client() as client:
            status, reason, headers, contents = client.delete_object(
                *path.split('/', 1), headers=context.headers,
                query=context.query, cdn=context.cdn, body=body)
            if status // 100 != 2:
                if status == 404 and context.ignore_404:
                    return
                raise ReturnCode(
                    'deleting object %r: %s %s' % (path, status, reason))


Instruction:
Create a Python 3 function to
instance method decorator to convert an optional file keyword argument into an actual value, whether it be a passed value, a value obtained from an io_manager, or sys.stdout.

Response:
def _stdout_filed(func):
    """
    Instance method decorator to convert an optional file keyword
    argument into an actual value, whether it be a passed value, a
    value obtained from an io_manager, or sys.stdout.
    """
    def wrapper(self, file=None):
        if file:
            return func(self, file=file)
        elif self.io_manager:
            with self.io_manager.with_stdout() as stdout:
                return func(self, file=stdout)
        else:
            return func(self, file=sys.stdout)
    wrapper.__doc__ = func.__doc__
    return wrapper


Instruction:
Write a Python 3 function for
instancing method decorator to convert an optional file keyword argument into an actual value, whether it be a passed value, a value obtained from an io_manager, or sys.stderr.

Response:
def _stderr_filed(func):
    """
    Instance method decorator to convert an optional file keyword
    argument into an actual value, whether it be a passed value, a
    value obtained from an io_manager, or sys.stderr.
    """
    def wrapper(self, msg, file=None):
        if file:
            return func(self, msg, file=file)
        elif self.io_manager:
            with self.io_manager.with_stderr() as stderr:
                return func(self, msg, file=stderr)
        else:
            return func(self, msg, file=sys.stderr)
    wrapper.__doc__ = func.__doc__
    return wrapper


Instruction:
Write a Python 3 function for
outputting the error message to the file if specified.

Response:
def error(self, msg, file=None):
        """
        Outputs the error msg to the file if specified, or to the
        io_manager's stderr if available, or to sys.stderr.
        """
        self.error_encountered = True
        file.write(self.error_prefix)
        file.write(msg)
        file.write('\n')
        file.flush()


Instruction:
Can you generate a brief explanation for the following Python 3 code
def exit(self, status=0, msg=None):
        if msg:
            self.error(msg)
        sys.exit(status)

Response: Immediately exits Python with the given status and optionally outputs the given msg.


Instruction:
Write a Python 3 script to
print help information to the file if specified or to sys. stdout.

Response:
def print_help(self, file=None):
        """
        Outputs help information to the file if specified, or to the
        io_manager's stdout if available, or to sys.stdout.
        """
        optparse.OptionParser.print_help(self, file)
        if self.raw_epilog:
            file.write(self.raw_epilog)
        file.flush()


Instruction:
Can you generate the documentation for the following Python 3 function
def print_usage(self, file=None):
        optparse.OptionParser.print_usage(self, file)
        file.flush()

Response: Prints usage information to the file if specified or to sys. stdout.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def print_version(self, file=None):
        optparse.OptionParser.print_version(self, file)
        file.flush()

Response: Prints version information to the file if specified or to sys. stdout.


Instruction:
How would you code a function in Python 3 to
parse the args and create a new context.

Response:
def parse_args_and_create_context(self, args):
        """
        Helper method that will parse the args into options and
        remaining args as well as create an initial
        :py:class:`swiftly.cli.context.CLIContext`.

        The new context will be a copy of
        :py:attr:`swiftly.cli.cli.CLI.context` with the following
        attributes added:

        =======================  ===================================
        muted_account_headers    The headers to omit when outputting
                                 account headers.
        muted_container_headers  The headers to omit when outputting
                                 container headers.
        muted_object_headers     The headers to omit when outputting
                                 object headers.
        =======================  ===================================

        :returns: options, args, context
        """
        original_args = args
        try:
            options, args = self.option_parser.parse_args(args)
        except UnboundLocalError:
            # Happens sometimes with an error handler that doesn't raise its
            # own exception. We'll catch the error below with
            # error_encountered.
            pass
        if self.option_parser.error_encountered:
            if '-?' in original_args or '-h' in original_args or \
                    '--help' in original_args:
                self.option_parser.print_help()
            raise ReturnCode()
        if options.help:
            self.option_parser.print_help()
            raise ReturnCode()
        if self.min_args is not None and len(args) < self.min_args:
            raise ReturnCode(
                'requires at least %s args.' % self.min_args)
        if self.max_args is not None and len(args) > self.max_args:
            raise ReturnCode(
                'requires no more than %s args.' % self.max_args)
        context = self.cli.context.copy()
        context.muted_account_headers = [
            'accept-ranges', 'content-length', 'content-type', 'date']
        context.muted_container_headers = [
            'accept-ranges', 'content-length', 'content-type', 'date']
        context.muted_object_headers = ['accept-ranges', 'date']
        return options, args, context


Instruction:
Explain what the following Python 3 code does
def request(self, method, path, contents, headers, decode_json=False,
                stream=False, query=None, cdn=False):
        """
        Performs a direct HTTP request to the Swift service.

        :param method: The request method ('GET', 'HEAD', etc.)
        :param path: The request path.
        :param contents: The body of the request. May be a string or
            a file-like object.
        :param headers: A dict of request headers and values.
        :param decode_json: If set True, the response body will be
            treated as JSON and decoded result returned instead of
            the raw contents.
        :param stream: If set True, the response body will return as
            a file-like object; otherwise, the response body will be
            read in its entirety and returned as a string. Overrides
            decode_json.
        :param query: A dict of query parameters and values to append
            to the path.
        :param cdn: If set True, the request will be sent to the CDN
            management endpoint instead of the default storage
            endpoint.
        :returns: A tuple of (status, reason, headers, contents).

            :status: An int for the HTTP status code.
            :reason: The str for the HTTP status (ex: "Ok").
            :headers: A dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be
                a list.
            :contents: Depending on the decode_json and stream
                settings, this will either be the raw response
                string, the JSON decoded object, or a file-like
                object.
        """
        raise Exception('request method not implemented')

Response: This method performs a direct HTTP request to the Swift service.


Instruction:
Create a Python 3 function for
heading the account and returns the results.

Response:
def head_account(self, headers=None, query=None, cdn=False):
        """
        HEADs the account and returns the results. Useful headers
        returned are:

        =========================== =================================
        x-account-bytes-used        Object storage used for the
                                    account, in bytes.
        x-account-container-count   The number of containers in the
                                    account.
        x-account-object-count      The number of objects in the
                                    account.
        =========================== =================================

        Also, any user headers beginning with x-account-meta- are
        returned.

        These values can be delayed depending the Swift cluster.

        :param headers: Additional headers to send with the request.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the str for the HTTP body.
        """
        return self.request(
            'HEAD', '', '', headers, query=query, cdn=cdn)


Instruction:
Can you generate the documentation for the following Python 3 function
def get_account(self, headers=None, prefix=None, delimiter=None,
                    marker=None, end_marker=None, limit=None, query=None,
                    cdn=False, decode_json=True):
        """
        GETs the account and returns the results. This is done to list
        the containers for the account. Some useful headers are also
        returned:

        =========================== =================================
        x-account-bytes-used        Object storage used for the
                                    account, in bytes.
        x-account-container-count   The number of containers in the
                                    account.
        x-account-object-count      The number of objects in the
                                    account.
        =========================== =================================

        Also, any user headers beginning with x-account-meta- are
        returned.

        These values can be delayed depending the Swift cluster.

        :param headers: Additional headers to send with the request.
        :param prefix: The prefix container names must match to be
            listed.
        :param delimiter: The delimiter for the listing. Delimiters
            indicate how far to progress through container names
            before "rolling them up". For instance, a delimiter='.'
            query on an account with the containers::

                one.one
                one.two
                two
                three.one

            would return the JSON value of::

                [{'subdir': 'one.'},
                 {'count': 0, 'bytes': 0, 'name': 'two'},
                 {'subdir': 'three.'}]

            Using this with prefix can allow you to traverse a psuedo
            hierarchy.
        :param marker: Only container names after this marker will be
            returned. Swift returns a limited number of containers
            per request (often 10,000). To get the next batch of
            names, you issue another query with the marker set to the
            last name you received. You can continue to issue
            requests until you receive no more names.
        :param end_marker: Only container names before this marker will be
            returned.
        :param limit: Limits the size of the list returned per
            request. The default and maximum depends on the Swift
            cluster (usually 10,000).
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :param decode_json: If set False, the usual decoding of the
            JSON response will be skipped and the raw contents will
            be returned instead.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the decoded JSON response or the raw str
                for the HTTP body.
        """
        query = dict(query or {})
        query['format'] = 'json'
        if prefix:
            query['prefix'] = prefix
        if delimiter:
            query['delimiter'] = delimiter
        if marker:
            query['marker'] = marker
        if end_marker:
            query['end_marker'] = end_marker
        if limit:
            query['limit'] = limit
        return self.request(
            'GET', '', '', headers, decode_json=decode_json, query=query,
            cdn=cdn)

Response: This method is used to get the account and returns the containers for the account.


Instruction:
Can you tell what is the following Python 3 function doing
def put_account(self, headers=None, query=None, cdn=False, body=None):
        return self.request(
            'PUT', '', body or '', headers, query=query, cdn=cdn)

Response: This is the actual PUT method that is used to send a request to the server to set the HTTP status code and the HTTP reason and the HTTP body.


Instruction:
How would you implement a function in Python 3 that
posts the account and returns the results.

Response:
def post_account(self, headers=None, query=None, cdn=False, body=None):
        """
        POSTs the account and returns the results. This is usually
        done to set X-Account-Meta-xxx headers. Note that any existing
        X-Account-Meta-xxx headers will remain untouched. To remove an
        X-Account-Meta-xxx header, send the header with an empty
        string as its value.

        :param headers: Additional headers to send with the request.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :param body: No known Swift POSTs take a body; but the option
            is there for the future.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the str for the HTTP body.
        """
        return self.request(
            'POST', '', body or '', headers, query=query, cdn=cdn)


Instruction:
Can you tell what is the following Python 3 function doing
def delete_account(self, headers=None,
                       yes_i_mean_delete_the_account=False, query=None,
                       cdn=False, body=None):
        """
        Sends a DELETE request to the account and returns the results.

        With ``query['bulk-delete'] = ''`` this might mean a bulk
        delete request where the body of the request is new-line
        separated, url-encoded list of names to delete. Be careful
        with this! One wrong move and you might mark your account for
        deletion of you have the access to do so!

        For a plain DELETE to the account, on clusters that support
        it and, assuming you have permissions to do so, the account
        will be marked as deleted and immediately begin removing the
        objects from the cluster in the backgound.

        THERE IS NO GOING BACK!

        :param headers: Additional headers to send with the request.
        :param yes_i_mean_delete_the_account: Set to True to verify
            you really mean to delete the entire account. This is
            required unless ``body and 'bulk-delete' in query``.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :param body: Some account DELETE requests, like the bulk
            delete request, take a body.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be
                a list.
            :contents: is the str for the HTTP body.
        """
        if not yes_i_mean_delete_the_account and (
                not body or not query or 'bulk-delete' not in query):
            return (0, 'yes_i_mean_delete_the_account was not set to True', {},
                    '')
        return self.request(
            'DELETE', '', body or '', headers, query=query, cdn=cdn)

Response: Sends a DELETE request to the account and returns the results.


Instruction:
Create a Python 3 function to
head the container and returns the results.

Response:
def head_container(self, container, headers=None, query=None, cdn=False):
        """
        HEADs the container and returns the results. Useful headers
        returned are:

        =========================== =================================
        x-container-bytes-used      Object storage used for the
                                    container, in bytes.
        x-container-object-count    The number of objects in the
                                    container.
        =========================== =================================

        Also, any user headers beginning with x-container-meta- are
        returned.

        These values can be delayed depending the Swift cluster.

        :param container: The name of the container.
        :param headers: Additional headers to send with the request.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the str for the HTTP body.
        """
        path = self._container_path(container)
        return self.request(
            'HEAD', path, '', headers, query=query, cdn=cdn)


Instruction:
Can you tell what is the following Python 3 function doing
def get_container(self, container, headers=None, prefix=None,
                      delimiter=None, marker=None, end_marker=None,
                      limit=None, query=None, cdn=False, decode_json=True):
        """
        GETs the container and returns the results. This is done to
        list the objects for the container. Some useful headers are
        also returned:

        =========================== =================================
        x-container-bytes-used      Object storage used for the
                                    container, in bytes.
        x-container-object-count    The number of objects in the
                                    container.
        =========================== =================================

        Also, any user headers beginning with x-container-meta- are
        returned.

        These values can be delayed depending the Swift cluster.

        :param container: The name of the container.
        :param headers: Additional headers to send with the request.
        :param prefix: The prefix object names must match to be
            listed.
        :param delimiter: The delimiter for the listing. Delimiters
            indicate how far to progress through object names before
            "rolling them up". For instance, a delimiter='/' query on
            an container with the objects::

                one/one
                one/two
                two
                three/one

            would return the JSON value of::

                [{'subdir': 'one/'},
                 {'count': 0, 'bytes': 0, 'name': 'two'},
                 {'subdir': 'three/'}]

            Using this with prefix can allow you to traverse a psuedo
            hierarchy.
        :param marker: Only object names after this marker will be
            returned. Swift returns a limited number of objects per
            request (often 10,000). To get the next batch of names,
            you issue another query with the marker set to the last
            name you received. You can continue to issue requests
            until you receive no more names.
        :param end_marker: Only object names before this marker will be
            returned.
        :param limit: Limits the size of the list returned per
            request. The default and maximum depends on the Swift
            cluster (usually 10,000).
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :param decode_json: If set False, the usual decoding of the
            JSON response will be skipped and the raw contents will
            be returned instead.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the decoded JSON response or the raw str
                for the HTTP body.
        """
        query = dict(query or {})
        query['format'] = 'json'
        if prefix:
            query['prefix'] = prefix
        if delimiter:
            query['delimiter'] = delimiter
        if marker:
            query['marker'] = marker
        if end_marker:
            query['end_marker'] = end_marker
        if limit:
            query['limit'] = limit
        return self.request(
            'GET', self._container_path(container), '', headers,
            decode_json=decode_json, query=query, cdn=cdn)

Response: This method is used to get the container and returns the results.


Instruction:
Can you generate the documentation for the following Python 3 function
def put_container(self, container, headers=None, query=None, cdn=False,
                      body=None):
        """
        PUTs the container and returns the results. This is usually
        done to create new containers and can also be used to set
        X-Container-Meta-xxx headers. Note that if the container
        already exists, any existing X-Container-Meta-xxx headers will
        remain untouched. To remove an X-Container-Meta-xxx header,
        send the header with an empty string as its value.

        :param container: The name of the container.
        :param headers: Additional headers to send with the request.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :param body: Some container PUT requests, like the
            extract-archive bulk upload request, take a body.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the str for the HTTP body.
        """
        path = self._container_path(container)
        return self.request(
            'PUT', path, body or '', headers, query=query, cdn=cdn)

Response: This method PUTs a container and returns the results.


Instruction:
How would you code a function in Python 3 to
head the object and returns the results.

Response:
def head_object(self, container, obj, headers=None, query=None, cdn=False):
        """
        HEADs the object and returns the results.

        :param container: The name of the container.
        :param obj: The name of the object.
        :param headers: Additional headers to send with the request.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the str for the HTTP body.
        """
        path = self._object_path(container, obj)
        return self.request(
            'HEAD', path, '', headers, query=query, cdn=cdn)


Instruction:
How would you code a function in Python 3 to
get the object from the object store.

Response:
def get_object(self, container, obj, headers=None, stream=True, query=None,
                   cdn=False):
        """
        GETs the object and returns the results.

        :param container: The name of the container.
        :param obj: The name of the object.
        :param headers: Additional headers to send with the request.
        :param stream: Indicates whether to stream the contents or
            preread them fully and return them as a str. Default:
            True to stream the contents. When streaming, contents
            will have the standard file-like-object read function,
            which accepts an optional size parameter to limit how
            much data is read per call. When streaming is on, be
            certain to fully read the contents before issuing another
            request.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: if *stream* was True, *contents* is a
                file-like-object of the contents of the HTTP body. If
                *stream* was False, *contents* is just a simple str of
                the HTTP body.
        """
        path = self._object_path(container, obj)
        return self.request(
            'GET', path, '', headers, query=query, stream=stream, cdn=cdn)


Instruction:
How would you explain what the following Python 3 function does
def put_object(self, container, obj, contents, headers=None, query=None,
                   cdn=False):
        """
        PUTs the object and returns the results. This is used to
        create or overwrite objects. X-Object-Meta-xxx can optionally
        be sent to be stored with the object. Content-Type,
        Content-Encoding and other standard HTTP headers can often
        also be set, depending on the Swift cluster.

        Note that you can set the ETag header to the MD5 sum of the
        contents for extra verification the object was stored
        correctly.

        :param container: The name of the container.
        :param obj: The name of the object.
        :param contents: The contents of the object to store. This can
            be a simple str, or a file-like-object with at least a
            read function. If the file-like-object also has tell and
            seek functions, the PUT can be reattempted on any server
            error.
        :param headers: Additional headers to send with the request.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the str for the HTTP body.
        """
        path = self._object_path(container, obj)
        return self.request(
            'PUT', path, contents, headers, query=query, cdn=cdn)

Response: This method PUTs the object in the specified container and returns the results.


Instruction:
How would you code a function in Python 3 to
post an object to the specified container and returns the results.

Response:
def post_object(self, container, obj, headers=None, query=None, cdn=False,
                    body=None):
        """
        POSTs the object and returns the results. This is used to
        update the object's header values. Note that all headers must
        be sent with the POST, unlike the account and container POSTs.
        With account and container POSTs, existing headers are
        untouched. But with object POSTs, any existing headers are
        removed. The full list of supported headers depends on the
        Swift cluster, but usually include Content-Type,
        Content-Encoding, and any X-Object-Meta-xxx headers.

        :param container: The name of the container.
        :param obj: The name of the object.
        :param headers: Additional headers to send with the request.
        :param query: Set to a dict of query values to send on the
            query string of the request.
        :param cdn: If set True, the CDN management interface will be
            used.
        :param body: No known Swift POSTs take a body; but the option
            is there for the future.
        :returns: A tuple of (status, reason, headers, contents).

            :status: is an int for the HTTP status code.
            :reason: is the str for the HTTP status (ex: "Ok").
            :headers: is a dict with all lowercase keys of the HTTP
                headers; if a header has multiple values, it will be a
                list.
            :contents: is the str for the HTTP body.
        """
        path = self._object_path(container, obj)
        return self.request(
            'POST', path, body or '', headers, query=query, cdn=cdn)