Test your AI Agents with the all-new Agent to Agent Testing Platform.Learn More

How to use _create_image_html method in autotest

Best Python code snippet using autotest_python

graphing_utils.py

Source:graphing_utils.py

...371    image = image.crop(bounding_box)372    image_data = StringIO.StringIO()373    image.save(image_data, format='PNG')374    return image_data.getvalue(), bounding_box375def _create_image_html(figure, area_data, plot_info):376    """\377    Given the figure and drilldown data, construct the HTML that will render the378    graph as a PNG image, and attach the image map to that image.379    figure: figure containing the drawn plot(s)380    area_data: list of parameters for each area of the image map. See the381               definition of the template string '_AREA_TEMPLATE'382    plot_info: a MetricsPlot or QualHistogram383    """384    png, bbox = _create_png(figure)385    # Construct the list of image map areas386    areas = [_AREA_TEMPLATE %387             (data['left'] - bbox[0], data['top'] - bbox[1],388              data['right'] - bbox[0], data['bottom'] - bbox[1],389              data['title'], data['callback'],390              _json_encoder.encode(data['callback_arguments'])391                  .replace('"', '&quot;'))392             for data in area_data]393    map_name = plot_info.drilldown_callback + '_map'394    return _HTML_TEMPLATE % (base64.b64encode(png), map_name, map_name,395                             '\n'.join(areas))396def _find_plot_by_label(plots, label):397    for index, plot in enumerate(plots):398        if plot['label'] == label:399            return index400    raise ValueError('no plot labeled "%s" found' % label)401def _normalize_to_series(plots, base_series):402    base_series_index = _find_plot_by_label(plots, base_series)403    base_plot = plots[base_series_index]404    base_xs = base_plot['x']405    base_values = base_plot['y']406    base_errors = base_plot['errors']407    del plots[base_series_index]408    for plot in plots:409        old_xs, old_values, old_errors = plot['x'], plot['y'], plot['errors']410        new_xs, new_values, new_errors = [], [], []411        new_base_values, new_base_errors = [], []412        # Select only points in the to-be-normalized data that have a413        # corresponding baseline value414        for index, x_value in enumerate(old_xs):415            try:416                base_index = base_xs.index(x_value)417            except ValueError:418                continue419            new_xs.append(x_value)420            new_values.append(old_values[index])421            new_base_values.append(base_values[base_index])422            if old_errors:423                new_errors.append(old_errors[index])424                new_base_errors.append(base_errors[base_index])425        if not new_xs:426            raise NoDataError('No normalizable data for series ' +427                              plot['label'])428        plot['x'] = new_xs429        plot['y'] = new_values430        if old_errors:431            plot['errors'] = new_errors432        plot['y'], plot['errors'] = _normalize(plot['y'], plot['errors'],433                                               new_base_values,434                                               new_base_errors)435def _create_metrics_plot_helper(plot_info, extra_text=None):436    """437    Create a metrics plot of the given plot data.438    plot_info: a MetricsPlot object.439    extra_text: text to show at the uppper-left of the graph440    TODO(showard): move some/all of this logic into methods on MetricsPlot441    """442    query = plot_info.query_dict['__main__']443    cursor = readonly_connection.cursor()444    cursor.execute(query)445    if not cursor.rowcount:446        raise NoDataError('query did not return any data')447    rows = cursor.fetchall()448    # "transpose" rows, so columns[0] is all the values from the first column,449    # etc.450    columns = zip(*rows)451    plots = []452    labels = [str(label) for label in columns[0]]453    needs_resort = (cursor.description[0][0] == 'kernel')454    # Collect all the data for the plot455    col = 1456    while col < len(cursor.description):457        y = columns[col]458        label = cursor.description[col][0]459        col += 1460        if (col < len(cursor.description) and461            'errors-' + label == cursor.description[col][0]):462            errors = columns[col]463            col += 1464        else:465            errors = None466        if needs_resort:467            y = _resort(labels, y)468            if errors:469                errors = _resort(labels, errors)470        x = [index for index, value in enumerate(y) if value is not None]471        if not x:472            raise NoDataError('No data for series ' + label)473        y = [y[i] for i in x]474        if errors:475            errors = [errors[i] for i in x]476        plots.append({477            'label': label,478            'x': x,479            'y': y,480            'errors': errors481        })482    if needs_resort:483        labels = _resort(labels, labels)484    # Normalize the data if necessary485    normalize_to = plot_info.normalize_to486    if normalize_to == 'first' or normalize_to.startswith('x__'):487        if normalize_to != 'first':488            baseline = normalize_to[3:]489            try:490                baseline_index = labels.index(baseline)491            except ValueError:492                raise ValidationError({493                    'Normalize' : 'Invalid baseline %s' % baseline494                    })495        for plot in plots:496            if normalize_to == 'first':497                plot_index = 0498            else:499                try:500                    plot_index = plot['x'].index(baseline_index)501                # if the value is not found, then we cannot normalize502                except ValueError:503                    raise ValidationError({504                        'Normalize' : ('%s does not have a value for %s'505                                       % (plot['label'], normalize_to[3:]))506                        })507            base_values = [plot['y'][plot_index]] * len(plot['y'])508            if plot['errors']:509                base_errors = [plot['errors'][plot_index]] * len(plot['errors'])510            plot['y'], plot['errors'] = _normalize(plot['y'], plot['errors'],511                                                   base_values,512                                                   None or base_errors)513    elif normalize_to.startswith('series__'):514        base_series = normalize_to[8:]515        _normalize_to_series(plots, base_series)516    # Call the appropriate function to draw the line or bar plot517    if plot_info.is_line:518        figure, area_data = _create_line(plots, labels, plot_info)519    else:520        figure, area_data = _create_bar(plots, labels, plot_info)521    # TODO(showard): extract these magic numbers to named constants522    if extra_text:523        text_y = .95 - .0075 * len(plots)524        figure.text(.1, text_y, extra_text, size='xx-small')525    return (figure, area_data)526def create_metrics_plot(query_dict, plot_type, inverted_series, normalize_to,527                        drilldown_callback, extra_text=None):528    plot_info = MetricsPlot(query_dict, plot_type, inverted_series,529                            normalize_to, drilldown_callback)530    figure, area_data = _create_metrics_plot_helper(plot_info, extra_text)531    return _create_image_html(figure, area_data, plot_info)532def _get_hostnames_in_bucket(hist_data, bucket):533    """\534    Get all the hostnames that constitute a particular bucket in the histogram.535    hist_data: list containing tuples of (hostname, pass_rate)536    bucket: tuple containing the (low, high) values of the target bucket537    """538    return [hostname for hostname, pass_rate in hist_data539            if bucket[0] <= pass_rate < bucket[1]]540def _create_qual_histogram_helper(plot_info, extra_text=None):541    """\542    Create a machine qualification histogram of the given data.543    plot_info: a QualificationHistogram544    extra_text: text to show at the upper-left of the graph545    TODO(showard): move much or all of this into methods on546    QualificationHistogram547    """548    cursor = readonly_connection.cursor()549    cursor.execute(plot_info.query)550    if not cursor.rowcount:551        raise NoDataError('query did not return any data')552    # Lists to store the plot data.553    # hist_data store tuples of (hostname, pass_rate) for machines that have554    #     pass rates between 0 and 100%, exclusive.555    # no_tests is a list of machines that have run none of the selected tests556    # no_pass is a list of machines with 0% pass rate557    # perfect is a list of machines with a 100% pass rate558    hist_data = []559    no_tests = []560    no_pass = []561    perfect = []562    # Construct the lists of data to plot563    for hostname, total, good in cursor.fetchall():564        if total == 0:565            no_tests.append(hostname)566            continue567        if good == 0:568            no_pass.append(hostname)569        elif good == total:570            perfect.append(hostname)571        else:572            percentage = 100.0 * good / total573            hist_data.append((hostname, percentage))574    interval = plot_info.interval575    bins = range(0, 100, interval)576    if bins[-1] != 100:577        bins.append(bins[-1] + interval)578    figure, height = _create_figure(_SINGLE_PLOT_HEIGHT)579    subplot = figure.add_subplot(1, 1, 1)580    # Plot the data and get all the bars plotted581    _,_, bars = subplot.hist([data[1] for data in hist_data],582                         bins=bins, align='left')583    bars += subplot.bar([-interval], len(no_pass),584                    width=interval, align='center')585    bars += subplot.bar([bins[-1]], len(perfect),586                    width=interval, align='center')587    bars += subplot.bar([-3 * interval], len(no_tests),588                    width=interval, align='center')589    buckets = [(bin, min(bin + interval, 100)) for bin in bins[:-1]]590    # set the x-axis range to cover all the normal bins plus the three "special"591    # ones - N/A (3 intervals left), 0% (1 interval left) ,and 100% (far right)592    subplot.set_xlim(-4 * interval, bins[-1] + interval)593    subplot.set_xticks([-3 * interval, -interval] + bins + [100 + interval])594    subplot.set_xticklabels(['N/A', '0%'] +595                        ['%d%% - <%d%%' % bucket for bucket in buckets] +596                        ['100%'], rotation=90, size='small')597    # Find the coordinates on the image for each bar598    x = []599    y = []600    for bar in bars:601        x.append(bar.get_x())602        y.append(bar.get_height())603    f = subplot.plot(x, y, linestyle='None')[0]604    upper_left_coords = f.get_transform().transform(zip(x, y))605    bottom_right_coords = f.get_transform().transform(606        [(x_val + interval, 0) for x_val in x])607    # Set the title attributes608    titles = ['%d%% - <%d%%: %d machines' % (bucket[0], bucket[1], y_val)609              for bucket, y_val in zip(buckets, y)]610    titles.append('0%%: %d machines' % len(no_pass))611    titles.append('100%%: %d machines' % len(perfect))612    titles.append('N/A: %d machines' % len(no_tests))613    # Get the hostnames for each bucket in the histogram614    names_list = [_get_hostnames_in_bucket(hist_data, bucket)615                  for bucket in buckets]616    names_list += [no_pass, perfect]617    if plot_info.filter_string:618        plot_info.filter_string += ' AND '619    # Construct the list of drilldown parameters to be passed when the user620    # clicks on the bar.621    params = []622    for names in names_list:623        if names:624            hostnames = ','.join(_quote(hostname) for hostname in names)625            hostname_filter = 'hostname IN (%s)' % hostnames626            full_filter = plot_info.filter_string + hostname_filter627            params.append({'type': 'normal',628                           'filterString': full_filter})629        else:630            params.append({'type': 'empty'})631    params.append({'type': 'not_applicable',632                   'hosts': '<br />'.join(no_tests)})633    area_data = [dict(left=ulx, top=height - uly,634                      right=brx, bottom=height - bry,635                      title=title, callback=plot_info.drilldown_callback,636                      callback_arguments=param_dict)637                 for (ulx, uly), (brx, bry), title, param_dict638                 in zip(upper_left_coords, bottom_right_coords, titles, params)]639    # TODO(showard): extract these magic numbers to named constants640    if extra_text:641        figure.text(.1, .95, extra_text, size='xx-small')642    return (figure, area_data)643def create_qual_histogram(query, filter_string, interval, drilldown_callback,644                          extra_text=None):645    plot_info = QualificationHistogram(query, filter_string, interval,646                                       drilldown_callback)647    figure, area_data = _create_qual_histogram_helper(plot_info, extra_text)648    return _create_image_html(figure, area_data, plot_info)649def create_embedded_plot(model, update_time):650    """\651    Given an EmbeddedGraphingQuery object, generate the PNG image for it.652    model: EmbeddedGraphingQuery object653    update_time: 'Last updated' time654    """655    params = pickle.loads(model.params)656    extra_text = 'Last updated: %s' % update_time657    if model.graph_type == 'metrics':658        plot_info = MetricsPlot(query_dict=params['queries'],659                                plot_type=params['plot'],660                                inverted_series=params['invert'],661                                normalize_to=None,662                                drilldown_callback='')...

emails.py

Source:emails.py

...49    @abstractmethod50    def _create_html_body(self, recipient: Recipient) -> MIMEText:51        ...52        53    def _create_image_html(self, image: Image) -> str:54        return f'''<div dir="ltr"><img src="cid:{image.cid}" 55        alt="{html.escape('image not found', quote=True)}" 56        width="{image.width}" height="{image.height}"><br></div>'''57    def _generate_alternative(self) -> MIMEMultipart:58        alternative = MIMEMultipart('alternative')59        text = MIMEText(u'Image not working', 'plain', 'utf-8')60        alternative.attach(text)61        return alternative62    def _generate_message(self, recipient: Recipient, header: str) -> MIMEMultipart:63        msg = MIMEMultipart('related')64        msg['Subject'] = Header(header, 'utf-8')65        msg['From'] = self.email_address66        msg['To'] = recipient.email_address67        return msg68    def _create_signoff_html(self) -> str:69        return f'''<p>Have a great day!</p><p>From Sara (SIIF Automated Reporting Assistant)</p>70        {self._create_image_html(self.logo)}71        <p>---------------------------------</p>72        <p><small>Do not reply to this email</small></p>73        <p><small>Code available at https://github.com/CameronChandler/SARA</small></p>74        <p><small>Disclaimer: This email is automated and the data/visualisations/calculations are subject to errors!</small></p>75        <p><small>This has not been checked by a human, so please do not use to inform your financial decisions.</small></p>'''76    77    def _create_email(self) -> str:78        msg = self._generate_message(self.recipient, self.header)79        alt = self._generate_alternative()80        msg.attach(alt)81        alt.attach(self._create_html_body(self.recipient))82        for image in self.images + [self.logo]:83            msg.attach(image.graphic)84        return msg.as_string()85class WeeklyEmail(Email):86    ''' Create and send weekly emails '''87    header = 'SIIF Weekly Report'88    def __init__(89        self, email_address: str, recipient: Recipient, images: List[Image], portfolio: "pd.Series[float]"90    ) -> None:91        self.portfolio = portfolio92        super().__init__(email_address, recipient, images)93    94    def _create_html_body(self, recipient: Recipient) -> MIMEText:95        # Strategy Comparison96        last_week_date: datetime.date = self.portfolio.index[-1] - pd.Timedelta(days=7)97        last_week_portfolio_value: np.float64 = self.portfolio[self.portfolio.index <= last_week_date][-1]98        pct_change: float = round(100*(self.portfolio[-1]/last_week_portfolio_value - 1), 1)99        msg_html = f'''<p>Dear {recipient.name},</p>100        <p>Here\'s an update on the SIIF portfolio:</p>101        <p>The current portfolio value is <b>${round(self.portfolio[-1], 2)}</b>, 102        that is <b>{abs(pct_change)}% {"up" if pct_change >= 0 else "down"}</b> from last week.</p>103        {self._create_image_html(self.images[0])}104        <p>The above graph compares SIIF's current portfolio against several other strategies. They are:</p>105        <p>Investing entirely in the NASDAQ 100, ASX 200, or into a 3% p.a. savings account.</p>106        <p>Here is the breakdown of SIIF's portfolio:</p>107        {self._create_image_html(self.images[1])}108        {self._create_signoff_html()}'''109        return MIMEText(msg_html, 'html', 'utf-8')110class DailyEmail(Email):111    ''' Create and send daily emails '''112    header = 'SIIF - Large Stock Movement Alert'113    def __init__(self, email_address: str, recipient: Recipient, images: List[Image], daily_changes: List[Tuple[str, float]]) -> None:114        self.daily_changes = daily_changes115        super().__init__(email_address, recipient, images)116    def _daily_changes_html(self) -> str:117        out = ''118        for code, change in self.daily_changes:119            out += f"<p>Today {code} <b>{'dropped' if change < 0 else 'rose'} {round(abs(change), 1)}</b>%</p>"120        return out121    def _create_html_body(self, recipient: Recipient) -> MIMEText:122        first_code = self.daily_changes[0][0]123        msg_html = f'''<p>Dear {recipient.name},</p>124        {self._daily_changes_html()}125        <p>You may like to investigate why. <a href="https://www.google.com/search?q={first_code}+asx">Click here to begin researching!</a></p>126        {self._create_image_html(self.images[0])}127        {self._create_signoff_html()}'''128        return MIMEText(msg_html, 'html', 'utf-8')129def send_email(email: Email, email_address: str, email_password: str) -> None:130    ''' Establishes connection and sends email `message` '''131    mailServer = smtplib.SMTP('smtp.gmail.com', 587)132    mailServer.ehlo()133    mailServer.starttls()134    mailServer.ehlo()135    mailServer.login(email_address, email_password)136    mailServer.sendmail(email_address, email.recipient.email_address, email.email)...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.