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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)...

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