How to use _create_image_html method in autotest

Best Python code snippet using autotest_python Github


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...371 image = image.crop(bounding_box)372 image_data = StringIO.StringIO()373, 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 +=[-interval], len(no_pass),584 width=interval, align='center')585 bars +=[bins[-1]], len(perfect),586 width=interval, align='center')587 bars +=[-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='')...

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...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</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: = 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 {},</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 {},</p>124 {self._daily_changes_html()}125 <p>You may like to investigate why. <a href="{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('', 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,

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