def generate_report():
dd_object = DailyDiscussion()
alpha_vantage = AlphaVantageAPI()
tickers = dd_object.get_daily_discussion(for_date=dt.date.today())
temp_dict = {k: v['count'] for (k, v) in tickers[0].get('tickers').items() if k != 'misc'}
c = collections.Counter(temp_dict)
report = Reporter()
report.set_title('Markov Chain Report')
for tuple_c in c.most_common(20):
ticker = tuple_c[0]
mc = MarkovChain(ticker)
mc.build_markov_chain()
x, y = mc.predict()
if x is None or y is None:
continue
mu = mc.expected_value(x, y)
var = mc.var(x, y)
prev_day_change = alpha_vantage.get_quote(ticker)
prev_day_change = prev_day_change['Global Quote']['10. change percent']
ds = DataSet()
ds.set_x(x.tolist())
ds.append_y_set({'data': y.tolist(), 'label': ''})
report.append_to_body(ChartBuilder(title='Markov Chain: ' + ticker, chart_type='line', data_set=ds, y_label=ticker))
report.append_to_body(HTMLUtil.wrap_in_tag("Expected Value: " + str(round(mu, 3)) + "%", 'p'))
report.append_to_body(HTMLUtil.wrap_in_tag("Variance: " + str(round(var, 3)) + "%", 'p'))
report.append_to_body(HTMLUtil.wrap_in_tag("Previous day's change: " + prev_day_change, 'p'))
report.compile()
return report.title
def compile(self):
self.compile_data()
self.build_script()
self._compiled_html = HTMLUtil.get_indent(
1) + self._base_html + HTMLUtil.get_indent(
1) + self._compiled_script
return self._compiled_html
def _compile_template(self):
if self.body == '':
self.body = '\n\t\t<section>\n\t\t\t<p>Empty Report</p>\n\t\t</section>'
if self.summary != '':
self.summary = HTMLUtil.wrap_in_tag(self.summary, 'p') + '\n'
self.body = HTMLUtil.wrap_in_tag(self.body, 'main', indent=1, one_line=False)
return self.template.replace('$$__TITLE__$$', self.title, 2)\
.replace('$$__BODY__$$', self.summary + str(self.body))\
.replace('$$__HEAD__$$', '')
def render(self, indent=1):
if len(self._class_list) > 0:
self._attrs[Attributes.CLASS] = ' '.join(self._class_list)
if len(self._children) == 0:
return HTMLUtil.wrap_in_tag(self._text, self._node_type, indent, self._attrs, one_line=True)
child_markup = ''
for child in self._children:
if isinstance(child, HTMLElement):
child_markup += child.render(indent=indent + 1)
else:
child_markup += str(child)
return HTMLUtil.wrap_in_tag(child_markup, self._node_type, indent, self._attrs, one_line=False)
def get_ticker_table(tickers_found, lookup_thresh=3, force_reload=False):
table_header = ['Ticker', 'Mentions', 'Name', 'Description', 'Movement', 'Links']
norm_factor = 0
for tf in tickers_found:
norm_factor += tickers_found[tf]['count']
table_values = []
for tf in tickers_found:
addendum = ''
counter = 0
for submission in tickers_found[tf]['submissions']:
addendum += LinkBuilder('[%d] - %d' % (counter, submission['score']),
'https://www.reddit.com' + submission['link']).compile() + '<br />'
counter += 1
addendum = ScrollableDiv(addendum, '5rem').compile()
desc = '...'
if 'description' in tickers_found[tf] and tickers_found[tf]['description'] is not None:
desc = tickers_found[tf]['description']
if tickers_found[tf]['count'] >= lookup_thresh - 1:
print('crawling AV for %s' % tf)
pct_change = AlphaVantageAPI().get_parsed_quote(tf, force_reload)['10. change percent']
pct_in_tag = HTMLUtil.wrap_in_tag(pct_change, 'div',
attributes={'class': 'negative' if '-' in pct_change else 'positive'})
else:
pct_in_tag = 'N/A'
table_values.append([tf, tickers_found[tf]['count'], tickers_found[tf]['name'],
desc[:200] + '...', pct_in_tag, addendum])
table_values.sort(key=Sorting.sort_by_mentions, reverse=True)
return TableBuilder(headers=table_header, rows=table_values)
def __init__(self,
chart_type='bar',
title='',
data_set=None,
x_label='',
y_label=''):
if data_set is None:
data_set = DataSet()
data_set.set_x([])
data_set.set_ys([{'label': 'no data', 'data': []}])
elif isinstance(data_set, dict):
data_set = DataSet(from_data=data_set)
self._raw_data_set = data_set.get_data_dict()
self._ys = self._raw_data_set['ys']
self._x = self._raw_data_set['x']
self._type = chart_type
self._title = title
self._id = title.replace(' ', '_', 100)
self._compiled_html = ''
self._compiled_script = ''
self._data_string = ''
self._base_html = HTMLUtil.wrap_in_tag('',
'canvas',
indent=3,
attributes={'id': self._id})
self._color_index = -1
self._x_label = x_label
self._y_label = y_label
def resolve_options(opts):
options_str = ''
for key in opts:
options_str += '"' + key + '": ' + BaseChart.resolve_value(
opts[key]) + ',' + HTMLUtil.get_indent(6)
return options_str
def index():
report_path = path.join(client_path, 'compiled')
# read out and sort all compiled reports (ignore the README)
files = [
f for f in listdir(report_path)
if path.isfile(path.join(report_path, f)) and f != "README.md"
]
files.sort()
file_links = [
LinkBuilder(text=f.replace('.html', ''), url='/report?name=' + f)
for f in files
]
file_list = ListBuilder(list_items=file_links,
list_header='Your Reports')
buttons = [
ButtonBuilder(text='New ' + b + ' Report',
button_id=b,
attrs={"data-type": b}) for b in valid_report_types
]
button_list = ListBuilder(list_items=buttons,
list_header=' Generate Reports')
template = HTMLUtil.get_template('index.html')\
.replace('$$__REPORTS__$$', file_list.compile())\
.replace('$$__GEN_REPORTS__$$', button_list.compile())
return template
def compile_data(self):
self._data_string = ''
for data in self._raw_data_set['ys']:
color = self.resolve_data_color(data)
self._data_string += HTMLUtil.get_indent(7) + self.get_data_set_template()\
.replace(TITLE_FORMAT, data['label'])\
.replace(DATA_FORMAT, str(data['data']))\
.replace(COLOR_PATTERN, color, 2)\
.replace(Y_AX_ID, "'A'")
for data in self._raw_data_set['secondary_ys']:
color = self.resolve_data_color(data)
self._data_string += HTMLUtil.get_indent(7) + self.get_data_set_template() \
.replace(TITLE_FORMAT, data['label']) \
.replace(DATA_FORMAT, str(data['data'])) \
.replace(COLOR_PATTERN, color, 2) \
.replace(Y_AX_ID, "'B'")
self._data_string = self._data_string[:-1]
def compile_data(self):
self._data_string = ''
for data in self._ys:
color = self.resolve_data_color(data)
self._data_string += HTMLUtil.get_indent(7) + self.get_data_set_template()\
.replace(TITLE_FORMAT, data['label'])\
.replace(DATA_FORMAT, str(data['data']))\
.replace(COLOR_PATTERN, color, 2)
self._data_string = self._data_string[:-1]
def compile_data(self):
self._data_string = ''
for data in self._ys:
if 'color' in data:
color = data['color']
else:
color = str([self.get_next_color() for _ in range(0, len(data['data']))]).replace("'", "", 100)
self._data_string += HTMLUtil.get_indent(7) + DATA_SET_TEMPLATE.replace(TITLE_FORMAT, data['label']) \
.replace(DATA_FORMAT, str(data['data'])) \
.replace(COLOR_FORMAT, str(color))
def append_to_body(self, html, section_id=""):
if section_id == "":
self.body += '\n\t\t<br />' + HTMLUtil.wrap_in_tag(html, 'section', indent=2, one_line=False)
else:
self.body += '\n\t\t<br />' + HTMLUtil.wrap_in_tag(html, 'section', indent=2, one_line=False,
attributes={"id": section_id})
def set_body(self, body):
self.body = HTMLUtil.wrap_in_tag(body, 'section', indent=2, one_line=False)
def report():
report_file = request.args.get('name', default='NOT_FOUND', type=str)
return HTMLUtil.get_report(report_file)
def generate_report():
# gather the current hot 1000 posts from WSB
reddit = RedditAPI()
submissions = reddit.get_hot('wallstreetbets', limit=1000)
# loop through and try to pick out tickers
tickers_found = {}
for sub in range(0, len(submissions['title'])):
title = submissions['title'][sub]
self_text = submissions['body'][sub]
url = submissions['url'][sub]
score = submissions['score'][sub]
ticker = NLUSubjectTickerEstimator.estimate(title, self_text)
if ticker is None:
continue
ticker_symbol = ticker[0]
# if it is, write down information about the ticker and how many times we've seen it
if ticker_symbol in tickers_found:
tickers_found[ticker_symbol]['count'] += 1
tickers_found[ticker_symbol]['submissions'].append({
'link': url,
'title': title,
'score': score
})
else:
tickers_found[ticker_symbol] = {
'count': 1,
'submissions': [{
'link': url,
'title': title,
'score': score
}],
'name': LinkBuilder(ticker[1], ticker[-3]),
'description': ticker[2]
}
# sort the submissions by score
for tf in tickers_found:
tickers_found[tf]['submissions'].sort(reverse=True,
key=Sorting.sort_by_score)
# then reformat the result so that we can put it in a tabular format
table_values = []
horizontal_x = []
horizontal_y = []
mentions_to_movement = []
for tf in tickers_found:
addendum = ''
counter = 0
for submission in tickers_found[tf]['submissions']:
addendum += LinkBuilder('[%d] - %d' % (counter, submission['score']),
'https://reddit.com' + submission['link']).compile() + \
'<br />'
counter += 1
addendum = ScrollableDiv(addendum, '5rem').compile()
desc = '...'
if 'description' in tickers_found[tf] and tickers_found[tf][
'description'] is not None:
desc = tickers_found[tf]['description']
if tickers_found[tf]['count'] > 2:
print('crawling AV for %s' % tf)
pct_change = AlphaVantageAPI().get_parsed_quote(tf).get(
'10. change percent')
if pct_change is None:
pct_change = "0%"
horizontal_y.append(pct_change.replace('%', ''))
horizontal_x.append(tf)
mentions_to_movement.append({
'data': [{
'x': tickers_found[tf]['count'],
'y': pct_change.replace('%', '')
}],
'label':
tf
})
pct_in_tag = HTMLUtil.wrap_in_tag(
pct_change,
'div',
attributes={
'class': 'negative' if '-' in pct_change else 'positive'
})
else:
pct_in_tag = 'N/A'
table_values.append([
tf, tickers_found[tf]['count'], tickers_found[tf]['name'],
desc[:200] + '...', pct_in_tag, addendum
])
horizontal_ds = DataSet()
horizontal_ds.set_x(horizontal_x)
horizontal_ds.append_y_set({'label': 'Sample', 'data': horizontal_y})
table_values.sort(key=Sorting.sort_by_mentions, reverse=True)
# and then mutate the data again to match the data format for bar charts
x = []
y = []
for arr in table_values:
x.append(arr[0])
y.append(arr[1])
ds = DataSet()
ds.set_x(x)
ds.append_y_set({'data': y, 'label': ''})
# Build the actual report from our parsed data
report = Reporter()
report.set_title('NLU Report')
# set up a table
table_header = [
'Ticker', 'Mentions', 'Name', 'Description', 'Movement', 'Links'
]
report.set_body(TableBuilder(headers=table_header, rows=table_values))
# and a chart
report.append_to_body(
ChartBuilder(title='WSB Mentions',
chart_type='bar',
data_set=ds,
y_label='# of Mentions'))
# and another chart
report.append_to_body(
ChartBuilder(title='Stock % Change',
chart_type='horizontal-bar',
data_set=horizontal_ds,
x_label='% Change'))
# and another
ds_scatter = DataSet()
ds_scatter.set_ys(mentions_to_movement)
report.append_to_body(
ChartBuilder(title='Mentions vs Movement',
chart_type='scatter',
data_set=ds_scatter,
x_label='Mentions',
y_label='Movement (%)'))
report.compile()
return report.title
def get_stock_search():
return HTMLUtil.get_template('stock-search.html')