def parse_results_line(chars):
_left = chars[chars["x0rel"] < 125]
left = collate_chars(_left) if len(_left) else None
_right = chars[(chars["x0rel"] > 155)]
right = int(collate_chars(_right)) if len(_right) else None
_mid = chars[(chars["x0rel"] > 125) & (chars["x0rel"] < 155)]
mid = collate_chars(_mid) if len(_mid) else None
return {"text": left, "aff": mid, "votes": right}
def test_pandas(self):
page = self.pdf.pages[0]
cropped = page.crop((0, 80, self.PDF_WIDTH, 485))
table = cropped.extract_table({
"horizontal_strategy":
"text",
"explicit_vertical_lines":
[min(map(itemgetter("x0"), cropped.chars))],
"intersection_tolerance":
5
})
table = pd.DataFrame(table)
def parse_value(x):
if pd.isnull(x) or x == "": return None
return int(x.replace(",", ""))
table.columns = COLUMNS
table[table.columns[1:]] = table[table.columns[1:]].applymap(
parse_value)
# [1:] because first column is state name
for c in COLUMNS[1:]:
total = table[c].iloc[-1]
colsum = table[c].sum()
assert (colsum == (total * 2))
month_chars = within_bbox(page.chars, (0, 35, self.PDF_WIDTH, 65))
month_text = collate_chars(month_chars)
assert (month_text == "November - 2015")
def test_plain(self):
page = self.pdf.pages[0]
cropped = page.crop((0, 80, self.PDF_WIDTH, 485))
table = cropped.extract_table({
"horizontal_strategy":
"text",
"explicit_vertical_lines":
[min(map(itemgetter("x0"), cropped.chars))],
"intersection_tolerance":
5
})
print(table)
def parse_value(k, x):
if k == 0: return x
if x in (None, ""): return None
return int(x.replace(",", ""))
def parse_row(row):
return dict(
(COLUMNS[i], parse_value(i, v)) for i, v in enumerate(row))
parsed_table = [parse_row(row) for row in table]
# [1:] because first column is state name
for c in COLUMNS[1:]:
total = parsed_table[-1][c]
colsum = sum(row[c] or 0 for row in parsed_table)
assert (colsum == (total * 2))
month_chars = within_bbox(page.chars, (0, 35, self.PDF_WIDTH, 65))
month_text = collate_chars(month_chars)
assert (month_text == "November - 2015")
def test_pandas(self):
page = self.pdf.pages[0]
cropped = page.crop((0, 80, self.PDF_WIDTH, 485))
_table = cropped.extract_table(h="gutters", x_tolerance=5, y_tolerance=5, gutter_min_height=5)
table = pd.DataFrame(_table)
def parse_value(x):
if pd.isnull(x):
return None
return int(x.replace(",", ""))
table.columns = COLUMNS
table[table.columns[1:]] = table[table.columns[1:]].applymap(parse_value)
# [1:] because first column is state name
for c in COLUMNS[1:]:
total = table[c].iloc[-1]
colsum = table[c].sum()
assert colsum == (total * 2)
month_chars = within_bbox(page.chars, (0, 35, self.PDF_WIDTH, 65))
month_text = collate_chars(month_chars, x_tolerance=2)
assert month_text == "November - 2015"
def test_pandas(self):
page = self.pdf.pages[0]
cropped = page.crop((0, 80, self.PDF_WIDTH, 485))
_table = cropped.extract_table(h="gutters",
x_tolerance=5,
y_tolerance=5,
gutter_min_height=5)
table = pd.DataFrame(_table)
def parse_value(x):
if pd.isnull(x): return None
return int(x.replace(",", ""))
table.columns = COLUMNS
table[table.columns[1:]] = table[table.columns[1:]].applymap(
parse_value)
# [1:] because first column is state name
for c in COLUMNS[1:]:
total = table[c].iloc[-1]
colsum = table[c].sum()
assert (colsum == (total * 2))
month_chars = within_bbox(page.chars, (0, 35, self.PDF_WIDTH, 65))
month_text = collate_chars(month_chars, x_tolerance=2)
assert (month_text == "November - 2015")
def test_plain(self):
page = self.pdf.pages[0]
cropped = page.crop((0, 80, self.PDF_WIDTH, 485))
table = cropped.extract_table(h="gutters",
x_tolerance=5,
y_tolerance=5,
gutter_min_height=5)
def parse_value(k, x):
if k == 0: return x
if x == None: return None
return int(x.replace(",", ""))
def parse_row(row):
return dict(
(COLUMNS[i], parse_value(i, v)) for i, v in enumerate(row))
parsed_table = [parse_row(row) for row in table]
# [1:] because first column is state name
for c in COLUMNS[1:]:
total = parsed_table[-1][c]
colsum = sum(row[c] or 0 for row in parsed_table)
assert (colsum == (total * 2))
month_chars = within_bbox(page.chars, (0, 35, self.PDF_WIDTH, 65))
month_text = collate_chars(month_chars, x_tolerance=2)
assert (month_text == "November - 2015")
def _collate_chars(x):
return collate_chars(x, x_tolerance=1)
def _collate_chars(x):
return collate_chars(x, x_tolerance=1)
def test_plain(self):
page = self.pdf.pages[0]
cropped = page.crop((0, 80, self.PDF_WIDTH, 485))
table = cropped.extract_table(h="gutters", x_tolerance=5, y_tolerance=5, gutter_min_height=5)
def parse_value(k, x):
if k == 0:
return x
if x == None:
return None
return int(x.replace(",", ""))
def parse_row(row):
return dict((COLUMNS[i], parse_value(i, v)) for i, v in enumerate(row))
parsed_table = [parse_row(row) for row in table]
# [1:] because first column is state name
for c in COLUMNS[1:]:
total = parsed_table[-1][c]
colsum = sum(row[c] or 0 for row in parsed_table)
assert colsum == (total * 2)
month_chars = within_bbox(page.chars, (0, 35, self.PDF_WIDTH, 65))
month_text = collate_chars(month_chars, x_tolerance=2)
assert month_text == "November - 2015"