def download_organizations():
"Download organizations JSON and extract its properties"
response = requests.get(URL)
data = response.json()
organizations = [organization["properties"] for organization in data["features"]]
return rows.import_from_dicts(organizations)
def test_import_from_dicts_return_desired_data(self):
table = rows.import_from_dicts(self.data)
self.assertEqual(len(table), 3)
self.assertEqual(len(table.fields), 4)
self.assertEqual(
set(table.field_names), set(["ids", "name", "number", "other"])
)
self.assertEqual(table.fields["name"], rows.fields.TextField)
self.assertEqual(table.fields["ids"], rows.fields.TextField)
self.assertEqual(table.fields["number"], rows.fields.IntegerField)
self.assertEqual(table.fields["other"], rows.fields.FloatField)
self.assertEqual(table[0].name, "Álvaro")
self.assertEqual(table[0].ids, "123")
self.assertEqual(table[0].number, 3)
self.assertEqual(table[0].other, None)
self.assertEqual(table[1].name, "Test")
self.assertEqual(table[1].ids, "456")
self.assertEqual(table[1].number, None)
self.assertEqual(table[1].other, None)
self.assertEqual(table[2].name, "Python")
self.assertEqual(table[2].ids, "123, 456")
self.assertEqual(table[2].number, None)
self.assertEqual(table[2].other, 3.14)
def download_organizations():
'Download organizations JSON and extract its properties'
page = urllib.urlopen(URL)
data = json.loads(page.read())
organizations = [organization['properties']
for organization in data['features']]
return rows.import_from_dicts(organizations)
def test_export_callback(self):
table = rows.import_from_dicts([{"id": number} for number in range(10)])
myfunc = mock.Mock()
rows.export_to_sqlite(table, ":memory:", callback=myfunc, batch_size=3)
self.assertEqual(myfunc.call_count, 4)
self.assertEqual(
[(x[0][0], x[0][1]) for x in myfunc.call_args_list],
[(3, 3), (3, 6), (3, 9), (1, 10)],
)
def test_import_field_limit(self):
temp = tempfile.NamedTemporaryFile(delete=False)
filename = "{}.{}".format(temp.name, self.file_extension)
self.files_to_delete.append(filename)
table = rows.import_from_dicts([{"f1": "a" * 132000}])
rows.export_to_csv(table, filename)
# The following line must not raise the exception:
# `_csv.Error: field larger than field limit (131072)`
new = rows.import_from_csv(filename)
def test_export_to_dicts(self):
table = rows.import_from_dicts(self.data)
result = rows.export_to_dicts(table)
full_data = [
{"name": "Álvaro", "ids": "123", "number": 3, "other": None},
{"name": "Test", "ids": "456", "number": None, "other": None},
{"name": "Python", "ids": "123, 456", "number": None, "other": 3.14},
]
self.assertEqual(len(result), len(table))
for expected, actual in zip(full_data, result):
self.assertDictEqual(expected, actual)
def test_import_from_dicts_accepts_generator(self):
max_size = 1000
samples = 200
generator = utils.LazyDictGenerator(max_size)
datagen = iter(generator)
table = rows.import_from_dicts(datagen, lazy=True, samples=samples)
# `create_table` will consume the whole generator
self.assertEqual(generator.last, max_size - 1)
data = list(table)
self.assertTrue(len(data), max_size)
self.assertEqual(generator.last, max_size - 1)
def test_import_from_dicts_accepts_generator(self):
max_size = 1000
samples = 200
generator = utils.LazyDictGenerator(max_size)
datagen = iter(generator)
table = rows.import_from_dicts(datagen, lazy=True, samples=samples)
# `create_table` will consume the whole generator
self.assertEqual(generator.last, max_size - 1)
data = list(table)
self.assertTrue(len(data), max_size)
self.assertEqual(generator.last, max_size - 1)
def test_import_from_dicts_maintains_header_order(self):
headers = list(string.ascii_lowercase)
random.shuffle(headers)
data = [
OrderedDict([(header, 1) for header in headers]),
OrderedDict([(header, 2) for header in headers]),
OrderedDict([(header, 3) for header in headers]),
OrderedDict([(header, 4) for header in headers]),
OrderedDict([(header, 5) for header in headers]),
]
table = rows.import_from_dicts(data)
self.assertEqual(table.field_names, headers)
def test_import_from_dicts_uses_create_table(self, mocked_create_table):
mocked_create_table.return_value = 42
kwargs = {'some_key': 123, 'other': 456, }
result = rows.import_from_dicts(self.data, **kwargs)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
self.assertEqual(result, 42)
call = mocked_create_table.call_args
kwargs['meta'] = {'imported_from': 'dicts', }
self.assertEqual(call[1], kwargs)
def test_import_from_dicts_maintains_header_order(self):
headers = list(string.ascii_lowercase)
random.shuffle(headers)
data = [
OrderedDict([(header, 1) for header in headers]),
OrderedDict([(header, 2) for header in headers]),
OrderedDict([(header, 3) for header in headers]),
OrderedDict([(header, 4) for header in headers]),
OrderedDict([(header, 5) for header in headers]),
]
table = rows.import_from_dicts(data)
self.assertEqual(table.field_names, headers)
def test_import_from_dicts_uses_create_table(self, mocked_create_table):
mocked_create_table.return_value = 42
kwargs = {'some_key': 123, 'other': 456, }
result = rows.import_from_dicts(self.data, **kwargs)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
self.assertEqual(result, 42)
call = mocked_create_table.call_args
kwargs['meta'] = {'imported_from': 'dicts', }
self.assertEqual(call[1], kwargs)
def execute(self, year, action):
logging.info(f"[Budget-CE] Starting for {year} and action {action}")
self.select_year(year)
self.select_month(
"Dezembro") # December has the cumulative for the year
self.select_action(action)
self.select_modality_91("TUDO")
self.select_report("Outros", "PA")
filename = self.do_search()
result = self.parse_budget(filename, year, action)
for row in rows.import_from_dicts(result):
yield row._asdict()
def extract_boletim(state, data):
table = rows.import_from_dicts(
data,
force_types={
"date": rows.fields.DateField,
"notes": rows.fields.TextField,
"state": rows.fields.TextField,
"url": rows.fields.TextField,
},
)
for row in table:
row = row._asdict()
yield row
def test_import_from_dicts_uses_create_table(self, mocked_create_table):
mocked_create_table.return_value = 42
kwargs = {"some_key": 123, "other": 456}
result = rows.import_from_dicts(self.data, **kwargs)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
self.assertEqual(result, 42)
call = mocked_create_table.call_args
kwargs["meta"] = {"imported_from": "dicts"}
kwargs["samples"] = None
self.assertEqual(call[1], kwargs)
def csv_to_sqlite(
input_filename,
output_filename,
samples=None,
dialect=None,
batch_size=10000,
encoding="utf-8",
callback=None,
force_types=None,
chunk_size=8388608,
table_name="table1",
schema=None,
):
"Export a CSV file to SQLite, based on field type detection from samples"
# TODO: automatically detect encoding if encoding == `None`
# TODO: should be able to specify fields
if dialect is None: # Get a sample to detect dialect
fobj = open_compressed(input_filename, mode="rb")
sample = fobj.read(chunk_size)
dialect = rows.plugins.csv.discover_dialect(sample, encoding=encoding)
elif isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
if schema is None: # Identify data types
fobj = open_compressed(input_filename, encoding=encoding)
data = list(islice(csv.DictReader(fobj, dialect=dialect), samples))
schema = rows.import_from_dicts(data).fields
if force_types is not None:
schema.update(force_types)
# Create lazy table object to be converted
# TODO: this lazyness feature will be incorported into the library soon so
# we can call here `rows.import_from_csv` instead of `csv.reader`.
reader = csv.reader(
open_compressed(input_filename, encoding=encoding), dialect=dialect
)
header = make_header(next(reader)) # skip header
table = rows.Table(fields=OrderedDict([(field, schema[field]) for field in header]))
table._rows = reader
# Export to SQLite
return rows.export_to_sqlite(
table,
output_filename,
table_name=table_name,
batch_size=batch_size,
callback=callback,
)
def test_import_from_dicts_uses_create_table(self, mocked_create_table):
mocked_create_table.return_value = 42
kwargs = {"some_key": 123, "other": 456}
result = rows.import_from_dicts(self.data, **kwargs)
self.assertTrue(mocked_create_table.called)
self.assertEqual(mocked_create_table.call_count, 1)
self.assertEqual(result, 42)
call = mocked_create_table.call_args
kwargs["meta"] = {"imported_from": "dicts"}
kwargs["samples"] = None
self.assertEqual(call[1], kwargs)
def pdf_to_csv(input_filename, output_filename):
total_pages = rows.plugins.pdf.number_of_pages(input_filename)
pdf = rows.plugins.pdf.PyMuPDFBackend(input_filename)
result = []
for page_number in range(1, total_pages + 1):
page = list(next(pdf.objects(page_numbers=(page_number, ))))
data = list(rows.plugins.utils.ipartition(page, 4))
header = [obj.text for obj in data[0]]
for row in data[1:]:
row = dict(zip(header, [obj.text for obj in row]))
row["codigo_ibge"] = row.pop("IBGE")
row["perfil"] = row.pop("Perfil Município")
result.append(row)
table = rows.import_from_dicts(result)
rows.export_to_csv(table, output_filename)
def parse_file(filename):
"""Parse Amazonas' PDF file containing state employee information"""
total_pages = rows.plugins.pdf.number_of_pages(filename)
result = []
for page in range(1, total_pages + 1):
table = rows.import_from_pdf(
filename,
page_numbers=(page, ),
starts_after="NOME",
fields=PDF_FIELD_TYPES,
skip_header=True,
)
for row in table:
result.append(convert_row(row))
return rows.import_from_dicts(result)
def convert(state, input_filename, output_filename):
table = rows.import_from_csv(
input_filename,
force_types={
"confirmed": rows.fields.IntegerField,
"deaths": rows.fields.IntegerField,
},
)
state_cities = ["TOTAL NO ESTADO", "Importados/Indefinidos"] + sorted(
row.municipio for row in cities if row.uf == state
)
confirmed, deaths, dates = {}, {}, []
for row in table:
row_confirmed = row.confirmed or 0
row_date = row.date
row_deaths = row.deaths or 0
row_name = row.city if row.place_type == "city" else "TOTAL NO ESTADO"
if row_name not in state_cities:
print(f"ERRO: município {repr(row_name)} não encontrado.")
continue
if row_confirmed == 0 and row_deaths == 0:
# No data for this city in this day
continue
if row_date not in confirmed:
confirmed[row_date] = {}
if row_date not in deaths:
deaths[row_date] = {}
if row_name in confirmed[row_date] or row_name in deaths[row_date]:
print(f"ERRO: conflito em {repr(row_name)} para {row_date}.")
continue
confirmed[row_date][row_name] = row_confirmed
deaths[row_date][row_name] = row_deaths
result = []
dates = sorted(confirmed.keys(), reverse=True)
for city in state_cities:
row = {"municipio": city}
for date in dates:
date_str = f"{date.day:02d}_{date.month:02d}"
row[f"confirmados_{date_str}"] = confirmed[date].get(city, None)
row[f"mortes_{date_str}"] = deaths[date].get(city, None)
result.append(row)
rows.export_to_csv(rows.import_from_dicts(result), output_filename)
def parse_boletim(self, state, data):
self.logger.info(f"Parsing {state} boletim")
try:
reports = rows.import_from_dicts(
data,
force_types={
"date": rows.fields.DateField,
"notes": rows.fields.TextField,
"state": rows.fields.TextField,
"url": rows.fields.TextField,
},
)
except Exception as exp:
self.errors[state].append(("boletim", state, f"{exp.__class__.__name__}: {exp}"))
return
for report in reports:
report = report._asdict()
self.logger.debug(report)
self.boletim_writer.writerow(report)
def main():
csv_filename = pathlib.Path('data/names.csv')
output = pathlib.Path('output/names-stats.csv')
if not csv_filename.parent.exists():
os.makedirs(str(csv_filename.parent.absolute()), exist_ok=True)
if not output.parent.exists():
os.makedirs(str(output.parent.absolute()), exist_ok=True)
requests_cache.install_cache('nomes-ibge')
result = []
for name in unique_names(csv_filename):
print(name)
row = download_name_stats(name)
if row is None:
continue
row['alternative_names'] = '|'.join(row['alternative_names'])
result.append(row)
table = rows.import_from_dicts(result)
table.order_by('name')
rows.utils.export_to_uri(table, str(output.absolute()))
def test_export_to_dicts(self):
table = rows.import_from_dicts(self.data)
result = rows.export_to_dicts(table)
full_data = [
{'name': 'Álvaro',
'ids': '123',
'number': 3,
'other': None, },
{'name': 'Test',
'ids': '456',
'number': None,
'other': None, },
{'name': 'Python',
'ids': '123, 456',
'number': None,
'other': 3.14, },]
self.assertEqual(len(result), len(table))
for expected, actual in zip(full_data, result):
self.assertDictEqual(expected, actual)
def test_export_to_dicts(self):
table = rows.import_from_dicts(self.data)
result = rows.export_to_dicts(table)
full_data = [
{'name': 'Álvaro',
'ids': '123',
'number': 3,
'other': None, },
{'name': 'Test',
'ids': '456',
'number': None,
'other': None, },
{'name': 'Python',
'ids': '123, 456',
'number': None,
'other': 3.14, },]
self.assertEqual(len(result), len(table))
for expected, actual in zip(full_data, result):
self.assertDictEqual(expected, actual)
def csv2sqlite(
input_filename,
output_filename,
table_name,
samples=30000,
batch_size=10000,
encoding="utf-8",
callback=None,
force_types=None,
):
# Identify data types
fobj = open_compressed(input_filename, encoding)
reader = csv.reader(fobj)
header = next(reader)
data = []
for index, row in enumerate(reader):
row = dict(zip(header, row))
if index == samples:
break
data.append(row)
fields = rows.import_from_dicts(data, import_fields=header).fields
if force_types is not None:
fields.update(force_types)
# Create lazy table object to be converted
table = rows.Table(fields=fields)
reader = csv.reader(open_compressed(input_filename, encoding))
next(reader) # skip header
table._rows = reader
# Export to SQLite
rows.export_to_sqlite(table,
output_filename,
table_name=table_name,
callback=callback,
batch_size=batch_size)
def parse_state_file(self, response):
state = response.meta["state"]
if response.status >= 400:
self.errors[state].append(
("connection", state, f"HTTP status code: {response.status}")
)
else:
response_data = json.load(io.BytesIO(response.body))
try:
self.parse_boletim(state, response_data["reports"])
except Exception as exp:
self.errors[state].append(
("boletim", state, f"{exp.__class__.__name__}: {exp}")
)
try:
self.parse_caso(state, response_data["cases"])
except Exception as exp:
self.errors[state].append(
("caso", state, f"{exp.__class__.__name__}: {exp}")
)
if self.errors[state]:
error_counter = Counter(error[0] for error in self.errors[state])
error_counter_str = ", ".join(
f"{error_type}: {count}" for error_type, count in error_counter.items()
)
self.logger.error(
f"{len(self.errors[state])} errors found when parsing {state} ({error_counter_str})"
)
error_header = ("sheet", "state", "message")
errors = rows.import_from_dicts(
[dict(zip(error_header, row)) for row in self.errors[state]]
)
filename = ERROR_PATH / f"errors-{state}.csv"
if not filename.parent.exists():
filename.parent.mkdir(parents=True)
rows.export_to_csv(errors, filename)
def test_import_from_dicts_return_desired_data(self):
table = rows.import_from_dicts(self.data)
self.assertEqual(len(table), 3)
self.assertEqual(len(table.fields), 4)
self.assertEqual(set(table.field_names),
set(["ids", "name", "number", "other"]))
self.assertEqual(table.fields["name"], rows.fields.TextField)
self.assertEqual(table.fields["ids"], rows.fields.TextField)
self.assertEqual(table.fields["number"], rows.fields.IntegerField)
self.assertEqual(table.fields["other"], rows.fields.FloatField)
self.assertEqual(table[0].name, "Álvaro")
self.assertEqual(table[0].ids, "123")
self.assertEqual(table[0].number, 3)
self.assertEqual(table[0].other, None)
self.assertEqual(table[1].name, "Test")
self.assertEqual(table[1].ids, "456")
self.assertEqual(table[1].number, None)
self.assertEqual(table[1].other, None)
self.assertEqual(table[2].name, "Python")
self.assertEqual(table[2].ids, "123, 456")
self.assertEqual(table[2].number, None)
self.assertEqual(table[2].other, 3.14)
def test_import_from_dicts_return_desired_data(self):
table = rows.import_from_dicts(self.data)
self.assertEqual(len(table), 3)
self.assertEqual(len(table.fields), 4)
self.assertEqual(set(table.field_names),
set(['ids', 'name', 'number', 'other']))
self.assertEqual(table.fields['name'], rows.fields.TextField)
self.assertEqual(table.fields['ids'], rows.fields.TextField)
self.assertEqual(table.fields['number'], rows.fields.IntegerField)
self.assertEqual(table.fields['other'], rows.fields.FloatField)
self.assertEqual(table[0].name, 'Álvaro')
self.assertEqual(table[0].ids, '123')
self.assertEqual(table[0].number, 3)
self.assertEqual(table[0].other, None)
self.assertEqual(table[1].name, 'Test')
self.assertEqual(table[1].ids, '456')
self.assertEqual(table[1].number, None)
self.assertEqual(table[1].other, None)
self.assertEqual(table[2].name, 'Python')
self.assertEqual(table[2].ids, '123, 456')
self.assertEqual(table[2].number, None)
self.assertEqual(table[2].other, 3.14)
def test_import_from_dicts_return_desired_data(self):
table = rows.import_from_dicts(self.data)
self.assertEqual(len(table), 3)
self.assertEqual(len(table.fields), 4)
self.assertEqual(set(table.field_names),
set(['ids', 'name', 'number', 'other']))
self.assertEqual(table.fields['name'], rows.fields.TextField)
self.assertEqual(table.fields['ids'], rows.fields.TextField)
self.assertEqual(table.fields['number'], rows.fields.IntegerField)
self.assertEqual(table.fields['other'], rows.fields.FloatField)
self.assertEqual(table[0].name, 'Álvaro')
self.assertEqual(table[0].ids, '123')
self.assertEqual(table[0].number, 3)
self.assertEqual(table[0].other, None)
self.assertEqual(table[1].name, 'Test')
self.assertEqual(table[1].ids, '456')
self.assertEqual(table[1].number, None)
self.assertEqual(table[1].other, None)
self.assertEqual(table[2].name, 'Python')
self.assertEqual(table[2].ids, '123, 456')
self.assertEqual(table[2].number, None)
self.assertEqual(table[2].other, 3.14)
def to_csv(self, path: Path) -> Path:
data = (
{"date": key, "value": self.data[key]} for key in sorted(self.data.keys())
)
export_to_csv(import_from_dicts(data), path)
return path
def pgimport(
filename,
database_uri,
table_name,
encoding="utf-8",
dialect=None,
create_table=True,
schema=None,
callback=None,
timeout=0.1,
chunk_size=8388608,
max_samples=10000,
):
"""Import data from CSV into PostgreSQL using the fastest method
Required: psql command
"""
fobj = open_compressed(filename, mode="r", encoding=encoding)
sample = fobj.read(chunk_size)
if dialect is None: # Detect dialect
dialect = rows.plugins.csv.discover_dialect(
sample.encode(encoding), encoding=encoding
)
elif isinstance(dialect, six.text_type):
dialect = csv.get_dialect(dialect)
if schema is None:
# Detect field names
reader = csv.reader(io.StringIO(sample), dialect=dialect)
field_names = [slug(field_name) for field_name in next(reader)]
else:
field_names = list(schema.keys())
if create_table:
if schema is None:
data = [
dict(zip(field_names, row))
for row in itertools.islice(reader, max_samples)
]
table = rows.import_from_dicts(data)
field_types = [table.fields[field_name] for field_name in field_names]
else:
field_types = list(schema.values())
columns = [
"{} {}".format(name, POSTGRESQL_TYPES.get(type_, DEFAULT_POSTGRESQL_TYPE))
for name, type_ in zip(field_names, field_types)
]
create_table = SQL_CREATE_TABLE.format(
table_name=table_name, field_types=", ".join(columns)
)
execute_command(get_psql_command(create_table, database_uri=database_uri))
# Prepare the `psql` command to be executed based on collected metadata
command = get_psql_copy_command(
database_uri=database_uri,
dialect=dialect,
direction="FROM",
encoding=encoding,
header=field_names,
table_name=table_name,
)
rows_imported, error = 0, None
fobj = open_compressed(filename, mode="rb")
try:
process = subprocess.Popen(
shlex.split(command),
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
data = fobj.read(chunk_size)
total_written = 0
while data != b"":
written = process.stdin.write(data)
total_written += written
if callback:
callback(written, total_written)
data = fobj.read(chunk_size)
stdout, stderr = process.communicate()
if stderr != b"":
raise RuntimeError(stderr.decode("utf-8"))
rows_imported = int(stdout.replace(b"COPY ", b"").strip())
except FileNotFoundError:
raise RuntimeError("Command `psql` not found")
except BrokenPipeError:
raise RuntimeError(process.stderr.read().decode("utf-8"))
return {"bytes_written": total_written, "rows_imported": rows_imported}
import argparse
import os
import rows
import rows.utils
from ba_parse_pdf import extract_table as ba_extract_table
from sc_parse_pdf import extract_table as sc_extract_table
extract_table_functions = {"BA": ba_extract_table, "SC": sc_extract_table}
parser = argparse.ArgumentParser()
parser.add_argument("state", choices=["BA", "SC"])
parser.add_argument("input_uri")
parser.add_argument("output_filename")
args = parser.parse_args()
input_uri, delete = args.input_uri, False
if input_uri.lower().startswith("http://") or input_uri.lower().startswith(
"https://"):
source = rows.utils.download_file(input_uri, progress=True, detect=False)
input_uri, delete = source.uri, True
data = extract_table_functions[args.state](input_uri)
table = rows.import_from_dicts(data)
rows.export_to_csv(table, args.output_filename)
if delete:
os.unlink(input_uri)
if 'db.sqlite3' not in os.listdir(settings.BASE_DIR):
os.system("""
rm -rf db.sqlite3 &&
touch db.sqlite3 &&
python manage.py makemigrations
python manage.py migrate
""")
arquivo = open('db.json', mode='r').read()
data = json.loads(arquivo)
for (k, v) in data.items():
print('\n', k)
if type(v).__name__ == 'list':
data = rows.import_from_dicts(v)
for row in data:
if k == 'calendario_temporada':
try:
pais = Pais.objects.get(pais=row.localizacao['pais'])
except Pais.DoesNotExist:
pais = Pais.objects.create(
pais=row.localizacao['pais']
)
try:
cidade = Cidade.objects.get(cidade=row.localizacao['cidade'])
except Cidade.DoesNotExist:
cidade = Cidade.objects.create(
cidade=row.localizacao['cidade'],
def test_extract_table_3():
expected = rows.import_from_csv(DATA_PATH / "expected_3.csv")
result = rows.import_from_dicts(extract_table(DATA_PATH / "example_3.pdf"))
assert_equal(result, expected)
def test_extract_table_2():
expected = []
result = rows.import_from_dicts(
extract_table(DATA_PATH / "example_2.pdf")[: len(expected)]
)
assert_equal(result, expected)
import os
import rows
properties_of_interest = []
for result in os.listdir("results"):
results = rows.import_from_csv("results/" + result)
properties = [
p._asdict() for p in results
if p.for_rent and p.property_type == "casa" and p.rent_price <= 1500
and "campinas" in p.city.lower()
]
properties_of_interest.extend(properties)
table = rows.import_from_dicts(properties_of_interest)
rows.export_to_csv(table, "properties_of_interest_2.csv")
def convert_names(names, csv_output):
table = rows.import_from_dicts(
[name_ibge(name) for name in names if name_ibge(name)])
rows.export_to_csv(table, csv_output)
def export(path: Path = DEFAULT_EXPORT_FILE) -> None:
"""Export all data to CSV."""
table = import_from_dicts(data())
export_to_csv(table, path)
def test_export_callback(self):
table = rows.import_from_dicts([{"id": number} for number in range(10)])
myfunc = mock.Mock()
rows.export_to_csv(table, callback=myfunc, batch_size=3)
self.assertEqual(myfunc.call_count, 4)
self.assertEqual([x[0][0] for x in myfunc.call_args_list], [3, 6, 9, 10])
def pgimport(filename,
database_uri,
table_name,
encoding='utf-8',
create_table=True,
progress=False,
timeout=0.1,
chunk_size=8388608,
max_samples=10000):
"""Import data from CSV into PostgreSQL using the fastest method
Required: psql command
"""
# Extract a sample from the CSV to detect its dialect and header
fobj = open_compressed(filename, mode='r', encoding=encoding)
sample = fobj.read(chunk_size).encode(encoding)
dialect = rows.plugins.csv.discover_dialect(sample, encoding=encoding)
reader = csv.reader(io.StringIO(sample.decode(encoding)))
field_names = [slug(field_name) for field_name in next(reader)]
if create_table:
data = [
dict(zip(field_names, row))
for row in itertools.islice(reader, max_samples)
]
table = rows.import_from_dicts(data)
field_types = [table.fields[field_name] for field_name in field_names]
columns = [
'{} {}'.format(
name, POSTGRESQL_TYPES.get(type_, DEFAULT_POSTGRESQL_TYPE))
for name, type_ in zip(field_names, field_types)
]
create_table = SQL_CREATE_TABLE.format(
table_name=table_name,
field_types=', '.join(columns),
)
execute_command(
get_psql_command(create_table, database_uri=database_uri))
# Prepare the `psql` command to be executed based on collected metadata
command = get_psql_copy_command(
database_uri=database_uri,
table_name=table_name,
header=field_names,
dialect=dialect,
encoding=encoding,
)
rows_imported, error, total_size = 0, None, None
try:
total_size = uncompressed_size(filename)
except (RuntimeError, ValueError):
pass
if progress:
progress_bar = tqdm(
desc='Importing data',
unit='bytes',
unit_scale=True,
unit_divisor=1024,
total=total_size,
)
fobj = open_compressed(filename, mode='rb')
try:
process = subprocess.Popen(
shlex.split(command),
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
data = fobj.read(chunk_size)
while data != b'':
data_written = process.stdin.write(data)
if progress:
progress_bar.update(data_written)
data = fobj.read(chunk_size)
stdout, stderr = process.communicate()
if stderr != b'':
raise RuntimeError(stderr.decode('utf-8'))
rows_imported = int(stdout.replace(b'COPY ', b'').strip())
except FileNotFoundError:
raise RuntimeError('Command `psql` not found')
except BrokenPipeError:
raise RuntimeError(process.stderr.read().decode('utf-8'))
if progress:
progress_bar.close()
return rows_imported
def to_csv(self, path: Path) -> Path:
"""Export the adapter's data to a CSV file."""
table = import_from_dicts(self.export())
export_to_csv(table, path)
return path
def process_item(self, item, spider):
row = import_from_dicts([dict(item)])
logger.debug(row)
export_to_sqlite(row, self.conn, self.table)
return item
