Python csv.DictReader方法代碼示例

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def ls(args):
    bucket = resources.s3.Bucket(args.billing_reports_bucket.format(account_id=ARN.get_account_id()))
    now = datetime.utcnow()
    year = args.year or now.year
    month = str(args.month or now.month).zfill(2)
    next_year = year + ((args.month or now.month) + 1) // 12
    next_month = str(((args.month or now.month) + 1) % 12).zfill(2)
    manifest_name = "aegea/{report}/{yr}{mo}01-{next_yr}{next_mo}01/{report}-Manifest.json"
    manifest_name = manifest_name.format(report=__name__, yr=year, mo=month, next_yr=next_year, next_mo=next_month)
    try:
        manifest = json.loads(bucket.Object(manifest_name).get().get("Body").read())
        for report_key in manifest["reportKeys"]:
            report = BytesIO(bucket.Object(report_key).get().get("Body").read())
            with gzip.GzipFile(fileobj=report) as fh:
                reader = csv.DictReader(fh)
                for line in reader:
                    page_output(tabulate(filter_line_items(reader, args), args))
    except ClientError as e:
        msg = 'Unable to get report {} from {}: {}. Run "aegea billing configure" to enable reports.'
        raise AegeaException(msg.format(manifest_name, bucket, e)) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def test_csv_response(self, testapp):
        # create a department and an LMPD uof incident
        department = Department.create(name="LM Police Department", short_name="LMPD", load_defaults=False)

        uof_check = dict(department_id=department.id, opaque_id="Check Opaque ID", occured_date=datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'), bureau="Check Bureau", division="Check Division", unit="Check Unit", platoon="Check Platoon", disposition="Check Disposition", use_of_force_reason="Check UOF Reason", officer_force_type="Check Officer Force Type", service_type="Check Service Type", arrest_made=False, arrest_charges="Check Arrest Charges", resident_injured=True, resident_hospitalized=False, resident_condition="Check Resident Condition", officer_injured=False, officer_hospitalized=False, officer_condition="Check Officer Condition", resident_identifier="Check Resident Identifier", resident_race="Check Resident Race", resident_sex="Check Resident Sex", resident_age="Check Resident Age", officer_race="Check Officer Race", officer_sex="Check Officer Sex", officer_age="Check Officer Age", officer_years_of_service="Check Officer Years Of Service", officer_identifier="Check Officer Identifier")

        UseOfForceIncidentLMPD.create(**uof_check)

        response = testapp.get("/department/{}/uof.csv".format(department.id))

        incidents = list(csv.DictReader(io.StringIO(response.text)))

        # build a variable to csv header lookup from the csv schema
        csv_schema = UseOfForceIncidentLMPD.get_csv_schema()
        schema_lookup = dict(zip([col[1] for col in csv_schema], [col[0] for col in csv_schema]))

        assert len(incidents) == 1
        for check_key in uof_check.keys():
            if check_key == 'department_id':
                continue
            assert str(uof_check[check_key]) == incidents[0][schema_lookup[check_key]] 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def test_csv_filtered_by_dept(self, testapp):
        # create a department
        department1 = Department.create(name="IM Police Department", short_name="IMPD", load_defaults=False)
        department2 = Department.create(name="B Police Department", short_name="BPD", load_defaults=False)

        incidentclass1 = getattr(importlib.import_module("comport.data.models"), "UseOfForceIncident{}".format(department1.short_name))
        incidentclass2 = getattr(importlib.import_module("comport.data.models"), "UseOfForceIncident{}".format(department2.short_name))

        incidentclass1.create(opaque_id="123ABC", department_id=department1.id)
        incidentclass2.create(opaque_id="123XYZ", department_id=department2.id)

        response1 = testapp.get("/department/{}/uof.csv".format(department1.id))
        response2 = testapp.get("/department/{}/uof.csv".format(department2.id))

        incidents1 = list(csv.DictReader(io.StringIO(response1.text)))
        incidents2 = list(csv.DictReader(io.StringIO(response2.text)))

        assert len(incidents1) == 1 and len(incidents2) == 1
        assert incidents1[0]['id'] == '123ABC' and incidents2[0]['id'] == '123XYZ' 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def clean(self):
        if self.batch_file and self.batch_file.file:
            csvfile = csv.DictReader(self.batch_file.file, delimiter="\t")
            row = csvfile.next()
            for field in self.core_fields:
                if field not in row.keys():
                    raise ValidationError('CSV File does not have the necessary field: '+ field)

            uris = []
            for row in csvfile:
                fcode = row.get("FEATURE_CODE")
                if not fcode:
                    raise ValidationError("A Feature code is missing")
                uri = row.get("URIS").split("|")[0]
                if not uri:
                    raise ValidationError('CSV file is missing a uri')
                if uri in uris:
                    raise ValidationError('duplicate URI detected')
            uris.append(uri) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def get_msr_paraphrase() -> Dict[str, List[Dict[str, str]]]:

    url = 'https://raw.githubusercontent.com/wasiahmad/paraphrase_identification/master/dataset/msr-paraphrase-corpus/msr_paraphrase_{}.txt'  # NOQA
    root = download.get_cache_directory(os.path.join('datasets', 'msr_paraphrase'))

    def creator(path):
        dataset = {}
        fieldnames = ('quality', 'id1', 'id2', 'string1', 'string2')
        for split in ('train', 'test'):
            data_path = gdown.cached_download(url.format(split))
            with io.open(data_path, 'r', encoding='utf-8') as f:
                f.readline()  # skip header
                reader = csv.DictReader(f, delimiter='\t', fieldnames=fieldnames)
                dataset[split] = [dict(row) for row in reader]

        with io.open(path, 'wb') as f:
            pickle.dump(dataset, f)
        return dataset

    def loader(path):
        with io.open(path, 'rb') as f:
            return pickle.load(f)

    pkl_path = os.path.join(root, 'msr_paraphrase.pkl')
    return download.cache_or_load_file(pkl_path, creator, loader) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def query_landsat_catalogue(collection_file, cc_limit, date_start, date_end, wr2path, wr2row,
                            sensor, latest=False):
    """Query the Landsat index catalogue and retrieve urls for the best images found."""
    print("Searching for Landsat-{} images in catalog...".format(sensor))
    cc_values = []
    all_urls = []
    all_acqdates = []
    with open(collection_file) as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            year_acq = int(row['DATE_ACQUIRED'][0:4])
            month_acq = int(row['DATE_ACQUIRED'][5:7])
            day_acq = int(row['DATE_ACQUIRED'][8:10])
            acqdate = datetime.datetime(year_acq, month_acq, day_acq)
            if int(row['WRS_PATH']) == int(wr2path) and int(row['WRS_ROW']) == int(wr2row) \
                    and row['SENSOR_ID'] == sensor and float(row['CLOUD_COVER']) <= cc_limit \
                    and date_start < acqdate < date_end:
                all_urls.append(row['BASE_URL'])
                cc_values.append(float(row['CLOUD_COVER']))
                all_acqdates.append(acqdate)

    if latest and all_urls:
        return [sort_url_list(cc_values, all_acqdates, all_urls).pop()]
    return sort_url_list(cc_values, all_acqdates, all_urls) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def query_sentinel2_catalogue(collection_file, cc_limit, date_start, date_end, tile, latest=False):
    """Query the Sentinel-2 index catalogue and retrieve urls for the best images found."""
    print("Searching for Sentinel-2 images in catalog...")
    cc_values = []
    all_urls = []
    all_acqdates = []
    with open(collection_file) as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            year_acq = int(row['SENSING_TIME'][0:4])
            month_acq = int(row['SENSING_TIME'][5:7])
            day_acq = int(row['SENSING_TIME'][8:10])
            acqdate = datetime.datetime(year_acq, month_acq, day_acq)
            if row['MGRS_TILE'] == tile and float(row['CLOUD_COVER']) <= cc_limit \
                    and date_start < acqdate < date_end:
                all_urls.append(row['BASE_URL'])
                cc_values.append(float(row['CLOUD_COVER']))
                all_acqdates.append(acqdate)

    if latest and all_urls:
        return [sort_url_list(cc_values, all_acqdates, all_urls).pop()]
    return sort_url_list(cc_values, all_acqdates, all_urls) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def find_best_hyper(dataset, model, metric="test_rmse"):
    path = "../../result/{}/{}/".format(model, dataset)

    # Get list of hyperparameters
    names, losses, stds = [], [], []
    for root, dirs, files in walk_level(path, level=0):
        for dir_name in dirs:
            loss = []
            if os.path.isfile(path + dir_name + "/results.csv"):
                with open(path + dir_name + "/results.csv") as file:
                    reader = csv.DictReader(file)
                    for row in reader:
                        loss.append(row[metric])

                names.append(dir_name)
                losses.append(float(loss[0]))
                stds.append(float(loss[1]))

    # Sort by loss
    losses, stds, names = zip(*sorted(zip(losses, stds, names)))

    # Choose lowest loss hyper
    path += names[np.argmin(losses)] + '/'

    return path 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def write(self, ordered_dict):
        '''
        write an entry
        :param ordered_dict: something like {'name':'exp1', 'acc':90.5, 'epoch':50}
        :return:
        '''
        if os.path.exists(self.filename) == False:
            headers = list(ordered_dict.keys())
            prev_rec = None
        else:
            with open(self.filename) as f:
                reader = csv.DictReader(f)
                headers = reader.fieldnames
                prev_rec = [row for row in reader]
            headers = self.merge_headers(headers, list(ordered_dict.keys()))

        with open(self.filename, 'w', newline='') as f:
            writer = csv.DictWriter(f, headers)
            writer.writeheader()
            if not prev_rec == None:
                writer.writerows(prev_rec)
            writer.writerow(ordered_dict) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def csv_to_deck(csv_path):
    """Creates a Tinycards deck from a CSV file.

    The CSV file is expected to have two columns named 'front' and 'back'.
    """
    # Create new deck.
    tinycards = Tinycards(user_identifier, user_password)
    deck = Deck('French Words')
    deck = tinycards.create_deck(deck)

    # Extract data from CSV file.
    word_pairs = []
    with open(csv_path, 'r') as csv_file:
        csv_reader = csv.DictReader(csv_file)
        for row in csv_reader:
            current_word_pair = (row['front'], row['back'])
            word_pairs.append(current_word_pair)

    # Populate deck with cards from CSV data.
    for pair in word_pairs:
        deck.add_card(pair)

    # Save changes to Tinycards.
    tinycards.update_deck(deck) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def add_cards_from_csv(self, csv_file,
                           front_column='front',
                           back_column='back'):
        """Add word pairs from a CSV file as cards to the deck.

        Args:
            csv_file: The file buffer that contains the CSV data.
            front_column (str): Optional name for the 'front' column.
            back_column (str): Optional name for the 'back' column.

        Example:
            >>> with open(csv_path, 'r') as csv_file:
            >>>     deck.add_cards_from_csv(csv_file)

        """
        csv_reader = csv.DictReader(csv_file)
        for row in csv_reader:
            current_word_pair = (row[front_column], row[back_column])
            self.add_card(current_word_pair) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def import_business_data_relations(self, data_source):
        """
        Imports business data relations
        """
        if isinstance(data_source, str):
            data_source = [data_source]

        for path in data_source:
            if os.path.isabs(path):
                if os.path.isfile(os.path.join(path)):
                    relations = csv.DictReader(open(path, "r"))
                    RelationImporter().import_relations(relations)
                else:
                    utils.print_message("No file found at indicated location: {0}".format(path))
                    sys.exit()
            else:
                utils.print_message(
                    "ERROR: The specified file path appears to be relative. \
                    Please rerun command with an absolute file path."
                )
                sys.exit() 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def insert_question_to_sqlt():
    question_set = []
    last_question = ""
    with open(CORPUS_DIR+"/"+WIKI_QA_TSV) as file:
        wiki_file = csv.DictReader(file, dialect='excel-tab')
        if wiki_file is not None:
            for row in wiki_file:
                if row['Question'] != last_question:
                    question = (row['Question'], )
                    question_set.append(question)
                    last_question = row['Question']

    if question_set is not None:
        sqlt_man = SqLiteManager()
        # sqlt_man.remove_old_results()
        sqlt_man.remove_all_data()
        logger.info("Removed Old test results")
        sqlt_man.insert_many_question(question_set)
        logger.info("Inserted {0} questions".format(sqlt_man.get_question_count())) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def generate_modified_file(src, dst, sample, corrupt):
    """원본 파일을 샘플링하고 결측치 넣은 새 파일 생성"""

    # 랜덤 시드 고정. 매번 동일한 결과가 보장되도록.
    random.seed(0)
    with open(src, 'r') as fr:
        with open(dst, 'w') as fw:
            csvr = csv.DictReader(fr)
            csvw = csv.DictWriter(fw, csvr.fieldnames)

            csvw.writeheader()

            rows = csvr

            # 샘플링
            if sample:
                rows = (row for row in rows if random.random() <= SAMPLE_RATE)
            # 결측치 추가
            if corrupt:
                rows = (corrupt_row(row) for row in rows)

            csvw.writerows(rows) 

# 需要導入模塊: import csv [as 別名]
# 或者: from csv import DictReader [as 別名]
def handle(self, *args, **options):
        # Get the only instance of Magazine Department Index Page
        magazine_department_index_page = MagazineDepartmentIndexPage.objects.get()

        with open(options["file"]) as import_file:
            departments = csv.DictReader(import_file)

            for department in departments:
                import_department = MagazineDepartment(
                    title=department["title"],
                )

                # Add department to site page hiererchy
                magazine_department_index_page.add_child(instance=import_department)
                magazine_department_index_page.save()

        self.stdout.write("All done!")