def main():
parser = argparse.ArgumentParser()
parser.add_argument("-s",
"--selective_harvesting",
action="store_true",
help=ARG_HELP_STRINGS["selective_harvesting"])
args = parser.parse_args()
with open("harvest_list.csv", "r") as harvest_list:
reader = oat.UnicodeDictReader(harvest_list, encoding="utf-8")
for line in reader:
basic_url = line["basic_url"]
if line["active"] == "TRUE":
oat.print_g("Starting harvest from source " + basic_url)
oai_set = line["oai_set"] if len(line["oai_set"]) > 0 else None
prefix = line["metadata_prefix"] if len(
line["metadata_prefix"]) > 0 else None
processing = line["processing"] if len(
line["processing"]) > 0 else None
oat.oai_harvest(basic_url, prefix, oai_set, processing,
args.selective_harvesting)
now = datetime.datetime.now()
date_string = now.strftime("%Y_%m_%d")
file_name = "oai_harvest_" + date_string + ".csv"
target = os.path.join("..", line["directory"], file_name)
os.rename("out.csv", target)
else:
oat.print_y("Skipping inactive source " + basic_url)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("-s", "--selective_harvesting", action="store_true",
help=ARG_HELP_STRINGS["selective_harvesting"])
args = parser.parse_args()
with open("harvest_list.csv", "r") as harvest_list:
reader = oat.UnicodeDictReader(harvest_list, encoding="utf-8")
for line in reader:
basic_url = line["basic_url"]
if line["active"] == "TRUE":
oat.print_g("Starting harvest from source " + basic_url)
processing = None
if len(line["processing"]) > 0:
processing = line["processing"]
oat.oai_harvest(basic_url,
line["metadata_prefix"],
line["oai_set"],
processing,
args.selective_harvesting)
now = datetime.datetime.now()
date_string = now.strftime("%Y_%m_%d")
file_name = "oai_harvest_" + date_string + ".csv"
target = os.path.join("..", line["directory"], file_name)
os.rename("out.csv", target)
else:
oat.print_y("Skipping inactive source " + basic_url)
def get_hybrid_status(line, username):
for issn in [7, 8, 9, 10]:
if not oat.has_value(line[issn]):
continue
msg = 'Looking up ISSN {}...'
oat.print_y(msg.format(line[issn]))
jtoc_metadata = get_jtoc_metadata(line[issn], username)
sleep(1)
if jtoc_metadata["jtoc_id"] is not None:
msg = ('Entry found (publisher: {}, title: {}, jtoc_ID: {}, ' +
'obtaining hybrid status...)')
oat.print_g(
msg.format(jtoc_metadata["jtoc_publisher"],
jtoc_metadata["jtoc_title"],
jtoc_metadata["jtoc_id"]))
journal_type = get_jtoc_journal_type(jtoc_metadata["jtoc_id"])
if not journal_type:
oat.print_r("Error while obtaining hybrid status!")
continue
sleep(1)
msg = "journaltocs type is '{}' , mapped to is_hybrid = {}"
oat.print_g(msg.format(journal_type[0], journal_type[1]))
return journal_type[1]
oat.print_r("None of the ISSN values found in journaltocs!")
return None
def main():
with open("harvest_list.csv", "r") as harvest_list:
reader = DictReader(harvest_list)
for line in reader:
basic_url = line["basic_url"]
if line["active"] == "TRUE":
oat.print_g("Starting harvest from source " + basic_url)
oai_set = line["oai_set"] if len(line["oai_set"]) > 0 else None
prefix = line["metadata_prefix"] if len(line["metadata_prefix"]) > 0 else None
processing = line["processing"] if len(line["processing"]) > 0 else None
directory = os.path.join("..", line["directory"])
articles = oat.oai_harvest(basic_url, prefix, oai_set, processing)
harvest_file_path = os.path.join(directory, "all_harvested_articles.csv")
enriched_file_path = os.path.join(directory, "all_harvested_articles_enriched.csv")
new_article_dicts, header = integrate_changes(articles, harvest_file_path, False)
integrate_changes(articles, enriched_file_path, True)
if header is None:
# if no header was returned, an "all_harvested" file doesn't exist yet
header = oat.OAI_COLLECTION_CONTENT.values()
new_articles = [header]
for article_dict in new_article_dicts:
new_articles.append([article_dict[key] for key in header])
now = datetime.datetime.now()
date_string = now.strftime("%Y_%m_%d")
file_name = "new_articles_" + date_string + ".csv"
target = os.path.join(directory, file_name)
with open(target, "w") as t:
writer = oat.OpenAPCUnicodeWriter(t, openapc_quote_rules=True, has_header=True)
writer.write_rows(new_articles)
else:
oat.print_y("Skipping inactive source " + basic_url)
def main():
with open("harvest_list.csv", "r") as harvest_list:
reader = DictReader(harvest_list)
for line in reader:
basic_url = line["basic_url"]
if line["active"] == "TRUE":
oat.print_g("Starting harvest from source " + basic_url)
oai_set = line["oai_set"] if len(line["oai_set"]) > 0 else None
prefix = line["metadata_prefix"] if len(line["metadata_prefix"]) > 0 else None
processing = line["processing"] if len(line["processing"]) > 0 else None
directory = os.path.join("..", line["directory"])
articles = oat.oai_harvest(basic_url, prefix, oai_set, processing)
harvest_file_path = os.path.join(directory, "all_harvested_articles.csv")
enriched_file_path = os.path.join(directory, "all_harvested_articles_enriched.csv")
new_article_dicts, header = integrate_changes(articles, harvest_file_path, False)
integrate_changes(articles, enriched_file_path, True)
deal_wiley_path = os.path.join(directory, "all_harvested_articles_enriched_deal_wiley.csv")
if os.path.isfile(deal_wiley_path):
integrate_changes(articles, deal_wiley_path, True)
if header is None:
# if no header was returned, an "all_harvested" file doesn't exist yet
header = list(oat.OAI_COLLECTION_CONTENT.keys())
new_articles = [header]
for article_dict in new_article_dicts:
new_articles.append([article_dict[key] for key in header])
now = datetime.datetime.now()
date_string = now.strftime("%Y_%m_%d")
file_name = "new_articles_" + date_string + ".csv"
target = os.path.join(directory, file_name)
with open(target, "w") as t:
writer = oat.OpenAPCUnicodeWriter(t, openapc_quote_rules=True, has_header=True)
writer.write_rows(new_articles)
else:
oat.print_y("Skipping inactive source " + basic_url)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("source_file", help=ARG_HELP_STRINGS["source_file"])
parser.add_argument("count_column",
type=int,
help=ARG_HELP_STRINGS["count_column"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-s",
"--sort",
action="store_true",
help=ARG_HELP_STRINGS["sort"])
args = parser.parse_args()
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
print("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
enc = args.encoding
except LookupError:
oat.print_r(
"Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
header, content = oat.get_csv_file_content(args.source_file, enc)
column_name = "column " + str(args.count_column)
if header:
header_line = header[0]
column_name = header_line[args.count_column]
oat.print_g("Performing occurence count in column '" + column_name + "'")
occurence_dict = OrderedDict()
for line in content:
try:
value = line[args.count_column]
except IndexError as ie:
oat.print_y("IndexError ({}) at line {}, skipping...".format(
ie.message, line))
continue
if value not in occurence_dict:
occurence_dict[value] = 1
else:
occurence_dict[value] += 1
if args.sort:
occurence_dict = OrderedDict(
sorted(occurence_dict.items(), key=lambda x: x[1], reverse=True))
for item in occurence_dict.items():
print item[0] + ": " + str(item[1])
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q", "--quotemask", help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o", "--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
print ("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
enc = args.encoding
except LookupError:
print ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print ("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
header, content = oat.get_csv_file_content(args.csv_file, enc)
line_num = 1
for line in content:
publisher = line[5]
journal = line[6]
journal_new = oat.get_unified_journal_title(journal)
publisher_new = oat.get_unified_publisher_name(publisher)
if publisher_new != publisher:
line[5] = publisher_new
msg = u"Line {}: Updated publisher name ({} -> {})"
oat.print_g(msg.format(line_num, publisher, publisher_new))
if journal_new != journal:
line[6] = journal_new
msg = u"Line {}: Updated journal_full_title ({} -> {})"
oat.print_g(msg.format(line_num, journal, journal_new))
line_num += 1
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, True)
writer.write_rows(header + content)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("-i",
"--integrate",
help=ARG_HELP_STRINGS["integrate"],
action="store_true")
parser.add_argument("-o",
"--output",
help=ARG_HELP_STRINGS["output"],
action="store_true")
args = parser.parse_args()
with open("harvest_list.csv", "r") as harvest_list:
reader = DictReader(harvest_list)
for line in reader:
basic_url = line["basic_url"]
if line["active"] == "TRUE":
oat.print_g("Starting harvest from source " + basic_url)
oai_set = line["oai_set"] if len(line["oai_set"]) > 0 else None
prefix = line["metadata_prefix"] if len(
line["metadata_prefix"]) > 0 else None
processing = line["processing"] if len(
line["processing"]) > 0 else None
directory = os.path.join("..", line["directory"])
out_file_suffix = os.path.basename(
line["directory"]) if args.output else None
articles = oat.oai_harvest(basic_url, prefix, oai_set,
processing, out_file_suffix)
harvest_file_path = os.path.join(directory,
"all_harvested_articles.csv")
enriched_file_path = os.path.join(
directory, "all_harvested_articles_enriched.csv")
new_article_dicts, header = integrate_changes(
articles, harvest_file_path, False, not args.integrate)
integrate_changes(articles, enriched_file_path, True,
not args.integrate)
if header is None:
# if no header was returned, an "all_harvested" file doesn't exist yet
header = list(oat.OAI_COLLECTION_CONTENT.keys())
new_articles = [header]
for article_dict in new_article_dicts:
new_articles.append([article_dict[key] for key in header])
now = datetime.datetime.now()
date_string = now.strftime("%Y_%m_%d")
file_name = "new_articles_" + date_string + ".csv"
target = os.path.join(directory, file_name)
with open(target, "w") as t:
writer = oat.OpenAPCUnicodeWriter(t,
openapc_quote_rules=True,
has_header=True)
writer.write_rows(new_articles)
else:
oat.print_y("Skipping inactive source " + basic_url)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("source_file", help=ARG_HELP_STRINGS["source_file"])
parser.add_argument("count_column", type=int, help=ARG_HELP_STRINGS["count_column"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-s", "--sort", action="store_true", help=ARG_HELP_STRINGS["sort"])
args = parser.parse_args()
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
print(msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
oat.print_r("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
header, content = oat.get_csv_file_content(args.source_file, enc)
column_name = "column " + str(args.count_column)
if header:
header_line = header[0]
column_name = header_line[args.count_column]
oat.print_g("Performing occurence count in column '" + column_name + "'")
occurence_dict = OrderedDict()
for line in content:
try:
value = line[args.count_column]
except IndexError as ie:
oat.print_y("IndexError ({}) at line {}, skipping...".format(ie.message, line))
continue
if value not in occurence_dict:
occurence_dict[value] = 1
else:
occurence_dict[value] += 1
if args.sort:
occurence_dict = OrderedDict(sorted(occurence_dict.items(), key=lambda x: x[1],
reverse=True))
for item in occurence_dict.items():
print(item[0] + ": " + str(item[1]))
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-start", type=int, default=1, help=ARG_HELP_STRINGS["start"])
parser.add_argument("-end", type=int, help=ARG_HELP_STRINGS["start"])
args = parser.parse_args()
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(oat.ANSIColorFormatter())
bufferedHandler = oat.BufferedErrorHandler(handler)
bufferedHandler.setFormatter(oat.ANSIColorFormatter())
logging.root.addHandler(handler)
logging.root.addHandler(bufferedHandler)
logging.root.setLevel(logging.INFO)
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = ("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
oat.print_g(msg)
enc = args.encoding
except LookupError:
msg = ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
oat.print_r(msg)
sys.exit()
head, content = oat.get_csv_file_content(args.csv_file, enc)
content = head + content
line_num = 0
for line in content:
line_num += 1
if args.start and args.start > line_num:
continue
if args.end and args.end < line_num:
continue
# Check hybrid status
if line[4] != "TRUE":
continue
institution = line[0]
period = line[1]
doi = line[3]
publisher = line[5]
journal = line[6]
for lpl in lpl_list:
if lpl.publisher_matches(publisher):
init_msg = (u"Line {}: Checking {} article from {}, published in '" +
"{}'...").format(line_num, institution, period, journal)
oat.print_b(init_msg)
page_content = get_landingpage_content(doi, lpl)
if page_content is None:
continue
pdf_link = lpl.search_for_oa(page_content)
if pdf_link is None:
error_msg = (u"No PDF link found! (line {}, DOI: " +
"http://doi.org/{}").format(line_num, doi)
logging.error(error_msg)
elif pdf_link == "":
warning_msg = (u"A RegexGroup matched, but no PDF " +
"link was found! (line {}, DOI: " +
"http://doi.org/{}").format(line_num, doi)
logging.warning(warning_msg)
else:
oat.print_g(u"PDF link found: " + pdf_link)
time.sleep(1)
if not bufferedHandler.buffer:
oat.print_g("\nLookup finished, all articles were accessible on sciencedirect")
else:
oat.print_r("\nLookup finished, not all articles could be accessed on sciencedirect:\n")
# closing will implicitly flush the handler and print any buffered
# messages to stderr
bufferedHandler.close()
def main():
parser = argparse.ArgumentParser()
parser.add_argument("new_file", help=ARG_HELP_STRINGS["new_file"])
parser.add_argument("target_file", help=ARG_HELP_STRINGS["new_file"])
parser.add_argument('cost_tolerance', type=float, help=ARG_HELP_STRINGS["cost_tolerance"])
parser.add_argument('enriched_files', nargs='+', help=ARG_HELP_STRINGS["enriched_files"])
parser.add_argument('-b', '--batch', type=int, help=ARG_HELP_STRINGS["batch"])
args = parser.parse_args()
target_file_name = get_filename(args.target_file)
new_file_name = get_filename(args.new_file)
for path in args.enriched_files:
if not os.path.isfile(path):
oat.print_r('Error: "' + path + '" is no valid file path!')
sys.exit()
ENRICHED_FILES[path] = {"modified": False, "file_name": get_filename(path)}
ENRICHED_FILES[path]["header"], ENRICHED_FILES[path]["content"] = oat.get_csv_file_content(path, enc="utf-8", force_header=True)
target_header, target_content = oat.get_csv_file_content(args.target_file, enc="utf-8", force_header=True)
new_header, new_content = oat.get_csv_file_content(args.new_file, enc="utf-8", force_header=True)
ud_header, ud_content = oat.get_csv_file_content(UD_FILE, enc="utf-8", force_header=True)
duplicates = []
target_dois = [line[3] for line in target_content]
for new_index, line in enumerate(new_content):
doi = line[3]
if doi == "NA" or doi not in target_dois:
continue
else:
target_index = get_duplicate_index(target_content, doi)
duplicates.append((new_index, target_index))
count = 0
for pair in duplicates:
new_line = new_content[pair[0]]
target_line = target_content[pair[1]]
doi = target_line[3]
new_cost = float(new_line[2])
target_cost = float(target_line[2])
if new_cost >= target_cost:
deviation = (new_cost - target_cost) / new_cost
else:
deviation = (target_cost - new_cost) / target_cost
oat.print_b("Duplicate found:")
print("In new file " + new_file_name + ":")
print(",".join(new_line))
print("In target file " + target_file_name + ":")
print(",".join(target_line))
if new_line[0] != target_line[0]:
msg = 'Institutional mismatch "{}"/"{}". Lines will be deleted and added to the unresolved duplicates file.'
oat.print_r(msg.format(new_line[0],target_line[0]))
new_content[pair[0]] = list(EMPTY_LINE)
target_content[pair[1]] = REPLACEMENT
ud_content += [target_line]
ud_content += [new_line]
path, index = find_in_enriched_files(doi)
ENRICHED_FILES[path]["content"][index] = list(EMPTY_LINE)
ENRICHED_FILES[path]["modified"] = True
elif deviation <= args.cost_tolerance:
msg = "Cost deviation between {} and {} is below tolerance threshold ({} <= {}). Entries are treated as equal, only the new one will be deleted."
oat.print_g(msg.format(new_cost, target_cost, deviation, args.cost_tolerance))
new_content[pair[0]] = list(EMPTY_LINE)
else:
msg = "Cost deviation between {} and {} exceeds tolerance threshold ({} > {}). Entries are treated as different, both will be deleted."
oat.print_y(msg.format(new_cost, target_cost, deviation, args.cost_tolerance))
new_content[pair[0]] = list(EMPTY_LINE)
target_content[pair[1]] = REPLACEMENT
path, index = find_in_enriched_files(doi)
ENRICHED_FILES[path]["content"][index] = list(EMPTY_LINE)
ENRICHED_FILES[path]["modified"] = True
count += 1
if args.batch and count >= args.batch:
break
while REPLACEMENT in target_content:
target_content.remove(REPLACEMENT)
with open(args.target_file, 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, QUOTE_MASK, True, True)
writer.write_rows(target_header + target_content)
with open(args.new_file, 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, QUOTE_MASK, True, True)
writer.write_rows(new_header + new_content)
with open(UD_FILE, 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, QUOTE_MASK, True, True)
writer.write_rows(ud_header + ud_content)
for path, enriched_file in ENRICHED_FILES.items():
if enriched_file["modified"]:
with open(path, 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, QUOTE_MASK, True, True)
writer.write_rows(enriched_file["header"] + enriched_file["content"])
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-O", "--offsetting_mode", help=ARG_HELP_STRINGS["offsetting"])
parser.add_argument("-b", "--bypass-cert-verification", action="store_true",
help=ARG_HELP_STRINGS["bypass"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-f", "--force", action="store_true",
help=ARG_HELP_STRINGS["force"])
parser.add_argument("-i", "--ignore-header", action="store_true",
help=ARG_HELP_STRINGS["ignore_header"])
parser.add_argument("-j", "--force-header", action="store_true",
help=ARG_HELP_STRINGS["force_header"])
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-a", "--add-unknown-columns", action="store_true",
help=ARG_HELP_STRINGS["unknown_columns"])
parser.add_argument("-d", "--dialect", choices=["excel", "excel-tab", "unix"],
help=ARG_HELP_STRINGS["dialect"])
parser.add_argument("-v", "--verbose", action="store_true",
help=ARG_HELP_STRINGS["verbose"])
parser.add_argument("-o", "--overwrite", action="store_true",
help=ARG_HELP_STRINGS["overwrite"])
parser.add_argument("-u", "--update", action="store_true",
help=ARG_HELP_STRINGS["update"])
parser.add_argument("-r", "--round_monetary", action="store_true",
help=ARG_HELP_STRINGS["round_monetary"])
parser.add_argument("--no-crossref", action="store_true",
help=ARG_HELP_STRINGS["no_crossref"])
parser.add_argument("--no-pubmed", action="store_true",
help=ARG_HELP_STRINGS["no_pubmed"])
parser.add_argument("--no-doaj", action="store_true",
help=ARG_HELP_STRINGS["no_doaj"])
parser.add_argument("-institution", "--institution_column", type=int,
help=ARG_HELP_STRINGS["institution"])
parser.add_argument("-period", "--period_column", type=int,
help=ARG_HELP_STRINGS["period"])
parser.add_argument("-doi", "--doi_column", type=int,
help=ARG_HELP_STRINGS["doi"])
parser.add_argument("-euro", "--euro_column", type=int,
help=ARG_HELP_STRINGS["euro"])
parser.add_argument("-is_hybrid", "--is_hybrid_column", type=int,
help=ARG_HELP_STRINGS["is_hybrid"])
parser.add_argument("-publisher", "--publisher_column", type=int,
help=ARG_HELP_STRINGS["publisher"])
parser.add_argument("-journal_full_title", "--journal_full_title_column",
type=int, help=ARG_HELP_STRINGS["journal_full_title"])
parser.add_argument("-book_title", "--book_title_column",
type=int, help=ARG_HELP_STRINGS["book_title"])
parser.add_argument("-issn", "--issn_column",
type=int, help=ARG_HELP_STRINGS["issn"])
parser.add_argument("-isbn", "--isbn_column",
type=int, help=ARG_HELP_STRINGS["isbn"])
parser.add_argument("-backlist_oa", "--backlist_oa_column",
type=int, help=ARG_HELP_STRINGS["backlist_oa"])
parser.add_argument("-additional_isbns", "--additional_isbn_columns", type=int, nargs='+',
help=ARG_HELP_STRINGS["additional_isbns"])
parser.add_argument("-url", "--url_column",
type=int, help=ARG_HELP_STRINGS["url"])
parser.add_argument("-start", type=int, help=ARG_HELP_STRINGS["start"])
parser.add_argument("-end", type=int, help=ARG_HELP_STRINGS["end"])
args = parser.parse_args()
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(oat.ANSIColorFormatter())
bufferedHandler = oat.BufferedErrorHandler(handler)
bufferedHandler.setFormatter(oat.ANSIColorFormatter())
logging.root.addHandler(handler)
logging.root.addHandler(bufferedHandler)
logging.root.setLevel(logging.INFO)
if args.locale:
norm = locale.normalize(args.locale)
if norm != args.locale:
msg = "locale '{}' not found, normalised to '{}'".format(
args.locale, norm)
oat.print_y(msg)
try:
loc = locale.setlocale(locale.LC_ALL, norm)
oat.print_g("Using locale " + loc)
except locale.Error as loce:
msg = "Setting locale to {} failed: {}".format(norm, loce.message)
oat.print_r(msg)
sys.exit()
enc = None # CSV file encoding
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = ("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
oat.print_g(msg)
enc = args.encoding
except LookupError:
msg = ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
oat.print_r(msg)
sys.exit()
result = oat.analyze_csv_file(args.csv_file, enc=enc)
if result["success"]:
csv_analysis = result["data"]
print(csv_analysis)
else:
print(result["error_msg"])
sys.exit()
if args.dialect:
dialect = args.dialect
oat.print_g('Dialect sniffing results ignored, using built-in CSV dialect "' + dialect + '"')
else:
dialect = csv_analysis.dialect
if enc is None:
enc = csv_analysis.enc
has_header = csv_analysis.has_header or args.force_header
if enc is None:
print("Error: No encoding given for CSV file and automated " +
"detection failed. Please set the encoding manually via the " +
"--enc argument")
sys.exit()
csv_file = open(args.csv_file, "r", encoding=enc)
reader = csv.reader(csv_file, dialect=dialect)
first_row = next(reader)
num_columns = len(first_row)
print("\nCSV file has {} columns.".format(num_columns))
csv_file.seek(0)
reader = csv.reader(csv_file, dialect=dialect)
if args.update and args.overwrite:
oat.print_r("Error: Either use the -u or the -o option, not both.")
sys.exit()
if args.overwrite:
for column in OVERWRITE_STRATEGY.keys():
OVERWRITE_STRATEGY[column] = CSVColumn.OW_ALWAYS
elif not args.update:
for column in OVERWRITE_STRATEGY.keys():
OVERWRITE_STRATEGY[column] = CSVColumn.OW_ASK
additional_isbn_columns = []
if args.additional_isbn_columns:
for index in args.additional_isbn_columns:
if index > num_columns:
msg = "Error: Additional ISBN column index {} exceeds number of columns ({})."
oat.print_r(msg.format(index, num_columns))
sys.exit()
else:
additional_isbn_columns.append(index)
column_map = {
"institution": CSVColumn("institution", {"articles": CSVColumn.MANDATORY, "books": CSVColumn.MANDATORY}, args.institution_column, overwrite=OVERWRITE_STRATEGY["institution"]),
"period": CSVColumn("period",{"articles": CSVColumn.MANDATORY, "books": CSVColumn.MANDATORY}, args.period_column, overwrite=OVERWRITE_STRATEGY["period"]),
"euro": CSVColumn("euro", {"articles": CSVColumn.MANDATORY, "books": CSVColumn.MANDATORY}, args.euro_column, overwrite=OVERWRITE_STRATEGY["euro"]),
"doi": CSVColumn("doi", {"articles": CSVColumn.MANDATORY, "books": CSVColumn.MANDATORY}, args.doi_column, overwrite=OVERWRITE_STRATEGY["doi"]),
"is_hybrid": CSVColumn("is_hybrid", {"articles": CSVColumn.MANDATORY, "books": CSVColumn.NONE}, args.is_hybrid_column, overwrite=OVERWRITE_STRATEGY["is_hybrid"]),
"publisher": CSVColumn("publisher", {"articles": CSVColumn.BACKUP, "books": CSVColumn.NONE}, args.publisher_column, overwrite=OVERWRITE_STRATEGY["publisher"]),
"journal_full_title": CSVColumn("journal_full_title", {"articles": CSVColumn.BACKUP, "books": CSVColumn.NONE}, args.journal_full_title_column, overwrite=OVERWRITE_STRATEGY["journal_full_title"]),
"issn": CSVColumn("issn", {"articles": CSVColumn.BACKUP, "books": CSVColumn.NONE}, args.issn_column, overwrite=OVERWRITE_STRATEGY["issn"]),
"issn_print": CSVColumn("issn_print", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["issn_print"]),
"issn_electronic": CSVColumn("issn_electronic", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["issn_electronic"]),
"issn_l": CSVColumn("issn_l", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["issn_l"]),
"license_ref": CSVColumn("license_ref", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE} , None, overwrite=OVERWRITE_STRATEGY["license_ref"]),
"indexed_in_crossref": CSVColumn("indexed_in_crossref", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["indexed_in_crossref"]),
"pmid": CSVColumn("pmid", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["pmid"]),
"pmcid": CSVColumn("pmcid", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["pmcid"]),
"ut": CSVColumn("ut", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["ut"]),
"url": CSVColumn("url", {"articles": CSVColumn.BACKUP, "books": CSVColumn.NONE}, args.url_column, overwrite=OVERWRITE_STRATEGY["url"]),
"doaj": CSVColumn("doaj", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["doaj"]),
"agreement": CSVColumn("agreement", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["agreement"]),
"book_title": CSVColumn("book_title", {"articles": CSVColumn.NONE, "books": CSVColumn.RECOMMENDED}, args.book_title_column, overwrite=OVERWRITE_STRATEGY["book_title"]),
"backlist_oa": CSVColumn("backlist_oa", {"articles": CSVColumn.NONE, "books": CSVColumn.MANDATORY}, args.backlist_oa_column, overwrite=OVERWRITE_STRATEGY["backlist_oa"]),
"isbn": CSVColumn("isbn", {"articles": CSVColumn.NONE, "books": CSVColumn.BACKUP}, args.isbn_column, overwrite=OVERWRITE_STRATEGY["isbn"]),
"isbn_print": CSVColumn("isbn_print", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["isbn_print"]),
"isbn_electronic": CSVColumn("isbn_electronic", {"articles": CSVColumn.NONE, "books": CSVColumn.NONE}, None, overwrite=OVERWRITE_STRATEGY["isbn_electronic"])
}
header = None
if has_header:
for row in reader:
if not row: # Skip empty lines
continue
header = row # First non-empty row should be the header
if args.ignore_header:
print("Skipping header analysis due to command line argument.")
break
else:
print("\n *** Analyzing CSV header ***\n")
for (index, item) in enumerate(header):
if index in additional_isbn_columns:
msg = "Column named '{}' at index {} is designated as additional ISBN column"
print(msg.format(item, index))
continue
column_type = oat.get_column_type_from_whitelist(item)
if column_type is not None and column_map[column_type].index is None:
column_map[column_type].index = index
column_map[column_type].column_name = item
found_msg = ("Found column named '{}' at index {}, " +
"assuming this to be the '{}' column.")
print(found_msg.format(item, index, column_type))
break
print("\n *** Starting heuristical analysis ***\n")
for row in reader:
if not row: # Skip empty lines
# We analyze the first non-empty line, a possible header should
# have been processed by now.
continue
column_candidates = {
"doi": [],
"period": [],
"euro": []
}
found_msg = "The entry in column {} looks like a potential {}: {}"
for (index, entry) in enumerate(row):
if index in [csvcolumn.index for csvcolumn in column_map.values()] + additional_isbn_columns:
# Skip columns already assigned
continue
entry = entry.strip()
# Search for a DOI
if column_map['doi'].index is None:
if oat.DOI_RE.match(entry):
column_id = str(index)
# identify column either numerically or by column header
if header:
column_id += " ('" + header[index] + "')"
print(found_msg.format(column_id, "DOI", entry))
column_candidates['doi'].append(index)
continue
# Search for a potential year string
if column_map['period'].index is None:
try:
maybe_period = int(entry)
now = datetime.date.today().year
# Should be a wide enough margin
if maybe_period >= 2000 and maybe_period <= now + 2:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print(found_msg.format(column_id, "year", entry))
column_candidates['period'].append(index)
continue
except ValueError:
pass
# Search for a potential monetary amount
if column_map['euro'].index is None:
try:
maybe_euro = locale.atof(entry)
if maybe_euro >= 10 and maybe_euro <= 10000:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print (found_msg.format(column_id, "euro amount", entry))
column_candidates['euro'].append(index)
continue
except ValueError:
pass
for column_type, candidates in column_candidates.items():
if column_map[column_type].index is not None:
continue
if len(candidates) > 1:
print("Could not reliably identify the '" + column_type +
"' column - more than one possible candiate!")
elif len(candidates) < 1:
print("No candidate found for column '" + column_type + "'!")
else:
index = candidates.pop()
column_map[column_type].index = index
if header:
column_id = header[index]
column_map[column_type].column_name = column_id
else:
column_id = index
msg = "Assuming column '{}' to be the '{}' column."
print(msg.format(column_id, column_type))
column_map[column_type].index = index
break
print("\n *** CSV file analysis summary ***\n")
index_dict = {csvc.index: csvc for csvc in column_map.values()}
for index in range(num_columns):
column_name = ""
if header:
column_name = header[index]
if index in index_dict:
column = index_dict[index]
msg = u"column number {} ({}) is the '{}' column ({})".format(
index, column_name, column.column_type, column.get_req_description())
print(msg)
elif index in additional_isbn_columns:
msg = u"column number {} ({}) is an additional ISBN column".format(index, column_name)
oat.print_c(msg)
else:
if args.add_unknown_columns:
msg = (u"column number {} ({}) is an unknown column, it will be " +
"appended to the generated CSV file")
print(msg.format(index, column_name))
if not column_name:
# Use a generic name
column_name = "unknown"
while column_name in column_map.keys():
# TODO: Replace by a numerical, increasing suffix
column_name += "_"
column_map[column_name] = CSVColumn(column_name, CSVColumn.NONE, index)
else:
msg = (u"column number {} ({}) is an unknown column, it will be " +
"ignored")
print(msg.format(index, column_name))
print()
for column in column_map.values():
if column.index is None:
msg = "The '{}' column could not be identified ({})"
print(msg.format(column.column_type, column.get_req_description()))
print()
article_mand_missing = [x.column_type for x in column_map.values() if x.requirement["articles"] == CSVColumn.MANDATORY and x.index is None]
article_back_missing = [x.column_type for x in column_map.values() if x.requirement["articles"] == CSVColumn.BACKUP and x.index is None]
book_mand_missing = [x.column_type for x in column_map.values() if x.requirement["books"] == CSVColumn.MANDATORY and x.index is None]
book_back_missing = [x.column_type for x in column_map.values() if x.requirement["books"] == CSVColumn.BACKUP and x.index is None]
if article_mand_missing:
msg = "Article enrichment is not possible - mandatory columns are missing ({})"
oat.print_y(msg.format(", ".join(article_mand_missing)))
elif article_back_missing:
msg = "Article enrichment is possible, but backup columns are missing ({}) - each record will need a valid DOI"
oat.print_b(msg.format(", ".join(article_back_missing)))
else:
oat.print_g("Article enrichment is possible with all backup columns in place")
if book_mand_missing:
msg = "Book enrichment is not possible - mandatory columns are missing ({})"
oat.print_y(msg.format(", ".join(book_mand_missing)))
elif book_back_missing:
msg = "Book enrichment is possible, but backup columns are missing ({}) - each record will need a valid DOI"
oat.print_b(msg.format(", ".join(book_back_missing)))
else:
oat.print_g("Book enrichment is possible with all backup columns in place")
print()
if article_mand_missing and book_mand_missing:
if not args.force:
oat.print_r("ERROR: Could not detect the minimum mandatory data set for any " +
"publication type. There are 2 ways to fix this:")
if not header:
print("1) Add a header row to your file and identify the " +
"column(s) by assigning them an appropiate column name.")
else:
print("1) Identify the missing column(s) by assigning them " +
"a different column name in the CSV header (You can " +
"use the column name(s) mentioned in the message above)")
print("2) Use command line parameters when calling this script " +
"to identify the missing columns (use -h for help) ")
sys.exit()
else:
oat.print_y("WARNING: Could not detect the minimum mandatory data set for any " +
"publication type - forced to continue.")
start = input("\nStart metadata aggregation? (y/n):")
while start not in ["y", "n"]:
start = input("Please type 'y' or 'n':")
if start == "n":
sys.exit()
print("\n *** Starting metadata aggregation ***\n")
enriched_content = {}
for record_type, fields in oat.COLUMN_SCHEMAS.items():
# add headers
enriched_content[record_type] = {
"count": 0,
"content": [list(fields)]
}
if not os.path.isdir("tempfiles"):
os.mkdir("tempfiles")
isbn_handling = oat.ISBNHandling("tempfiles/ISBNRangeFile.xml")
doab_analysis = oat.DOABAnalysis(isbn_handling, "tempfiles/DOAB.csv", verbose=False)
doaj_analysis = oat.DOAJAnalysis("tempfiles/DOAJ.csv")
csv_file.seek(0)
reader = csv.reader(csv_file, dialect=dialect)
header_processed = False
row_num = 0
for row in reader:
row_num += 1
if not row:
continue # skip empty lines
if not header_processed:
header_processed = True
if has_header:
# If the CSV file has a header, we are currently there - skip it
# to get to the first data row
continue
if args.start and args.start > row_num:
continue
if args.end and args.end < row_num:
continue
print("---Processing line number " + str(row_num) + "---")
result_type, enriched_row = oat.process_row(row, row_num, column_map, num_columns, additional_isbn_columns, doab_analysis, doaj_analysis,
args.no_crossref, args.no_pubmed,
args.no_doaj, args.round_monetary,
args.offsetting_mode)
for record_type, value in enriched_content.items():
if record_type == result_type:
value["content"].append(enriched_row)
value["count"] += 1
else:
empty_line = ["" for x in value["content"][0]]
value["content"].append(empty_line)
csv_file.close()
for record_type, value in enriched_content.items():
if value["count"] > 0:
with open('out_' + record_type + '.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, oat.OPENAPC_STANDARD_QUOTEMASK,
True, True, True)
writer.write_rows(value["content"])
if not bufferedHandler.buffer:
oat.print_g("Metadata enrichment successful, no errors occured")
else:
oat.print_r("There were errors during the enrichment process:\n")
# closing will implicitly flush the handler and print any buffered
# messages to stderr
bufferedHandler.close()
def main():
parser = argparse.ArgumentParser()
parser.add_argument("source_file")
parser.add_argument("source_column", type=int)
parser.add_argument("currency_column", type=int)
parser.add_argument("period_column", type=int)
parser.add_argument("target_column", type=int)
parser.add_argument("-f", "--force_overwrite", action="store_true")
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q", "--quotemask", help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o", "--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print ("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
oat.print_g(msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
print ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
if args.locale:
norm = locale.normalize(args.locale)
if norm != args.locale:
msg = "locale '{}' not found, normalised to '{}'".format(
args.locale, norm)
oat.print_y(msg)
try:
loc = locale.setlocale(locale.LC_ALL, norm)
oat.print_g("Using locale " + loc)
except locale.Error as loce:
msg = "Setting locale to {} failed: {}".format(norm, loce.message)
oat.print_r(msg)
sys.exit()
header, content = oat.get_csv_file_content(args.source_file, enc, True)
fieldnames = header.pop()
modified_content = []
line_num = 0
for column_type in ["source_column", "currency_column", "period_column", "target_column"]:
index = getattr(args, column_type)
msg = "Column {} ('{}') is the {}."
oat.print_g(msg.format(index, fieldnames[index], column_type))
start = input("\nStart conversion? (y/n):")
while start not in ["y", "n"]:
start = input("Please type 'y' or 'n':")
if start == "n":
sys.exit()
for line in content:
line_num += 1
if not oat.has_value(line[args.source_column]):
oat.print_y("WARNING: No source value found in line " + str(line_num) + ", skipping...")
modified_content.append(line)
continue
monetary_value = None
try:
monetary_value = locale.atof(line[args.source_column])
except ValueError:
msg = "WARNING: Could not extract a valid monetary value from source column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, line[args.source_column]))
modified_content.append(line)
continue
currency = line[args.currency_column]
if currency == "EUR":
msg = "WARNING: Currency in line {} is already EUR, skipping..."
oat.print_y(msg.format(line_num))
line[args.target_column] = line[args.source_column]
modified_content.append(line)
continue
if not oat.has_value(currency):
msg = "WARNING: Could not extract a valid currency indicator from currency column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, currency))
modified_content.append(line)
continue
period = line[args.period_column]
frequency = get_frequency(period)
if frequency is None:
msg = "WARNING: Could not extract a valid date string from period column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, period))
modified_content.append(line)
continue
if currency not in EXCHANGE_RATES[frequency]:
msg = 'No exchange rates ({}) found for currency "{}", querying ECB data warehouse...'
oat.print_b(msg.format(frequency, currency))
rates = oat.get_euro_exchange_rates(currency, frequency)
EXCHANGE_RATES[frequency][currency] = rates
rate = EXCHANGE_RATES[frequency][currency].get(period)
if rate is None and frequency == "A":
rate = _calulate_preliminary_annual_average(period, currency)
if rate:
EXCHANGE_RATES[frequency][currency][period] = rate
if rate is None:
if frequency != "D":
msg = "Error: No conversion rate found for currency {} for period {} (line {}), aborting..."
oat.print_r(msg.format(currency, period, line_num))
sys.exit()
day_retries = 0
while rate is None:
msg = "Warning: No conversion rate found for currency {} for period {} (line {}), trying next day..."
oat.print_y(msg.format(currency, period, line_num))
period = get_next_day(period)
rate = EXCHANGE_RATES[frequency][currency].get(period)
day_retries += 1
if day_retries > 5:
msg = "Error: Look-ahead limit for days exceeded, aborting..."
oat.print_r(msg)
sys.exit()
euro_value = round(monetary_value/float(rate), 2)
line[args.target_column] = str(euro_value)
msg = "Line {}: {} exchange rate ({}) for date {} is {} -> {} / {} = {} EUR"
msg = msg.format(line_num, currency, frequency, period, rate, monetary_value, rate, euro_value)
oat.print_g(msg)
modified_content.append(line)
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, True)
writer.write_rows([fieldnames] + modified_content)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("apc_file", help=ARG_HELP_STRINGS["apc_file"])
parser.add_argument("issn_l_file", help=ARG_HELP_STRINGS["issn_l_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q",
"--quotemask",
help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o",
"--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true",
default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
oat.print_g(msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
print("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
header, content = oat.get_csv_file_content(args.apc_file, enc)
oat.print_g("Preparing mapping table...")
itself = other = 0
issn_l_re = re.compile(
"^(?P<issn>\d{4}-\d{3}[\dxX])\t(?P<issn_l>\d{4}-\d{3}[\dxX])$")
issn_l_file = open(args.issn_l_file, "r")
issn_l_dict = {}
for i, line in enumerate(issn_l_file):
if i % 100000 == 0:
print(str(i) + " lines processed.")
match = issn_l_re.match(line)
if match:
match_dict = match.groupdict()
issn_l_dict[match_dict['issn']] = match_dict['issn_l']
if match_dict['issn'] == match_dict['issn_l']:
itself += 1
else:
other += 1
print(
str(itself) + " ISSNs pointing to itself as ISSN-L, " + str(other) +
" to another value.")
oat.print_g("Starting enrichment...")
issn_matches = issn_p_matches = issn_e_matches = unmatched = different = corrections = 0
enriched_lines = []
for line in content:
if len(line) == 0:
enriched_lines.append(line)
continue
issn = reformat_issn(line[7])
issn_p = reformat_issn(line[8])
issn_e = reformat_issn(line[9])
target = None
if issn in issn_l_dict:
target = issn_l_dict[issn]
corrected_target = oat.get_corrected_issn_l(target)
if corrected_target != target:
corrections += 1
line[10] = corrected_target
issn_matches += 1
elif issn_p in issn_l_dict:
target = issn_l_dict[issn_p]
corrected_target = oat.get_corrected_issn_l(target)
if corrected_target != target:
corrections += 1
line[10] = corrected_target
issn_p_matches += 1
elif issn_e in issn_l_dict:
target = issn_l_dict[issn_e]
corrected_target = oat.get_corrected_issn_l(target)
if corrected_target != target:
corrections += 1
line[10] = corrected_target
issn_e_matches += 1
else:
unmatched += 1
if target is not None and target not in [issn, issn_p, issn_e]:
different += 1
enriched_lines.append(line)
msg = ("{} issn_l values mapped by issn, {} by issn_p, {} by issn_e. {} " +
"could not be assigned.\n{} issn_l values were corrected during " +
"the process.\n In {} cases the ISSN-L was different from all " +
"existing ISSN values")
print(
msg.format(issn_matches, issn_p_matches, issn_e_matches, unmatched,
corrections, different))
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, True)
writer.write_rows(header + enriched_lines)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q",
"--quotemask",
help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o",
"--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true",
default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
codec_msg = "Encoding '{}' found in Python's codec collection as '{}'"
oat.print_g(codec_msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
print("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
header, content = oat.get_csv_file_content(args.csv_file, enc)
correction_schema = None
for schema_type, schema in oat.COLUMN_SCHEMAS.items():
if header[0] == schema:
oat.print_g("Schema autodetection: " + schema_type)
correction_schema = CORRECTION_SCHEMAS[schema_type]
break
else:
oat.print_r(
"Error: CSV header does not match any known OpenAPC data schema")
line_num = 1
for line in content:
for tup in correction_schema:
if tup[0] == "publisher":
index = tup[1]
publisher = line[index]
publisher_new = oat.get_unified_publisher_name(publisher)
if publisher_new != publisher:
line[index] = publisher_new
msg = u"Line {}: Updated publisher name ({} -> {})"
oat.print_g(msg.format(line_num, publisher, publisher_new))
if tup[0] == "journal_full_title":
index = tup[1]
journal = line[index]
journal_new = oat.get_unified_journal_title(journal)
if journal_new != journal:
line[index] = journal_new
msg = u"Line {}: Updated journal_full_title ({} -> {})"
oat.print_g(msg.format(line_num, journal, journal_new))
line_num += 1
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, True)
writer.write_rows(header + content)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("source_file")
parser.add_argument("source_column", type=int)
parser.add_argument("currency_column", type=int)
parser.add_argument("period_column", type=int)
parser.add_argument("target_column", type=int)
parser.add_argument("-f", "--force_overwrite", action="store_true")
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q",
"--quotemask",
help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o",
"--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true",
default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
oat.print_g(msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
print("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
if args.locale:
norm = locale.normalize(args.locale)
if norm != args.locale:
msg = "locale '{}' not found, normalised to '{}'".format(
args.locale, norm)
oat.print_y(msg)
try:
loc = locale.setlocale(locale.LC_ALL, norm)
oat.print_g("Using locale " + loc)
except locale.Error as loce:
msg = "Setting locale to {} failed: {}".format(norm, loce.message)
oat.print_r(msg)
sys.exit()
header, content = oat.get_csv_file_content(args.source_file, enc)
fieldnames = header.pop()
modified_content = []
line_num = 0
for column_type in [
"source_column", "currency_column", "period_column",
"target_column"
]:
index = getattr(args, column_type)
msg = "Column {} ('{}') is the {}."
oat.print_g(msg.format(index, fieldnames[index], column_type))
start = input("\nStart conversion? (y/n):")
while start not in ["y", "n"]:
start = input("Please type 'y' or 'n':")
if start == "n":
sys.exit()
for line in content:
line_num += 1
if not oat.has_value(line[args.source_column]):
oat.print_y("WARNING: No source value found in line " +
str(line_num) + ", skipping...")
modified_content.append(line)
continue
monetary_value = None
try:
monetary_value = locale.atof(line[args.source_column])
except ValueError:
msg = "WARNING: Could not extract a valid monetary value from source column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, line[args.source_column]))
modified_content.append(line)
continue
period = line[args.period_column]
if not oat.has_value(period) or not period.isdigit():
msg = "WARNING: Could not extract a valid year string from period column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, period))
modified_content.append(line)
continue
currency = line[args.currency_column]
if not oat.has_value(currency):
msg = "WARNING: Could not extract a valid currency indicator from currency column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, currency))
modified_content.append(line)
continue
try:
rate = AVG_YEARLY_CONVERSION_RATES[currency][period]
except KeyError:
msg = "ERROR: No conversion rate found for currency {} in year {} (line {}), aborting..."
oat.print_r(msg.format(currency, period, line_num))
sys.exit()
euro_value = round(monetary_value / rate, 2)
line[args.target_column] = str(euro_value)
modified_content.append(line)
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, True)
writer.write_rows([fieldnames] + modified_content)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("source_file", help=ARG_HELP_STRINGS["source_file"])
parser.add_argument("source_file_key_column", type=int, help=ARG_HELP_STRINGS["source_file_key_column"])
parser.add_argument("source_file_value_column", type=int, help=ARG_HELP_STRINGS["source_file_value_column"])
parser.add_argument("target_file", help=ARG_HELP_STRINGS["target_file"])
parser.add_argument("target_file_key_column", type=int, help=ARG_HELP_STRINGS["target_file_key_column"])
parser.add_argument("target_file_value_column", type=int, help=ARG_HELP_STRINGS["target_file_value_column"])
parser.add_argument("-s", "--strict", action="store_true", help=ARG_HELP_STRINGS["strict"])
parser.add_argument("-f", "--force_overwrite", action="store_true", help=ARG_HELP_STRINGS["force_overwrite"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-e2", "--other_encoding", help=ARG_HELP_STRINGS["other_encoding"])
parser.add_argument("-q", "--quotemask", help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o", "--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
encs = [] #CSV file encodings
for encoding in [args.encoding, args.other_encoding]:
if encoding:
try:
codec = codecs.lookup(encoding)
print ("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(encoding, codec.name)
enc = args.encoding
except LookupError:
print ("Error: '" + encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
encs.append(encoding)
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print ("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
source_header, source_content = oat.get_csv_file_content(args.source_file, enc=encs[0])
key_column_name = "column " + str(args.source_file_key_column)
value_column_name = "column " + str(args.source_file_value_column)
if source_header:
header = source_header[0]
key_column_name = header[args.source_file_key_column]
value_column_name = header[args.source_file_value_column]
msg = u"Creating mapping table ({} -> {}) for source file {}...".format(key_column_name, value_column_name, args.source_file)
oat.print_g(msg)
mapping_table = {}
ambiguous_keys = []
for line in source_content:
if line:
key = line[args.source_file_key_column]
if key == 'NA':
continue
value = line[args.source_file_value_column]
if key not in mapping_table:
mapping_table[key] = value
else:
if mapping_table[key] != value:
if not args.strict:
msg = u"WARNING: Replacing existing value '{}' for key '{}' with new value '{}'".format(mapping_table[key], key, value)
mapping_table[key] = value
oat.print_y(msg)
else:
if key not in ambiguous_keys:
ambiguous_keys.append(key)
if args.strict:
for key in ambiguous_keys:
del(mapping_table[key])
msg = u"INFO: Ambiguous key '{}' dropped from mapping table".format(key)
oat.print_b(msg)
oat.print_g("mapping table created, contains " + str(len(mapping_table)) + " entries")
target_header, target_content = oat.get_csv_file_content(args.target_file, enc=encs[1])
line_num = 0 if not target_header else 1
replace_msg = u"Line {}: Found matching key '{}', replaced old value '{}' by '{}'"
modified_content = []
for line in target_content:
key = line[args.target_file_key_column]
if key in mapping_table:
new_value = mapping_table[key]
old_value = line[args.target_file_value_column]
if old_value != new_value:
if len(old_value) == 0 or old_value == "NA":
line[args.target_file_value_column] = new_value
msg = replace_msg.format(line_num, key, old_value, new_value)
oat.print_g(msg)
else:
if args.force_overwrite:
line[args.target_file_value_column] = new_value
msg = replace_msg.format(line_num, key, old_value, new_value)
oat.print_y(msg)
modified_content.append(line)
line_num += 1
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(target_header + modified_content)
return "ElementTree ParseError: {}".format(str(etpe))
parser = argparse.ArgumentParser()
parser.add_argument(
"doi_or_file",
help=
"An OpenAPC-compatible CSV file or a single DOI to look up in crossref.")
args = parser.parse_args()
arg = args.doi_or_file
if os.path.isfile(arg):
csv_file = open(arg, "r", encoding="utf8")
reader = csv.reader(csv_file)
line_number = 0
for line in reader:
if not line:
prefix = ""
else:
prefix = get_prefix(line[3])
result = str(line_number) + ": " + prefix
if prefix == "Springer (Biomed Central Ltd.)":
oat.print_g(result)
elif prefix == "Nature Publishing Group":
oat.print_r(result)
else:
print(result)
line_number += 1
else:
print(get_prefix(arg))
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-v",
"--verbose",
action="store_true",
help=ARG_HELP_STRINGS["verbose"])
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-i",
"--ignore-header",
action="store_true",
help=ARG_HELP_STRINGS["headers"])
parser.add_argument("-f",
"--force",
action="store_true",
help=ARG_HELP_STRINGS["force"])
parser.add_argument("-b",
"--bypass-cert-verification",
action="store_true",
help=ARG_HELP_STRINGS["bypass"])
parser.add_argument("-institution",
"--institution_column",
type=int,
help=ARG_HELP_STRINGS["institution"])
parser.add_argument("-period",
"--period_column",
type=int,
help=ARG_HELP_STRINGS["period"])
parser.add_argument("-doi",
"--doi_column",
type=int,
help=ARG_HELP_STRINGS["doi"])
parser.add_argument("-euro",
"--euro_column",
type=int,
help=ARG_HELP_STRINGS["euro"])
parser.add_argument("-is_hybrid",
"--is_hybrid_column",
type=int,
help=ARG_HELP_STRINGS["is_hybrid"])
parser.add_argument("-publisher",
"--publisher_column",
type=int,
help=ARG_HELP_STRINGS["publisher"])
parser.add_argument("-journal_full_title",
"--journal_full_title_column",
type=int,
help=ARG_HELP_STRINGS["journal_full_title"])
parser.add_argument("-issn",
"--issn_column",
type=int,
help=ARG_HELP_STRINGS["issn"])
parser.add_argument("-url",
"--url_column",
type=int,
help=ARG_HELP_STRINGS["url"])
args = parser.parse_args()
enc = None # CSV file encoding
if args.locale:
norm = locale.normalize(args.locale)
if norm != args.locale:
print "locale '{}' not found, normalized to '{}'".format(
args.locale, norm)
try:
loc = locale.setlocale(locale.LC_ALL, norm)
print "Using locale", loc
except locale.Error as loce:
print "Setting locale to " + norm + " failed: " + loce.message
sys.exit()
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
print("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
enc = args.encoding
except LookupError:
print("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
result = oat.analyze_csv_file(args.csv_file)
if result["success"]:
csv_analysis = result["data"]
print csv_analysis
else:
print result["error_msg"]
sys.exit()
if enc is None:
enc = csv_analysis.enc
dialect = csv_analysis.dialect
has_header = csv_analysis.has_header
if enc is None:
print("Error: No encoding given for CSV file and automated " +
"detection failed. Please set the encoding manually via the " +
"--enc argument")
sys.exit()
csv_file = open(args.csv_file, "r")
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
first_row = reader.next()
num_columns = len(first_row)
print "\nCSV file has {} columns.".format(num_columns)
csv_file.seek(0)
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
column_map = OrderedDict([
("institution",
CSVColumn("institution", CSVColumn.MANDATORY,
args.institution_column)),
("period", CSVColumn("period", CSVColumn.MANDATORY,
args.period_column)),
("euro", CSVColumn("euro", CSVColumn.MANDATORY, args.euro_column)),
("doi", CSVColumn("doi", CSVColumn.MANDATORY, args.doi_column)),
("is_hybrid",
CSVColumn("is_hybrid", CSVColumn.MANDATORY, args.is_hybrid_column)),
("publisher",
CSVColumn("publisher", CSVColumn.OPTIONAL, args.publisher_column)),
("journal_full_title",
CSVColumn("journal_full_title", CSVColumn.OPTIONAL,
args.journal_full_title_column)),
("issn", CSVColumn("issn", CSVColumn.OPTIONAL, args.issn_column)),
("issn_print", CSVColumn("issn_print", CSVColumn.NONE, None)),
("issn_electronic", CSVColumn("issn_electronic", CSVColumn.NONE,
None)),
("license_ref", CSVColumn("license_ref", CSVColumn.NONE, None)),
("indexed_in_crossref",
CSVColumn("indexed_in_crossref", CSVColumn.NONE, None)),
("pmid", CSVColumn("pmid", CSVColumn.NONE, None)),
("pmcid", CSVColumn("pmcid", CSVColumn.NONE, None)),
("ut", CSVColumn("ut", CSVColumn.NONE, None)),
("url", CSVColumn("url", CSVColumn.OPTIONAL, args.url_column)),
("doaj", CSVColumn("doaj", CSVColumn.NONE, None))
])
# Do not quote the values in the 'period' and 'euro' columns
quotemask = [
True,
False,
False,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
]
header = None
if has_header:
for row in reader:
if not row: # Skip empty lines
continue
header = row # First non-empty row should be the header
if args.ignore_header:
print "Skipping header analysis due to command line argument."
break
else:
print "\n *** Analyzing CSV header ***\n"
for (index, item) in enumerate(header):
column_type = oat.get_column_type_from_whitelist(item)
if column_type is not None and column_map[
column_type].index is None:
column_map[column_type].index = index
column_map[column_type].column_name = item
print("Found column named '{}' at index {}, " +
"assuming this to be the {} column.").format(
item, index, column_type)
break
print "\n *** Starting heuristical analysis ***\n"
for row in reader:
if not row: # Skip empty lines
# We analyze the first non-empty line, a possible header should
# have been processed by now.
continue
column_candidates = {"doi": [], "period": [], "euro": []}
for (index, entry) in enumerate(row):
if index in [csvcolumn.index for csvcolumn in column_map.values()]:
# Skip columns already assigned
continue
entry = entry.strip()
# Search for a DOI
if column_map['doi'].index is None:
if oat.DOI_RE.match(entry):
column_id = str(index)
# identify column either numerical or by column header
if header:
column_id += " ('" + header[index] + "')"
print("The entry in column {} looks like a " +
"DOI: {}").format(column_id, entry)
column_candidates['doi'].append(index)
continue
# Search for a potential year string
if column_map['period'].index is None:
try:
maybe_period = int(entry)
now = datetime.date.today().year
# Should be a wide enough margin
if maybe_period >= 2000 and maybe_period <= now + 2:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print("The entry in column {} looks like a " +
"potential period: {}").format(column_id, entry)
column_candidates['period'].append(index)
continue
except ValueError:
pass
# Search for a potential monetary amount
if column_map['euro'].index is None:
try:
maybe_euro = locale.atof(entry)
# Are there APCs above 6000€ ??
if maybe_euro >= 10 and maybe_euro <= 6000:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print("The entry in column {} looks like a " +
"potential euro amount: {}").format(
column_id, entry)
column_candidates['euro'].append(index)
continue
except ValueError:
pass
for column_type, candidates in column_candidates.iteritems():
if column_map[column_type].index is not None:
continue
if len(candidates) > 1:
print("Could not reliably identify the '" + column_type +
"' column - more than one possible candiate!")
elif len(candidates) < 1:
print "No candidate found for column '" + column_type + "'!"
else:
index = candidates.pop()
column_map[column_type].index = index
if header:
column_id = header[index]
column_map[column_type].column_name = column_id
else:
column_id = index
print("Assuming column '{}' to be the '{}' " +
"column.").format(column_id, column_type)
column_map[column_type].index = index
break
# Wrap up: Check if there any mandatory column types left which have not
# yet been identified - we cannot continue in that case (unless forced).
unassigned = filter(
lambda
(k, v): v.requirement == CSVColumn.MANDATORY and v.index is None,
column_map.iteritems())
if unassigned:
for item in unassigned:
print "The {} column is still unidentified.".format(item[0])
if header:
print "The CSV header is:\n" + dialect.delimiter.join(header)
if not args.force:
print("ERROR: We cannot continue because not all mandatory " +
"column types in the CSV file could be automatically " +
"identified. There are 2 ways to fix this:")
if not header:
print(
"1) Add a header row to your file and identify the " +
"column(s) by assigning them an appropiate column name.")
else:
print(
"1) Identify the missing column(s) by assigning them " +
"a different column name in the CSV header (You can " +
"use the column name(s) mentioned in the message above)")
print("2) Use command line parameters when calling this script " +
"to identify the missing columns (use -h for help) ")
sys.exit()
else:
print("WARNING: Not all mandatory column types in the CSV file " +
"could be automatically identified - forced to continue.")
print "\n *** CSV file analysis summary ***\n"
index_dict = {csvc.index: csvc for csvc in column_map.values()}
for index in range(num_columns):
column_name = ""
if header:
column_name = header[index]
if index in index_dict:
column = index_dict[index]
msg = "column number {} ({}) is the {} column '{}'".format(
index, column_name, column.requirement, column.column_type)
if column.requirement in [CSVColumn.MANDATORY, CSVColumn.OPTIONAL]:
oat.print_g(msg)
else:
oat.print_b(msg)
else:
msg = ("column number {} ({}) is an unknown column, it will be " +
"appended to the generated CSV file")
oat.print_y(msg.format(index, column_name))
if not column_name:
# Use a generic name
column_name = "unknown"
while column_name in column_map.keys():
# TODO: Replace by a numerical, increasing suffix
column_name += "_"
column_map[column_name] = CSVColumn(column_name, CSVColumn.NONE,
index)
print ""
for column in column_map.values():
if column.index is None:
msg = "The {} column '{}' could not be identified."
print msg.format(column.requirement, column.column_type)
# Check for unassigned optional column types. We can continue but should
# issue a warning as all entries will need a valid DOI in this case.
unassigned = filter(
lambda (k, v): v.requirement == CSVColumn.OPTIONAL and v.index is None,
column_map.iteritems())
if unassigned:
print("\nWARNING: Not all optional column types could be " +
"identified. Metadata aggregation is still possible, but " +
"every entry in the CSV file will need a valid DOI.")
start = raw_input("\nStart metadata aggregation? (y/n):")
while start not in ["y", "n"]:
start = raw_input("Please type 'y' or 'n':")
if start == "n":
sys.exit()
print "\n *** Starting metadata aggregation ***\n"
enriched_content = []
error_messages = []
csv_file.seek(0)
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
header_processed = False
row_num = 0
for row in reader:
row_num += 1
if not row:
continue # skip empty lines
if not header_processed:
header_processed = True
enriched_content.append(column_map.keys())
if has_header:
# If the CSV file has a header, we are currently there - skip it
# to get to the first data row
continue
print "---Processing line number " + str(row_num) + "---"
if len(row) != num_columns:
error_msg = (
"Syntax: the number of values in line {} ({}) " +
"differs from the number of columns ({}). Line left " +
"unchanged, please correct the error in the result " +
"file and re-run.")
error_msg_fmt = error_msg.format(row_num, len(row), num_columns)
error_messages.append("Line {}: {}".format(row_num, error_msg_fmt))
oat.print_r(error_msg_fmt)
enriched_content.append(row)
continue
doi = row[column_map["doi"].index]
current_row = OrderedDict()
# Copy content of identified columns
for csv_column in column_map.values():
if csv_column.index is not None and len(row[csv_column.index]) > 0:
if csv_column.column_type == "euro":
# special case for monetary values: Cast to float to ensure
# the decimal point is a dot (instead of a comma)
euro_value = row[csv_column.index]
try:
euro = locale.atof(euro_value)
if euro.is_integer():
euro = int(euro)
current_row[csv_column.column_type] = str(euro)
except ValueError:
msg = ERROR_MSGS["locale"].format(
euro_value, csv_column.index)
oat.print_r(msg)
sys.exit()
else:
current_row[csv_column.column_type] = row[csv_column.index]
else:
current_row[csv_column.column_type] = "NA"
# include crossref metadata
crossref_result = oat.get_metadata_from_crossref(doi)
if crossref_result["success"]:
print "Crossref: DOI resolved: " + doi
current_row["indexed_in_crossref"] = "TRUE"
data = crossref_result["data"]
for key, value in data.iteritems():
if value is not None:
if key == "journal_full_title":
unified_value = oat.get_unified_journal_title(value)
if unified_value != value:
msg = INFO_MSGS["unify"].format(
"journal title", value, unified_value)
oat.print_b(msg)
new_value = unified_value
elif key == "publisher":
unified_value = oat.get_unified_publisher_name(value)
if unified_value != value:
msg = INFO_MSGS["unify"].format(
"publisher name", value, unified_value)
oat.print_b(msg)
new_value = unified_value
else:
new_value = value
else:
new_value = "NA"
if args.verbose:
print(u"WARNING: Element '{}' not found in in " +
"response for doi {}.").format(key, doi)
old_value = current_row[key]
current_row[key] = column_map[key].check_overwrite(
old_value, new_value)
else:
error_msg = ("Crossref: Error while trying to resolve DOI " + doi +
": " + crossref_result["error_msg"])
oat.print_r(error_msg)
error_messages.append("Line {}: {}".format(row_num, error_msg))
current_row["indexed_in_crossref"] = "FALSE"
# include pubmed metadata
pubmed_result = oat.get_metadata_from_pubmed(doi)
if pubmed_result["success"]:
print "Pubmed: DOI resolved: " + doi
data = pubmed_result["data"]
for key, value in data.iteritems():
if value is not None:
new_value = value
else:
new_value = "NA"
if args.verbose:
print(u"WARNING: Element '{}' not found in in " +
"response for doi {}.").format(key, doi)
old_value = current_row[key]
current_row[key] = column_map[key].check_overwrite(
old_value, new_value)
else:
error_msg = ("Pubmed: Error while trying to resolve DOI " + doi +
": " + pubmed_result["error_msg"])
oat.print_r(error_msg)
error_messages.append("Line {}: {}".format(row_num, error_msg))
# lookup in DOAJ. try the EISSN first, then ISSN and finally print ISSN
if current_row["doaj"] != "TRUE":
issns = []
if current_row["issn_electronic"] != "NA":
issns.append(current_row["issn_electronic"])
if current_row["issn"] != "NA":
issns.append(current_row["issn"])
if current_row["issn_print"] != "NA":
issns.append(current_row["issn_print"])
for issn in issns:
doaj_res = oat.lookup_journal_in_doaj(
issn, args.bypass_cert_verification)
if doaj_res["data_received"]:
if doaj_res["data"]["in_doaj"]:
msg = "DOAJ: Journal ISSN ({}) found in DOAJ ('{}')."
print msg.format(issn, doaj_res["data"]["title"])
current_row["doaj"] = "TRUE"
break
else:
msg = "DOAJ: Journal ISSN ({}) not found in DOAJ."
current_row["doaj"] = "FALSE"
print msg.format(issn)
else:
msg = "DOAJ: Error while trying to look up ISSN {}: {}"
msg_fmt = msg.format(issn, doaj_res["error_msg"])
oat.print_r(msg_fmt)
error_messages.append("Line {}: {}".format(
row_num, msg_fmt))
enriched_content.append(current_row.values())
csv_file.close()
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, quotemask, True, True)
writer.write_rows(enriched_content)
if not error_messages:
oat.print_g("Metadata enrichment successful, no errors occured")
else:
oat.print_r("There were errors during the enrichment process:\n")
for msg in error_messages:
print msg + "\n"
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("column", type=int, help=ARG_HELP_STRINGS["column"])
parser.add_argument("other_csv_file", nargs="?", help=ARG_HELP_STRINGS["other_csv_file"])
parser.add_argument("other_column", type=int, nargs="?", help=ARG_HELP_STRINGS["other_column"])
parser.add_argument("-e2", "--other_encoding", help=ARG_HELP_STRINGS["other_encoding"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-i", "--ignore_case", action="store_true", default=False,
help=ARG_HELP_STRINGS["ignore_case"])
parser.add_argument("-q", "--quotemask", help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o", "--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
encs = [] #CSV file encodings
for encoding in [args.encoding, args.other_encoding]:
if encoding:
try:
codec = codecs.lookup(encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
print(msg.format(encoding, codec.name))
except LookupError:
print("Error: '" + encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
encs.append(encoding)
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if reduced:
print("Error: A quotemask may only contain the letters 't' and 'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
header, content = oat.get_csv_file_content(args.csv_file, enc=encs[0])
column = args.column
if not args.other_csv_file:
rearranged_content = header + sorted(content, key=lambda x: x[column])
else:
rearranged_content = []
_, second_content = oat.get_csv_file_content(args.other_csv_file, enc=encs[1])
other_column = column # default: use same column index as in first file
if args.other_column:
other_column = args.other_column
for other_row in second_content:
if args.ignore_case:
matching_rows = [row for row in content if row[column].lower() == other_row[other_column].lower()]
else:
matching_rows = [row for row in content if row[column] == other_row[other_column]]
rearranged_content += matching_rows
for matching_row in matching_rows:
content.remove(matching_row)
unmatched_msg = ("{} rows could not be rearranged (unmatched in second csv file) " +
"and were appended to the end of the result file " +
"in original order.")
if content:
oat.print_y(unmatched_msg.format(len(content)))
else:
oat.print_g("All rows matched.")
rearranged_content = header + rearranged_content + content # append any unmatched rows
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(rearranged_content)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("original_file", help=ARG_HELP_STRINGS["original_file"])
parser.add_argument("update_file", help=ARG_HELP_STRINGS["update_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-eu", "--update_encoding", help=ARG_HELP_STRINGS["update_encoding"])
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-lu", "--update_locale", help=ARG_HELP_STRINGS["update_locale"])
parser.add_argument("-a", "--autocreate_mappings", action="store_true", help=ARG_HELP_STRINGS["autocreate_mappings"])
parser.add_argument("-g", "--grouping", action="store_true", help=ARG_HELP_STRINGS["grouping"])
args = parser.parse_args()
params = {
"original": {
"file": args.original_file,
"encoding": args.encoding,
"locale": args.locale,
"csv_analysis": None,
"fieldnames": None,
"doi_field": None,
"euro_field": None,
"mappings": []
},
"update": {
"file": args.update_file,
"encoding": args.update_encoding,
"locale": args.update_locale,
"csv_analysis": None,
"fieldnames": None,
"doi_field": None,
"euro_field": None,
"mappings": []
}
}
def field_mapped(file_type, field_name):
if field_name == params[file_type]["euro_field"]:
return True
if field_name == params[file_type]["doi_field"]:
return True
if field_name in params[file_type]["mappings"]:
return True
return False
for file_type in params.keys():
msg = "*** Performing analysis for {} file ***"
oat.print_b(msg.format(file_type))
encoding = params[file_type]["encoding"]
if encoding is not None:
try:
codec = codecs.lookup(encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
print(msg.format(encoding, codec.name))
params[file_type]["encoding"] = encoding
except LookupError:
print ("Error: '" + encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
loc = params[file_type]["locale"]
if loc is not None:
norm = locale.normalize(loc)
if norm != loc:
msg = "locale '{}' not found, normalised to '{}'".format(loc, norm)
oat.print_y(msg)
params[file_type]["locale"] = norm
csv_analysis = oat.analyze_csv_file(params[file_type]["file"], enc=params[file_type]["encoding"])
if not csv_analysis["success"]:
oat.print_r(csv_analysis["error_msg"])
sys.exit()
params[file_type]["csv_analysis"] = csv_analysis["data"]
print(params[file_type]["csv_analysis"])
if params[file_type]["encoding"] is None:
guessed_enc = params[file_type]["csv_analysis"].enc
params[file_type]["encoding"] = guessed_enc
locale_name = "default locale"
if params[file_type]["locale"] is not None:
locale_name = "locale " + params[file_type]["locale"]
msg = "{} file will be opened with encoding {} and {}"
oat.print_g(msg.format(file_type, params[file_type]["encoding"], locale_name))
with open(params[file_type]["file"], "r", encoding=params[file_type]["encoding"]) as f:
reader = csv.DictReader(f, dialect=params[file_type]["csv_analysis"].dialect)
params[file_type]["fieldnames"] = list(reader.fieldnames)
for index, name in enumerate(params[file_type]["fieldnames"]):
field_type = oat.get_column_type_from_whitelist(name)
found = False
if field_type == "doi":
params[file_type]["doi_field"] = name
found = True
elif field_type == "euro":
params[file_type]["euro_field"] = name
found = True
if found:
msg = '{} file: Found {} column at index {} ("{}")'
msg = msg.format(file_type, field_type, index, name)
oat.print_b(msg)
for field_type in ["doi_field", "euro_field"]:
if params[file_type][field_type] is None:
msg = "Error: No {} found in {} file"
oat.print_r(msg.format(field_type, file_type))
sys.exit()
for orig_index, orig_field in enumerate(params["original"]["fieldnames"]):
if field_mapped("original", orig_field):
continue
norm_orig_field = orig_field.lower().strip()
for update_index, update_field in enumerate(params["update"]["fieldnames"]):
if field_mapped("update", update_field):
continue
norm_update_field = update_field.lower().strip()
if norm_orig_field == norm_update_field:
if args.autocreate_mappings:
params["original"]["mappings"].append(orig_field)
params["update"]["mappings"].append(update_field)
msg = 'Auto-created mapping "{}" (update file, index {}) -> "{}" (original file, index {})'
oat.print_b(msg.format(update_field, update_index, orig_field, orig_index))
else:
msg = 'Possible mapping found: "{}" (update file, index {}) -> "{}" (original file, index {}). Create mapping (y/n)?'
msg = msg.format(update_field, update_index, orig_field, orig_index)
create = input(msg)
while create not in ["y", "n"]:
create = input("Please type 'y' or 'n':")
if create == "y":
params["original"]["mappings"].append(orig_field)
params["update"]["mappings"].append(update_field)
update_mappings = {}
with open(params["update"]["file"], "r", encoding=params["update"]["encoding"]) as f:
doi_field = params["update"]["doi_field"]
euro_field = params["update"]["euro_field"]
reader = csv.DictReader(f, dialect=params["update"]["csv_analysis"].dialect)
locale.setlocale(locale.LC_ALL, params["update"]["locale"])
for line in reader:
doi = oat.get_normalised_DOI(line[doi_field])
if doi is None:
msg = 'Warning: Empty or invalid DOI in update file (line {}): "{}"'
oat.print_y(msg.format(reader.line_num, line[doi_field]))
continue
if doi in update_mappings:
msg = "Error: Duplicate doi in update file ({})".format(line[doi_field])
oat.print_r(msg)
sys.exit()
update_mappings[doi] = {}
euro_value = locale.atof(line[euro_field])
orig_euro_field = params["original"]["euro_field"]
update_mappings[doi][orig_euro_field] = euro_value
for index, update_field_name in enumerate(params["update"]["mappings"]):
orig_field_name = params["original"]["mappings"][index]
update_mappings[doi][orig_field_name] = line[update_field_name]
#print(json.dumps(update_mappings, sort_keys=False, indent=4))
modified_content = []
fieldnames = None
with open(params["original"]["file"], "r", encoding=params["original"]["encoding"]) as f:
doi_field = params["original"]["doi_field"]
euro_field = params["original"]["euro_field"]
reader = csv.DictReader(f, dialect=params["original"]["csv_analysis"].dialect)
fieldnames = list(reader.fieldnames)
locale.setlocale(locale.LC_ALL, params["original"]["locale"])
for line in reader:
doi = oat.get_normalised_DOI(line[doi_field])
if doi not in update_mappings:
msg = "line {}: DOI {} not found in update file!"
oat.print_r(msg.format(reader.line_num, doi))
continue
changes = []
old_euro_value = locale.atof(line[euro_field])
new_euro_value = update_mappings[doi][euro_field]
if old_euro_value != new_euro_value:
changes.append(Change(euro_field, old_euro_value, new_euro_value, monetary=True))
for field in update_mappings[doi].keys():
if field == euro_field:
continue
if line[field] != update_mappings[doi][field]:
changes.append(Change(field, line[field], update_mappings[doi][field]))
if not changes:
msg = "line {}: DOI {} found in update file, but nothing changed."
oat.print_g(msg.format(reader.line_num, doi))
else:
msg = "line {}: DOI {} found in update file with the following updates:"
oat.print_y(msg.format(reader.line_num, doi))
for change in changes:
oat.print_y(str(change))
if change.monetary:
line[change.field_name] = locale.currency(change.new_value,symbol=False, grouping=args.grouping)
else:
line[change.field_name] = change.new_value
del(update_mappings[doi])
modified_content.append(line)
if update_mappings:
oat.print_y("{} entries in update file not contained in original file:".format(len(update_mappings)))
for doi, changes in update_mappings.items():
oat.print_y(doi)
new_line = changes
new_line[params["original"]["doi_field"]] = doi
formatted_euro = locale.currency(new_line[params["original"]["euro_field"]], symbol=False, grouping=args.grouping)
new_line[params["original"]["euro_field"]] = formatted_euro
modified_content.append(new_line)
with open("out.csv", "w", encoding=params["original"]["encoding"]) as out:
writer = csv.DictWriter(out, fieldnames, dialect=params["original"]["csv_analysis"].dialect)
writer.writeheader()
for line in modified_content:
writer.writerow(line)
def integrate_changes(articles, file_path, enriched_file=False, dry_run=False):
'''
Update existing entries in a previously created harvest file.
Args:
articles: A list of article dicts, as retured by openapc_toolkit.oai_harvest()
file_path: Path to the CSV file the new values should be integrated into.
enriched_file: If true, columns which are overwritten during enrichment
will not be updated
dry_run: Do not make any changes to the file (but still report changes and
return the list of unencountered articles)
Returns:
A tuple. The first element is a reduced list of article dicts, containing
those which did not find a matching DOI in the file (Order preserved).
The second element is the list of column headers encountered in the harvest
file.
'''
messages = {
'wet': {
'start':
'Integrating changes in harvest data into existing file {}',
'line_change':
'Line {}: Updating value in column {} ("{}" -> "{}")',
'remove':
'PID {} no longer found in harvest data, removing article',
},
'dry': {
'start':
'Dry Run: Comparing harvest data to existing file {}',
'line_change':
'Line {} ({}): Change in column {} ("{}" -> "{}")',
'remove':
'PID {} no longer found in harvest data, article would be removed',
}
}
messages = messages['dry'] if dry_run else messages['wet']
if not os.path.isfile(file_path):
return (articles, None)
enriched_blacklist = [
"institution", "publisher", "journal_full_title", "issn",
"license_ref", "pmid"
]
article_dict = OrderedDict()
for article in articles:
# Harvested articles use OAI record IDs in the url field as PID.
url = article["url"]
if oat.has_value(url):
article_dict[url] = article
updated_lines = []
fieldnames = None
with open(file_path, "r") as f:
reader = DictReader(f)
fieldnames = reader.fieldnames
updated_lines.append(list(fieldnames)) #header
oat.print_y(messages["start"].format(file_path))
for line in reader:
url = line["url"]
if not oat.has_value(line["institution"]):
# Do not change empty lines
updated_lines.append([line[key] for key in fieldnames])
continue
line_num = reader.reader.line_num
if url in article_dict:
for key, value in article_dict[url].items():
if enriched_file and key in enriched_blacklist:
continue
if key in line and value != line[key]:
oat.print_g(messages["line_change"].format(
line_num, line["url"], key, line[key], value))
line[key] = value
del (article_dict[url])
updated_line = [line[key] for key in fieldnames]
updated_lines.append(updated_line)
else:
oat.print_r(messages["remove"].format(url))
if not dry_run:
with open(file_path, "w") as f:
mask = oat.OPENAPC_STANDARD_QUOTEMASK if enriched_file else None
writer = oat.OpenAPCUnicodeWriter(f,
quotemask=mask,
openapc_quote_rules=True,
has_header=True)
writer.write_rows(updated_lines)
return (article_dict.values(), fieldnames)
def integrate_changes(articles, file_path, enriched_file=False):
'''
Update existing entries in a previously created harvest file.
Args:
articles: A list of article dicts, as retured by openapc_toolkit.oai_harvest()
file_path: Path to the CSV file the new values should be integrated into.
enriched_file: If true, columns which are overwritten during enrichment
will not be updated
Returns:
A tuple. The first element is a reduced list of article dicts, containing
those which did not find a matching DOI in the file (Order preserved).
The second element is the list of column headers encountered in the harvest
file.
'''
if not os.path.isfile(file_path):
return (articles, None)
enriched_blacklist = [
"institution", "publisher", "journal_full_title", "issn",
"license_ref", "pmid"
]
article_dict = OrderedDict()
for article in articles:
# This is possible because currently all repos use a local ID/record url, but it's just
# a workaround. We might have to change to OAI record IDs later.
url = article["url"]
if oat.has_value(url):
article_dict[url] = article
updated_lines = []
fieldnames = None
with open(file_path, "r") as f:
reader = DictReader(f)
fieldnames = reader.fieldnames
updated_lines.append(list(fieldnames)) #header
start_msg = "Integrating changes in harvest data into existing file {}"
oat.print_g(start_msg.format(file_path))
for line in reader:
url = line["url"]
line_num = reader.reader.line_num
msg = "Line {}: Checking for changes ({})"
oat.print_b(msg.format(line_num, url))
if url in article_dict:
for key, value in article_dict[url].items():
if enriched_file and key in enriched_blacklist:
continue
if key in line and value != line[key]:
update_msg = 'Updating value in column {} ("{}" -> "{}")'
oat.print_g(update_msg.format(key, line[key], value))
line[key] = value
del (article_dict[url])
updated_line = [line[key] for key in fieldnames]
updated_lines.append(updated_line)
else:
remove_msg = "URL {} no longer found in harvest data, removing article"
oat.print_r(remove_msg.format(url))
with open(file_path, "w") as f:
mask = oat.OPENAPC_STANDARD_QUOTEMASK if enriched_file else None
writer = oat.OpenAPCUnicodeWriter(f,
quotemask=mask,
openapc_quote_rules=True,
has_header=True)
writer.write_rows(updated_lines)
return (article_dict.values(), fieldnames)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("index", type=int, help=ARG_HELP_STRINGS["index"])
parser.add_argument("-v", "--value", help=ARG_HELP_STRINGS["value"])
parser.add_argument("-f", "--file", help=ARG_HELP_STRINGS["file"])
parser.add_argument("-d", "--full_delete", action="store_true", help=ARG_HELP_STRINGS["full_delete"])
parser.add_argument("-i", "--ignore_case", action="store_true", help=ARG_HELP_STRINGS["ignore_case"])
parser.add_argument("-r", "--results_file", action="store_true", help=ARG_HELP_STRINGS["results_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q", "--quotemask", help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o", "--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
if args.value is None and args.file is None:
parser.error("Either a single value (-v option) or a file of " +
"multiple values (-f option) must be given.")
values = []
if args.file:
if not os.path.isfile(args.file):
print("Error: '" + args.file + "' is no valid file!")
sys.exit()
with open(args.file, "r") as f:
for line in f:
if len(line) > 0:
value = line.strip("\r\n")
if args.ignore_case:
values.append(value.lower())
else:
values.append(value)
oat.print_g(str(len(values)) + " values read from file")
if args.value is not None:
if args.ignore_case:
values.append(args.value.lower())
else:
values.append(args.value)
if args.file:
oat.print_y("Value argument given in addition to file " +
"argument, adding value to file imports...")
quote_rules = args.openapc_quote_rules
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
print (msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
print ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
header, content = oat.get_csv_file_content(args.csv_file, enc)
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print ("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
empty_line = ['' for element in content[0]]
column_name = "column " + str(args.index)
if header:
header_line = header[0]
column_name = header_line[args.index]
empty_line = ['' for element in header_line]
msg = u"Performing line deletion on condition '{}' in {}".format(column_name, values)
oat.print_g(msg)
modified_content = []
deleted_lines = []
num_total_lines = num_deleted_lines = 0
for line in content:
if len(line) == 0:
continue
num_total_lines += 1
current_value = line[args.index]
if args.ignore_case:
current_value = current_value.lower()
if current_value not in values:
modified_content.append(line)
else:
num_deleted_lines += 1
if not args.full_delete:
modified_content.append(list(empty_line))
if args.results_file:
deleted_lines.append(line)
msg = u"Process complete, deleted {} out of {} total lines"
oat.print_g(msg.format(num_deleted_lines, num_total_lines))
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(copy.deepcopy(header) + modified_content)
if args.results_file and len(deleted_lines) > 0:
with open('del.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(copy.deepcopy(header) + deleted_lines)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-start", type=int, default=1, help=ARG_HELP_STRINGS["start"])
parser.add_argument("-end", type=int, help=ARG_HELP_STRINGS["start"])
args = parser.parse_args()
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(oat.ANSIColorFormatter())
bufferedHandler = oat.BufferedErrorHandler(handler)
bufferedHandler.setFormatter(oat.ANSIColorFormatter())
logging.root.addHandler(handler)
logging.root.addHandler(bufferedHandler)
logging.root.setLevel(logging.INFO)
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
oat.print_g(msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
msg = ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
oat.print_r(msg)
sys.exit()
head, content = oat.get_csv_file_content(args.csv_file, enc)
content = head + content
line_num = 0
for line in content:
line_num += 1
if args.start and args.start > line_num:
continue
if args.end and args.end < line_num:
continue
# Check hybrid status
if line[4] != "TRUE":
continue
institution = line[0]
period = line[1]
doi = line[3]
publisher = line[5]
journal = line[6]
for lpl in lpl_list:
if lpl.publisher_matches(publisher):
init_msg = (u"Line {}: Checking {} article from {}, published in '" +
"{}'...").format(line_num, institution, period, journal)
oat.print_b(init_msg)
page_content = get_landingpage_content(doi, lpl)
if page_content is None:
continue
pdf_link = lpl.search_for_oa(page_content)
if pdf_link is None:
error_msg = (u"No PDF link found! (line {}, DOI: " +
"http://doi.org/{}").format(line_num, doi)
logging.error(error_msg)
elif pdf_link == "":
warning_msg = (u"A RegexGroup matched, but no PDF " +
"link was found! (line {}, DOI: " +
"http://doi.org/{}").format(line_num, doi)
logging.warning(warning_msg)
else:
oat.print_g(u"PDF link found: " + pdf_link)
time.sleep(1)
if not bufferedHandler.buffer:
oat.print_g("\nLookup finished, all articles were accessible")
else:
oat.print_r("\nLookup finished, not all articles could be accessed:\n")
# closing will implicitly flush the handler and print any buffered
# messages to stderr
bufferedHandler.close()
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-v", "--verbose", action="store_true",
help=ARG_HELP_STRINGS["verbose"])
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-i", "--ignore-header", action="store_true",
help=ARG_HELP_STRINGS["headers"])
parser.add_argument("-f", "--force", action="store_true",
help=ARG_HELP_STRINGS["force"])
parser.add_argument("-b", "--bypass-cert-verification", action="store_true",
help=ARG_HELP_STRINGS["bypass"])
parser.add_argument("-institution", "--institution_column", type=int,
help=ARG_HELP_STRINGS["institution"])
parser.add_argument("-period", "--period_column", type=int,
help=ARG_HELP_STRINGS["period"])
parser.add_argument("-doi", "--doi_column", type=int,
help=ARG_HELP_STRINGS["doi"])
parser.add_argument("-euro", "--euro_column", type=int,
help=ARG_HELP_STRINGS["euro"])
parser.add_argument("-is_hybrid", "--is_hybrid_column", type=int,
help=ARG_HELP_STRINGS["is_hybrid"])
parser.add_argument("-publisher", "--publisher_column", type=int,
help=ARG_HELP_STRINGS["publisher"])
parser.add_argument("-journal_full_title", "--journal_full_title_column",
type=int, help=ARG_HELP_STRINGS["journal_full_title"])
parser.add_argument("-issn", "--issn_column",
type=int, help=ARG_HELP_STRINGS["issn"])
parser.add_argument("-url", "--url_column",
type=int, help=ARG_HELP_STRINGS["url"])
args = parser.parse_args()
enc = None # CSV file encoding
if args.locale:
norm = locale.normalize(args.locale)
if norm != args.locale:
print "locale '{}' not found, normalized to '{}'".format(
args.locale, norm)
try:
loc = locale.setlocale(locale.LC_ALL, norm)
print "Using locale", loc
except locale.Error as loce:
print "Setting locale to " + norm + " failed: " + loce.message
sys.exit()
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
print ("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
enc = args.encoding
except LookupError:
print ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
result = oat.analyze_csv_file(args.csv_file)
if result["success"]:
csv_analysis = result["data"]
print csv_analysis
else:
print result["error_msg"]
sys.exit()
if enc is None:
enc = csv_analysis.enc
dialect = csv_analysis.dialect
has_header = csv_analysis.has_header
if enc is None:
print ("Error: No encoding given for CSV file and automated " +
"detection failed. Please set the encoding manually via the " +
"--enc argument")
sys.exit()
csv_file = open(args.csv_file, "r")
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
first_row = reader.next()
num_columns = len(first_row)
print "\nCSV file has {} columns.".format(num_columns)
csv_file.seek(0)
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
column_map = OrderedDict([
("institution", CSVColumn("institution", CSVColumn.MANDATORY, args.institution_column)),
("period", CSVColumn("period", CSVColumn.MANDATORY, args.period_column)),
("euro", CSVColumn("euro", CSVColumn.MANDATORY, args.euro_column)),
("doi", CSVColumn("doi", CSVColumn.MANDATORY, args.doi_column)),
("is_hybrid", CSVColumn("is_hybrid", CSVColumn.MANDATORY, args.is_hybrid_column)),
("publisher", CSVColumn("publisher", CSVColumn.OPTIONAL, args.publisher_column)),
("journal_full_title", CSVColumn("journal_full_title", CSVColumn.OPTIONAL,
args.journal_full_title_column)),
("issn", CSVColumn("issn", CSVColumn.OPTIONAL, args.issn_column)),
("issn_print", CSVColumn("issn_print", CSVColumn.NONE, None)),
("issn_electronic", CSVColumn("issn_electronic", CSVColumn.NONE, None)),
("license_ref", CSVColumn("license_ref", CSVColumn.NONE, None)),
("indexed_in_crossref", CSVColumn("indexed_in_crossref", CSVColumn.NONE, None)),
("pmid", CSVColumn("pmid", CSVColumn.NONE, None)),
("pmcid", CSVColumn("pmcid", CSVColumn.NONE, None)),
("ut", CSVColumn("ut", CSVColumn.NONE, None)),
("url", CSVColumn("url", CSVColumn.OPTIONAL, args.url_column)),
("doaj", CSVColumn("doaj", CSVColumn.NONE, None))
])
# Do not quote the values in the 'period' and 'euro' columns
quotemask = [
True,
False,
False,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
]
header = None
if has_header:
for row in reader:
if not row: # Skip empty lines
continue
header = row # First non-empty row should be the header
if args.ignore_header:
print "Skipping header analysis due to command line argument."
break
else:
print "\n *** Analyzing CSV header ***\n"
for (index, item) in enumerate(header):
column_type = oat.get_column_type_from_whitelist(item)
if column_type is not None and column_map[column_type].index is None:
column_map[column_type].index = index
column_map[column_type].column_name = item
print ("Found column named '{}' at index {}, " +
"assuming this to be the {} column.").format(
item, index, column_type)
break
print "\n *** Starting heuristical analysis ***\n"
for row in reader:
if not row: # Skip empty lines
# We analyze the first non-empty line, a possible header should
# have been processed by now.
continue
column_candidates = {
"doi": [],
"period": [],
"euro": []
}
for (index, entry) in enumerate(row):
if index in [csvcolumn.index for csvcolumn in column_map.values()]:
# Skip columns already assigned
continue
entry = entry.strip()
# Search for a DOI
if column_map['doi'].index is None:
if oat.DOI_RE.match(entry):
column_id = str(index)
# identify column either numerical or by column header
if header:
column_id += " ('" + header[index] + "')"
print ("The entry in column {} looks like a " +
"DOI: {}").format(column_id, entry)
column_candidates['doi'].append(index)
continue
# Search for a potential year string
if column_map['period'].index is None:
try:
maybe_period = int(entry)
now = datetime.date.today().year
# Should be a wide enough margin
if maybe_period >= 2000 and maybe_period <= now + 2:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print ("The entry in column {} looks like a " +
"potential period: {}").format(column_id, entry)
column_candidates['period'].append(index)
continue
except ValueError:
pass
# Search for a potential monetary amount
if column_map['euro'].index is None:
try:
maybe_euro = locale.atof(entry)
# Are there APCs above 6000€ ??
if maybe_euro >= 10 and maybe_euro <= 6000:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print ("The entry in column {} looks like a " +
"potential euro amount: {}").format(column_id,
entry)
column_candidates['euro'].append(index)
continue
except ValueError:
pass
for column_type, candidates in column_candidates.iteritems():
if column_map[column_type].index is not None:
continue
if len(candidates) > 1:
print ("Could not reliably identify the '" + column_type +
"' column - more than one possible candiate!")
elif len(candidates) < 1:
print "No candidate found for column '" + column_type + "'!"
else:
index = candidates.pop()
column_map[column_type].index = index
if header:
column_id = header[index]
column_map[column_type].column_name = column_id
else:
column_id = index
print ("Assuming column '{}' to be the '{}' " +
"column.").format(column_id, column_type)
column_map[column_type].index = index
break
# Wrap up: Check if there any mandatory column types left which have not
# yet been identified - we cannot continue in that case (unless forced).
unassigned = filter(lambda (k, v): v.requirement == CSVColumn.MANDATORY and v.index is None,
column_map.iteritems())
if unassigned:
for item in unassigned:
print "The {} column is still unidentified.".format(item[0])
if header:
print "The CSV header is:\n" + dialect.delimiter.join(header)
if not args.force:
print ("ERROR: We cannot continue because not all mandatory " +
"column types in the CSV file could be automatically " +
"identified. There are 2 ways to fix this:")
if not header:
print ("1) Add a header row to your file and identify the " +
"column(s) by assigning them an appropiate column name.")
else:
print ("1) Identify the missing column(s) by assigning them " +
"a different column name in the CSV header (You can " +
"use the column name(s) mentioned in the message above)")
print ("2) Use command line parameters when calling this script " +
"to identify the missing columns (use -h for help) ")
sys.exit()
else:
print ("WARNING: Not all mandatory column types in the CSV file " +
"could be automatically identified - forced to continue.")
print "\n *** CSV file analysis summary ***\n"
index_dict = {csvc.index: csvc for csvc in column_map.values()}
for index in range(num_columns):
column_name = ""
if header:
column_name = header[index]
if index in index_dict:
column = index_dict[index]
msg = "column number {} ({}) is the {} column '{}'".format(
index, column_name, column.requirement, column.column_type)
if column.requirement in [CSVColumn.MANDATORY, CSVColumn.OPTIONAL]:
oat.print_g(msg)
else:
oat.print_b(msg)
else:
msg = ("column number {} ({}) is an unknown column, it will be " +
"appended to the generated CSV file")
oat.print_y(msg.format(index, column_name))
if not column_name:
# Use a generic name
column_name = "unknown"
while column_name in column_map.keys():
# TODO: Replace by a numerical, increasing suffix
column_name += "_"
column_map[column_name] = CSVColumn(column_name, CSVColumn.NONE, index)
print ""
for column in column_map.values():
if column.index is None:
msg = "The {} column '{}' could not be identified."
print msg.format(column.requirement, column.column_type)
# Check for unassigned optional column types. We can continue but should
# issue a warning as all entries will need a valid DOI in this case.
unassigned = filter(lambda (k, v): v.requirement == CSVColumn.OPTIONAL and v.index is None,
column_map.iteritems())
if unassigned:
print ("\nWARNING: Not all optional column types could be " +
"identified. Metadata aggregation is still possible, but " +
"every entry in the CSV file will need a valid DOI.")
start = raw_input("\nStart metadata aggregation? (y/n):")
while start not in ["y", "n"]:
start = raw_input("Please type 'y' or 'n':")
if start == "n":
sys.exit()
print "\n *** Starting metadata aggregation ***\n"
enriched_content = []
error_messages = []
csv_file.seek(0)
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
header_processed = False
row_num = 0
for row in reader:
row_num += 1
if not row:
continue # skip empty lines
if not header_processed:
header_processed = True
enriched_content.append(column_map.keys())
if has_header:
# If the CSV file has a header, we are currently there - skip it
# to get to the first data row
continue
print "---Processing line number " + str(row_num) + "---"
if len(row) != num_columns:
error_msg = ("Syntax: the number of values in line {} ({}) " +
"differs from the number of columns ({}). Line left " +
"unchanged, please correct the error in the result " +
"file and re-run.")
error_msg_fmt = error_msg.format(row_num, len(row), num_columns)
error_messages.append("Line {}: {}".format(row_num, error_msg_fmt))
oat.print_r(error_msg_fmt)
enriched_content.append(row)
continue
doi = row[column_map["doi"].index]
current_row = OrderedDict()
# Copy content of identified columns
for csv_column in column_map.values():
if csv_column.index is not None and len(row[csv_column.index]) > 0:
if csv_column.column_type == "euro":
# special case for monetary values: Cast to float to ensure
# the decimal point is a dot (instead of a comma)
euro_value = row[csv_column.index]
try:
euro = locale.atof(euro_value)
if euro.is_integer():
euro = int(euro)
current_row[csv_column.column_type] = str(euro)
except ValueError:
msg = ERROR_MSGS["locale"].format(euro_value,
csv_column.index)
oat.print_r(msg)
sys.exit()
else:
current_row[csv_column.column_type] = row[csv_column.index]
else:
current_row[csv_column.column_type] = "NA"
# include crossref metadata
crossref_result = oat.get_metadata_from_crossref(doi)
if crossref_result["success"]:
print "Crossref: DOI resolved: " + doi
current_row["indexed_in_crossref"] = "TRUE"
data = crossref_result["data"]
for key, value in data.iteritems():
if value is not None:
if key == "journal_full_title":
unified_value = oat.get_unified_journal_title(value)
if unified_value != value:
msg = INFO_MSGS["unify"].format("journal title",
value,
unified_value)
oat.print_b(msg)
new_value = unified_value
elif key == "publisher":
unified_value = oat.get_unified_publisher_name(value)
if unified_value != value:
msg = INFO_MSGS["unify"].format("publisher name",
value,
unified_value)
oat.print_b(msg)
new_value = unified_value
else:
new_value = value
else:
new_value = "NA"
if args.verbose:
print (u"WARNING: Element '{}' not found in in " +
"response for doi {}.").format(key, doi)
old_value = current_row[key]
current_row[key] = column_map[key].check_overwrite(old_value, new_value)
else:
error_msg = ("Crossref: Error while trying to resolve DOI " + doi +
": " + crossref_result["error_msg"])
oat.print_r(error_msg)
error_messages.append("Line {}: {}".format(row_num, error_msg))
current_row["indexed_in_crossref"] = "FALSE"
# include pubmed metadata
pubmed_result = oat.get_metadata_from_pubmed(doi)
if pubmed_result["success"]:
print "Pubmed: DOI resolved: " + doi
data = pubmed_result["data"]
for key, value in data.iteritems():
if value is not None:
new_value = value
else:
new_value = "NA"
if args.verbose:
print (u"WARNING: Element '{}' not found in in " +
"response for doi {}.").format(key, doi)
old_value = current_row[key]
current_row[key] = column_map[key].check_overwrite(old_value, new_value)
else:
error_msg = ("Pubmed: Error while trying to resolve DOI " + doi +
": " + pubmed_result["error_msg"])
oat.print_r(error_msg)
error_messages.append("Line {}: {}".format(row_num, error_msg))
# lookup in DOAJ. try the EISSN first, then ISSN and finally print ISSN
if current_row["doaj"] != "TRUE":
issns = []
if current_row["issn_electronic"] != "NA":
issns.append(current_row["issn_electronic"])
if current_row["issn"] != "NA":
issns.append(current_row["issn"])
if current_row["issn_print"] != "NA":
issns.append(current_row["issn_print"])
for issn in issns:
doaj_res = oat.lookup_journal_in_doaj(issn, args.bypass_cert_verification)
if doaj_res["data_received"]:
if doaj_res["data"]["in_doaj"]:
msg = "DOAJ: Journal ISSN ({}) found in DOAJ ('{}')."
print msg.format(issn, doaj_res["data"]["title"])
current_row["doaj"] = "TRUE"
break
else:
msg = "DOAJ: Journal ISSN ({}) not found in DOAJ."
current_row["doaj"] = "FALSE"
print msg.format(issn)
else:
msg = "DOAJ: Error while trying to look up ISSN {}: {}"
msg_fmt = msg.format(issn, doaj_res["error_msg"])
oat.print_r(msg_fmt)
error_messages.append("Line {}: {}".format(row_num, msg_fmt))
enriched_content.append(current_row.values())
csv_file.close()
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, quotemask, True, True)
writer.write_rows(enriched_content)
if not error_messages:
oat.print_g("Metadata enrichment successful, no errors occured")
else:
oat.print_r("There were errors during the enrichment process:\n")
for msg in error_messages:
print msg + "\n"
def main():
parser = argparse.ArgumentParser()
parser.add_argument("apc_file", help=ARG_HELP_STRINGS["apc_file"])
parser.add_argument("issn_l_file", help=ARG_HELP_STRINGS["issn_l_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q", "--quotemask", help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o", "--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print ("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
print ("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
enc = args.encoding
except LookupError:
print ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
result = oat.analyze_csv_file(args.apc_file, 500)
if result["success"]:
csv_analysis = result["data"]
print csv_analysis
else:
print result["error_msg"]
sys.exit()
if enc is None:
enc = csv_analysis.enc
if enc is None:
print ("Error: No encoding given for CSV file and automated " +
"detection failed. Please set the encoding manually via the " +
"--enc argument")
sys.exit()
dialect = csv_analysis.dialect
has_header = csv_analysis.has_header
csv_file = open(args.apc_file, "r")
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
oat.print_g("Preparing mapping table...")
itself = other = 0
issn_l_re = re.compile("^(?P<issn>\d{4}-\d{3}[\dxX])\t(?P<issn_l>\d{4}-\d{3}[\dxX])$")
issn_l_file = open(args.issn_l_file, "r")
issn_l_dict = {}
for i, line in enumerate(issn_l_file):
if i % 100000 == 0:
print str(i) + " lines processed."
match = issn_l_re.match(line)
if match:
match_dict = match.groupdict()
issn_l_dict[match_dict['issn']] = match_dict['issn_l']
if match_dict['issn'] == match_dict['issn_l']:
itself += 1
else:
other += 1
print str(itself) + " ISSNs pointing to itself as ISSN-L, " + str(other) + " to another value."
oat.print_g("Starting enrichment...")
issn_matches = issn_p_matches = issn_e_matches = unmatched = different = corrections = 0
enriched_lines = []
for line in reader:
if len(line) == 0:
enriched_lines.append(line)
continue
issn = reformat_issn(line[7])
issn_p = reformat_issn(line[8])
issn_e = reformat_issn(line[9])
target = None
if issn in issn_l_dict:
target = issn_l_dict[issn]
corrected_target = oat.get_corrected_issn_l(target)
if corrected_target != target:
corrections += 1
line[10] = corrected_target
issn_matches += 1
elif issn_p in issn_l_dict:
target = issn_l_dict[issn_p]
corrected_target = oat.get_corrected_issn_l(target)
if corrected_target != target:
corrections += 1
line[10] = corrected_target
issn_p_matches += 1
elif issn_e in issn_l_dict:
target = issn_l_dict[issn_e]
corrected_target = oat.get_corrected_issn_l(target)
if corrected_target != target:
corrections += 1
line[10] = corrected_target
issn_e_matches += 1
else:
unmatched += 1
if target is not None and target not in [issn, issn_p, issn_e]:
different += 1
enriched_lines.append(line)
print "{} issn_l values mapped by issn, {} by issn_p, {} by issn_e. {} could not be assigned.\n{} issn_l values were corrected during the process.\n In {} cases the ISSN-L was different from all existing ISSN values".format(issn_matches, issn_p_matches, issn_e_matches, unmatched, corrections, different)
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, has_header)
writer.write_rows(enriched_lines)
return "HTTPError: {} - {}".format(code, httpe.reason)
except urllib2.URLError as urle:
return "URLError: {}".format(urle.reason)
except ET.ParseError as etpe:
return "ElementTree ParseError: {}".format(str(etpe))
parser = argparse.ArgumentParser()
parser.add_argument("doi_or_file", help="An OpenAPC-compatible CSV file or a single DOI to look up in crossref.")
args = parser.parse_args()
arg = args.doi_or_file
if os.path.isfile(arg):
csv_file = open(arg, "r")
reader = oat.UnicodeReader(csv_file)
line_number = 0
for line in reader:
if not line:
prefix = ""
else:
prefix = get_prefix(line[3])
result = str(line_number) + ": " + prefix
if prefix == "Springer (Biomed Central Ltd.)":
oat.print_g(result)
elif prefix == "Nature Publishing Group":
oat.print_r(result)
else:
print result
line_number += 1
else:
print get_prefix(arg)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("source_file")
parser.add_argument("source_column", type=int)
parser.add_argument("currency_column", type=int)
parser.add_argument("period_column", type=int)
parser.add_argument("target_column", type=int)
parser.add_argument("-f", "--force_overwrite", action="store_true")
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q", "--quotemask", help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o", "--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print ("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
oat.print_g(msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
print ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
if args.locale:
norm = locale.normalize(args.locale)
if norm != args.locale:
msg = "locale '{}' not found, normalised to '{}'".format(
args.locale, norm)
oat.print_y(msg)
try:
loc = locale.setlocale(locale.LC_ALL, norm)
oat.print_g("Using locale " + loc)
except locale.Error as loce:
msg = "Setting locale to {} failed: {}".format(norm, loce.message)
oat.print_r(msg)
sys.exit()
header, content = oat.get_csv_file_content(args.source_file, enc, True)
fieldnames = header.pop()
modified_content = []
line_num = 0
for column_type in ["source_column", "currency_column", "period_column", "target_column"]:
index = getattr(args, column_type)
msg = "Column {} ('{}') is the {}."
oat.print_g(msg.format(index, fieldnames[index], column_type))
start = input("\nStart conversion? (y/n):")
while start not in ["y", "n"]:
start = input("Please type 'y' or 'n':")
if start == "n":
sys.exit()
for line in content:
line_num += 1
if not oat.has_value(line[args.source_column]):
oat.print_y("WARNING: No source value found in line " + str(line_num) + ", skipping...")
modified_content.append(line)
continue
monetary_value = None
try:
monetary_value = locale.atof(line[args.source_column])
except ValueError:
msg = "WARNING: Could not extract a valid monetary value from source column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, line[args.source_column]))
modified_content.append(line)
continue
currency = line[args.currency_column]
if not oat.has_value(currency):
msg = "WARNING: Could not extract a valid currency indicator from currency column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, currency))
modified_content.append(line)
continue
period = line[args.period_column]
frequency = get_frequency(period)
if frequency is None:
msg = "WARNING: Could not extract a valid date string from period column in line {} ('{}'), skipping..."
oat.print_y(msg.format(line_num, period))
modified_content.append(line)
continue
if currency not in EXCHANGE_RATES[frequency]:
msg = 'No exchange rates ({}) found for currency "{}", querying ECB data warehouse...'
oat.print_b(msg.format(frequency, currency))
rates = oat.get_euro_exchange_rates(currency, frequency)
EXCHANGE_RATES[frequency][currency] = rates
try:
rate = EXCHANGE_RATES[frequency][currency][period]
except KeyError:
msg = "ERROR: No conversion rate found for currency {} for period {} (line {}), aborting..."
oat.print_r(msg.format(currency, period, line_num))
sys.exit()
euro_value = round(monetary_value/float(rate), 2)
line[args.target_column] = str(euro_value)
msg = "Line {}: {} exchange rate ({}) for date {} is {} -> {} / {} = {} EUR"
msg = msg.format(line_num, currency, frequency, period, rate, monetary_value, rate, euro_value)
oat.print_g(msg)
modified_content.append(line)
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, True)
writer.write_rows([fieldnames] + modified_content)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-O", "--offsetting_mode", help=ARG_HELP_STRINGS["offsetting"])
parser.add_argument("-b", "--bypass-cert-verification", action="store_true",
help=ARG_HELP_STRINGS["bypass"])
parser.add_argument("-d", "--offline_doaj",
help=ARG_HELP_STRINGS["offline_doaj"])
parser.add_argument("-D", "--offline_doaj_download",
help=ARG_HELP_STRINGS["offline_doaj_download"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-f", "--force", action="store_true",
help=ARG_HELP_STRINGS["force"])
parser.add_argument("-i", "--ignore-header", action="store_true",
help=ARG_HELP_STRINGS["ignore_header"])
parser.add_argument("-j", "--force-header", action="store_true",
help=ARG_HELP_STRINGS["force_header"])
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-u", "--add-unknown-columns", action="store_true",
help=ARG_HELP_STRINGS["unknown_columns"])
parser.add_argument("-v", "--verbose", action="store_true",
help=ARG_HELP_STRINGS["verbose"])
parser.add_argument("-o", "--overwrite", action="store_true",
help=ARG_HELP_STRINGS["overwrite"])
parser.add_argument("-r", "--round_monetary", action="store_true",
help=ARG_HELP_STRINGS["round_monetary"])
parser.add_argument("--no-crossref", action="store_true",
help=ARG_HELP_STRINGS["no_crossref"])
parser.add_argument("--no-pubmed", action="store_true",
help=ARG_HELP_STRINGS["no_pubmed"])
parser.add_argument("--no-doaj", action="store_true",
help=ARG_HELP_STRINGS["no_doaj"])
parser.add_argument("-institution", "--institution_column", type=int,
help=ARG_HELP_STRINGS["institution"])
parser.add_argument("-period", "--period_column", type=int,
help=ARG_HELP_STRINGS["period"])
parser.add_argument("-doi", "--doi_column", type=int,
help=ARG_HELP_STRINGS["doi"])
parser.add_argument("-euro", "--euro_column", type=int,
help=ARG_HELP_STRINGS["euro"])
parser.add_argument("-is_hybrid", "--is_hybrid_column", type=int,
help=ARG_HELP_STRINGS["is_hybrid"])
parser.add_argument("-publisher", "--publisher_column", type=int,
help=ARG_HELP_STRINGS["publisher"])
parser.add_argument("-journal_full_title", "--journal_full_title_column",
type=int, help=ARG_HELP_STRINGS["journal_full_title"])
parser.add_argument("-issn", "--issn_column",
type=int, help=ARG_HELP_STRINGS["issn"])
parser.add_argument("-url", "--url_column",
type=int, help=ARG_HELP_STRINGS["url"])
parser.add_argument("-start", type=int, help=ARG_HELP_STRINGS["start"])
parser.add_argument("-end", type=int, help=ARG_HELP_STRINGS["end"])
parser.add_argument("-q", "--quotemask", default="tfftttttttttttttttt",
help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-n", "--no-openapc-quote-rules",
help=ARG_HELP_STRINGS["no_openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(oat.ANSIColorFormatter())
bufferedHandler = oat.BufferedErrorHandler(handler)
bufferedHandler.setFormatter(oat.ANSIColorFormatter())
logging.root.addHandler(handler)
logging.root.addHandler(bufferedHandler)
logging.root.setLevel(logging.INFO)
if args.offline_doaj and args.offline_doaj_download:
oat.print_r("Error: Either use the -d or the -D option, not both.")
sys.exit()
if args.locale:
norm = locale.normalize(args.locale)
if norm != args.locale:
msg = "locale '{}' not found, normalised to '{}'".format(
args.locale, norm)
oat.print_y(msg)
try:
loc = locale.setlocale(locale.LC_ALL, norm)
oat.print_g("Using locale " + loc)
except locale.Error as loce:
msg = "Setting locale to {} failed: {}".format(norm, loce.message)
oat.print_r(msg)
sys.exit()
enc = None # CSV file encoding
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = ("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
oat.print_g(msg)
enc = args.encoding
except LookupError:
msg = ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
oat.print_r(msg)
sys.exit()
result = oat.analyze_csv_file(args.csv_file, enc=enc)
if result["success"]:
csv_analysis = result["data"]
print(csv_analysis)
else:
print(result["error_msg"])
sys.exit()
if enc is None:
enc = csv_analysis.enc
dialect = csv_analysis.dialect
has_header = csv_analysis.has_header or args.force_header
if enc is None:
print("Error: No encoding given for CSV file and automated " +
"detection failed. Please set the encoding manually via the " +
"--enc argument")
sys.exit()
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print("Error: A quotemask may only contain the letters 't' and " +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
doaj_offline_analysis = None
if args.offline_doaj:
if os.path.isfile(args.offline_doaj):
doaj_offline_analysis = oat.DOAJOfflineAnalysis(args.offline_doaj)
else:
oat.print_r("Error: " + args.offline_doaj + " does not seem "
"to be a file!")
sys.exit()
elif args.offline_doaj_download:
if os.path.isfile(args.offline_doaj_download):
oat.print_r("Error: Target file '" + args.offline_doaj_download + "' already exists!")
sys.exit()
doaj_offline_analysis = oat.DOAJOfflineAnalysis(args.offline_doaj_download, download=True)
csv_file = open(args.csv_file, "r", encoding=enc)
reader = csv.reader(csv_file, dialect=dialect)
first_row = next(reader)
num_columns = len(first_row)
print("\nCSV file has {} columns.".format(num_columns))
csv_file.seek(0)
reader = csv.reader(csv_file, dialect=dialect)
if args.overwrite:
ow_strategy = CSVColumn.OW_ALWAYS
else:
ow_strategy = CSVColumn.OW_ASK
openapc_column_map = OrderedDict([
("institution", CSVColumn("institution", CSVColumn.MANDATORY, args.institution_column, overwrite=ow_strategy)),
("period", CSVColumn("period", CSVColumn.MANDATORY, args.period_column, overwrite=ow_strategy)),
("euro", CSVColumn("euro", CSVColumn.MANDATORY, args.euro_column, overwrite=ow_strategy)),
("doi", CSVColumn("doi", CSVColumn.MANDATORY, args.doi_column, overwrite=ow_strategy)),
("is_hybrid", CSVColumn("is_hybrid", CSVColumn.MANDATORY, args.is_hybrid_column, overwrite=ow_strategy)),
("publisher", CSVColumn("publisher", CSVColumn.OPTIONAL, args.publisher_column, overwrite=ow_strategy)),
("journal_full_title", CSVColumn("journal_full_title", CSVColumn.OPTIONAL,
args.journal_full_title_column, overwrite=ow_strategy)),
("issn", CSVColumn("issn", CSVColumn.OPTIONAL, args.issn_column, overwrite=ow_strategy)),
("issn_print", CSVColumn("issn_print", CSVColumn.NONE, None, overwrite=ow_strategy)),
("issn_electronic", CSVColumn("issn_electronic", CSVColumn.NONE, None, overwrite=ow_strategy)),
("issn_l", CSVColumn("issn_l", CSVColumn.NONE, None, overwrite=ow_strategy)),
("license_ref", CSVColumn("license_ref", CSVColumn.NONE, None, overwrite=ow_strategy)),
("indexed_in_crossref", CSVColumn("indexed_in_crossref", CSVColumn.NONE, None, overwrite=ow_strategy)),
("pmid", CSVColumn("pmid", CSVColumn.NONE, None, overwrite=ow_strategy)),
("pmcid", CSVColumn("pmcid", CSVColumn.NONE, None, overwrite=ow_strategy)),
("ut", CSVColumn("ut", CSVColumn.NONE, None, overwrite=ow_strategy)),
("url", CSVColumn("url", CSVColumn.OPTIONAL, args.url_column, overwrite=ow_strategy)),
("doaj", CSVColumn("doaj", CSVColumn.NONE, None, overwrite=ow_strategy))
])
offsetting_column_map = OrderedDict([
("institution", CSVColumn("institution", CSVColumn.MANDATORY, args.institution_column, overwrite=ow_strategy)),
("period", CSVColumn("period", CSVColumn.MANDATORY, args.period_column, overwrite=ow_strategy)),
("euro", CSVColumn("euro", CSVColumn.NONE, args.euro_column, overwrite=ow_strategy)),
("doi", CSVColumn("doi", CSVColumn.MANDATORY, args.doi_column, overwrite=ow_strategy)),
("is_hybrid", CSVColumn("is_hybrid", CSVColumn.MANDATORY, args.is_hybrid_column, overwrite=ow_strategy)),
("publisher", CSVColumn("publisher", CSVColumn.OPTIONAL, args.publisher_column, overwrite=ow_strategy)),
("journal_full_title", CSVColumn("journal_full_title", CSVColumn.OPTIONAL,
args.journal_full_title_column, overwrite=ow_strategy)),
("issn", CSVColumn("issn", CSVColumn.OPTIONAL, args.issn_column, overwrite=ow_strategy)),
("issn_print", CSVColumn("issn_print", CSVColumn.NONE, None, overwrite=ow_strategy)),
("issn_electronic", CSVColumn("issn_electronic", CSVColumn.NONE, None, overwrite=ow_strategy)),
("issn_l", CSVColumn("issn_l", CSVColumn.NONE, None, overwrite=ow_strategy)),
("license_ref", CSVColumn("license_ref", CSVColumn.NONE, None, overwrite=ow_strategy)),
("indexed_in_crossref", CSVColumn("indexed_in_crossref", CSVColumn.NONE, None, overwrite=ow_strategy)),
("pmid", CSVColumn("pmid", CSVColumn.NONE, None, overwrite=ow_strategy)),
("pmcid", CSVColumn("pmcid", CSVColumn.NONE, None, overwrite=ow_strategy)),
("ut", CSVColumn("ut", CSVColumn.NONE, None, overwrite=ow_strategy)),
("url", CSVColumn("url", CSVColumn.OPTIONAL, args.url_column, overwrite=ow_strategy)),
("doaj", CSVColumn("doaj", CSVColumn.NONE, None, overwrite=ow_strategy)),
("agreement", CSVColumn("agreement", CSVColumn.NONE, None, overwrite=ow_strategy)),
])
if args.offsetting_mode:
column_map = offsetting_column_map
else:
column_map = openapc_column_map
header = None
if has_header:
for row in reader:
if not row: # Skip empty lines
continue
header = row # First non-empty row should be the header
if args.ignore_header:
print("Skipping header analysis due to command line argument.")
break
else:
print("\n *** Analyzing CSV header ***\n")
for (index, item) in enumerate(header):
column_type = oat.get_column_type_from_whitelist(item)
if column_type is not None and column_map[column_type].index is None:
column_map[column_type].index = index
column_map[column_type].column_name = item
found_msg = ("Found column named '{}' at index {}, " +
"assuming this to be the {} column.")
print(found_msg.format(item, index, column_type))
break
print("\n *** Starting heuristical analysis ***\n")
for row in reader:
if not row: # Skip empty lines
# We analyze the first non-empty line, a possible header should
# have been processed by now.
continue
column_candidates = {
"doi": [],
"period": [],
"euro": []
}
found_msg = "The entry in column {} looks like a potential {}: {}"
for (index, entry) in enumerate(row):
if index in [csvcolumn.index for csvcolumn in column_map.values()]:
# Skip columns already assigned
continue
entry = entry.strip()
# Search for a DOI
if column_map['doi'].index is None:
if oat.DOI_RE.match(entry):
column_id = str(index)
# identify column either numerically or by column header
if header:
column_id += " ('" + header[index] + "')"
print(found_msg.format(column_id, "DOI", entry))
column_candidates['doi'].append(index)
continue
# Search for a potential year string
if column_map['period'].index is None:
try:
maybe_period = int(entry)
now = datetime.date.today().year
# Should be a wide enough margin
if maybe_period >= 2000 and maybe_period <= now + 2:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print(found_msg.format(column_id, "year", entry))
column_candidates['period'].append(index)
continue
except ValueError:
pass
# Search for a potential monetary amount
if column_map['euro'].index is None:
try:
maybe_euro = locale.atof(entry)
if maybe_euro >= 10 and maybe_euro <= 10000:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print (found_msg.format(column_id, "euro amount", entry))
column_candidates['euro'].append(index)
continue
except ValueError:
pass
for column_type, candidates in column_candidates.items():
if column_map[column_type].index is not None:
continue
if len(candidates) > 1:
print("Could not reliably identify the '" + column_type +
"' column - more than one possible candiate!")
elif len(candidates) < 1:
print("No candidate found for column '" + column_type + "'!")
else:
index = candidates.pop()
column_map[column_type].index = index
if header:
column_id = header[index]
column_map[column_type].column_name = column_id
else:
column_id = index
msg = "Assuming column '{}' to be the '{}' column."
print(msg.format(column_id, column_type))
column_map[column_type].index = index
break
# Wrap up: Check if there any mandatory column types left which have not
# yet been identified - we cannot continue in that case (unless forced).
unassigned = [x for x in iter(column_map.items()) if x[1].requirement == CSVColumn.MANDATORY and x[1].index is None]
if unassigned:
for item in unassigned:
print("The {} column is still unidentified.".format(item[0]))
if header:
print("The CSV header is:\n" + dialect.delimiter.join(header))
if not args.force:
print("ERROR: We cannot continue because not all mandatory " +
"column types in the CSV file could be automatically " +
"identified. There are 2 ways to fix this:")
if not header:
print("1) Add a header row to your file and identify the " +
"column(s) by assigning them an appropiate column name.")
else:
print("1) Identify the missing column(s) by assigning them " +
"a different column name in the CSV header (You can " +
"use the column name(s) mentioned in the message above)")
print("2) Use command line parameters when calling this script " +
"to identify the missing columns (use -h for help) ")
sys.exit()
else:
print("WARNING: Not all mandatory column types in the CSV file " +
"could be automatically identified - forced to continue.")
print("\n *** CSV file analysis summary ***\n")
index_dict = {csvc.index: csvc for csvc in column_map.values()}
for index in range(num_columns):
column_name = ""
if header:
column_name = header[index]
if index in index_dict:
column = index_dict[index]
msg = u"column number {} ({}) is the {} column '{}'".format(
index, column_name, column.requirement, column.column_type)
if column.requirement in [CSVColumn.MANDATORY, CSVColumn.OPTIONAL]:
oat.print_g(msg)
else:
oat.print_b(msg)
else:
if args.add_unknown_columns:
msg = (u"column number {} ({}) is an unknown column, it will be " +
"appended to the generated CSV file")
oat.print_y(msg.format(index, column_name))
if not column_name:
# Use a generic name
column_name = "unknown"
while column_name in column_map.keys():
# TODO: Replace by a numerical, increasing suffix
column_name += "_"
column_map[column_name] = CSVColumn(column_name, CSVColumn.NONE, index)
else:
msg = (u"column number {} ({}) is an unknown column, it will be " +
"ignored")
oat.print_y(msg.format(index, column_name))
print()
for column in column_map.values():
if column.index is None:
msg = "The {} column '{}' could not be identified."
print(msg.format(column.requirement, column.column_type))
# Check for unassigned optional column types. We can continue but should
# issue a warning as all entries will need a valid DOI in this case.
unassigned = filter(lambda k, v: v.requirement == CSVColumn.OPTIONAL and v.index is None,
column_map.items())
if unassigned:
print ("\nWARNING: Not all optional column types could be " +
"identified. Metadata aggregation is still possible, but " +
"every entry in the CSV file will need a valid DOI.")
start = input("\nStart metadata aggregation? (y/n):")
while start not in ["y", "n"]:
start = input("Please type 'y' or 'n':")
if start == "n":
sys.exit()
print("\n *** Starting metadata aggregation ***\n")
enriched_content = []
csv_file.seek(0)
reader = csv.reader(csv_file, dialect=dialect)
header_processed = False
row_num = 0
for row in reader:
row_num += 1
if not row:
continue # skip empty lines
if not header_processed:
header_processed = True
enriched_content.append(list(column_map.keys()))
if has_header:
# If the CSV file has a header, we are currently there - skip it
# to get to the first data row
continue
if args.start and args.start > row_num:
continue
if args.end and args.end < row_num:
continue
print("---Processing line number " + str(row_num) + "---")
enriched_row = oat.process_row(row, row_num, column_map, num_columns,
args.no_crossref, args.no_pubmed,
args.no_doaj, doaj_offline_analysis, args.round_monetary,
args.offsetting_mode)
enriched_content.append(enriched_row)
csv_file.close()
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask,
not args.no_openapc_quote_rules, True,
True)
writer.write_rows(enriched_content)
if not bufferedHandler.buffer:
oat.print_g("Metadata enrichment successful, no errors occured")
else:
oat.print_r("There were errors during the enrichment process:\n")
# closing will implicitly flush the handler and print any buffered
# messages to stderr
bufferedHandler.close()
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("index", type=int, help=ARG_HELP_STRINGS["index"])
parser.add_argument("-v", "--value", help=ARG_HELP_STRINGS["value"])
parser.add_argument("-f", "--file", help=ARG_HELP_STRINGS["file"])
parser.add_argument("-d",
"--full_delete",
action="store_true",
help=ARG_HELP_STRINGS["full_delete"])
parser.add_argument("-i",
"--ignore_case",
action="store_true",
help=ARG_HELP_STRINGS["ignore_case"])
parser.add_argument("-r",
"--results_file",
action="store_true",
help=ARG_HELP_STRINGS["results_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q",
"--quotemask",
help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o",
"--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true",
default=False)
args = parser.parse_args()
if args.value is None and args.file is None:
parser.error("Either a single value (-v option) or a file of " +
"multiple values (-f option) must be given.")
values = []
if args.file:
if not os.path.isfile(args.file):
print("Error: '" + args.file + "' is no valid file!")
sys.exit()
with open(args.file, "r") as f:
for line in f:
if len(line) > 0:
value = line.strip("\r\n")
if args.ignore_case:
values.append(value.lower())
else:
values.append(value)
oat.print_g(str(len(values)) + " values read from file")
if args.value is not None:
if args.ignore_case:
values.append(args.value.lower())
else:
values.append(args.value)
if args.file:
oat.print_y("Value argument given in addition to file " +
"argument, adding value to file imports...")
quote_rules = args.openapc_quote_rules
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
print(msg.format(args.encoding, codec.name))
enc = args.encoding
except LookupError:
print("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
header, content = oat.get_csv_file_content(args.csv_file, enc)
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
empty_line = ['' for element in content[0]]
column_name = "column " + str(args.index)
if header:
header_line = header[0]
column_name = header_line[args.index]
empty_line = ['' for element in header_line]
msg = u"Performing line deletion on condition '{}' in {}".format(
column_name, values)
oat.print_g(msg)
modified_content = []
deleted_lines = []
num_total_lines = num_deleted_lines = 0
for line in content:
if len(line) == 0:
continue
num_total_lines += 1
current_value = line[args.index]
if args.ignore_case:
current_value = current_value.lower()
if current_value not in values:
modified_content.append(line)
else:
num_deleted_lines += 1
if not args.full_delete:
modified_content.append(list(empty_line))
if args.results_file:
deleted_lines.append(line)
msg = u"Process complete, deleted {} out of {} total lines"
oat.print_g(msg.format(num_deleted_lines, num_total_lines))
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(copy.deepcopy(header) + modified_content)
if args.results_file and len(deleted_lines) > 0:
with open('del.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(copy.deepcopy(header) + deleted_lines)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-b",
"--bypass-cert-verification",
action="store_true",
help=ARG_HELP_STRINGS["bypass"])
parser.add_argument("-d",
"--offline_doaj",
help=ARG_HELP_STRINGS["offline_doaj"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-f",
"--force",
action="store_true",
help=ARG_HELP_STRINGS["force"])
parser.add_argument("-i",
"--ignore-header",
action="store_true",
help=ARG_HELP_STRINGS["ignore_header"])
parser.add_argument("-j",
"--force-header",
action="store_true",
help=ARG_HELP_STRINGS["force_header"])
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-u",
"--add-unknown-columns",
action="store_true",
help=ARG_HELP_STRINGS["unknown_columns"])
parser.add_argument("-v",
"--verbose",
action="store_true",
help=ARG_HELP_STRINGS["verbose"])
parser.add_argument("-institution",
"--institution_column",
type=int,
help=ARG_HELP_STRINGS["institution"])
parser.add_argument("-period",
"--period_column",
type=int,
help=ARG_HELP_STRINGS["period"])
parser.add_argument("-doi",
"--doi_column",
type=int,
help=ARG_HELP_STRINGS["doi"])
parser.add_argument("-euro",
"--euro_column",
type=int,
help=ARG_HELP_STRINGS["euro"])
parser.add_argument("-is_hybrid",
"--is_hybrid_column",
type=int,
help=ARG_HELP_STRINGS["is_hybrid"])
parser.add_argument("-publisher",
"--publisher_column",
type=int,
help=ARG_HELP_STRINGS["publisher"])
parser.add_argument("-journal_full_title",
"--journal_full_title_column",
type=int,
help=ARG_HELP_STRINGS["journal_full_title"])
parser.add_argument("-issn",
"--issn_column",
type=int,
help=ARG_HELP_STRINGS["issn"])
parser.add_argument("-url",
"--url_column",
type=int,
help=ARG_HELP_STRINGS["url"])
parser.add_argument("-start", type=int, help=ARG_HELP_STRINGS["start"])
parser.add_argument("-end", type=int, help=ARG_HELP_STRINGS["end"])
args = parser.parse_args()
enc = None # CSV file encoding
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(ANSIColorFormatter())
bufferedHandler = BufferedErrorHandler(handler)
bufferedHandler.setFormatter(ANSIColorFormatter())
logging.root.addHandler(handler)
logging.root.addHandler(bufferedHandler)
logging.root.setLevel(logging.INFO)
if args.locale:
norm = locale.normalize(args.locale)
if norm != args.locale:
print "locale '{}' not found, normalized to '{}'".format(
args.locale, norm)
try:
loc = locale.setlocale(locale.LC_ALL, norm)
print "Using locale", loc
except locale.Error as loce:
print "Setting locale to " + norm + " failed: " + loce.message
sys.exit()
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
print("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
enc = args.encoding
except LookupError:
print("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
result = oat.analyze_csv_file(args.csv_file)
if result["success"]:
csv_analysis = result["data"]
print csv_analysis
else:
print result["error_msg"]
sys.exit()
if enc is None:
enc = csv_analysis.enc
dialect = csv_analysis.dialect
has_header = csv_analysis.has_header or args.force_header
if enc is None:
print("Error: No encoding given for CSV file and automated " +
"detection failed. Please set the encoding manually via the " +
"--enc argument")
sys.exit()
doaj_offline_analysis = None
if args.offline_doaj:
if os.path.isfile(args.offline_doaj):
doaj_offline_analysis = oat.DOAJOfflineAnalysis(args.offline_doaj)
else:
oat.print_r("Error: " + args.offline_doaj + " does not seem "
"to be a file!")
csv_file = open(args.csv_file, "r")
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
first_row = reader.next()
num_columns = len(first_row)
print "\nCSV file has {} columns.".format(num_columns)
csv_file.seek(0)
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
column_map = OrderedDict([
("institution",
CSVColumn("institution", CSVColumn.MANDATORY,
args.institution_column)),
("period", CSVColumn("period", CSVColumn.MANDATORY,
args.period_column)),
("euro", CSVColumn("euro", CSVColumn.MANDATORY, args.euro_column)),
("doi", CSVColumn("doi", CSVColumn.MANDATORY, args.doi_column)),
("is_hybrid",
CSVColumn("is_hybrid", CSVColumn.MANDATORY, args.is_hybrid_column)),
("publisher",
CSVColumn("publisher", CSVColumn.OPTIONAL, args.publisher_column)),
("journal_full_title",
CSVColumn("journal_full_title", CSVColumn.OPTIONAL,
args.journal_full_title_column)),
("issn", CSVColumn("issn", CSVColumn.OPTIONAL, args.issn_column)),
("issn_print", CSVColumn("issn_print", CSVColumn.NONE, None)),
("issn_electronic", CSVColumn("issn_electronic", CSVColumn.NONE,
None)),
("license_ref", CSVColumn("license_ref", CSVColumn.NONE, None)),
("indexed_in_crossref",
CSVColumn("indexed_in_crossref", CSVColumn.NONE, None)),
("pmid", CSVColumn("pmid", CSVColumn.NONE, None)),
("pmcid", CSVColumn("pmcid", CSVColumn.NONE, None)),
("ut", CSVColumn("ut", CSVColumn.NONE, None)),
("url", CSVColumn("url", CSVColumn.OPTIONAL, args.url_column)),
("doaj", CSVColumn("doaj", CSVColumn.NONE, None))
])
# Do not quote the values in the 'period' and 'euro' columns
quotemask = [
True,
False,
False,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
True,
]
header = None
if has_header:
for row in reader:
if not row: # Skip empty lines
continue
header = row # First non-empty row should be the header
if args.ignore_header:
print "Skipping header analysis due to command line argument."
break
else:
print "\n *** Analyzing CSV header ***\n"
for (index, item) in enumerate(header):
column_type = oat.get_column_type_from_whitelist(item)
if column_type is not None and column_map[
column_type].index is None:
column_map[column_type].index = index
column_map[column_type].column_name = item
print("Found column named '{}' at index {}, " +
"assuming this to be the {} column.").format(
item, index, column_type)
break
print "\n *** Starting heuristical analysis ***\n"
for row in reader:
if not row: # Skip empty lines
# We analyze the first non-empty line, a possible header should
# have been processed by now.
continue
column_candidates = {"doi": [], "period": [], "euro": []}
for (index, entry) in enumerate(row):
if index in [csvcolumn.index for csvcolumn in column_map.values()]:
# Skip columns already assigned
continue
entry = entry.strip()
# Search for a DOI
if column_map['doi'].index is None:
if oat.DOI_RE.match(entry):
column_id = str(index)
# identify column either numerical or by column header
if header:
column_id += " ('" + header[index] + "')"
print("The entry in column {} looks like a " +
"DOI: {}").format(column_id, entry)
column_candidates['doi'].append(index)
continue
# Search for a potential year string
if column_map['period'].index is None:
try:
maybe_period = int(entry)
now = datetime.date.today().year
# Should be a wide enough margin
if maybe_period >= 2000 and maybe_period <= now + 2:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print("The entry in column {} looks like a " +
"potential period: {}").format(column_id, entry)
column_candidates['period'].append(index)
continue
except ValueError:
pass
# Search for a potential monetary amount
if column_map['euro'].index is None:
try:
maybe_euro = locale.atof(entry)
# Are there APCs above 6000€ ??
if maybe_euro >= 10 and maybe_euro <= 6000:
column_id = str(index)
if header:
column_id += " ('" + header[index] + "')"
print("The entry in column {} looks like a " +
"potential euro amount: {}").format(
column_id, entry)
column_candidates['euro'].append(index)
continue
except ValueError:
pass
for column_type, candidates in column_candidates.iteritems():
if column_map[column_type].index is not None:
continue
if len(candidates) > 1:
print("Could not reliably identify the '" + column_type +
"' column - more than one possible candiate!")
elif len(candidates) < 1:
print "No candidate found for column '" + column_type + "'!"
else:
index = candidates.pop()
column_map[column_type].index = index
if header:
column_id = header[index]
column_map[column_type].column_name = column_id
else:
column_id = index
print("Assuming column '{}' to be the '{}' " +
"column.").format(column_id, column_type)
column_map[column_type].index = index
break
# Wrap up: Check if there any mandatory column types left which have not
# yet been identified - we cannot continue in that case (unless forced).
unassigned = filter(
lambda
(k, v): v.requirement == CSVColumn.MANDATORY and v.index is None,
column_map.iteritems())
if unassigned:
for item in unassigned:
print "The {} column is still unidentified.".format(item[0])
if header:
print "The CSV header is:\n" + dialect.delimiter.join(header)
if not args.force:
print("ERROR: We cannot continue because not all mandatory " +
"column types in the CSV file could be automatically " +
"identified. There are 2 ways to fix this:")
if not header:
print(
"1) Add a header row to your file and identify the " +
"column(s) by assigning them an appropiate column name.")
else:
print(
"1) Identify the missing column(s) by assigning them " +
"a different column name in the CSV header (You can " +
"use the column name(s) mentioned in the message above)")
print("2) Use command line parameters when calling this script " +
"to identify the missing columns (use -h for help) ")
sys.exit()
else:
print("WARNING: Not all mandatory column types in the CSV file " +
"could be automatically identified - forced to continue.")
print "\n *** CSV file analysis summary ***\n"
index_dict = {csvc.index: csvc for csvc in column_map.values()}
for index in range(num_columns):
column_name = ""
if header:
column_name = header[index]
if index in index_dict:
column = index_dict[index]
msg = "column number {} ({}) is the {} column '{}'".format(
index, column_name, column.requirement, column.column_type)
if column.requirement in [CSVColumn.MANDATORY, CSVColumn.OPTIONAL]:
oat.print_g(msg)
else:
oat.print_b(msg)
else:
if args.add_unknown_columns:
msg = (
"column number {} ({}) is an unknown column, it will be " +
"appended to the generated CSV file")
oat.print_y(msg.format(index, column_name))
if not column_name:
# Use a generic name
column_name = "unknown"
while column_name in column_map.keys():
# TODO: Replace by a numerical, increasing suffix
column_name += "_"
column_map[column_name] = CSVColumn(column_name,
CSVColumn.NONE, index)
else:
msg = (
"column number {} ({}) is an unknown column, it will be " +
"ignored")
oat.print_y(msg.format(index, column_name))
print ""
for column in column_map.values():
if column.index is None:
msg = "The {} column '{}' could not be identified."
print msg.format(column.requirement, column.column_type)
# Check for unassigned optional column types. We can continue but should
# issue a warning as all entries will need a valid DOI in this case.
unassigned = filter(
lambda (k, v): v.requirement == CSVColumn.OPTIONAL and v.index is None,
column_map.iteritems())
if unassigned:
print("\nWARNING: Not all optional column types could be " +
"identified. Metadata aggregation is still possible, but " +
"every entry in the CSV file will need a valid DOI.")
start = raw_input("\nStart metadata aggregation? (y/n):")
while start not in ["y", "n"]:
start = raw_input("Please type 'y' or 'n':")
if start == "n":
sys.exit()
print "\n *** Starting metadata aggregation ***\n"
enriched_content = []
csv_file.seek(0)
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
header_processed = False
row_num = 0
for row in reader:
row_num += 1
if not row:
continue # skip empty lines
if not header_processed:
header_processed = True
enriched_content.append(column_map.keys())
if has_header:
# If the CSV file has a header, we are currently there - skip it
# to get to the first data row
continue
if args.start and args.start > row_num:
continue
if args.end and args.end < row_num:
continue
print "---Processing line number " + str(row_num) + "---"
enriched_row = oat.process_row(row, row_num, column_map, num_columns,
doaj_offline_analysis,
args.bypass_cert_verification)
enriched_content.append(enriched_row)
csv_file.close()
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, quotemask, True, True)
writer.write_rows(enriched_content)
if not bufferedHandler.buffer:
oat.print_g("Metadata enrichment successful, no errors occured")
else:
oat.print_r("There were errors during the enrichment process:\n")
# closing will implicitly flush the handler and print any buffered
# messages to stderr
bufferedHandler.close()
def main():
parser = argparse.ArgumentParser()
parser.add_argument("apc_file", help=ARG_HELP_STRINGS["apc_file"])
parser.add_argument("issn_l_file", help=ARG_HELP_STRINGS["issn_l_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-q",
"--quotemask",
help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o",
"--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true",
default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if len(reduced) > 0:
print("Error: A quotemask may only contain the letters 't' and" +
"'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
print("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
enc = args.encoding
except LookupError:
print("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
result = oat.analyze_csv_file(args.apc_file, 500)
if result["success"]:
csv_analysis = result["data"]
print csv_analysis
else:
print result["error_msg"]
sys.exit()
if enc is None:
enc = csv_analysis.enc
if enc is None:
print("Error: No encoding given for CSV file and automated " +
"detection failed. Please set the encoding manually via the " +
"--enc argument")
sys.exit()
dialect = csv_analysis.dialect
csv_file = open(args.apc_file, "r")
reader = oat.UnicodeReader(csv_file, dialect=dialect, encoding=enc)
oat.print_g("Preparing mapping table...")
itself = other = 0
issn_l_re = re.compile(
"^(?P<issn>\d{4}-\d{3}[\dxX])\t(?P<issn_l>\d{4}-\d{3}[\dxX])$")
issn_l_file = open(args.issn_l_file, "r")
issn_l_dict = {}
for i, line in enumerate(issn_l_file):
if i % 100000 == 0:
print str(i) + " lines processed."
match = issn_l_re.match(line)
if match:
match_dict = match.groupdict()
issn_l_dict[match_dict['issn']] = match_dict['issn_l']
if match_dict['issn'] == match_dict['issn_l']:
itself += 1
else:
other += 1
print str(itself) + " ISSNs pointing to itself as ISSN-L, " + str(
other) + " to another value."
oat.print_g("Starting enrichment...")
issn_matches = issn_p_matches = issn_e_matches = unmatched = different = 0
enriched_lines = []
for line in reader:
if len(line) == 0:
enriched_lines.append(line)
continue
issn = reformat_issn(line[7])
issn_p = reformat_issn(line[8])
issn_e = reformat_issn(line[9])
target = None
if issn in issn_l_dict:
target = issn_l_dict[issn]
line[10] = target
issn_matches += 1
elif issn_p in issn_l_dict:
target = issn_l_dict[issn_p]
line[10] = target
issn_p_matches += 1
elif issn_e in issn_l_dict:
target = issn_l_dict[issn_e]
line[10] = target
issn_e_matches += 1
else:
unmatched += 1
if target is not None and target not in [issn, issn_p, issn_e]:
different += 1
enriched_lines.append(line)
print "{} issn_l values mapped by issn, {} by issn_p, {} by issn_e. {} could not be assigned.\n In {} cases the ISSN-L was different from all existing ISSN values".format(
issn_matches, issn_p_matches, issn_e_matches, unmatched, different)
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(enriched_lines)
def integrate_changes(articles, file_path, enriched_file=False):
'''
Update existing entries in a previously created harvest file.
Args:
articles: A list of article dicts, as retured by openapc_toolkit.oai_harvest()
file_path: Path to the CSV file the new values should be integrated into.
enriched_file: If true, columns which are overwritten during enrichment
will not be updated
Returns:
A tuple. The first element is a reduced list of article dicts, containing
those which did not find a matching DOI in the file (Order preserved).
The second element is the list of column headers encountered in the harvest
file.
'''
if not os.path.isfile(file_path):
return (articles, None)
enriched_blacklist = ["institution", "publisher", "journal_full_title", "issn", "license_ref", "pmid"]
article_dict = OrderedDict()
for article in articles:
doi = article["doi"]
if oat.has_value(doi):
article_dict[doi] = article
updated_lines = []
fieldnames = None
with open(file_path, "r") as f:
reader = DictReader(f)
fieldnames = reader.fieldnames
updated_lines.append(list(fieldnames)) #header
start_msg = "Integrating changes in harvest data into existing file {}"
oat.print_g(start_msg.format(file_path))
for line in reader:
doi = line["doi"]
line_num = reader.reader.line_num
if not oat.has_value(doi):
msg = "Line {}: No DOI found, change check not possible"
oat.print_y(msg.format(line_num))
updated_line = [line[key] for key in fieldnames]
updated_lines.append(updated_line)
else:
msg = "Line {}: Checking for changes ({})"
oat.print_b(msg.format(line_num, doi))
if doi in article_dict:
for key, value in article_dict[doi].items():
if enriched_file and key in enriched_blacklist:
continue
if key in line and value != line[key]:
update_msg = 'Updating value in column {} ("{}" -> "{}")'
oat.print_g(update_msg.format(key, line[key], value))
line[key] = value
del(article_dict[doi])
updated_line = [line[key] for key in fieldnames]
updated_lines.append(updated_line)
else:
remove_msg = "DOI {} no longer found in harvest data, removing article"
oat.print_r(remove_msg.format(doi))
with open(file_path, "w") as f:
mask = oat.OPENAPC_STANDARD_QUOTEMASK if enriched_file else None
writer = oat.OpenAPCUnicodeWriter(f, quotemask=mask, openapc_quote_rules=True, has_header=True)
writer.write_rows(updated_lines)
return (article_dict.values(), fieldnames)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("original_file",
help=ARG_HELP_STRINGS["original_file"])
parser.add_argument("update_file", help=ARG_HELP_STRINGS["update_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-eu",
"--update_encoding",
help=ARG_HELP_STRINGS["update_encoding"])
parser.add_argument("-l", "--locale", help=ARG_HELP_STRINGS["locale"])
parser.add_argument("-lu",
"--update_locale",
help=ARG_HELP_STRINGS["update_locale"])
parser.add_argument("-a",
"--autocreate_mappings",
action="store_true",
help=ARG_HELP_STRINGS["autocreate_mappings"])
parser.add_argument("-g",
"--grouping",
action="store_true",
help=ARG_HELP_STRINGS["grouping"])
args = parser.parse_args()
params = {
"original": {
"file": args.original_file,
"encoding": args.encoding,
"locale": args.locale,
"csv_analysis": None,
"fieldnames": None,
"doi_field": None,
"euro_field": None,
"mappings": []
},
"update": {
"file": args.update_file,
"encoding": args.update_encoding,
"locale": args.update_locale,
"csv_analysis": None,
"fieldnames": None,
"doi_field": None,
"euro_field": None,
"mappings": []
}
}
def field_mapped(file_type, field_name):
if field_name == params[file_type]["euro_field"]:
return True
if field_name == params[file_type]["doi_field"]:
return True
if field_name in params[file_type]["mappings"]:
return True
return False
for file_type in params.keys():
msg = "*** Performing analysis for {} file ***"
oat.print_b(msg.format(file_type))
encoding = params[file_type]["encoding"]
if encoding is not None:
try:
codec = codecs.lookup(encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
print(msg.format(encoding, codec.name))
params[file_type]["encoding"] = encoding
except LookupError:
print(
"Error: '" + encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-"
+ "encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
loc = params[file_type]["locale"]
if loc is not None:
norm = locale.normalize(loc)
if norm != loc:
msg = "locale '{}' not found, normalised to '{}'".format(
loc, norm)
oat.print_y(msg)
params[file_type]["locale"] = norm
csv_analysis = oat.analyze_csv_file(params[file_type]["file"],
enc=params[file_type]["encoding"])
if not csv_analysis["success"]:
oat.print_r(csv_analysis["error_msg"])
sys.exit()
params[file_type]["csv_analysis"] = csv_analysis["data"]
print(params[file_type]["csv_analysis"])
if params[file_type]["encoding"] is None:
guessed_enc = params[file_type]["csv_analysis"].enc
params[file_type]["encoding"] = guessed_enc
locale_name = "default locale"
if params[file_type]["locale"] is not None:
locale_name = "locale " + params[file_type]["locale"]
msg = "{} file will be opened with encoding {} and {}"
oat.print_g(
msg.format(file_type, params[file_type]["encoding"], locale_name))
with open(params[file_type]["file"],
"r",
encoding=params[file_type]["encoding"]) as f:
reader = csv.DictReader(
f, dialect=params[file_type]["csv_analysis"].dialect)
params[file_type]["fieldnames"] = list(reader.fieldnames)
for index, name in enumerate(params[file_type]["fieldnames"]):
field_type = oat.get_column_type_from_whitelist(name)
found = False
if field_type == "doi":
params[file_type]["doi_field"] = name
found = True
elif field_type == "euro":
params[file_type]["euro_field"] = name
found = True
if found:
msg = '{} file: Found {} column at index {} ("{}")'
msg = msg.format(file_type, field_type, index, name)
oat.print_b(msg)
for field_type in ["doi_field", "euro_field"]:
if params[file_type][field_type] is None:
msg = "Error: No {} found in {} file"
oat.print_r(msg.format(field_type, file_type))
sys.exit()
for orig_index, orig_field in enumerate(params["original"]["fieldnames"]):
if field_mapped("original", orig_field):
continue
norm_orig_field = orig_field.lower().strip()
for update_index, update_field in enumerate(
params["update"]["fieldnames"]):
if field_mapped("update", update_field):
continue
norm_update_field = update_field.lower().strip()
if norm_orig_field == norm_update_field:
if args.autocreate_mappings:
params["original"]["mappings"].append(orig_field)
params["update"]["mappings"].append(update_field)
msg = 'Auto-created mapping "{}" (update file, index {}) -> "{}" (original file, index {})'
oat.print_b(
msg.format(update_field, update_index, orig_field,
orig_index))
else:
msg = 'Possible mapping found: "{}" (update file, index {}) -> "{}" (original file, index {}). Create mapping (y/n)?'
msg = msg.format(update_field, update_index, orig_field,
orig_index)
create = input(msg)
while create not in ["y", "n"]:
create = input("Please type 'y' or 'n':")
if create == "y":
params["original"]["mappings"].append(orig_field)
params["update"]["mappings"].append(update_field)
update_mappings = {}
with open(params["update"]["file"],
"r",
encoding=params["update"]["encoding"]) as f:
doi_field = params["update"]["doi_field"]
euro_field = params["update"]["euro_field"]
reader = csv.DictReader(
f, dialect=params["update"]["csv_analysis"].dialect)
locale.setlocale(locale.LC_ALL, params["update"]["locale"])
for line in reader:
doi = oat.get_normalised_DOI(line[doi_field])
if doi is None:
msg = 'Warning: Empty or invalid DOI in update file (line {}): "{}"'
oat.print_y(msg.format(reader.line_num, line[doi_field]))
continue
if doi in update_mappings:
msg = "Error: Duplicate doi in update file ({})".format(
line[doi_field])
oat.print_r(msg)
sys.exit()
update_mappings[doi] = {}
euro_value = locale.atof(line[euro_field])
orig_euro_field = params["original"]["euro_field"]
update_mappings[doi][orig_euro_field] = euro_value
for index, update_field_name in enumerate(
params["update"]["mappings"]):
orig_field_name = params["original"]["mappings"][index]
update_mappings[doi][orig_field_name] = line[update_field_name]
#print(json.dumps(update_mappings, sort_keys=False, indent=4))
modified_content = []
fieldnames = None
with open(params["original"]["file"],
"r",
encoding=params["original"]["encoding"]) as f:
doi_field = params["original"]["doi_field"]
euro_field = params["original"]["euro_field"]
reader = csv.DictReader(
f, dialect=params["original"]["csv_analysis"].dialect)
fieldnames = list(reader.fieldnames)
locale.setlocale(locale.LC_ALL, params["original"]["locale"])
for line in reader:
doi = oat.get_normalised_DOI(line[doi_field])
if doi not in update_mappings:
msg = "line {}: DOI {} not found in update file!"
oat.print_r(msg.format(reader.line_num, doi))
continue
changes = []
old_euro_value = locale.atof(line[euro_field])
new_euro_value = update_mappings[doi][euro_field]
if old_euro_value != new_euro_value:
changes.append(
Change(euro_field,
old_euro_value,
new_euro_value,
monetary=True))
for field in update_mappings[doi].keys():
if field == euro_field:
continue
if line[field] != update_mappings[doi][field]:
changes.append(
Change(field, line[field],
update_mappings[doi][field]))
if not changes:
msg = "line {}: DOI {} found in update file, but nothing changed."
oat.print_g(msg.format(reader.line_num, doi))
else:
msg = "line {}: DOI {} found in update file with the following updates:"
oat.print_y(msg.format(reader.line_num, doi))
for change in changes:
oat.print_y(str(change))
if change.monetary:
line[change.field_name] = locale.currency(
change.new_value,
symbol=False,
grouping=args.grouping)
else:
line[change.field_name] = change.new_value
del (update_mappings[doi])
modified_content.append(line)
if update_mappings:
oat.print_y(
"{} entries in update file not contained in original file:".
format(len(update_mappings)))
for doi, changes in update_mappings.items():
oat.print_y(doi)
new_line = changes
new_line[params["original"]["doi_field"]] = doi
formatted_euro = locale.currency(
new_line[params["original"]["euro_field"]],
symbol=False,
grouping=args.grouping)
new_line[params["original"]["euro_field"]] = formatted_euro
modified_content.append(new_line)
with open("out.csv", "w", encoding=params["original"]["encoding"]) as out:
writer = csv.DictWriter(
out,
fieldnames,
dialect=params["original"]["csv_analysis"].dialect)
writer.writeheader()
for line in modified_content:
writer.writerow(line)
def find_significant_apc_differences(apc_content, institution, verbose=False):
titles = {}
articles = []
# 1st run: Find all journals the institution has published articles in
for line in apc_content:
if line[0] != institution:
continue
title = line[6]
if title not in titles:
titles[title] = {"lines": []}
articles.append(line)
# 2nd run: Aggregate all articles for the journals found in 1
for line in apc_content:
title = line[6]
if title in titles:
titles[title]["lines"].append(line)
for title in titles:
apc_values = [float(line[2]) for line in titles[title]["lines"]]
titles[title]["count"] = len(apc_values)
titles[title]["stddev"] = stddev(apc_values)
titles[title]["mean"] = mean(apc_values)
stats = {
"articles": len(articles),
"not_checked": 0,
"within_limits": 0,
"significant": 0
}
sig_articles = []
for article in articles:
apc = article[2]
doi = article[3]
title = article[6]
if titles[title]["count"] < 20:
if verbose:
msg = 'Article {}, journal "{}": Could not check costs, too few occurences ({})'
oat.print_b(msg.format(doi, title, titles[title]["count"]))
stats["not_checked"] += 1
continue
if abs(float(apc) - titles[title]["mean"]) > 2 * titles[title]["stddev"]:
rounded_mean = round(titles[title]["mean"], 2)
rounded_stddev = round(titles[title]["stddev"], 2)
diff = round(float(apc) - rounded_mean, 2)
if verbose:
msg = ('Article {}, journal "{}": Cost ({}€) differs more than 2 standard ' +
'deviations (2 * {}€) from mean APC ({}€)')
oat.print_y(msg.format(doi, title, apc, rounded_stddev, rounded_mean))
stats["significant"] += 1
article.append(rounded_mean)
article.append(rounded_stddev)
article.append(diff)
article.append(titles[title]["count"])
sig_articles.append(article)
else:
if verbose:
msg = ('Article {}, journal "{}": No significant cost difference ({}€, mean ' +
'APC is {}€)')
oat.print_g(msg.format(doi, title, apc, round(titles[title]["mean"], 2)))
stats["within_limits"] += 1
if verbose:
oat.print_g("\nAnalysis finished, results:")
for key, value in stats.items():
oat.print_g(key + ": " + str(value))
return sig_articles, stats
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-start", type=int, default=1, help=ARG_HELP_STRINGS["start"])
parser.add_argument("-end", type=int, help=ARG_HELP_STRINGS["start"])
args = parser.parse_args()
handler = logging.StreamHandler(sys.stderr)
handler.setFormatter(oat.ANSIColorFormatter())
bufferedHandler = oat.BufferedErrorHandler(handler)
bufferedHandler.setFormatter(oat.ANSIColorFormatter())
logging.root.addHandler(handler)
logging.root.addHandler(bufferedHandler)
logging.root.setLevel(logging.INFO)
enc = None
if args.encoding:
try:
codec = codecs.lookup(args.encoding)
msg = ("Encoding '{}' found in Python's codec collection " +
"as '{}'").format(args.encoding, codec.name)
oat.print_g(msg)
enc = args.encoding
except LookupError:
msg = ("Error: '" + args.encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
oat.print_r(msg)
sys.exit()
head, content = oat.get_csv_file_content(args.csv_file, enc)
content = head + content
header = {"User-Agent": "Mozilla/5.0 Firefox/45.0"}
line_num = 0
for line in content:
line_num += 1
if args.start and args.start > line_num:
continue
if args.end and args.end < line_num:
continue
institution = line[0]
period = line[1]
doi = line[3]
is_hybrid = line[4]
publisher = line[5]
journal = line[6]
if publisher != "Elsevier" or is_hybrid != "TRUE":
continue
init_msg = (u"Line {}: Checking {} article from {}, published in " +
"{}...").format(line_num, institution, period, journal)
oat.print_b(init_msg)
url = 'http://doi.org/' + doi
req = urllib2.Request(url, None, header)
ret_value = {'success': True}
try:
response = urllib2.urlopen(req)
target = response.geturl()
resolve_msg = u"DOI {} resolved, led us to {}".format(doi, target)
if "sciencedirect.com" not in target:
oat.print_y(resolve_msg)
oat.print_y("Journal not located at sciencedirect, skipping...")
continue
oat.print_b(resolve_msg)
content_string = response.read()
single_match = pdflink_re.search(content_string)
if single_match:
link_url = single_match.groups()[0]
oat.print_g(u"PDF link found: " + link_url)
else:
multi_match = pdflink_multi_re.search(content_string)
if multi_match:
link_url = multi_match.groups()[0]
link_url = link_url.replace("&", "&")
oat.print_g(u"PDF link found (more than one document): " + link_url)
else:
error_msg = (u"No PDF link found! (line {}, DOI: {}, " +
"landing page: {})").format(line_num, doi, target)
logging.error(error_msg)
time.sleep(1)
except urllib2.HTTPError as httpe:
code = str(httpe.getcode())
oat.print_r("HTTPError: {} - {}".format(code, httpe.reason))
except urllib2.URLError as urle:
oat.print_r("URLError: {}".format(urle.reason))
if not bufferedHandler.buffer:
oat.print_g("\nLookup finished, all articles were accessible on sciencedirect")
else:
oat.print_r("\nLookup finished, not all articles could be accessed on sciencedirect:\n")
# closing will implicitly flush the handler and print any buffered
# messages to stderr
bufferedHandler.close()
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("column", type=int, help=ARG_HELP_STRINGS["column"])
parser.add_argument("other_csv_file",
nargs="?",
help=ARG_HELP_STRINGS["other_csv_file"])
parser.add_argument("other_column",
type=int,
nargs="?",
help=ARG_HELP_STRINGS["other_column"])
parser.add_argument("-e2",
"--other_encoding",
help=ARG_HELP_STRINGS["other_encoding"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-i",
"--ignore_case",
action="store_true",
default=False,
help=ARG_HELP_STRINGS["ignore_case"])
parser.add_argument("-q",
"--quotemask",
help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o",
"--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true",
default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
encs = [] #CSV file encodings
for encoding in [args.encoding, args.other_encoding]:
if encoding:
try:
codec = codecs.lookup(encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
print(msg.format(encoding, codec.name))
except LookupError:
print(
"Error: '" + encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-"
+ "encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
encs.append(encoding)
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if reduced:
print(
"Error: A quotemask may only contain the letters 't' and 'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
header, content = oat.get_csv_file_content(args.csv_file, enc=encs[0])
column = args.column
if not args.other_csv_file:
rearranged_content = header + sorted(content, key=lambda x: x[column])
else:
rearranged_content = []
_, second_content = oat.get_csv_file_content(args.other_csv_file,
enc=encs[1])
other_column = column # default: use same column index as in first file
if args.other_column:
other_column = args.other_column
for other_row in second_content:
if args.ignore_case:
matching_rows = [
row for row in content
if row[column].lower() == other_row[other_column].lower()
]
else:
matching_rows = [
row for row in content
if row[column] == other_row[other_column]
]
rearranged_content += matching_rows
for matching_row in matching_rows:
content.remove(matching_row)
unmatched_msg = (
"{} rows could not be rearranged (unmatched in second csv file) " +
"and were appended to the end of the result file " +
"in original order.")
if content:
oat.print_y(unmatched_msg.format(len(content)))
else:
oat.print_g("All rows matched.")
rearranged_content = header + rearranged_content + content # append any unmatched rows
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(rearranged_content)
def main():
analysed_journals = {}
if os.path.isfile(JOURNALTOC_RESULTS_FILE):
with open(JOURNALTOC_RESULTS_FILE) as results:
reader = DictReader(results)
for line in reader:
title = line["journal_full_title"]
if title not in analysed_journals:
analysed_journals[title] = line
remaining_journals = {}
with open(APC_DE_FILE) as apc_de:
reader = DictReader(apc_de)
for line in reader:
title = line["journal_full_title"]
if title in analysed_journals:
continue
if title not in remaining_journals:
remaining_journals[title] = {
"journal_full_title": line["journal_full_title"],
"publisher": line["publisher"],
"is_hybrid": line["is_hybrid"],
"issns": []
}
for issn_type in ISSN_TYPES:
issn = line[issn_type]
if issn not in remaining_journals[title][
"issns"] and oat.is_wellformed_ISSN(issn):
remaining_journals[title]["issns"].append(issn)
is_hybrid = line["is_hybrid"]
if is_hybrid in [
"TRUE", "FALSE"
] and is_hybrid != remaining_journals[title]["is_hybrid"]:
remaining_journals[title]["is_hybrid"] = "FLIPPED"
msg = "{} unique journals found in OpenAPC core data file, {} already analysed, {} remaining."
oat.print_g(
msg.format(
len(remaining_journals) + len(analysed_journals),
len(analysed_journals), len(remaining_journals)))
count = 0
for title, fields in remaining_journals.items():
count += 1
entry = {field: None for field in RESULTS_FILE_FIELDNAMES}
entry["journal_full_title"] = title
for key in ["publisher", "is_hybrid"]:
entry[key] = fields[key]
entry["issns"] = "|".join(fields["issns"])
msg = 'Analysing journal "{}" ({}), OpenAPC hybrid status is {}...'
msg = msg.format(entry["journal_full_title"], entry["issns"],
entry["is_hybrid"])
oat.print_b(msg)
for issn in fields["issns"]:
oat.print_y("Looking up ISSN " + issn + "...")
jtoc_metadata = get_jtoc_metadata(issn)
if jtoc_metadata["jtoc_id"] is not None:
entry["in_jtoc"] = "TRUE"
for key in ["jtoc_publisher", "jtoc_title"]:
entry[key] = jtoc_metadata[key]
journal_type = get_jtoc_journal_type(jtoc_metadata["jtoc_id"])
entry["jtoc_type"] = journal_type
msg = 'Journal found ("{}"), JournalTOCs type is {}'
oat.print_g(msg.format(entry["jtoc_title"],
entry["jtoc_type"]))
break
else:
oat.print_r("None of the associated ISSNS found in JTOCs!")
analysed_journals[title] = entry
if count < BATCH_SIZE:
sleep(2)
else:
break
with open(JOURNALTOC_RESULTS_FILE, "w") as res_file:
writer = DictWriter(res_file, fieldnames=RESULTS_FILE_FIELDNAMES)
writer.writeheader()
for _, entry in analysed_journals.items():
writer.writerow(entry)
