Develop Reference

InvalidXMLError: InvalidXMLError: message: "BucketLocationConstraintResult" XML is not parsable

I am setting up a local database for datajoint following instructions here: https://github.com/datajoint/mysql-docker.
The mySQL database works but now I wanted to use MinIO for external storage. I fire up MySQL and MinIO as services using docker-compose and set up dj.config for external storage. I am using MinIO service despite running to make it s3 compatible.
Here is my dj.config:
dj.config['stores'] = {
'minio': { # store in s3
'protocol': 's3',
'endpoint': 'minio:9001',
'bucket': 'test',
'location': 'test2/',
'access_key': os.environ.get('MINIO_ROOT_USER', 'FAKEKEY'),
'secret_key': os.environ.get('MINIO_ROOT_PASSWORD', 'FAKEKEY')
}
}
But I get a weird parsing while populating the table. Here is the error stack:
---------------------------------------------------------------------------
ParseError Traceback (most recent call last)
/usr/local/lib/python3.8/dist-packages/minio/parsers.py in fromstring(cls, root_name, data)
68 try:
---> 69 return cls(root_name, ElementTree.fromstring(data.strip()))
70 except (ParseError, AttributeError, ValueError, TypeError) as error:
/usr/lib/python3.8/xml/etree/ElementTree.py in XML(text, parser)
1319 parser = XMLParser(target=TreeBuilder())
-> 1320 parser.feed(text)
1321 return parser.close()
ParseError: syntax error: line 1, column 0
During handling of the above exception, another exception occurred:
InvalidXMLError Traceback (most recent call last)
<ipython-input-24-884d9761b97d> in <module>
----> 1 TrainedModel.populate(reserve_jobs=True)
/usr/local/lib/python3.8/dist-packages/datajoint/autopopulate.py in populate(self, suppress_errors, return_exception_objects, reserve_jobs, order, limit, max_calls, display_progress, *restrictions)
157 self.__class__._allow_insert = True
158 try:
--> 159 make(dict(key))
160 except (KeyboardInterrupt, SystemExit, Exception) as error:
161 try:
/usr/local/lib/python3.8/dist-packages/nnfabrik/templates/trained_model.py in make(self, key)
273 key["model_state"] = filepath
274
--> 275 self.ModelStorage.insert1(key, ignore_extra_fields=True)
276
277
/usr/local/lib/python3.8/dist-packages/datajoint/table.py in insert1(self, row, **kwargs)
173 For kwargs, see insert()
174 """
--> 175 self.insert((row,), **kwargs)
176
177 def insert(self, rows, replace=False, skip_duplicates=False, ignore_extra_fields=False, allow_direct_insert=None):
/usr/local/lib/python3.8/dist-packages/datajoint/table.py in insert(self, rows, replace, skip_duplicates, ignore_extra_fields, allow_direct_insert)
334 return row_to_insert
335
--> 336 rows = list(make_row_to_insert(row) for row in rows)
337 if rows:
338 try:
/usr/local/lib/python3.8/dist-packages/datajoint/table.py in <genexpr>(.0)
334 return row_to_insert
335
--> 336 rows = list(make_row_to_insert(row) for row in rows)
337 if rows:
338 try:
/usr/local/lib/python3.8/dist-packages/datajoint/table.py in make_row_to_insert(row)
304 elif isinstance(row, collections.abc.Mapping): # dict-based
305 check_fields(row)
--> 306 attributes = [make_placeholder(name, row[name]) for name in heading if name in row]
307 else: # positional
308 try:
/usr/local/lib/python3.8/dist-packages/datajoint/table.py in <listcomp>(.0)
304 elif isinstance(row, collections.abc.Mapping): # dict-based
305 check_fields(row)
--> 306 attributes = [make_placeholder(name, row[name]) for name in heading if name in row]
307 else: # positional
308 try:
/usr/local/lib/python3.8/dist-packages/datajoint/table.py in make_placeholder(name, value)
275 if attr.is_external:
276 # value is hash of contents
--> 277 value = self.external[attr.store].upload_attachment(attachment_path).bytes
278 else:
279 # value is filename + contents
/usr/local/lib/python3.8/dist-packages/datajoint/external.py in upload_attachment(self, local_path)
199 uuid = uuid_from_file(local_path, init_string=attachment_name + '\0')
200 external_path = self._make_uuid_path(uuid, '.' + attachment_name)
--> 201 self._upload_file(local_path, external_path)
202 # insert tracking info
203 self.connection.query("""
/usr/local/lib/python3.8/dist-packages/datajoint/external.py in _upload_file(self, local_path, external_path, metadata)
100 def _upload_file(self, local_path, external_path, metadata=None):
101 if self.spec['protocol'] == 's3':
--> 102 self.s3.fput(local_path, external_path, metadata)
103 elif self.spec['protocol'] == 'file':
104 safe_copy(local_path, external_path, overwrite=True)
/usr/local/lib/python3.8/dist-packages/datajoint/external.py in s3(self)
71 def s3(self):
72 if self._s3 is None:
---> 73 self._s3 = s3.Folder(**self.spec)
74 return self._s3
75
/usr/local/lib/python3.8/dist-packages/datajoint/s3.py in __init__(self, endpoint, bucket, access_key, secret_key, secure, **_)
18 secure=secure)
19 self.bucket = bucket
---> 20 if not self.client.bucket_exists(bucket):
21 raise errors.BucketInaccessible('Inaccessible s3 bucket %s' % bucket) from None
22
/usr/local/lib/python3.8/dist-packages/minio/api.py in bucket_exists(self, bucket_name)
402
403 try:
--> 404 self._url_open('HEAD', bucket_name=bucket_name)
405 return True
406 except NoSuchBucket:
/usr/local/lib/python3.8/dist-packages/minio/api.py in _url_open(self, method, bucket_name, object_name, query, body, headers, content_sha256, preload_content)
2183
2184 # Get bucket region.
-> 2185 region = self._get_bucket_region(bucket_name)
2186
2187 # Construct target url.
/usr/local/lib/python3.8/dist-packages/minio/api.py in _get_bucket_region(self, bucket_name)
2061 region = self._region or self._region_map.get(bucket_name)
2062 if not region:
-> 2063 region = self._get_bucket_location(bucket_name)
2064 self._region_map[bucket_name] = region
2065 return region
/usr/local/lib/python3.8/dist-packages/minio/api.py in _get_bucket_location(self, bucket_name)
2105 raise ResponseError(response, method, bucket_name).get_exception()
2106
-> 2107 location = parse_location_constraint(response.data)
2108 # location is empty for 'US standard region'
2109 if not location:
/usr/local/lib/python3.8/dist-packages/minio/parsers.py in parse_location_constraint(data)
425 :return: Returns location of your bucket.
426 """
--> 427 root = S3Element.fromstring('BucketLocationConstraintResult', data)
428 return root.text()
429
/usr/local/lib/python3.8/dist-packages/minio/parsers.py in fromstring(cls, root_name, data)
69 return cls(root_name, ElementTree.fromstring(data.strip()))
70 except (ParseError, AttributeError, ValueError, TypeError) as error:
---> 71 raise InvalidXMLError(
72 '"{}" XML is not parsable. Message: {}'.format(
73 root_name, error
InvalidXMLError: InvalidXMLError: message: "BucketLocationConstraintResult" XML is not parsable. Message: syntax error: line 1, column 0

Accessing Trino Via Python

I'm trying to access trino via python and I keep getting the error below. This is to access the trino interface and retrieve data from oracle. Please advise on how this can be resolved.
HttpError Traceback (most recent call last)
/tmp/ipykernel_166/2315044439.py in <module>
10 )
11 cur = conn.cursor()
---> 12 cur.execute('SELECT * FROM system.runtime.nodes')
13 rows = cur.fetchall()
14 print(cur)
~/.local/lib/python3.9/site-packages/trino/dbapi.py in execute(self, operation, params)
394 else:
395 self._query = trino.client.TrinoQuery(self._request, sql=operation)
--> 396 result = self._query.execute()
397 self._iterator = iter(result)
398 return result
~/.local/lib/python3.9/site-packages/trino/client.py in execute(self, additional_http_headers)
505
506 response = self._request.post(self._sql, additional_http_headers)
--> 507 status = self._request.process(response)
508 self.query_id = status.id
509 self._stats.update({"queryId": self.query_id})
~/.local/lib/python3.9/site-packages/trino/client.py in process(self, http_response)
382 def process(self, http_response) -> TrinoStatus:
383 if not http_response.ok:
--> 384 self.raise_response_error(http_response)
385
386 http_response.encoding = "utf-8"
~/.local/lib/python3.9/site-packages/trino/client.py in raise_response_error(self, http_response)
373 raise exceptions.Http503Error("error 503: service unavailable")
374
--> 375 raise exceptions.HttpError(
376 "error {}{}".format(
377 http_response.status_code,
HttpError: error 401: b'Unknown signing key ID' ```

OSError: [Errno 5] Input/output error when using Google Colaboratory

I was working just fine with Google Colaboratory and suddenly this error started to pop up each time I try to load any type of file. It first started when I was trying to read an hdf file, now everything won't open.
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
<ipython-input-8-65c4e8d1c435> in <module>()
----> 1 eo=EOPatch.load('./20.Clean_Textural_features/eopatch_0')
2 eo
9 frames
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata.py in load(path, features, lazy_loading, filesystem)
530 path = '/'
531
--> 532 return load_eopatch(EOPatch(), filesystem, path, features=features, lazy_loading=lazy_loading)
533
534 def time_series(self, ref_date=None, scale_time=1):
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata_io.py in load_eopatch(eopatch, filesystem, patch_location, features, lazy_loading)
76 loading_data = executor.map(lambda loader: loader.load(), loading_data)
77
---> 78 for (ftype, fname, _), value in zip(features, loading_data):
79 eopatch[(ftype, fname)] = value
80
/usr/lib/python3.6/concurrent/futures/_base.py in result_iterator()
584 # Careful not to keep a reference to the popped future
585 if timeout is None:
--> 586 yield fs.pop().result()
587 else:
588 yield fs.pop().result(end_time - time.monotonic())
/usr/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
423 raise CancelledError()
424 elif self._state == FINISHED:
--> 425 return self.__get_result()
426
427 self._condition.wait(timeout)
/usr/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
382 def __get_result(self):
383 if self._exception:
--> 384 raise self._exception
385 else:
386 return self._result
/usr/lib/python3.6/concurrent/futures/thread.py in run(self)
54
55 try:
---> 56 result = self.fn(*self.args, **self.kwargs)
57 except BaseException as exc:
58 self.future.set_exception(exc)
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata_io.py in <lambda>(loader)
74 if not lazy_loading:
75 with concurrent.futures.ThreadPoolExecutor() as executor:
---> 76 loading_data = executor.map(lambda loader: loader.load(), loading_data)
77
78 for (ftype, fname, _), value in zip(features, loading_data):
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata_io.py in load(self)
217 return self._decode(gzip_fp, self.path)
218
--> 219 return self._decode(file_handle, self.path)
220
221 def save(self, data, file_format, compress_level=0):
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata_io.py in _decode(file, path)
268
269 if FileFormat.NPY.extension() in path:
--> 270 return np.load(file)
271
272 raise ValueError('Unsupported data type.')
/usr/local/lib/python3.6/dist-packages/numpy/lib/npyio.py in load(file, mmap_mode, allow_pickle, fix_imports, encoding)
434 _ZIP_SUFFIX = b'PK\x05\x06' # empty zip files start with this
435 N = len(format.MAGIC_PREFIX)
--> 436 magic = fid.read(N)
437 # If the file size is less than N, we need to make sure not
438 # to seek past the beginning of the file
OSError: [Errno 5] Input/output error
Also some notebooks won't open and this appears instead:
I looked around at similar posts here, but didn't understand anything. Therefore, any help would be highly appreciated.
PS: my files are in subfolders and not directly contained in 'My Drive'. I have a lso disabled all the adblocks ad the problem persists...

I think the file/link has been used for downloading beyond its weekly limit. This answer may help you.
Some discussion about Google's policy on hosting data on drive.
The solution is to wait for couple of hours/days and try again.

"Error while extracting" from tensorflow datasets

I want to train a tensorflow image segmentation model on COCO, and thought I would leverage the dataset builder already included. Download seems to be completed but it crashes on extracting the zip files.
Running with TF 2.0.0 on a Jupyter Notebook under a conda environment. Computer is 64-bit Windows 10. The Oxford Pet III dataset used in the official image segmentation tutorial works fine.
Below is the error message (my local user name replaced with %user%).
---------------------------------------------------------------------------
OutOfRangeError Traceback (most recent call last)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in _sync_extract(self, from_path, method, to_path)
88 try:
---> 89 for path, handle in iter_archive(from_path, method):
90 path = tf.compat.as_text(path)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in iter_zip(arch_f)
176 with _open_or_pass(arch_f) as fobj:
--> 177 z = zipfile.ZipFile(fobj)
178 for member in z.infolist():
~\.conda\envs\tf-tutorial\lib\zipfile.py in __init__(self, file, mode, compression, allowZip64)
1130 if mode == 'r':
-> 1131 self._RealGetContents()
1132 elif mode in ('w', 'x'):
~\.conda\envs\tf-tutorial\lib\zipfile.py in _RealGetContents(self)
1193 try:
-> 1194 endrec = _EndRecData(fp)
1195 except OSError:
~\.conda\envs\tf-tutorial\lib\zipfile.py in _EndRecData(fpin)
263 # Determine file size
--> 264 fpin.seek(0, 2)
265 filesize = fpin.tell()
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\util\deprecation.py in new_func(*args, **kwargs)
506 instructions)
--> 507 return func(*args, **kwargs)
508
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in seek(self, offset, whence, position)
166 elif whence == 2:
--> 167 offset += self.size()
168 else:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in size(self)
101 """Returns the size of the file."""
--> 102 return stat(self.__name).length
103
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in stat(filename)
726 """
--> 727 return stat_v2(filename)
728
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in stat_v2(path)
743 file_statistics = pywrap_tensorflow.FileStatistics()
--> 744 pywrap_tensorflow.Stat(compat.as_bytes(path), file_statistics)
745 return file_statistics
OutOfRangeError: C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip; Unknown error
During handling of the above exception, another exception occurred:
ExtractError Traceback (most recent call last)
<ipython-input-27-887fa0198611> in <module>
1 cocoBuilder = tfds.builder('coco')
2 info = cocoBuilder.info
----> 3 cocoBuilder.download_and_prepare()
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\api_utils.py in disallow_positional_args_dec(fn, instance, args, kwargs)
50 _check_no_positional(fn, args, ismethod, allowed=allowed)
51 _check_required(fn, kwargs)
---> 52 return fn(*args, **kwargs)
53
54 return disallow_positional_args_dec(wrapped) # pylint: disable=no-value-for-parameter
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in download_and_prepare(self, download_dir, download_config)
285 self._download_and_prepare(
286 dl_manager=dl_manager,
--> 287 download_config=download_config)
288
289 # NOTE: If modifying the lines below to put additional information in
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in _download_and_prepare(self, dl_manager, download_config)
946 super(GeneratorBasedBuilder, self)._download_and_prepare(
947 dl_manager=dl_manager,
--> 948 max_examples_per_split=download_config.max_examples_per_split,
949 )
950
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in _download_and_prepare(self, dl_manager, **prepare_split_kwargs)
802 # Generating data for all splits
803 split_dict = splits_lib.SplitDict()
--> 804 for split_generator in self._split_generators(dl_manager):
805 if splits_lib.Split.ALL == split_generator.split_info.name:
806 raise ValueError(
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\image\coco.py in _split_generators(self, dl_manager)
237 root_url = 'http://images.cocodataset.org/'
238 extracted_paths = dl_manager.download_and_extract({
--> 239 key: root_url + url for key, url in urls.items()
240 })
241
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in download_and_extract(self, url_or_urls)
357 with self._downloader.tqdm():
358 with self._extractor.tqdm():
--> 359 return _map_promise(self._download_extract, url_or_urls)
360
361 #property
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in _map_promise(map_fn, all_inputs)
393 """Map the function into each element and resolve the promise."""
394 all_promises = utils.map_nested(map_fn, all_inputs) # Apply the function
--> 395 res = utils.map_nested(_wait_on_promise, all_promises)
396 return res
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in map_nested(function, data_struct, dict_only, map_tuple)
127 return {
128 k: map_nested(function, v, dict_only, map_tuple)
--> 129 for k, v in data_struct.items()
130 }
131 elif not dict_only:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in <dictcomp>(.0)
127 return {
128 k: map_nested(function, v, dict_only, map_tuple)
--> 129 for k, v in data_struct.items()
130 }
131 elif not dict_only:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in map_nested(function, data_struct, dict_only, map_tuple)
141 return tuple(mapped)
142 # Singleton
--> 143 return function(data_struct)
144
145
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in _wait_on_promise(p)
377
378 def _wait_on_promise(p):
--> 379 return p.get()
380
381 else:
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in get(self, timeout)
508 target = self._target()
509 self._wait(timeout or DEFAULT_TIMEOUT)
--> 510 return self._target_settled_value(_raise=True)
511
512 def _target_settled_value(self, _raise=False):
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in _target_settled_value(self, _raise)
512 def _target_settled_value(self, _raise=False):
513 # type: (bool) -> Any
--> 514 return self._target()._settled_value(_raise)
515
516 _value = _reason = _target_settled_value
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in _settled_value(self, _raise)
222 if _raise:
223 raise_val = self._fulfillment_handler0
--> 224 reraise(type(raise_val), raise_val, self._traceback)
225 return self._fulfillment_handler0
226
~\.conda\envs\tf-tutorial\lib\site-packages\six.py in reraise(tp, value, tb)
694 if value.__traceback__ is not tb:
695 raise value.with_traceback(tb)
--> 696 raise value
697 finally:
698 value = None
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in handle_future_result(future)
840 # type: (Any) -> None
841 try:
--> 842 resolve(future.result())
843 except Exception as e:
844 tb = exc_info()[2]
~\.conda\envs\tf-tutorial\lib\concurrent\futures\_base.py in result(self, timeout)
423 raise CancelledError()
424 elif self._state == FINISHED:
--> 425 return self.__get_result()
426
427 self._condition.wait(timeout)
~\.conda\envs\tf-tutorial\lib\concurrent\futures\_base.py in __get_result(self)
382 def __get_result(self):
383 if self._exception:
--> 384 raise self._exception
385 else:
386 return self._result
~\.conda\envs\tf-tutorial\lib\concurrent\futures\thread.py in run(self)
54
55 try:
---> 56 result = self.fn(*self.args, **self.kwargs)
57 except BaseException as exc:
58 self.future.set_exception(exc)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in _sync_extract(self, from_path, method, to_path)
92 except BaseException as err:
93 msg = 'Error while extracting %s to %s : %s' % (from_path, to_path, err)
---> 94 raise ExtractError(msg)
95 # `tf.io.gfile.Rename(overwrite=True)` doesn't work for non empty
96 # directories, so delete destination first, if it already exists.
ExtractError: Error while extracting C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip to C:\Users\%user%\tensorflow_datasets\downloads\extracted\ZIP.images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip : C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip; Unknown error
The message seems cryptic to me. The folder to which it is trying to extract does not exist when the notebook is started - it is created by Tensorflow, and only at that command line. I obviously tried deleting it completely and running it again, to no effect.
The code that leads to the error is (everything runs fine until the last line):
import tensorflow as tf
from __future__ import absolute_import, division, print_function, unicode_literals
from tensorflow_examples.models.pix2pix import pix2pix
import tensorflow_datasets as tfds
from IPython.display import clear_output
import matplotlib.pyplot as plt
dataset, info = tfds.load('coco', with_info=True)
Also tried breaking down the last command into assigning the tdfs.builder object and then running download_and_extract, and again got the same error.
There is enough space in disk - after download, still 50+GB available, while the dataset is supposed to be 37GB in its largest version (2014).

I have a similar problem with Windows 10 & COCO 2017. My solution is simple. Extract the ZIP file manually according to the folder path in the error message.

what is the problem ?: application.connect() error

I am a beginner developer who started to study automation by using pywinauto.
An overflow error occurs when using application.connect () to connect to an already open program.
But application.start() works fine....
Please help me if someone know this part.
The source code and error contents are as follows.
Source code:
import pywinauto
app = pywinauto.application.Application()
app.connect(title_re='Calculator')
Error:
OverflowError Traceback (most recent call last)
in
1 import pywinauto
2 app = pywinauto.application.Application()
----> 3 app.connect(title_re='Calculator')
d:\Anaconda3\lib\site-packages\pywinauto\application.py in connect(self, **kwargs)
972 ).process_id
973 else:
--> 974 self.process = findwindows.find_element(**kwargs).process_id
975 connected = True
976
d:\Anaconda3\lib\site-packages\pywinauto\findwindows.py in find_element(**kwargs)
82 so please see :py:func:find_elements for the full parameters description.
83 """
---> 84 elements = find_elements(**kwargs)
85
86 if not elements:
d:\Anaconda3\lib\site-packages\pywinauto\findwindows.py in find_elements(class_name, class_name_re, parent, process, title, title_re, top_level_only, visible_only, enabled_only, best_match, handle, ctrl_index, found_index, predicate_func, active_only, control_id, control_type, auto_id, framework_id, backend, depth)
279 return title_regex.match(t)
280 return False
--> 281 elements = [elem for elem in elements if _title_match(elem)]
282
283 if visible_only:
d:\Anaconda3\lib\site-packages\pywinauto\findwindows.py in (.0)
279 return title_regex.match(t)
280 return False
--> 281 elements = [elem for elem in elements if _title_match(elem)]
282
283 if visible_only:
d:\Anaconda3\lib\site-packages\pywinauto\findwindows.py in _title_match(w)
275 def _title_match(w):
276 """Match a window title to the regexp"""
--> 277 t = w.rich_text
278 if t is not None:
279 return title_regex.match(t)
d:\Anaconda3\lib\site-packages\pywinauto\win32_element_info.py in rich_text(self)
81 def rich_text(self):
82 """Return the text of the window"""
---> 83 return handleprops.text(self.handle)
84
85 name = rich_text
d:\Anaconda3\lib\site-packages\pywinauto\handleprops.py in text(handle)
86 length += 1
87
---> 88 buffer_ = ctypes.create_unicode_buffer(length)
89
90 ret = win32functions.SendMessage(
d:\Anaconda3\lib\ctypes_init_.py in create_unicode_buffer(init, size)
286 return buf
287 elif isinstance(init, int):
--> 288 buftype = c_wchar * init
289 buf = buftype()
290 return buf
OverflowError: cannot fit 'int' into an index-sized integer

import pywinauto
app = pywinauto.Application(backend='uia').start('calc.exe')
try this if you are having problem you have to say the backennd is a uia it working fine for me.