It seems that getShortForm() of the IRI class is not able to process the classnames with spaces and some other symbols.
Is there a method in the OWL-API that parses IRIs more corectly (the same way as Protege does).
For this code
for (OWLClass cls : clses) {
String s = cls.toString();
String s1 = cls.asOWLClass().getIRI().getShortForm();
System.out.println("SHORT: "+s1+" LONG: "+s);
}
I've got the following strange results:
SHORT: CAPECCWEAttackPatterns#DoS: resource consumption (memory) LONG: <http://www.grsu.by/net/CAPECCWEAttackPatterns#DoS: resource consumption (memory)>
SHORT: restart LONG: <http://www.grsu.by/net/CAPECCWEAttackPatterns#DoS: crash / exit / restart>
SHORT: data LONG: <http://www.grsu.by/net/CAPECCWEAttackPatterns#Modify application data>
IRIs cannot contain spaces. They need to be escaped as %20 sequences. The same is true for a number of other characters.
For spaces and other characters, the common approach is to use rdfs:label annotations. Protege has renderers that use these to show classes and properties on screen.
Related
Classic Snowflake Web UI and the new Snowsight are great at importing sql from a file but neither allows you to export sql to a file. Is there a workaround?
You can use an IDE to connect to snowflake and write queries. Then the scripts can be downloaded using IDE features and can sync with git repo as well.
dbeaver is one such IDE which supports snowflake :
https://hevodata.com/learn/dbeaver-snowflake/
The query pane is interactive so the obvious workaround will be:
CTRL + A (select all)
CTRL + C (copy)
<open_favourite_text_editor>
CTRL + P (paste)
CTRL + S (save)
This tool can help you while the team develops a native feature to export worksheets:
"Snowflake Snowsight Extensions wrap Snowsight features that do not have API or SQL alternatives, such as manipulating Dashboards and Worksheets, and retrieving Query Profile and step timings."
https://github.com/Snowflake-Labs/sfsnowsightextensions
Further explained on this post:
https://medium.com/snowflake/importing-and-exporting-snowsight-dashboards-and-worksheets-3cd8e34d29c8
For example, to save to a file within PowerShell:
PS > $dashboards | foreach {$_.SaveToFolder(“path/to/folder”)}
PS > $dashboards[0].SaveToFile(“path/to/folder/mydashboard.json”)
ETA: I'm adding this edit to the front because this is what actually worked.
Again, BSON was a dead end & punycode is irrelevant. I don't know why punycode is referenced in the metadata file; but my best guess is that they might use punycode to encode the worksheet name itself (though I'm not sure why that would be needed since it shouldn't need to be part of a URL).
After doing terrible things and trying a number of complex ways of dealing with escape character hell, I found that the actual encoding is very simple. It just works as an 8 bit encoding with anything that might cause problems escaped away (null, control codes, double quotes, etc.). To load, treat the file as a text file using an 8-bit encoding; extract the data as a JSON field, then re-encode that extracted data as that same encoding. I just used latin_1 to read; but it may not even matter which encoding you use as long as you are consistent and use the same one to re-encode. The encoded field will then be valid zlib compressed data.
I decided that I wanted to start from scratch so I needed to back the worksheets first and I made a Python script based on my findings above. Be warned that this may return even worksheets that you previously closed for good. After running this and verifying that backups were created, I just ran rm #~/worksheet_data/;, closed the tab & reopened it.
Here's the code (fill in the appropriate base directory location):
import os
from collections import OrderedDict
import configparser
from sqlalchemy import create_engine, exc
from snowflake.sqlalchemy import URL
import pathlib
import json
import zlib
import string
def format_filename(s: str) -> str: # From https://gist.github.com/seanh/93666
"""Take a string and return a valid filename constructed from the string.
Uses a whitelist approach: any characters not present in valid_chars are
removed. Also spaces are replaced with underscores.
Note: this method may produce invalid filenames such as ``, `.` or `..`
When I use this method I prepend a date string like '2009_01_15_19_46_32_'
and append a file extension like '.txt', so I avoid the potential of using
an invalid filename.
"""
valid_chars = "-_.() %s%s" % (string.ascii_letters, string.digits)
filename = ''.join(c for c in s if c in valid_chars)
# filename = filename.replace(' ','_') # I don't like spaces in filenames.
return filename
def trlng_dash(s: str) -> str:
"""Removes trailing character if present."""
return s[:-1] if s[-1] == '-' else s
sso_authenticate = True
# Assumes CLI config file exists.
config = configparser.ConfigParser()
home = pathlib.Path.home()
config_loc = home/'.snowsql/config' # Assumes it's set up from Snowflake CLI.
base_dir = home/r'{your Desired base directory goes here.}'
json_dir = base_dir/'json' # Location for your worksheet stage JSON files.
sql_dir = base_dir/'sql' # Location for your worksheets.
# Assumes CLI config file exists.
config.read(config_loc)
# Add connection parameters here (assumes CLI config exists).
# Using sso so only 2 are needed.
# If there's no config file, etc. enter by hand here (or however you want to do it).
connection_params = {
'account': config['connections']['accountname'],
'user': config['connections']['username'],
}
if sso_authenticate:
connection_params['authenticator'] = 'externalbrowser'
if config['connections'].get('password', None) is not None:
connection_params['password'] = config['connections']['password']
if config['connections'].get('rolename', None) is not None:
connection_params['role'] = config['connections']['rolename']
if locals().get('database', None) is not None:
connection_params['database'] = database
if locals().get('schema', None) is not None:
connection_params['schema'] = schema
sf_engine = create_engine(URL(**connection_params))
if not base_dir.exists():
base_dir.mkdir()
if not json_dir.exists():
json_dir.mkdir()
if not (sql_dir).exists():
sql_dir.mkdir()
with sf_engine.connect() as connection:
connection.execute(f'get #~/worksheet_data/ \'file://{str(json_dir.as_posix())}\';')
for file in [path for path in json_dir.glob('*') if path.is_file()]:
if file.suffix != '.json':
file.replace(file.with_suffix(file.suffix + '.json'))
with open(json_dir/'metadata.json', 'r') as metadata_file:
files_meta = json.load(metadata_file)
# List of files from metadata file will contain some empty worksheets.
files_description_orig = OrderedDict((file_key_value['name'], file_key_value) for file_key_value in sorted(files_meta['activeWorksheets'] + list(files_meta['inactiveWorksheets'].values()), key=lambda x: x['name']) if file_key_value['name'])
# files_description will only track non empty worksheets
files_description = files_description_orig.copy()
# Create updated files description filtering out empty worksheets.
for item in files_description_orig:
json_file = json_dir/f"{files_description_orig[item]['name']}.json"
# If a file didn't make it or was deleted by hand, we should
# remove from the filtered description & continue to the next item.
if not (json_file.exists() and json_file.is_file()):
del files_description[item]
continue
with open(json_file, 'r', encoding='latin_1') as f:
json_dat = json.load(f)
# If the file represents a worksheet with a body field, we want it.
if not json_dat['wsContents'].get('body'):
del files_description[item]
## Delete JSON files corresponsing to empty worksheets.
# f.close()
# try:
# (json_dir/f"{files_description_orig[item]['name']}.json").unlink()
# except:
# pass
# Produce a list of normalized filenames (no illegal or awkward characters).
file_names = set(
format_filename(trlng_dash(files_description[item]['encodedDetails']['scriptName']).strip())
for item in files_description)
# Add useful information to our files_description OrderedDict
for file_name in file_names:
repeats_cnt = 0
file_name_repeats = (
item
for item
in files_description
if file_name == format_filename(trlng_dash(files_description[item]['encodedDetails']['scriptName']).strip())
)
for file_uuid in file_name_repeats:
files_description[file_uuid]['normalizedName'] = file_name
files_description[file_uuid]['stemSuffix'] = '' if repeats_cnt == 0 else f'({repeats_cnt:0>2})'
repeats_cnt += 1
# Now we iterate on non-empty worksheets only.
for item in files_description:
json_file = json_dir/f"{files_description[item]['name']}.json"
with open(json_file, 'r', encoding='latin_1') as f:
json_dat = json.load(f)
body = json_dat['wsContents']['body']
body_bin = body.encode('latin_1')
body_txt = zlib.decompress(body_bin).decode('utf8')
sql_file = sql_dir/f"{files_description[item]['normalizedName']}{files_description[item]['stemSuffix']}.sql"
with open(sql_file, 'w') as sql_f:
sql_f.write(body_txt)
creation_stamp = files_description[item]['created']/1000
os.utime(sql_file, (creation_stamp,creation_stamp))
print('Done!')
As mentioned at Is there any option in snowflake to save or load worksheets? (and in Snowflake's own documentation), in the Classic UI, the worksheets are saved at the user stage under #~/worksheet_data/.
You can download it with a get command like:
get #~/worksheet_data/<name> file:///<your local location>; (though you might need quoting if running from Windows).
The problem is that I do not know how to access it programmatically. The downloaded files look like JSON but it is not valid JSON. The main key is "wsContents" and contains most of the worksheet information. Its value includes two subkeys, "encoding" and "body".
The "encoding" key denotes that gzip is being used. The "body" key seems to be the actual worksheet data which looks a lot like a straight binary representation of the compressed text data. As such, any JSON reader will choke on it.
If it is anything like that, I do not currently know how to access it programmatically using Python.
I do see that a JSON like format exists, BSON, that is bundled into PyMongo. Trying to use this on these files fails. I even tried bson.is_valid and it returns False so I am assuming that it means that these files in Snowflake are not actually BSON.
Edited to add: Again, BSON is a dead end.
Examining the "body" value as just binary data, the first two bytes of sample files do seem to correspond to default zlib compression (0x789c). However, attempting to run straight zlib.decompress on the slice created from that first byte to the last corresponding to the first & last characters of the "body" value results in the error:
Error - 3 while decompressing data: invalid code lengths set
This makes me think that the bytes there, as is, are at least partly garbage and still need some processing before they can be decompressed.
One clue that I failed to mention earlier is that the metadata file (called "metadata" and which serves as an inventory of the remaining files at the #~/worksheet_data/ location) declares that the files use the punycode encoding. However, I have not known how to use that information. The data in these files doesn't particularly look like what I feel punycode should look like nor does it particularly make sense to me that you would use punycode on binary data that is not meant to ever be used to directly generate text such as zlib compressed data.
I am using next-routes and my application URL need to receive parameter as name that contains % and # characters. For example, "C#", "100%" etc.
So its URL will look like below.
https://myapp.com/name/C#
https://myapp.com/name/100%
https://myapp.com/name/harry_potter
For "C#", I have found that query value from the getInitialProps function will be "C" only (# character is cut)
and for "100%", I have found that next-routes return error as below. URI malformed has occurred on decodeURIComponent function because of % character.
https://user-images.githubusercontent.com/18202926/48536863-659f6d00-e8e2-11e8-8c64-a0180b51e921.png
If I need to handle both of characters, could you please suggest how can I handle them by using next-routes?
NB. I opened the issue on next-routes here
You will have to encode the URI component so that the special characters are not used.
if you must get C# it would be encoded as "C%23"
100% would be "100%25" and so forth.
use the encodeURIComponent() function to generate the appropriate URI.
Hope it helps.
refer if needed : escaping special character in a url
I have done some searching but cannot see how to actually code this. I am new to Python and not really sure what method I should use to try to do this.
I have some files that I would like to rename. Unfortunately the portion towards the file extension is never the same and would like to just remove it.
File name is like AC_DC - Shot Down In Flames (Official Video)-UKwVvSleM6w.mp3
Any help would be appreciated.
Since this looks like the result from youtube-dl, the "random" substring is most likely the unique video id, which in my experience is always 11 characters long. It can, however, include dashes (-), so the regex-approach suggested by smitrp would not always work.
I use this "dirty" workaround:
>>> original_name="AC_DC - Shot Down In Flames (Official Video)-UKwVvSleM6w.mp3"
>>> new_name=original_name[:-16]+".mp3"
>>> new_name
'AC_DC - Shot Down In Flames (Official Video).mp3'
Edit:
If you really, REALLY want to find the "-XXXX"-portion, have a look at str.rfind(). This will help you to find the index of the last dash (-), which you can directly use for the slice notation of the string.
Disclaimer:
This will provide wrong results, if the video id contains a dash, e.g. here: https://www.youtube.com/watch?v=7WVBEB8-wa0
Then you will find the last dash, remove -wa0 and be left with -7WVBEB8 at the end of the filename.
Using idea of the above answer, one can also take into account that a normal word does not
contain more than one capital character.
def youtube_name_fix(folder):
import os
from pathlib import Path
import re
REGEX = re.compile(r'[A-Z]')
for name in os.listdir(folder):
basename = Path(name)
last_12 = basename.stem[-12:]
# check if the end string is not all uppercase (then it could be part of a valid name)
if not last_12.isupper():
# check if the last string has more than one uppercase letters
if len(REGEX.findall(last_12)) > 1:
# remove the end youtube string and create new full path
new_name = os.path.join(folder, basename.stem[:-12] + basename.suffix)
try:
os.rename(os.path.join(folder,name), new_name)
except Exception as e:
print(e)
> youtube_name_fix(p)
old name -> "4-Discrete and Continuous Probability Models-esHwigpYggU.mp4"
new name -> "4-Discrete and Continuous Probability Models.mp4"
How to sort characters in a string e.g. "5121" -> "1125" ?
I can do this with code below but it seems too slow:
var nonSortedString = "5121"
var sortedString = String(Array(nonSortedString.characters).sort())
The CharacterView handles properly compound characters and provides proper ordering ("eěf" vs. "efě"). If you are ok with the way C++ handles unicode characters, try using one of the other views, like nonSortedString.utf16.sort(). It should give speed similar to C++.
I wrote some text search with use Google App Engine search.
In SDK I tested such query on atom field:
u'tag:"wartości"'
In production I run the same query but it not works on same data.
How can I do unicode query on atom field?
Is it possible to use unicode in Google App Engine search?
We are aware of this issue and plan to fix ASAP. The fix that we're currently planning will require that the atom field value include exactly the same accent characters in order to match. Matches will continue to be case-insensitive. We expect that at least initially, values that use combining diacritical marks will be treated as different values than those using precomposed characters. We may revisit that decision depending on feedback, but it's the most straightforward fix on our end.
For more on the precomposed characters vs. combining diacritical marks, see this Wikipedia article:
http://en.wikipedia.org/wiki/Precomposed_character
Chris
It looks that I need translate AtomField values into new string and I need to translate queries too. This workaround will allow only Polish unicode search. I do not know tonkenization rules so I use 'q', 'x' to expand alphabet since not used in Polish.
# coding=utf-8
translate = {
u'ą': u'aq',
u'Ą': u'Aq',
u'ć': u'cq',
u'Ć': u'Cq',
u'ę': u'eq',
u'Ę': u'Eq',
u'ł': u'lq',
u'Ł': u'Lq',
u'ń': u'nq',
u'Ń': u'Nq',
u'ó': u'oq',
u'Ó': u'Oq',
u'ś': u'sq',
u'Ś': u'Sq',
u'ż': u'zx',
u'Ż': u'Zx',
u'ź': u'zq',
u'Ź': u'Zq',
}
import re
reTranslate = re.compile(u'(%s)' % u'|'.join(translate))
print reTranslate.pattern
test = u"""\
Właściwie prowadzona komunikacja wewnętrzna w firmie,\
zwłaszcza dużej czy posiadającej rozproszoną sieć oddziałów,\
może przynieść oszczędność czasu, a co za tym idzie, również pieniędzy."""
print reTranslate.sub(lambda match: translate[match.group(0)], test)