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'm trying to load pre-trained word embeddings for the Arabic language (Mazajak embeddings: http://mazajak.inf.ed.ac.uk:8000/). The embeddings file does not have a particular extension and I'm struggling to get it to load. What's the usual process to load these embeddings?
I've tried doing with open("get_sg250", encoding = encoding) as file: file.readlines() for different encodings but it seems like none of them are the answer (utf-8 does not work at all), if I try windows-1256 I get gibberish:
e.g.
['8917028 300\n',
'</s> Hل®:0\x16ء:؟X§؛R8ڈ؛\xa0سî9K\u200fƒ::m¤9¼»“8¤p\u200c؛tعA:UU¾؛“_ع9‚Nƒ¹®G§¹قفگ؛ww$؛\u200eba:\x14.„:R¸پ:0–\x0b:–ü\x06:×#¦؛Yٍ²؛m ظ:{\x14¦:µ\x01‡:ه\x17S¹Yr¯:j\x03-¹ff€9×£P¸\n',
'W‚؛UUه9¼»é¹""§؛\u200c¶د:UU؟:\u200eb؟¹{\x14\u200d¸,ù19ïî\u200d؛ئ\x12¯؛\x00\x00ا:\u200c6°7A§a؛ذé„؛ذi†؛®G\x14:حجŒ8\x03\u200cè9ه\x17¸؛ق]¦؛ڈآ5¸قفا9حج^:\x00€ٹ؛q=²:\x00\x00¢9\x14®أ9×£T¹لz‚:\x1bèG؛®G7؛ڑ™<:m\xa0ƒ¹""´9\x14®\x1d:"¢²؛®G-؛ڑ™~:±ن¸:\x18ث«:¸\x1e…؛`,8؛Hل\u200d¹±ن.:\x1f…¥؛لْ‚:ڑ™s:R¸\x0b؛ئ’\x07؛0–C؛ڈآ¸:ذéھ:ة/خ¹A\'¸:ڑ™ز:m\xa0\x1e:è´ظ::ي‡؛\n',
'×\x05؛Œ%8؛ش\x06~؛أُu:\x00\x00\n',
":‰ˆ\x149\x14®?؛ِ(\x05:«ھ…:)\\‡833G:Haط؛\x1f…¼:¼»'9\x00\x00 ؛=\n",
'6؛R¸‚¹¼;€؛\x1bè¾؛\x1bèw؛قف؛:A§\x1a؛""j؛K~J:Hل\x14؛ىرد:\u200c6\x0c؛–|ب؛‚Nm:cةد·:mک؛‰ˆھ9\x00\x00ü9DD(¹ذi\x1f:ذé¬؛,ù™9¼»\x1e:wwƒ؛\x03\u200cF87ذ©·×£Q؛\x1f…w؛ئ\x12ح؛\x00\x00\x007ٍ‹U8\x0etZ6“ك«؛cةط؛Haد؛–ü¼؛33?¹Œ%َ9أُخ9=\n',
'‹؛ق]ع:ڈآ/؛0–ق¹¤pُ¹Dؤخ:¤p¤؛\x1bèت9\u200ebé¹ùE‹:–üb7=ٹ؛:؟Xv؛×£c؛ِ(·؛è4\xa0؛cة‹؛0\x16ˆ؛ئ’U:""#؛ة/j:R8،:أُى9ذé€:ىQX:\x1f…L:""›؛K\u200f•؛ڈآں؛‰ˆ8¸ww´:""o؛è´…؛\n',
'W·؛¤pگ:{”¶؛\x0etJ¹\u200eb>:ùإة؛`¬أ؛ِ(ü9K\u200f™:‚N؛:لz;:ِ(ٹ:Œ¥ˆ؛§\n',
'ں؛ِ¨\xad:ڑ™q؛\u200c6\x19:×£H9¤p\x1c:\x03\u200cخ¹–üٹ8UU\x13؛Hلؤ¹è´ء؛ïnژ؛®Gک:è´¯9\x0etN؛O\x1b\x0b؛\x00\x00Z:\n',
'Wڑ؛""J؛؟طخ:\x03\u200c¹:لْ¬؛\u200c6ک9ڑ™D؛\x1bèT8ق]ƒ:¼»س:0–-:~±³:,y‰:è´،¸jƒأ:m\xa0]:A\'د:j\x03\x15؛Haد:""½:wwù¹ه\x17ء؛×#س:&؟œ9×£5؛Hلz¹\\ڈ€¹)\\¨؛O\x1bْ¹ه\x17\x1b¹ڈB×؛\x03\u200c™؛ىQز¹لz¤¹ذi\x1c:\\ڈژ9ùإV¹R¸€:ùإü9ww?9‰\x08\u200d:~±ؤ¹‚Nù¹‰ˆ\x10¹UUn؛\x11\x11ƒ؛ٍ‹چ8‰ˆ½:\x1bèî¹O\x1bè¶`¬´؛=\n',
'¢:\n',
I've also tried using pickle but that also doesn't work.
Any suggestions on what I could try out?
I am an absolute novice to Python so go easy on me please. See my code below
import pdfplumber
with pdfplumber.open('C:/Users/hasan/simsani/Invoices/Invoice SB14082021-1.pdf') as pdf:
first_page = pdf.pages[0]
b = first_page.extract_text()
import numpy as np
c = np.array(b, dtype = 'S')
When i run the script above i get an error (line 6) that says the following
UnicodeEncode error: asci codec cannot encode character '\uf009' in position 25: ordinal not in range (128)
Is there a way to tell numpy to ignore the uf009 character and any other ones that may throw up a similar UnicodeEncode error when creating the array ?
Please give example code if you have an answer please, and make response simple (remember i am a novice here :)
Cheers
I am trying to write a GUI that will display the name of the sketch it was generated from using a simple text() command. However, I am running into trouble getting any of the general JS solutions to work for me. Many solutions I have found use the filename reserved word but that does not seem to be reserved in Processing 3.5.4. I have also tried parsing the strings using a similar method to what can be found here. I am very new to processing and this is only my 2nd attempt at using Processing.
Any advice would be greatly appreciated
You can get the path (as a string) to the sketch with sketchPath().
From there you could either parse the string (pull off everything after the last slash) to get the sketch name, or you can use sketchFile() to get a reference to the file itself and get the name from there:
String path = sketchPath();
File file = sketchFile(path);
String sketchName = file.getName();
println(sketchName);
You could combine this all into one line like so:
String sketchName = sketchFile(sketchPath()).getName();
I am a sage novice trying to export a table output to some image format (so that it might be shared). I tried using the .save() function as so:
my_table1 = table(my inputs)
result = my_table1.transpose()
result.save('here')
My table outputs properly after I run the program (not featured), but for some reason I receive the following error when I try and save the table:
"Error! /home/sage/Documents/here.sobj is not UTF-8 encoded
Saving disabled.
See Console for more details."
Any help in exporting this table is greatly appreciated. Additionally, if you require any more information please do not hesitate to ask!
Background: I am working in Jupyter for Sage on a browser via localhost/8000; not sure if that matters. My OS is Windows 10 and I am using Sage version 7.6.
Would LaTeX output help? Using an example in the documentation for table?:
rows = [['a', 'b', 'c'], [100,2,3], [4,5,60]]
table(rows)._latex_()
'\\begin{tabular}{lll}\na & b & c \\\\\n$100$ & $2$ & $3$ \\\\\n$4$ & $5$ & $60$ \\\\\n\\end{tabular}'
You could try for the html but that would be harder, because it returns a HTMLFragment object, and you'd need the MathJax for it to look right.
str(table(rows)._html_())
'<div class="notruncate">\n<table class="table_form">\n<tbody>\n<tr class ="row-a">\n<td>a</td>\n<td>b</td>\n<td>c</td>\n</tr>\n<tr class ="row-b">\n<td><script type="math/tex">100</script></td>\n<td><script type="math/tex">2</script></td>\n<td><script type="math/tex">3</script></td>\n</tr>\n<tr class ="row-a">\n<td><script type="math/tex">4</script></td>\n<td><script type="math/tex">5</script></td>\n<td><script type="math/tex">60</script></td>\n</tr>\n</tbody>\n</table>\n</div>'
In any case, the image wouldn't be savable as-is. Unless you took a screenshot!