fix corrupted shelve cache - python

A shelve that I've created isn't allowing me to access the keys without the following failure.
x = shelve.open('my_shelve.pkl')
x.keys()
bsddb.db.DBPageNotFoundError: (-30986, 'BDB0075 DB_PAGE_NOTFOUND: Requested page not found')
However, I am able to check if the Shelf contains a key like so:
'some-key' in x,
and additionally, the Shelf will return the correct data with
x['some-key']
I don't have the list of keys elsewhere, so I'd like to somehow retrieve the keys so I can retrieve the data, or otherwise fix the issue with the database.
I'm using Python 2.7.6

When the database file is damaged (e.g, maybe by failing to call close on it in the past), you probably can't recover all of its contents (the file format just doesn't have enough redundancy to support that).
However, you could perhaps recover a part of it as follows:
recov = {}
try:
for k in x:
recov[k] = x[k]
except Exception:
pass
It's impossible to predict how many keys (and associated values) you'll be able to recover this way, but at least by not asking for all keys (as I imagine you're doing with x.keys() -- you don't tell us which Python version you're using, but I guess it's 2.something) you might be able to recover some of them...

Related

Rasgo Error - Dataset with fqtn does not exist or this API key does not have access

I am trying to use rasgo.get.dataset(fqtn='vw_orders_main') but I am getting an error.
APIError: Dataset with fqtn 'vw_orders_main' does not exist or this API key does not have access.
When using rasgo.get.dataset(), you can either:
pass in a dataset_id
rasgo.get.dataset(123)
pass in a fully qualified table name (fqtn)
rasgo.get.dataset(fqtn="DB.SCHEMA.TABLE")
pass in a resource_key
rasgo.get.dataset(resource_key='mykey')
From the appearance of the string you are using, I believe that is a resource key.
If you are using a variable called vw_orders_main to hold the FQTN string, then try it without the single quotes.
Examples:
vw_orders_main = "DB.SCHEMA.TABLE"
rasgo.get.dataset(fqtn=vw_orders_main)
or
rasgo.get.dataset(fqtn="DB.SCHEMA.TABLE")
or, if what you meant was resource_key,
rasgo.get.dataset(resource_key='vw_orders_main')
A resource_key is randomly assigned when a dataset is published, unless you specify the string yourself (like it appears that you did). It provides you the ability to tie multiple datasets as 1, thus allowing “versions”.
Resource Links: get dataset, publish dataset

Extract text from a config file [duplicate]

This question already has answers here:
Parse key value pairs in a text file
(7 answers)
Closed 1 year ago.
I'm using a config file to inform my Python script of a few key-values, for use in authenticating the user against a website.
I have three variables: the URL, the user name, and the API token.
I've created a config file with each key on a different line, so:
url:<url string>
auth_user:<user name>
auth_token:<API token>
I want to be able to extract the text after the key words into variables, also stripping any "\n" that exist at the end of the line. Currently I'm doing this, and it works but seems clumsy:
with open(argv[1], mode='r') as config_file:
lines = config_file.readlines()
for line in lines:
url_match = match('jira_url:', line)
if url_match:
jira_url = line[9:].split("\n")[0]
user_match = match('auth_user:', line)
if user_match:
auth_user = line[10:].split("\n")[0]
token_match = match('auth_token', line)
if token_match:
auth_token = line[11:].split("\n")[0]
Can anybody suggest a more elegant solution? Specifically it's the ... = line[10:].split("\n")[0] lines that seem clunky to me.
I'm also slightly confused why I can't reuse my match object within the for loop, and have to create new match objects for each config item.
you could use a .yml file and read values with yaml.load() function:
import yaml
with open('settings.yml') as file:
settings = yaml.load(file, Loader=yaml.FullLoader)
now you can access elements like settings["url"] and so on
If the format is always <tag>:<value> you can easily parse it by splitting the line at the colon and filling up a custom dictionary:
config_file = open(filename,"r")
lines = config_file.readlines()
config_file.close()
settings = dict()
for l in lines:
elements = l[:-1].split(':')
settings[elements[0]] = ':'.join(elements[1:])
So, you get a dictionary that has the tags as keys and the values as values. You can then just refer to these dictionary entries in your pogram.
(e.g.: if you need the auth_token, just call settings["auth_token"]
if you can add 1 line for config file, configparser is good choice
https://docs.python.org/3/library/configparser.html
[1] config file : 1.cfg
[DEFAULT] # configparser's config file need section name
url:<url string>
auth_user:<user name>
auth_token:<API token>
[2] python scripts
import configparser
config = configparser.ConfigParser()
config.read('1.cfg')
print(config.get('DEFAULT','url'))
print(config.get('DEFAULT','auth_user'))
print(config.get('DEFAULT','auth_token'))
[3] output
<url string>
<user name>
<API token>
also configparser's methods is useful
whey you can't guarantee config file is always complete
You have a couple of great answers already, but I wanted to step back and provide some guidance on how you might approach these problems in the future. Getting quick answers sometimes prevents you from understanding how those people knew about the answers in the first place.
When you zoom out, the first thing that strikes me is that your task is to provide config, using a file, to your program. Software has the remarkable property of solve-once, use-anywhere. Config files have been a problem worth solving for at least 40 years, so you can bet your bottom dollar you don't need to solve this yourself. And already-solved means someone has already figured out all the little off-by-one and edge-case dramas like stripping line endings and dealing with expected input. The challenge of course, is knowing what solution already exists. If you haven't spent 40 years peeling back the covers of computers to see how they tick, it's difficult to "just know". So you might have a poke around on Google for "config file format" or something.
That would lead you to one of the most prevalent config file systems on the planet - the INI file. Just as useful now as it was 30 years ago, and as a bonus, looks not too dissimilar to your example config file. Then you might search for "read INI file in Python" or something, and come across configparser and you're basically done.
Or you might see that sometime in the last 30 years, YAML became the more trendy option, and wouldn't you know it, PyYAML will do most of the work for you.
But none of this gets you any better at using Python to extract from text files in general. So zooming in a bit, you want to know how to extract parts of lines in a text file. Again, this problem is an age-old problem, and if you were to learn about this problem (rather than just be handed the solution), you would learn that this is called parsing and often involves tokenisation. If you do some research on, say "parsing a text file in python" for example, you would learn about the general techniques that work regardless of the language, such as looping over lines and splitting each one in turn.
Zooming in one more step closer, you're looking to strip the new line off the end of the string so it doesn't get included in your value. Once again, this ain't a new problem, and with the right keywords you could dig up the well-trodden solutions. This is often called "chomping" or "stripping", and with some careful search terms, you'd find rstrip() and friends, and not have to do awkward things like splitting on the '\n' character.
Your final question is about re-using the match object. This is much harder to research. But again, the "solution" wont necessarily show you where you went wrong. What you need to keep in mind is that the statements in the for loop are sequential. To think them through you should literally execute them in your mind, one after one, and imagine what's happening. Each time you call match, it either returns None or a Match object. You never use the object, except to check for truthiness in the if statement. And next time you call match, you do so with different arguments so you get a new Match object (or None). Therefore, you don't need to keep the object around at all. You can simply do:
if match('jira_url:', line):
jira_url = line[9:].split("\n")[0]
if match('auth_user:', line):
auth_user = line[10:].split("\n")[0]
and so on. Not only that, if the first if triggered then you don't need to bother calling match again - it will certainly not trigger any of other matches for the same line. So you could do:
if match('jira_url:', line):
jira_url = line[9:].rstrip()
elif match('auth_user:', line):
auth_user = line[10:].rstrip()
and so on.
But then you can start to think - why bother doing all these matches on the colon, only to then manually split the string at the colon afterwards? You could just do:
tokens = line.rstrip().split(':')
if token[0] == 'jira_url':
jira_url = token[1]
elif token[0] == 'auth_user':
auth_user = token[1]
If you keep making these improvements (and there's lots more to make!), eventually you'll end up re-writing configparse, but at least you'll have learned why it's often a good idea to use an existing library where practical!

Why does ArangoDB (using Python-Arango) return ERR 1600 ERROR_CURSOR_NOT_FOUND?

The problem
I iterate over an entire vertex collection, e.g. journals, and use it to create edges, author, from a person to the given journal.
I use python-arango and the code is something like:
for journal in journals.all():
create_author_edge(journal)
I have a relatively small dataset, and the journals-collection has only ca. 1300 documents. However: this is more than 1000, which is the batch size in the Web Interface - but I don't know if this is of relevance.
The problem is that it raises a CursorNextError, and returns HTTP 404 and ERR 1600 from the database, which is the ERROR_CURSOR_NOT_FOUND error:
Will be raised when a cursor is requested via its id but a cursor with that id cannot be found.
Insights to the cause
From ArangoDB Cursor Timeout, and from this issue, I suspect that it's because the cursor's TTL has expired in the database, and in the python stacktrace something like this is seen:
# Part of the stacktrace in the error:
(...)
if not cursor.has_more():
raise StopIteration
cursor.fetch() <---- error raised here
(...)
If I iterate over the entire collection fast, i.e. if I do print(len(journals.all()) it outputs "1361" with no errors.
When I replace the journals.all() with AQL, and increase the TTL parameter, it works without errors:
for journal in db.aql.execute("FOR j IN journals RETURN j", ttl=3600):
create_author_edge(journal)
However, without the the ttl-parameter, the AQL approach gives the same error as using journals.all().
More information
A last piece of information is that I'm running this on my personal laptop when the error is raised. On my work computer, the same code was used to create the graph and populate it with the same data, but there no errors were raised. Because I'm on holiday I don't have access to my work computer to compare versions, but both systems were installed during the summer so there's a big chance the versions are the same.
The question
I don't know if this is an issue with python-arango, or with ArangoDB. I believe that because there is no problem when TTL is increased that it could indicate an issue with ArangodDB and not the Python driver, but I cannot know.
(I've added a feature request to add ttl-param to the .all()-method here.)
Any insights into why this is happening?
I don't have the rep to create the tag "python-arango", so it would be great if someone would create it and tag my question.
Inside of the server the simple queries will be translated to all().
As discussed on the referenced github issue, simple queries don't support the TTL parameter, and won't get them.
The prefered solution here is to use an AQL-Query on the client, so that you can specify the TTL parameter.
In general you should refrain from pulling all documents from the database at once, since this may introduce other scaling issues. You should use proper AQL with FILTER statements backed by indices (use explain() to revalidate) to fetch the documents you require.
If you need to iterate over all documents in the database, use paging. This is usually implemented the best way by combining a range FILTER with a LIMIT clause:
FOR x IN docs
FILTER x.offsetteableAttribute > #lastDocumentWithThisID
LIMIT 200
RETURN x
So here is how I did it. You can specify with the more args param makes it easy to do.
Looking at the source you can see the doc string says what to do
def AQLQuery(self, query, batchSize = 100, rawResults = False, bindVars = None, options = None, count = False, fullCount = False,
json_encoder = None, **moreArgs):
"""Set rawResults = True if you want the query to return dictionnaries instead of Document objects.
You can use **moreArgs to pass more arguments supported by the api, such as ttl=60 (time to live)"""
from pyArango.connection import *
conn = Connection(username=usr, password=pwd,arangoURL=url)# set this how ya need
db = conn['collectionName']#set this to the name of your collection
aql = """ for journal in journals.all():
create_author_edge(journal)"""
doc = db.AQLQuery(aql,ttl=300)
Thats all ya need to do!

Representation of python dictionaries with unicode in database queries

I have a problem that I would like to know how to efficiently tackle.
I have data that is JSON-formatted (used with dumps / loads) and contains unicode.
This is part of a protocol implemented with JSON to send messages. So messages will be sent as strings and then loaded into python dictionaries. This means that the representation, as a python dictionary, afterwards will look something like:
{u"mykey": u"myVal"}
It is no problem in itself for the system to handle such structures, but the thing happens when I'm going to make a database query to store this structure.
I'm using pyOrient towards OrientDB. The command ends up something like:
"CREATE VERTEX TestVertex SET data = {u'mykey': u'myVal'}"
Which will end up in the data field getting the following values in OrientDB:
{'_NOT_PARSED_': '_NOT_PARSED_'}
I'm assuming this problem relates to other cases as well when you wish to make a query or somehow represent a data object containing unicode.
How could I efficiently get a representation of this data, of arbitrary depth, to be able to use it in a query?
To clarify even more, this is the string the db expects:
"CREATE VERTEX TestVertex SET data = {'mykey': 'myVal'}"
If I'm simply stating the wrong problem/question and should handle it some other way, I'm very much open to suggestions. But what I want to achieve is to have an efficient way to use python2.7 to build a db-query towards orientdb (using pyorient) that specifies an arbitrary data structure. The data property being set is of the OrientDB type EMBEDDEDMAP.
Any help greatly appreciated.
EDIT1:
More explicitly stating that the first code block shows the object as a dict AFTER being dumped / loaded with json to avoid confusion.
Dargolith:
ok based on your last response it seems you are simply looking for code that will dump python expression in a way that you can control how unicode and other data types print. Here is a very simply function that provides this control. There are ways to make this function more efficient (for example, by using a string buffer rather than doing all of the recursive string concatenation happening here). Still this is a very simple function, and as it stands its execution is probably still dominated by your DB lookup.
As you can see in each of the 'if' statements, you have full control of how each data type prints.
def expr_to_str(thing):
if hasattr(thing, 'keys'):
pairs = ['%s:%s' % (expr_to_str(k),expr_to_str(v)) for k,v in thing.iteritems()]
return '{%s}' % ', '.join(pairs)
if hasattr(thing, '__setslice__'):
parts = [expr_to_str(ele) for ele in thing]
return '[%s]' % (', '.join(parts),)
if isinstance(thing, basestring):
return "'%s'" % (str(thing),)
return str(thing)
print "dumped: %s" % expr_to_str({'one': 33, 'two': [u'unicode', 'just a str', 44.44, {'hash': 'here'}]})
outputs:
dumped: {'two':['unicode', 'just a str', 44.44, {'hash':'here'}], 'one':33}
I went on to use json.dumps() as sobolevn suggested in the comment. I didn't think of that one at first since I wasn't really using json in the driver. It turned out however that json.dumps() provided exactly the formats I needed on all the data types I use. Some examples:
>>> json.dumps('test')
'"test"'
>>> json.dumps(['test1', 'test2'])
'["test1", "test2"]'
>>> json.dumps([u'test1', u'test2'])
'["test1", "test2"]'
>>> json.dumps({u'key1': u'val1', u'key2': [u'val21', 'val22', 1]})
'{"key2": ["val21", "val22", 1], "key1": "val1"}'
If you need to take more control of the format, quotes or other things regarding this conversion, see the reply by Dan Oblinger.

grabbing HTTP GET parameter from url using Box API in python

I am dealing with the Box.com API using python and am having some trouble automating a step in the authentication process.
I am able to supply my API key and client secret key to Box. Once Box.com accepts my login credentials, they supply me with an HTTP GET parameter like
'http://www.myapp.com/finish_box?code=my_code&'
I want to be able to read and store my_code using python. Any ideas? I am new to python and dealing with APIs.
This is actually a more robust question than it seems, as it exposes some useful functions with web dev in general. You're basically asking how to separate my_code in the string 'http://www.myapp.com/finish_box?code=my_code&'.
Well let's take it in bits and pieces. First of all, you know that you only really need the stuff after the question mark, right? I mean, you don't need to know what website you got it from (though that would be good to save, let's keep that in case we need it later), you just need to know what arguments are being passed back. Let's start with String.split():
>>> return_string = 'http://www.myapp.com/finish_box?code=my_code&'
>>> step1 = return_string.split('?')
["http://www.myapp.com/finish_box","code=my_code&"]
This will return a list to step1 containing two elements, "http://www.myapp.com/finish_box" and "code=my_code&". Well hell, we're there! Let's split the second one again on the equals sign!
>>> step2 = step1[1].split("=")
["code","my_code&"]
Well lookie there, we're almost done! However, this doesn't really allow any more robust uses of it. What if instead we're given:
>>> return_string = r'http://www.myapp.com/finish_box?code=my_code&junk_data=ohyestheresverymuch&my_birthday=nottoday&stackoverflow=usefulplaceforinfo'
Suddenly our plan doesn't work. Let's instead break that second set on the & sign, since that's what's separating the key:value pairs.
step2 = step1[1].split("&")
["code=my_code",
"junk_data=ohyestheresverymuch",
"my_birthday=nottoday",
"stackoverflow=usefulplaceforinfo"]
Now we're getting somewhere. Let's save those as a dict, shall we?
>>> list_those_args = []
>>> for each_item in step2:
>>> list_those_args[each_item.split("=")[0]] = each_item.split("=")[1]
Now we've got a dictionary in list_those_args that contains key and value for every argument the GET passed back to you! Science!
So how do you access it now?
>>> list_those_args['code']
my_code
You need a webserver and a cgi-script to do this. I have setup a single python script solution to this to run this. You can see my code at:
https://github.com/jkitchin/box-course/blob/master/box_course/cgi-bin/box-course-authenticate
When you access the script, it redirects you to box for authentication. After authentication, if "code" is in the incoming request, the code is grabbed and redirected to the site where tokens are granted.
You have to setup a .htaccess file to store your secret key and id.

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