I found a good list of tutorials about JQL, including a reference on how to write a plugin [1]. Is there already or would it be possible to add comments to a JQL query?
For example, to document my item, I'd like to be able to document that our sprint 'number' differs from the jira sprint 'id';
sprint = 777 (* Agile sprint #50 *)
//Update ; I notice that the Sprint ID is apparently not immediately created upon opening of a sprint. We just started a new sprint but there is no number for it, according to browsing the report page...
1.[] ; ; ; ; ; X.JQL recap! See everything in one post ; ; http://blogs.atlassian.com/2013/03/jql-recap/
Sorry, you can't.
If something is not here: https://confluence.atlassian.com/display/JIRA061/Advanced+Searching then you can't. (Except of course the custom JQL functions provided by plugins.)
I still wished for the answer to this old question, so I'll share what I finally came up with. This is a hack and not as pretty as I wish, but I add comments by adding a fake search. In the example below, before each complex set of terms, I add "SUMMARY !~ "♥♥ ".
SUMMARY !~ " ♥♥ No subtasks of stories in backlog: ♥♥ " AND issueFunction not in subtasksOf("type = story AND status = backlog") AND SUMMARY !~ " ♥♥ Filter for members of that team: ♥♥ " AND filter = 25233
or
SUMMARY !~ " ♥♥ No subtasks of stories in backlog: // " AND issueFunction not in subtasksOf("type = story AND status = backlog") AND SUMMARY !~ " \\ ♥♥ Filter for members of that team: ♥♥ // " AND filter = 25233 AND SUMMARY !~ " \\ ♥♥"
The !~ prevents the SUMMARY search from messing up your real JQL query. There is a chance that my comment could actually be found inside one of the results, so adding ♥♥ makes it highly unlikely. If your computer can't make that character (press Alt-3 and let go), using ** or other combinations may work for you.
I also like how the ♥♥ and the spaces to make the comment stand out, but perhaps there are better characters like ☻ or ♫ or -- or //. Sadly, [] and () are not allowed. Any spaces must be inside the quotes to be preserved when you save the query.
Sometimes I paste long queries into a programming tool like Notepad++ and make a User Defined Language to clarify the (sections). But note that the special characters don't transfer correctly.
That's the best I can come up with until this feature request is voted up enough and fulfilled:
https://jira.atlassian.com/browse/JRASERVER-20455
Related
I get a daily email that lists upcoming appointments, and their length. The number of appointments vary from day to day.
The emails go like this:
================
Today's Schedule
9:30 AM
3h
Brazilian Blowout
[Client #1 name]
12:30 PM
1h
Women's Cut
[Client 2 name]
6:00 PM
45m
Men's Cut
[Client #3 name]
Projected Revenue
===================
I want to create an event in a Google Calendar for each appointment, and it seems like zapier MIGHT be able to do this, but all the help resources I can find are very general in nature.
Is this do-able on Zapier? If so, any nudges in the right direction would be awesome.
Any thoughts greatly appreciated.
I had some time to kill and enjoy the odd challenge. So I have put together a solution that should do what you are looking for. I will break it down by steps.
TEMPLATE
Zapier Trigger - Step 1
Type: Trigger
Module: Gmail
Criteria: User Dependent
Comments: For the trigger zap you will want to use a Gmail specific trigger, something to the effect of "execute trigger on emails titled 'xyz'", or "emails labeled 'xyz'" if you setup a filter in your inbox.
Input screenshot:
Output Screenshot:
Zapier Action - Step 2
Type: Action
Module: Code (Python 3)
Comments: The Code offered by Zapier executes whatever (properly written) code you place in its container. It is especially handy as it allows you to incorporate data from previous steps in it through the use of a dictionary variable titled 'input_data'. Zapier offers the Code module in two languages: Javascript and Python. As I am most familiar with Python my solution for this step was written in Python. I will append the code to the end of this answer. Using the data held in the body of the email (retrieved in step 1) we can execute some string manipulations and datetime conversions to break apart the email into its component parts and pass those on to the following Action Step: Create Calendar Event.
Input Screenshot:
Output Screenshot:
Zapier Action - Step 3
Type: Action
Module: Google Calendar - Create Event
Comments: Using the data outputted from the previous code step we can fill out the required fields for creating a new appointment.
Input Screenshot:
Output Screenshot:
PYTHON CODE
from datetime import timedelta, date, datetime
'''
Goal: Extract individual appointment details from variable length email
Steps:
Remove all extraneous and new line characters.
Isolate each individual appointment and group its relevant details.
Derive appointment start and end times using appointment time and duration.
Return all appointments in a list.
'''
def format_appt_times(appt_dict):
appt_start_str = appt_dict.get("appt_start")
appt_dur_str = appt_dict.get("appt_length")
# isolate hour and minutes from appointment time
appt_s_hour = int(appt_start_str[:appt_start_str.find(":")])
if ("pm" in appt_start_str.lower()):
appt_s_hour = 12 if appt_s_hour + 12 >= 24 else appt_s_hour + 12
appt_s_min = int(appt_start_str[appt_start_str.find(":") + 1 :
appt_start_str.find(":") + 3])
# isolate hour and minutes from duration time
appt_d_hour = 0
appt_d_min = 0
if ("h" in appt_dur_str):
appt_d_hour = int(appt_dur_str[:appt_dur_str.find("h")])
if ("m" in appt_dur_str):
appt_d_min = int(appt_dur_str[appt_dur_str.find("m") - 2 : appt_dur_str.find("m")])
# NOTE: adjust timedelta hours depending on your relation to UTC
# create datetime objects for appointment start and end times
time_zone = timedelta(hours=0)
tdy = date.today() - time_zone
duration = timedelta(hours=appt_d_hour, minutes=appt_d_min)
appt_start_dto = datetime(year=tdy.year,
month=tdy.month,
day=tdy.day,
hour=appt_s_hour,
minute=appt_s_min)
appt_end_dto = appt_start_dto + duration
# return properly formatted datetime as string for use in next step.
return (appt_start_dto.strftime("%Y-%m-%dT%H:%M"),
appt_end_dto.strftime("%Y-%m-%dT%H:%M"))
def partition_list(target, part_size):
for data in range(0, len(target), part_size):
yield target[data : data + part_size]
def main():
# Remove all extraneous and new line characters.
email_body = input_data.get("email_body")
head,delin,*email_body,delin,foot = [text for text in email_body.splitlines() if text != ""]
appointment_list = []
# Isolate each individual appointment and group its relevant details.
for text in partition_list(email_body, 4):
template = {
"appt_start" : text[0],
"appt_end" : None,
"appt_length" : text[1],
"appt_title" : text[2],
"appt_client" : text[3]
}
appointment_list.append(template)
for appt in appointment_list:
appt["appt_start"], appt["appt_end"] = format_appt_times(appt)
return appointment_list
return main()
I am not sure of your familiarity with Python, or programming more generally, but the comments in the code explain what each section is doing. If you have any specific questions regarding aspects of the code let me know. Assuming your email template does not change this setup should work exactly as needed. Let me know if anything is unclear.
UPDATE
I thought it best to address your question in the original answer should anyone else have similar questions.
explaining how this code is removing the extra characters:
There is actually a fair bit going on in the first line, so I will do my best to break it down, and provide resources where necessary.
The code in question:
head,delin,*email_body,delin,foot = [text for text in email_body.splitlines() if text != ""]
First step here was to break the text into manageable chunks. I did so with the line email_body.splitlines() which, by default, breaks strings into a list at each newline character found (you can specify your own delimiter).
If we were to inspect the list at this moment its contents would be something of the following:
["================", "", "Today's Schedule", "", "9:30 AM", "", "3h", ..., "[Client #3 name]", "", "Projected Revenue", "", "==================="]
You will notice there is a fair amount of information in there that we really don't want.
First lets look at the "" elements. These are left over as a result of the blank lines between each line of text, which even though they are blank do still have newline characters at the end of them. There a number of ways you could address this within python. We could simply write a for-loop to go through and copy all elements that are not "" to a new list.
To me this felt like additional work, and besides, Python offers list comprehension for just such a scenario. I won't go too deep into list comprehension as there is a lot that can be said about it, and in more insightful ways than I could muster, but it essentially allows you to provide logic against a set of 'data' to form a list. In this case, I specifically wanted to filter out the "" elements returned from the call to splitlines().
And so you will see I address this with the following line
[text for text in email_body.splitlines() if text != ""]
With that we have a list as above less the "" elements. Now we must turn our attention towards the more 'dynamic' garbage strings. Again there are a number of ways to do this. A, not particularly flexible, option could be to simply store the strings we want to remove in variables something to the effect of:
garb_1 = "==================="
garb_2 = "Projected Revenue"
garb_3 = ...
and once again filter the list with yet another for-loop. I instead chose to leverage Python's list unpacking idiom. Which allows us to 'unpack' list objects (and I believe tuples) into variables. As an example:
one, two, three = ["a", "b", "c"]
I'm sure you can guess what is happening above, as long as we provide the same number of variables as are in the list we can 'unpack' it in this fashion. But wait! In our case we don't know how long the list is going to be as it is entirely dependent on the number of appointments you have for any given day. Well this is where star unpacking enters to elevate the functionality. Using my code as the example:
head,delin,*email_body,delin,foot = [text for text in email_body.splitlines() if text != ""]
The *, in plain-English, is saying "I don't know how many elements to expect just give me all of them in a list". As we know that there will always be two lines of garbage at the beginning and end of the email we can assign them to throw away variables and capture everything in between using our variable length *email_body container.
With all of this complete we now have a list with only the data we are looking to capture. If, as you say, there are additional lines of garbage before or after the email_body, you can simply add additional throw away variables to account for them.
Once again feel free to ask any follow up questions.
Michael
Resources
List Comprehension
Star Unpacking
I want to find all usages of my react component in code.
I tried <Button> but Special chars <> are not supported.
Tried "Button" and i get "Button" and button with lowercase as results as well.
So exact match is also not supported.
Is there is a way to find a string exactly without any additional results?
Unfortunately, search symbols (<> and "" in your scenario) is not supported in code search.
In tfs the symbol "" is used for finding an exact match to a set of words by enclosing your search terms in double-quotes. For example, "Client not found".
Is there is a way to find a string exactly without any additional
results?
Yes, but it seems a little complex, just reference my answer in another thread:Is there a way to make TFS code search recognize the "#" symbol?
Checked for some characters in code search. You can't use the symbol
characters except * and ? as part of your search query, which
including below characters: . , : ; / \ ` ' " # = ! # $ & + ^ | ~ < >
( ) { } [ ]. The search will simply ignore these symbols.
But you can use wildcard characters * and ? to broaden your search.
You can use wildcard characters anywhere in your search string except
as a prefix in a simple search string or a query that uses a code type
filter. For example, you cannot use a search query such as
*RequestHandler or class:?RequestHandler. However, you can use prefix wildcards with the other search filter functions; for
example, the
search query strings file:*RequestHandler.cs and repo:?Handlers are
valid.
Please see Broaden your search with wildcards for details.
If you want to search the strings including these symbol exactly(such
as '#' here), you can code search with other strings (eg,
testexample.com here) to narrow down the scope first, then copy the
specific code to text editor which support the symbols (eg,
Notepad++), then search stings with the symbol characters.
Besides, if you are using Git, another workaround is using the code
search tool Hound: a lightning fast code search tool, it supports
the symbol characters. Reference this thread to use it:
How can I publish source code (Visual Studio) on a intranet?
Also, there is a User Voice here to suggest the feature, you can go and vote it up to achieve that in future.
Symptoms:
Searching for a single word (i.e. "Snap") works
Searching for another word contained in the same field (i.e. "On") also works
Searching for "Snap On" at the same time returns 0 results, even though it shouldn't.
The setup:
SQL Server 2008 R2 with Advanced Features
nopCommerce 3.0
Things I have done:
I added the Product.MetaKeywords column to the full text search catalog
I added a bit into the Stored Procedure that performs the search to search through the MetaKeywords
Now the nopCommerce boards are fairly slow, but I'm positive the problem is within the SQL Stored Procedure anyway, so I figured I would ask for some SQL Server help here, even if you aren't familiar with the nopCommerce web app, you may have some information you can help me with.
The stored procedure in question is too large to post entirely here, but basically it dynamically adds "OR" or "AND" in between the keyword searches to generate the phrase used in a Contains clause. It selects through several unions various searchable fields by using Contains.
Here is the bit I added into the stored procedure
SET #sql = #sql + '
UNION
SELECT p.Id
FROM Product p with (NOLOCK)
WHERE '
IF #UseFullTextSearch = 1
SET #sql = #sql + 'CONTAINS(p.[MetaKeywords], #Keywords) '
ELSE
SET #sql = #sql + 'PATINDEX(#Keywords, p.[MetaKeywords]) > 0 '
#Keywords, at this point, if I am reading the procedure correctly, has a value of: "Snap* AND On*"
I don't understand why my query of "Snap On" returns 0 results, but "Snap" and "On" individually work fine.
The minimum search length is set to 1, so it's not that.
I should add that searching for "Snap* OR On*" works, but I cannot use OR because then searching for "Snap On" will also return "Snap Dragon" and other unrelated things.
--EDIT--
The problem wasn't any of that. I got some advice elsewhere and the problem was actually the stoplist. I managed to fix my issue simply by changing the stoplist on the product table from <system> to <off>.
To do this, follow these steps.
browse to your table in SQL Server management studio
Right click on the table and select "Full-Text Index"
Select "Properties" under "Full-Text Index"
In the "General" Tab, change "Full-Text Index Stoplist" to <off>
I had to do it this way because I was unable to get the transact SQL to work. It kept telling me there was no such object as the table I was attempting to modify. If anyone can provide any insight on how the Alter fulltext index statement works, I'm interested, because I was following the example on the MSDN page to the T and it just kept telling me there was no such object named Product.
The asterisk is not a plain old wildcard. If you are using it anywhere other than at the end of a search term, you're probably not using it correctly. See answers to a similar question
SQL Contains Question
In your case, each search term must be quoted separately. See this example from the docs http://technet.microsoft.com/en-us/library/ms187787(v=sql.90).aspx
SELECT Name
FROM Production.Product
WHERE CONTAINS(Name, '"chain*" OR "full*"');
I'm trying to return results more like the search
My curren algorithm is this
def search_conditions(column, q)
vars = []
vars2 = []
vars << q
if q.size > 3
(q.size-2).times do |i|
vars2 << q[i..(i+2)]
next if i == 0
vars << q[i..-1]
vars << q[0..(q.size-1-i)]
vars << q[i % 2 == 0 ? (i/2)..(q.size-(i/2)) : (i/2)..(q.size-1-(i/2))] if i > 1
end
end
query = "#{column} ILIKE ?"
vars = (vars+vars2).uniq
return [vars.map { query }.join(' OR ')] + vars.map { |x| "%#{x}%" }
end
If I search for "Ruby on Rails" it will make 4 search ways.
1) Removing the left letters "uby on Rails".."ils"
2) Removing the right letters "Ruby on Rail".."Rub"
3) Removing left and right letters "uby on Rails", "uby on Rail" ... "on "
4) Using only 3 letters "Rub", "uby", "by ", "y o", " on" ... "ils"
Is good to use these 4 ways? There any more?
Why are you removing these letters? Are you trying to make sure that if someone searches for 'widgets', you will also match 'widget'?
If so, what you are trying to do is called 'stemming', and it is really much more complicated than removing leading and trailing letters. You may also be interested in removing 'stop words' from your query. These are those extremely common words that are necessary to form grammatically-correct sentences, but are not very useful for search, such as 'a', 'the', etc.
Getting search right is an immensely complex and difficult problem. I would suggest that you don't try to solve it yourself, and instead focus on the core purpose of your site. Perhaps you can leverage the search functionality from the Lucene project in your code. This link may also be helpful for using Lucene in Ruby on Rails.
I hope that helps; I realize that I sort of side-stepped your original question, but I really would not recommend trying to tackle this yourself.
As pkaeding says, stemming is far too complicated to try to implement yourself. However, if you want to search for similar (not exact) strings in MySQL, and your user search terms are very close to the full value of a database field (ie, you're not searching a large body of text for a word or phrase), you might want to try using the Levenshtein distance. Here is a MySQL implementation.
The Levenshtein algorithm will allow you to do "fuzzy" matching, give you a similarity score, and help you avoid installation and configuration of a search daemon, which is complicated. However, this is really only for a very specific case, not a general site search.
While, were all suggesting other possible solutions, check out:
Sphinx - How do you implement full-text search for that 10+ million row table, keep up with the load, and stay relevant? Sphinx is good at those kinds of riddles.
Thinking Sphinx - A Ruby connector between Sphinx and ActiveRecord.
I have a list of keywords that I need to search against, using ThinkingSphinx
Some of them being more important than others, i need to find a way to weight those words.
So far, the only solution i came up with is to repeat x number of times the same word in my query to increase its relevance.
Eg:
3 keywords, each of them having a level of importance: Blue(1) Recent(2) Fun(3)
I run this query
MyModel.search "Blue Recent Recent Fun Fun Fun", :match_mode => :any
Not very elegant, and quite limiting.
Does anyone have a better idea?
If you can get those keywords into a separate field, then you could weight those fields to be more important. That's about the only good approach I can think of, though.
MyModel.search "Blue Recent Fun", :field_weights => {"keywords" => 100}
Recently I've been using Sphinx extensively, and since the death of UltraSphinx, I started using Pat's great plugin (Thanks Pat, I'll buy you a coffee in Melbourne soon!)
I see a possible solution based on your original idea, but you need to make changes to the data at "index time" not "run time".
Try this:
Modify your Sphinx SQL query to replace "Blue" with "Blue Blue Blue Blue", "Recent" with "Recent Recent Recent" and "Fun" with "Fun Fun". This will magnify any occurrences of your special keywords.
e.g. SELECT REPLACE(my_text_col,"blue","blue blue blue") as my_text_col ...
You probably want to do them all at once, so just nest the replace calls.
e.g. SELECT REPLACE(REPLACE(my_text_col,"fun","fun fun"),"blue","blue blue blue") as my_text_col ...
Next, change your ranking mode to SPH_RANK_WORDCOUNT. This way maximum relevancy is given to the frequency of the keywords.
(Optional) Imagine you have a list of keywords related to your special keywords. For example "pale blue" relates to "blue" and "pleasant" relates to "fun". At run time, rewrite the query text to look for the target word instead. You can store these words easily in a hash, and then loop through it to make the replacements.
# Add trigger words as the key,
# and the related special keyword as the value
trigger_words = {}
trigger_words['pale blue'] = 'blue'
trigger_words['pleasant'] = 'fun'
# Now loop through each query term and see if it should be replaced
new_query = ""
query.split.each do |word|
word = trigger_words[word] if trigger_words.has_key?(word)
new_query = new_query + ' ' word
end
Now you have quasi-keyword-clustering too. Sphinx is really a fantastic technology, enjoy!