which sql mode values to use for wordpress?
i have a wordpress site running on a do droplet and wordpress uses a localhost mysql db. i want to migrate the db to a do managed mysql db. i have created the new db and completed migrating the db data, however, i have run into a problem… i found a warning in the do documentation (the warning is in a red box near the bottom of page https://www.digitalocean.com/community/tutorials/how-to-install-wordpress-managed-database-ubuntu-18-04) that basically states wordpress will not work with a do managed mysql db unless changes are made to the global sql mode setting. unfortunately, the warning does not state what changes are needed. it provides links to mysql documentation that provides details about sql modes, but the mysql documentation says nothing about which sql mode values are incompatible with wordpress. so, my question is: what is a typical, safe set of values to use for a do managed mysql db’s global sql mode setting to ensure it will work properly with wordpress?
do managed dbs do work with wp, i ran many tests with them. you might bump into a couple of issues: in the do gui db settings, you need to set stricttranstables you might want to check this: https://www.digitalocean.com/community/questions/sql\_mode-only\_full\_group\_by?answer=54522
i encountered the same problem as you with mamp's mysql server. i think the source of the problem comes from setting the mysql port to 3306. i went through the same stack overflow solutions that you indicate but none of them fixed the issue. i then decided to reinstall mamp and reset the ports to default before launching the server for the first time (after reinstalling) and it worked. unfortunately, this means that the option to run wordpress locally using the folder's name as a url won't work :( 
wish you the best of luck finding a solution to this problem! if you do, it would be greatly appreciated if you could share your findings :) hello and welcome [@jhmauritz](/u/jhmauritz).

yes, changing the variables should be enough to connect to the server, and using docker-compose is absolutely a viable option.

if the server is publicly available you should configure ssl as well, otherwise your connections to it won’t be secure.

mind that although y… Here is a link to assist you.


<https://technet.microsoft.com/en-us/library/ms178078(v=sql.105).aspx>


If you had done a web search with the question you entered here, you would have found multiple sites that give you the instructions hi,

unfortunately due to wordpress restrictions we couldn’t add a confirmation on plugin delete action if the user wants to keep existing tables and charts. previously we were just keeping those in db, but it caused problems when someone wanted to clean up the site and remove the plugin. we are sti… Hi  

This is simple. First check whether you are able to connect Sql Server through SSMS or not.If you are able to connect through SSMS, then there may be a problem in connection string. If you are not able to connect through SSMS, then you had some problem with SQL Environment. if the server is that old then you'd likely be looking at sql server nearly the same vintage (perhaps sql 2008), you should be able to install a personal edition of 2008 sql on that, run a simple bak file restore with no problem.as stated though, those are well out of support (as you likely know) so it should be a priority that you get both slated for replacement.you mention audit, so i'd wager we are talking at least a public held company. definitely look towards a migration to newer software/hardware for security issues. SQL Express doesn’t support maintenance plans so the Tools don’t include those options. To use Maintenance plans you’ll need to get the Workgroup or above edition of SQL Server 2008. A couple of notes to get started:



> 
> .apply(literal\_eval)
> 
> 
> 


Wouldn't this be better as `map`?



> 
> I then re-create the Dask DF:
> 
> 
> ddf = dd.from\_pandas(ddf\_out, npartitions=nCores)
> 
> 
> 


`ddf_out` was already a dask dataframe, I don't know why you had to do this.



> 
> The columns in result seem to match those in metadir.
> 
> 
> 


The value of `result.columns` is taken from the meta you provided, no computing happens until you ask for it (dask is lazy in most operations). Does the ValueError exception not provide further information?


Here is a full example



```
x = ({'F9_07_PZ_COMP_DIRECT': '0',
  'F9_07_PZ_DIRTRSTKEY_NAME': 'DEBRA MEALY',
  'F9_07_PZ_COMP_OTHER': '0',
  'F9_07_PZ_COMP_RELATED': '0',
  'F9_07_PZ_TITLE': 'CHAIR PERSON',
  'F9_07_PZ_AVE_HOURS_WEEK': '1.00',
  'F9_07_PC_TRUSTEE_INDIVIDUAL': 'X'},
 {'F9_07_PZ_COMP_DIRECT': '0',
  'F9_07_PZ_DIRTRSTKEY_NAME': 'HELEN GORDON',
  'F9_07_PZ_COMP_OTHER': '0',
  'F9_07_PZ_COMP_RELATED': '0',
  'F9_07_PZ_TITLE': 'VICE CHAIR',
  'F9_07_PZ_AVE_HOURS_WEEK': '1.00',
  'F9_07_PC_TRUSTEE_INDIVIDUAL': 'X'})
df = pd.DataFrame({'a': x})
d = dd.from_pandas(df, 1)
meta = pd.DataFrame(columns=['F9_07_PZ_COMP_DIRECT', 
       'F9_07_PZ_DIRTRSTKEY_NAME',
       'F9_07_PZ_COMP_OTHER', 'F9_07_PZ_COMP_RELATED', 'F9_07_PZ_TITLE',
       'F9_07_PZ_AVE_HOURS_WEEK', 'F9_07_PC_TRUSTEE_INDIVIDUAL'], dtype="O")
d.map_partitions(lambda df: df.a.apply(pd.Series), meta=meta).compute()

```

How did I know what `meta` to use? I applied the function to the pandas dataframe - you might use a small piece of the dataframe to do this.


Some additional notes:


* it is an anti-pattern to load the data with pandas, pass to dask workers and then gather the whole result back to a pandas (in memory) dataframe, you are very unlikely to see a speedup this way and may incur a lot of overhead. You are better off loading with something like `dd.read_csv`, and aggregating or writing with dask functions too. Only `compute()` on something that will be small or not return anything (because it involves writing the output). The official examples do not use from\_pandas.
* string and dict processing are python methods, and so hold the interpreter lock (GIL) of any python function: threads will not actually run in parallel. To get parallelism, you need to run in processes, which is most easily achieved using <https://docs.dask.org/en/latest/setup/single-distributed.html>
* the distributed scheduler also gives you access to the dashboard, which has a lot of useful information to diagnose how your system is running. You can also configure a lot about its behaviour, in case you have firewall rules you need to obey. 1) Usage `yii`
  




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and `php yii`
  




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exactly the same. If you look at the file `yii`
  




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, you'll see it in the first line `#!/usr/bin/env php`
  




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. This is called the "shebang" syntax and instructs your shell to automatically execute the `yii`
  




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script using binary code `php`
  




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. See: [https://en.wikipedia.org/wiki/Shebang\_%28Unix%29](https://translate.googleusercontent.com/translate_c?depth=1&pto=aue&rurl=translate.google.com&sl=ru&sp=nmt4&tl=en&u=)


2) The difference here is flexibility. If you use the syntax `Schema::TYPE_PK`
  




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, Yii will automatically detect the exact column type based on your database database. For example, it `Schema::TYPE_PK`
  




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translates to `int(11) NOT NULL AUTO_INCREMENT PRIMARY KEY`
  




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in MySQL, but if you use Postgres as your database, it will translate to `serial NOT NULL PRIMARY KEY`
  




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. [1]



  




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In practice, it is unlikely which method you are using because you are probably not going to switch to a different type of database halfway through your project, and therefore there is no need for your migration scripts to be database agnostic. Based on your preference, you can choose the syntax `Schema`
  




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for added flexibility, or for a hard-coded syntax to make your hyphenation definitions more readable for future readers.


[1] See [https://github.com/yiisoft/yii2/blob/master/framework/db/pgsql/QueryBuilder.php#L21](https://translate.googleusercontent.com/translate_c?depth=1&pto=aue&rurl=translate.google.com&sl=ru&sp=nmt4&tl=en&u=) and [https://github.com/yiisoft/yii2/blob/master/framework /db/mysql/QueryBuilder.php#L24](https://translate.googleusercontent.com/translate_c?depth=1&pto=aue&rurl=translate.google.com&sl=ru&sp=nmt4&tl=en&u=) [localStorage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage) and [sessionStorage](https://developer.mozilla.org/en-US/docs/Web/API/Window/sessionStorage) both extend [Storage](https://developer.mozilla.org/en-US/docs/Web/API/Storage). There is no difference between them except for the intended "non-persistence" of `sessionStorage`.


That is, the data stored in `localStorage` persists until explicitly deleted. Changes made are saved and available for all current and future visits to the site.


For `sessionStorage`, changes are only available per tab. Changes made are saved and available for the current page **in that tab** until it is closed. Once it is closed, the stored data is deleted.