create a zone - jump start
when creating a zone i set “jump\_start”: true, however, it doesn’t fetch existing dns records. no records are added. i get a successful response and the zone is created but dns isn’t fetched.

<https://api.cloudflare.com/#zone-create-zone>
i checked in with the dns team on this one and we’re actually in the process of changing jump\_start to move to a newer system for scanning dns records which the ui uses already.

if you want to try it (the api is not documented yet), you can do this by creating the zone with jump\_start: false and th…
and it's done exactly what you told it to: generate a field that's capable of holding an SQL DATE. Which means a field without a time.  

The correct way of indicating a timestamp using JPA is as follows:



```
   /**
     * Time/date of creation of an entity.
     */
    @Temporal(TemporalType.TIMESTAMP)
    @Column(name = "CREATION_DATE")
    protected Date creationDate;

``` ok so you can crate a firewall rule as follows:

soucre = internal network
service= tcp 9000 (you will need to create the definition)
destination = 128.194.162.30 (create either a host definition if it is always the same ip or dns host if it changes) are you still forwarding dns requests to the old isp's dns servers?  that could slow things down...

 switch to google (8.8.8.8) or opendns (208.67.222.222 and 208.67.220.220) and see if that helps any, or find the dns servers for your new isp. A trigger is not what you want.


What you need is a scheduled job.


Take a look at the official documentation on the subject:


[Scheduling Jobs with Oracle Scheduler](http://docs.oracle.com/cd/B28359_01/server.111/b28310/scheduse.htm#i1033533)


Feel free to ask more questions if you find any trouble when creating your scheduled job. 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. [image] lwin:

how do i have to do the set-up?

ah, with duplex setup is quite simple: you just have to enter the same ip addresses and port names.

the internal osc server in renoise is not used for this purpose (although duplex is now using it for triggering notes, so you might want to leave … welcome rm.  the smtp server listed in the post is the correct one.  the is a short time lag between account creation and full activation on the server. please retry the outlook set up again and let us know if it successful. 
 
thank you just an update!

i have manage to get it to work.

here are the steps:

on your seagate freeagent theater just go to the network

create a shortcut, by clicking on the “my shortcut” and clicking “add”

put in the user/pass of your sharespace (either the admin username or other user name and pa… i successfully generated the link to the participant. my link was written incorrectly and should be changed to:

<https://localhost.streamlock.net/meeting/createmeeting.html>

now it works properly, thank you very much! You can call `context.Database.Migrate()`in your `Startup.cs`


eg:



```
using (var context = new MyContext(...))
{
    context.Database.Migrate();
}

```