> 
> The issue occurs when e.g. one channel can not be turned on and ramp for some temp/specific 
> reason, and someone else is working on the daq and reloads the odb for e.g. 1h ago.  
> 

So you want to ensure that some HV channels are turned off and stay turned off. Yes?

Most effective solution will depend on the consequences of unwanted turning-on of your channels:

- if hardware is destroyed if turned on - I think you should have a hardware lock-out. (unplug the HV cable)
- if hardware malfunctions and will degrade if left turned on for long time (i.e. a hot phototube or sparking wire chamber) - your data 
monitoring software should detect the anomaly (it will show up as a hot channel, dead channel, etc) and the people running the 
experiment will realize the mistake and turn the channel back off. also hardware monitoring (HV currents, etc) should detect this, with 
same effect.
- if collected data becomes useless (the turned-off channel make big noise in all other channels), then same thing, your data 
monitoring should catch it.

The next consideration is what are you protecting against:

a) one person flags channel defective, turns it off, next person knows nothing, turns it back on - you need to work on documentation, 
shift hand-off and other human-level procedures
b) people running experiment load random odb files - same thing, from human-level procedures and documentation it should be made 
clear which odb files are correct and which should not be used
c) software malfunction (not human person) causes data change in odb causes turned-off channel to turn back on
d) hardware malfunction causes turned-off channel to turn back on (HV power supply hardware or firmware malfunctions and decides 
that all channels should be turned on at maximum high voltage)

In the experiments I am most familiar with, problem (b) is avoided by never loading/reloading odb files directly, most/all interaction
with the experiment is done through web pages, and these web pages are carefully coded to be safe against most user mistakes.

Cases (a), (b) and (c) you can protect against by changing the frontend code to refuse to turn on some channels:

int set_hv(int channel, int voltage) {
   if (channel == 35) return COMMAND_REFUSED;
   write_to_hardware(channel, voltage);
   return COMMAND_SUCCESS;
}

But in reality this solution only creates problem (e):

e) people running the experiment start random versions of the frontend program, make random changes to the frontend source code, 
multiple people working on the frontend have their own personal versions/copies of the source code, etc.

This is the worst-case scenario, meaning the experiment lost control of software configuration, and even basic software version 
control tools (like svn or git) are not being used. If your experiment gets that chaotic, all protections are likely to be ineffective - 
documentation will not work (people will ignore post-it notes "do not turn on!"), hardware protections will not work (unplugged cable 
labeled "do not plug in!" will be plugged back in and powered), etc. good luck, then.

K.O.

There is a not-so-well-known function in the ODB to write protect some keys. You can do

odbedit> chmod 1 /Equipment/HV/Demand

which will write protect your Demand values. You see that by doing

odbedit> ls -ls

where you only see a "R" at the right end instead a "RWD". I haven't tried it yet (so better do a dry run yourself), but that should prevent an odb load to overwrite your demand values. To change the values, put some logic on a custom page to unprotect the 
values, change them, and then protect them again.

Stefan

I really like the concept of the odbxx interface.
I think it would be a nice feature if one could have a read_only connection, e.g. by declaring a "const midas::odb".
Just for fun I tried if this already works, but the compiler doesn't allow const midas::odb for e.g. the [] operator. I'm guessing this would be non-trivial to implement, but I like the idea of certain Midas clients being able to read the odb without risking corruption.

> I really like the concept of the odbxx interface.
> I think it would be a nice feature if one could have a read_only connection, e.g. by declaring a "const midas::odb".
> Just for fun I tried if this already works, but the compiler doesn't allow const midas::odb for e.g. the [] operator. I'm guessing this would be non-trivial to implement, but I like the idea of certain Midas clients being able to read the odb without risking corruption.

Having a "const midas::odb" probably does not work (at least I would not know how to implement that).

But I could make an internal flag analog to the auto refresh flags. So you would have

    o.set_write_protect(true);

to turn on write protection. Would that work for you?

Best,
Stefan

> Having a "const midas::odb" probably does not work (at least I would not know how to implement that).
> 
> But I could make an internal flag analog to the auto refresh flags. So you would have
> 
>     o.set_write_protect(true);
> 
> to turn on write protection. Would that work for you?

Absolutely. Looking at the underlying code I was also at a loss how const would work.
I'm mostly just interested in having small clients that only read from the odb (for whatever reason) without risking corrupting it by messing something 
up in the code, especially since such small clients are almost by definition hacked together quickly on the fly.

Ok, I implemented and committed that. Just call

o.set_write_protect(true)

on a key you don't want to modify. If you do so, an exception gets thrown.

Best,
Stefan

> 
> The only remaining problem when running my script is some kind of deadlock between the ODB and SYSMSG semaphores...
> 


In theory, we understand how programs that use 2 semaphores to protect 2 shared resources can deadlock
if there are mistakes in how locks are used.

For example, consider 2 semaphores A and B and 2 concurrent
subroutines foo() and bar() running at exactly the same time:

foo() { lock(A); lock(B); do stuff; unlock(B); unlock(A); } and
bar() { lock(B); lock(A); do stuff; unlock(A); unlock(B); }

This system will deadlock immediately with foo() taking semaphore A, bar() taking semaphore B,
then foo() waiting for B and bar() waiting for A forever.

This situation can also be described as a race condition where foo() and bar() are racing each
other to get the semaphores, with the result depending on who gets there first
and, in this case, sometimes the result is deadlock.

In this example, the size of the race condition time window is the wall clock time
between actually locking both semaphores in the sequence "lock(X); lock(Y);". While
locking a semaphore is "instantaneous", the actual function lock() takes time to call
and execute, and this time is not fixed - it can change if the CPU takes a hardware
interrupt (quick), a page fault (when we may have to wait until data is read from the swap file)
or a scheduler interrupt (when we are outright stopped for milliseconds while the CPU runs
some other process).

In reality, subroutines foo() and bar() do not run at exactly the same time, so the probability
of deadlock will depend on how often foo() and bar() are executed, the size of the race condition time window,
the number of processes executing foo() and bar(), and the amount of background activity
like swapping, hardware interrupts, etc.

(Also note that on a single-cpu system, we will probably never see a deadlock between foo() and bar()
because they will never be running at the same time. But the deadlock is still there, waiting
for the lucky moment when the scheduler switches from foo() to bar() just at the wrong place).

There is more on deadlocks and stuff written at:
http://en.wikipedia.org/wiki/Deadlock
http://en.wikipedia.org/wiki/Race_condition

In case of MIDAS, the 2 semaphores are the ODB lock and the SYSMSG lock (also remember about locks
for the shared memory event buffers, SYSTEM, etc, but they seem to be unlikely to deadlock).

The function foo() is any ODB function (db_xxx) that locks ODB and then calls cm_msg() (which locks SYSMSG).

The function bar() is cm_msg() which locks SYSMSG and then calls some ODB db_xxx() function which tries to lock ODB.

(This is made more interesting by cm_watchdog() periodically called by alarm(), where we alternately
take SYSMSG (via bm_cleanup) and ODB locks.)

I think this establishes a theoretical possibility for MIDAS to deadlock on the ODB and SYSMSG semaphores.

In practice, I think we almost never see this deadlock because cm_msg() is not called very often, and during normal
operation, is almost never called from inside ODB functions holding the ODB lock - almost all calls to cm_msg from
ODB functions are made to report some kind of problem with the ODB internal structure, something that "never"
happens.

By "luck" I stumbled into this deadlock when doing the "odbedit" fork-bomb torture tests, when high ODB lock
activity is combined with high cm_msg() activity reporting clients starting and stopping, combined with a large
number of MIDAS clients running, starting and stopping.

So a deadlock I see within 1 minute of running the torture test, other lucky people will see after running an experiment
for 1 year, or 1 month, or 1 day, depending.

In theory, this deadlock can be removed by establishing a fixed order of taking locks. There will never be a deadlock
if we always take the SYSMSG lock first, then ask for the ODB lock.

In practice, it means that using cm_msg() while holding an ODB lock is automatically dangerous
and should be avoided if not forbidden.

And it does work. By refactoring a few places in client startup, shutdown and cleanup code, I made the deadlock "go away",
and my test script (posted in my first message) no longer deadlocks, even if I run hundreds of odbedit's at the same time.

Unfortunately,  it is impractical to audit and refactor all of MIDAS to completely remove this problem. MIDAS call graphs
are sufficiently complicated for making manual analysis of lock sequences infeasible and
I expect any automatic lock analysis tool will be defeated by the cm_watchdog() periodic interrupt.

An improvement is possible if we make cm_msg() safe for calling from inside the ODB db_xxx() function. Instead
of immediately sending messages to SYSMSG (requiring a SYSMSG lock), if ODB is locked, cm_msg() could
save the messages in a buffer, which would be flushed when the ODB lock is released. (This does not fix
all the other places that take ODB and SYSMSG locks in arbitrary order, but I think those places are not as
likely to deadlock, compared to cm_msg()).

However, now that I have greatly reduced the probability of deadlock in the client startup/shutdown/cleanup code,
maybe there is no urgency for changing cm_msg() - remember that if we do not call cm_msg() we will never deadlock -
and during normal operation, cm_msg() is almost never called.

Investigation completed, I will now cleanup, retest and commit my changes to midas.c and odb.c. Looking into this
and writing it up was a good intellectual exercise.

P.S. Also remember that there are locks for shared memory event buffers (SYSTEM, etc), but those do not involve
lock inversion leading to deadlock. I think all lock sequences are like this: SYSTEM->ODB, SYSTEM->SYSMSG->ODB,
there are no inverted sequences SYSMSG->SYSTEM or ODB->SYSTEM and the only deadlocking
sequence SYSTEM->ODB->SYSMSG, does not really involve the SYSTEM lock.

K.O.

Ciao, 
we have a very strange issue with python lib with client.odb_get("/") function 
when running as midas process and matplotlib is used.


we are developing a remote console by means of sending via kafka producer the odb, 
camera image and pmt waveforms, in the INFN cloud where grafana make available 
data for non expert shifters, as well as sending midas events for online 
reconstruction to the htcondr queue on cloud. The process work perfectly and allow 
use to parallelise to standard midas pipeline for file production, ecc the online 
monitoring and data processing where we have computing resources (our DAQ is 
underground at LNGS). Part of the work will be presented next weak at CHEP
the full code is available at https://github.com/CYGNUS-
RD/middleware/blob/master/dev/event_producer_s3.py
but to get the strange behaviour I report here a test script:

----
def main(verbose=False):
    from matplotlib import pyplot as plt

    import time

    import midas
    import midas.client

    
    client = midas.client.MidasClient("middleware")
    buffer_handle = client.open_event_buffer("SYSTEM",None,1000000000)
    request_id = client.register_event_request(buffer_handle, sampling_type = 2) 
    
    fpath = os.path.dirname(os.path.realpath(sys.argv[0]))
    
    
    while True:
        # 
        odb = client.odb_get("/")
        if verbose:
            print(odb)
        start1 = time.time()
              
        client.communicate(10)
        time.sleep(1)
        

    client.deregister_event_request(buffer_handle, request_id)

    client.disconnect()
----
if I run it as cli interactivity including or not matplotlib the everything si ok. 
As I run it as midas "program" I get: 
-----
Traceback (most recent call last):
  File "/home/standard/daq/middleware/dev/test_midas_error.py", line 48, in 
<module>
    main(verbose=options.verbose)
  File "/home/standard/daq/middleware/dev/test_midas_error.py", line 29, in main
    odb = client.odb_get("/")
  File "/home/standard/packages/midas/python/midas/client.py", line 354, in 
odb_get
    retval = midas.safe_to_json(buf.value, use_ordered_dict=True)
  File "/home/standard/packages/midas/python/midas/__init__.py", line 552, in 
safe_to_json
    return json.loads(decoded, strict=False, 
object_pairs_hook=collections.OrderedDict)
  File "/usr/lib/python3.8/json/__init__.py", line 370, in loads
    return cls(**kw).decode(s)
  File "/usr/lib/python3.8/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/usr/lib/python3.8/json/decoder.py", line 353, in raw_decode
    obj, end = self.scan_once(s, idx)
json.decoder.JSONDecodeError: Expecting property name enclosed in double quotes: 
line 300 column 26 (char 17535)
----
if I comment out the import of matplotlib every think works perfectly again also 
as midas program. 

it seams that there is a difference between the to way of use the code, and that 
is sufficient the call to matplotlib to corrupt in some way the odb. any ideas?

> it seams that there is a difference between the to way of use the code, and that 
> is sufficient the call to matplotlib to corrupt in some way the odb. any ideas?

I can't reproduce this on my machines, so this is going to be fun to debug!

Can you try running the program below please? It takes the important bits from odb_get() but prints out the string before we try to parse it as JSON. Feel free to send me the output via email (bsmith@triumf.ca) if you don't want to post your entire ODB dump in the elog.




import sys
import os
import time
import midas
import midas.client
import ctypes

def debug_get(client):
    c_path = ctypes.create_string_buffer(b"/")
    hKey = ctypes.c_int()
    client.lib.c_db_find_key(client.hDB, 0, c_path, ctypes.byref(hKey))

    buf = ctypes.c_char_p()
    bufsize = ctypes.c_int()
    bufend = ctypes.c_int()

    client.lib.c_db_copy_json_save(client.hDB, hKey, ctypes.byref(buf), ctypes.byref(bufsize), ctypes.byref(bufend))

    print("-" * 80)
    print("FULL DUMP")
    print("-" * 80)
    print(buf.value)
    print("-" * 80)
    print("Chars 17000-18000")
    print("-" * 80)
    print(buf.value[17000:18000])
    print("-" * 80)

    as_dict = midas.safe_to_json(buf.value, use_ordered_dict=True)

    client.lib.c_free(buf)

    return as_dict

def main(verbose=False):
    client = midas.client.MidasClient("middleware")
    buffer_handle = client.open_event_buffer("SYSTEM",None,1000000000)
    request_id = client.register_event_request(buffer_handle, sampling_type = 2)

    fpath = os.path.dirname(os.path.realpath(sys.argv[0]))

    while True:
        # odb = client.odb_get("/")
        odb = debug_get(client)

        if verbose:
            print(odb)
        start1 = time.time()

        client.communicate(10)
        time.sleep(1)


    client.deregister_event_request(buffer_handle, request_id)

    client.disconnect()

if __name__ == "__main__":
    main()

> > it seams that there is a difference between the to way of use the code, and that 
> > is sufficient the call to matplotlib to corrupt in some way the odb. any ideas?
> 
> I can't reproduce this on my machines, so this is going to be fun to debug!
> 
> Can you try running the program below please? It takes the important bits from odb_get() but prints out the string before we try to parse it as JSON. Feel free to send me the output via email (bsmith@triumf.ca) if you don't want to post your entire ODB dump in the elog.
> 
> 
> 
> 
> import sys
> import os
> import time
> import midas
> import midas.client
> import ctypes
> 
> def debug_get(client):
>     c_path = ctypes.create_string_buffer(b"/")
>     hKey = ctypes.c_int()
>     client.lib.c_db_find_key(client.hDB, 0, c_path, ctypes.byref(hKey))
> 
>     buf = ctypes.c_char_p()
>     bufsize = ctypes.c_int()
>     bufend = ctypes.c_int()
> 
>     client.lib.c_db_copy_json_save(client.hDB, hKey, ctypes.byref(buf), ctypes.byref(bufsize), ctypes.byref(bufend))
> 
>     print("-" * 80)
>     print("FULL DUMP")
>     print("-" * 80)
>     print(buf.value)
>     print("-" * 80)
>     print("Chars 17000-18000")
>     print("-" * 80)
>     print(buf.value[17000:18000])
>     print("-" * 80)
> 
>     as_dict = midas.safe_to_json(buf.value, use_ordered_dict=True)
> 
>     client.lib.c_free(buf)
> 
>     return as_dict
> 
> def main(verbose=False):
>     client = midas.client.MidasClient("middleware")
>     buffer_handle = client.open_event_buffer("SYSTEM",None,1000000000)
>     request_id = client.register_event_request(buffer_handle, sampling_type = 2)
> 
>     fpath = os.path.dirname(os.path.realpath(sys.argv[0]))
> 
>     while True:
>         # odb = client.odb_get("/")
>         odb = debug_get(client)
> 
>         if verbose:
>             print(odb)
>         start1 = time.time()
> 
>         client.communicate(10)
>         time.sleep(1)
> 
> 
>     client.deregister_event_request(buffer_handle, request_id)
> 
>     client.disconnect()
> 
> if __name__ == "__main__":
>     main()
Thank you!
if I added the mat

> > it seams that there is a difference between the to way of use the code, and that 
> > is sufficient the call to matplotlib to corrupt in some way the odb. any ideas?
> 
> I can't reproduce this on my machines, so this is going to be fun to debug!
> 
> Can you try running the program below please? It takes the important bits from odb_get() but prints out the string before we try to parse it as JSON. Feel free to send me the output via email (bsmith@triumf.ca) if you don't want to post your entire ODB dump in the elog.

Thank you!
if I added the matplotlib as follow:

#!/usr/bin/env python3

import sys
import os
import time
import midas
import midas.client
import ctypes
from matplotlib import pyplot as plt

def debug_get(client):
    c_path = ctypes.create_string_buffer(b"/")
    hKey = ctypes.c_int()
    client.lib.c_db_find_key(client.hDB, 0, c_path, ctypes.byref(hKey))

    buf = ctypes.c_char_p()
    bufsize = ctypes.c_int()
    bufend = ctypes.c_int()

    client.lib.c_db_copy_json_save(client.hDB, hKey, ctypes.byref(buf), ctypes.byref(bufsize), ctypes.byref(bufend))

    print("-" * 80)
    print("FULL DUMP")
    print("-" * 80)
    print(buf.value)
    print("-" * 80)
    print("Chars 17000-18000")
    print("-" * 80)
    print(buf.value[17000:18000])
    print("-" * 80)

    as_dict = midas.safe_to_json(buf.value, use_ordered_dict=True)

    client.lib.c_free(buf)

    return as_dict

def main(verbose=False):
    client = midas.client.MidasClient("middleware")
    buffer_handle = client.open_event_buffer("SYSTEM",None,1000000000)
    request_id = client.register_event_request(buffer_handle, sampling_type = 2)

    fpath = os.path.dirname(os.path.realpath(sys.argv[0]))

    while True:
        # odb = client.odb_get("/")
        odb = debug_get(client)

        if verbose:
            print(odb)
        start1 = time.time()

        client.communicate(10)
        time.sleep(1)


    client.deregister_event_request(buffer_handle, request_id)

    client.disconnect()

        
if __name__ == "__main__":
    from optparse import OptionParser
    parser = OptionParser(usage='usage: %prog\t ')
    parser.add_option('-v','--verbose', dest='verbose', action="store_true", default=False, help='verbose output;');
    (options, args) = parser.parse_args()
    main(verbose=options.verbose)


then tested the code in interactive mode without any error. as soon as I submit as midas "Program" I get the attached output.
thank you again, Giovanni

Looks like a localisation issue. Your floats are formatted as "6,6584e+01", whereas the JSON decoder expects "6.6584e+01".

Can you run the following few lines please? Then I'll be able to write a test using the same setup as you:


import locale
print(locale.getlocale())
from matplotlib import pyplot as plt
print(locale.getlocale())
 

> Looks like a localisation issue. Your floats are formatted as "6,6584e+01", whereas the JSON decoder expects "6.6584e+01".

This should be fixed in the latest commit to the midas develop branch. The JSON specification requires a dot for the decimal separator, so we must ignore the user's locale when formatting floats/doubles for JSON.

I've tested the fix on my machine by manually changing the locale, and also added an automated test in the python directory.

> > Looks like a localisation issue. Your floats are formatted as "6,6584e+01", whereas the JSON decoder expects "6.6584e+01".
> 
> This should be fixed in the latest commit to the midas develop branch. The JSON specification requires a dot for the decimal separator, so we must ignore the user's locale when formatting floats/doubles for JSON.
> 
> I've tested the fix on my machine by manually changing the locale, and also added an automated test in the python directory.

Thanks very macth Ben,
so if I understand correctly we have to update MIDAS to latest develop branch available? can you sand me the link to be sure of install the right update. 
can you also tell me how you fix manually? we are restarting and then well be difficult install and makes updete.
thank you again, regards, Giovanni

Setup:
setting up midas, starting mhttpd and mlogger and running fetest.

The History page and the javascript mjsonrpc client are both able to fetch historical data for test_slow/data. Javascript code used is included here:

mjsonrpc_call(
  "hs_read_arraybuffer",
  {
    start_time: Math.floor((new Date()).getTime() /1000) - 1000,
    end_time: Math.floor((new Date()).getTime() /1000),
    events: ["test_slow/data"],
    tags: ["data"],
    index: [0],
  },
  "arraybuffer"
).then(console.log)

However, the python client does not find any valid events:

Setup:
An exptab is created and the environment variables MIDAS_EXPTAB and MIDAS_EXPT_NAME and MIDASSYS are set (together with the correct PATH)

Running /midas/python/examples/basic_hist_script.py and typing in data:

Valid events are:
* Run transitions
* rrandom/SLOW
* test_slow/data
Enter event name: test_slow/data
Valid tags for test_slow/data are:
* data
Enter tag name: data
Event/tag test_slow/data/data has 1 elements
How many hours: 1
Interval in seconds: 1 # other values were also tested, without success
0 entries found

We expect entries to be found, however do not.

Tested setups:
Macbook Pro Sequoia 15.3 with Python 3.13.2, ROOT latest, midas bitbucket commit 84c7ef7
Windows 11 with Python 3.11, ROOT latest, midas latest commit (development branch)

Unfortunately I again cannot reproduce this:

$ python ~/DAQ/midas_latest/python/examples/basic_hist_script.py
Valid events are:
* Run transitions
* test_slow/data
Enter event name: test_slow/data
Valid tags for test_slow/data are:
* data
Enter tag name: data
Event/tag test_slow/data/data has 1 elements
How many hours: 1
Interval in seconds: 1
78 entries found
2025/03/17 17:00:56 => 98.097391
2025/03/17 17:00:57 => 98.982151
2025/03/17 17:00:58 => 99.589187
2025/03/17 17:00:59 => 99.926821
2025/03/17 17:01:00 => 99.989878
2025/03/17 17:01:01 => 99.778216
2025/03/17 17:01:02 => 99.292485
.......


I want to narrow down whether the issue is in the basic_hist_script.py or the lower-level code. So there are a few steps of debugging to do.



1) Run code directly in the python interpreter: 

Can you run the following and send the output please?

```
import midas.client
c = midas.client.MidasClient("history_test")
data = c.hist_get_recent_data(1,1,"test_slow/data","data")
print(f"event_name='{data[0]['event_name']}', tag_name='{data[0]['tag_name']}', num_entries={data[0]['num_entries']}, status={data[0]['status']}, arrlen={len(data[0]['values'])}")
```

For me, I get:
event_name='test_slow/data', tag_name='data', num_entries=441, status=1, arrlen=441



2) If things look sensible for you (status=1, non-zero num_entries), then the problem is in the basic_hist_script.py. Can you add the same print() statement in basic_hist_script.py immediately after the call to hist_get_recent_data(), then run that script again and send the output of that?



3) Debug the python/C conversions.

In midas/client.py add the following line to hist_get_data() immediately before the call to self.lib.c_hs_read():

```
        print(f"c_start_time={c_start_time.value}, c_end_time={c_end_time.value}, c_interval={c_interval.value}, c_event_name={c_event_name.value}, c_tag_name={c_tag_name.value}")
```

Then run the following and send the output:

```
import midas.client
c = midas.client.MidasClient("history_test")
data = c.hist_get_recent_data(1,1,"test_slow/data","data")
```

For me, I get:
c_start_time=1742254428, c_end_time=1742258028, c_interval=1, c_event_name=b'test_slow/data', c_tag_name=b'data'

I want to check that the UNIX timestamps match what you expect for your server, and that nothing weird is going on with the python/C string conversions.


Thanks,
Ben

> Unfortunately I again cannot reproduce this:
> 
> $ python ~/DAQ/midas_latest/python/examples/basic_hist_script.py
> Valid events are:
> * Run transitions
> * test_slow/data
> Enter event name: test_slow/data
> Valid tags for test_slow/data are:
> * data
> Enter tag name: data
> Event/tag test_slow/data/data has 1 elements
> How many hours: 1
> Interval in seconds: 1
> 78 entries found
> 2025/03/17 17:00:56 => 98.097391
> 2025/03/17 17:00:57 => 98.982151
> 2025/03/17 17:00:58 => 99.589187
> 2025/03/17 17:00:59 => 99.926821
> 2025/03/17 17:01:00 => 99.989878
> 2025/03/17 17:01:01 => 99.778216
> 2025/03/17 17:01:02 => 99.292485
> .......
> 
> 
> I want to narrow down whether the issue is in the basic_hist_script.py or the lower-level code. So there are a few steps of debugging to do.
> 
> 
> 
> 1) Run code directly in the python interpreter: 
> 
> Can you run the following and send the output please?
> 
> ```
> import midas.client
> c = midas.client.MidasClient("history_test")
> data = c.hist_get_recent_data(1,1,"test_slow/data","data")
> print(f"event_name='{data[0]['event_name']}', tag_name='{data[0]['tag_name']}', num_entries={data[0]['num_entries']}, status={data[0]['status']}, arrlen={len(data[0]['values'])}")
> ```
> 
> For me, I get:
> event_name='test_slow/data', tag_name='data', num_entries=441, status=1, arrlen=441
> 
> 
> 
> 2) If things look sensible for you (status=1, non-zero num_entries), then the problem is in the basic_hist_script.py. Can you add the same print() statement in basic_hist_script.py immediately after the call to hist_get_recent_data(), then run that script again and send the output of that?
> 
> 
> 
> 3) Debug the python/C conversions.
> 
> In midas/client.py add the following line to hist_get_data() immediately before the call to self.lib.c_hs_read():
> 
> ```
>         print(f"c_start_time={c_start_time.value}, c_end_time={c_end_time.value}, c_interval={c_interval.value}, c_event_name={c_event_name.value}, c_tag_name={c_tag_name.value}")
> ```
> 
> Then run the following and send the output:
> 
> ```
> import midas.client
> c = midas.client.MidasClient("history_test")
> data = c.hist_get_recent_data(1,1,"test_slow/data","data")
> ```
> 
> For me, I get:
> c_start_time=1742254428, c_end_time=1742258028, c_interval=1, c_event_name=b'test_slow/data', c_tag_name=b'data'
> 
> I want to check that the UNIX timestamps match what you expect for your server, and that nothing weird is going on with the python/C string conversions.
> 
> 
> Thanks,
> Ben

Hi, thank you for the support!

1)
event_name='test_slow/data', tag_name='data', num_entries=0, status=1, arrlen=0
2)
The number of entries is zero
3)
I get
c_start_time=1742275653, c_end_time=1742279253, c_interval=1, c_event_name=b'test_slow/data', c_tag_name=b'data'

> Unfortunately I again cannot reproduce this:
> 
> $ python ~/DAQ/midas_latest/python/examples/basic_hist_script.py
> Valid events are:
> * Run transitions
> * test_slow/data
> Enter event name: test_slow/data
> Valid tags for test_slow/data are:
> * data
> Enter tag name: data
> Event/tag test_slow/data/data has 1 elements
> How many hours: 1
> Interval in seconds: 1
> 78 entries found
> 2025/03/17 17:00:56 => 98.097391
> 2025/03/17 17:00:57 => 98.982151
> 2025/03/17 17:00:58 => 99.589187
> 2025/03/17 17:00:59 => 99.926821
> 2025/03/17 17:01:00 => 99.989878
> 2025/03/17 17:01:01 => 99.778216
> 2025/03/17 17:01:02 => 99.292485
> .......
> 
> 
> I want to narrow down whether the issue is in the basic_hist_script.py or the lower-level code. So there are a few steps of debugging to do.
> 
> 
> 
> 1) Run code directly in the python interpreter: 
> 
> Can you run the following and send the output please?
> 
> ```
> import midas.client
> c = midas.client.MidasClient("history_test")
> data = c.hist_get_recent_data(1,1,"test_slow/data","data")
> print(f"event_name='{data[0]['event_name']}', tag_name='{data[0]['tag_name']}', num_entries={data[0]['num_entries']}, status={data[0]['status']}, arrlen={len(data[0]['values'])}")
> ```
> 
> For me, I get:
> event_name='test_slow/data', tag_name='data', num_entries=441, status=1, arrlen=441
> 
> 
> 
> 2) If things look sensible for you (status=1, non-zero num_entries), then the problem is in the basic_hist_script.py. Can you add the same print() statement in basic_hist_script.py immediately after the call to hist_get_recent_data(), then run that script again and send the output of that?
> 
> 
> 
> 3) Debug the python/C conversions.
> 
> In midas/client.py add the following line to hist_get_data() immediately before the call to self.lib.c_hs_read():
> 
> ```
>         print(f"c_start_time={c_start_time.value}, c_end_time={c_end_time.value}, c_interval={c_interval.value}, c_event_name={c_event_name.value}, c_tag_name={c_tag_name.value}")
> ```
> 
> Then run the following and send the output:
> 
> ```
> import midas.client
> c = midas.client.MidasClient("history_test")
> data = c.hist_get_recent_data(1,1,"test_slow/data","data")
> ```
> 
> For me, I get:
> c_start_time=1742254428, c_end_time=1742258028, c_interval=1, c_event_name=b'test_slow/data', c_tag_name=b'data'
> 
> I want to check that the UNIX timestamps match what you expect for your server, and that nothing weird is going on with the python/C string conversions.
> 
> 
> Thanks,
> Ben

Hi, thank you for the support!

Running the commands on the Macbook pro leads to
1)
event_name='test_slow/data', tag_name='data', num_entries=0, status=1, arrlen=0
2)
The number of entries is zero
3)
I get
c_start_time=1742275653, c_end_time=1742279253, c_interval=1, c_event_name=b'test_slow/data', c_tag_name=b'data'

However right after running these commands I removed a .SHM_HOST.TXT file
(due to me working both at home and at PSI, my computer hostname changes when I switch the network, so I remove .SHM_HOST.TXT to be able to run experiments)

and reran the code, and it suddenly worked! This is good, but I do not know what fixed it... I had done more extensive tests yesterday and also had to delete .SHM_HOST.TXT multiple times, to no avail.
Do you have any ideas as to what could be happening? Similarly to my previous bug report, which was fixed by updating macOS to a more stable version, could this have been due to an automatic update?

If the problem still persists on the Windows machine I will post an update.

>
> However right after running these commands I removed a .SHM_HOST.TXT file
>

Instead of deleting .SHM_HOSTS.TXT, please create it as an empty file. I thought the documentation is clear about it?

Also we recommend installing MIDAS to $HOME/packages/midas. There is a number of problems if installed at top level.

If you want to be compliant with the Linux LFS, /opt/midas is also a good place.

> 
> ... and it suddenly worked!
>

We still did not establish if mhist, mhdump and the other commands I sent you work correctly,
to confirm MIDAS is creating correct history files. (before you try to read them with python).

Also we did not establish that you have correct paths setup in ODB /Logger/History.

Many things can go wrong.

Next time python history malfunctions, please do all those other things and report to us. Thanks!

K.O.

After starting midas (mhttpd &, and mlogger -D) and running the `fetest` frontend I went into the midas/python/examples directory and ran basic_hist_script.py, and, even though I could see the 'pytest' program in the Programs page,

Valid events are:
Enter event name:

was printed out, which signified that no events were found. No errors were displayed.

Instead, when trying to do the same in javascript (using mjsonrpc_send_request( mjsonrpc_make_request("hs_get_events")).then(console.log)), I was able to get the expected events.

The History page also displayed the expected data and the plots worked correctly.

Device info: Chip: Apple M1 Pro, OS: Sequoia (15.3)

MIDAS version: bitbucket commit 84c7ef7

Python version: 3.13.2