I wrote some script which renders scenes and want see output on console I am using print but it not works what I should use to print something.
I run script with:
blender -b -P render.py
Want output such string from render.py:
print '#' * 80
It is little trivial question but print not works and not know how to progress development without debug messages.
use the logging module to setup your custom logger.
you can setup a Console handler to log the content to the console or/and
formatter = logging.Formatter('%(message)s')
console_handler = logging.StreamHandler(sys.stdout)
console_handler.setFormatter(formatter)
setup a File handler if you want to log to a file:
file_handler = logging.FileHandler(log_file)
file_handler.setFormatter(formatter)
# Add the handler to the logger:
logger.addHandler(console_handler)
logger.addHandler(file_handler)
They can both have different log levels which you can set via script or environement variable:
log_level = level
if 'LOG_LEVEL' in os.environ:
log_level = os.environ['LOG_LEVEL']
console_handler.setLevel(log_level)
file_handler.setLevel('INFO')
Read trough:
https://docs.python.org/3/howto/logging.html
Related
Snakemake allows creation of a log for each rule with log parameter that specifies the name of the log file. It is relatively straightforward to pipe results from shell output to this log, but I am not able to figure out a way of logging output of run output (i.e. python script).
One workaround is to save the python code in a script and then run it from the shell, but I wonder if there is another way?
I have some rules that use both the log and run directives. In the run directive, I "manually" open and write the log file.
For instance:
rule compute_RPM:
input:
counts_table = source_small_RNA_counts,
summary_table = rules.gather_read_counts_summaries.output.summary_table,
tags_table = rules.associate_small_type.output.tags_table,
output:
RPM_table = OPJ(
annot_counts_dir,
"all_{mapped_type}_on_%s" % genome, "{small_type}_RPM.txt"),
log:
log = OPJ(log_dir, "compute_RPM_{mapped_type}", "{small_type}.log"),
benchmark:
OPJ(log_dir, "compute_RPM_{mapped_type}", "{small_type}_benchmark.txt"),
run:
with open(log.log, "w") as logfile:
logfile.write(f"Reading column counts from {input.counts_table}\n")
counts_data = pd.read_table(
input.counts_table,
index_col="gene")
logfile.write(f"Reading number of non-structural mappers from {input.summary_table}\n")
norm = pd.read_table(input.summary_table, index_col=0).loc["non_structural"]
logfile.write(str(norm))
logfile.write("Computing counts per million non-structural mappers\n")
RPM = 1000000 * counts_data / norm
add_tags_column(RPM, input.tags_table, "small_type").to_csv(output.RPM_table, sep="\t")
For third-party code that writes to stdout, maybe the redirect_stdout context manager could be helpful (found in https://stackoverflow.com/a/40417352/1878788, documented at
https://docs.python.org/3/library/contextlib.html#contextlib.redirect_stdout).
Test snakefile, test_run_log.snakefile:
from contextlib import redirect_stdout
rule all:
input:
"test_run_log.txt"
rule test_run_log:
output:
"test_run_log.txt"
log:
"test_run_log.log"
run:
with open(log[0], "w") as log_file:
with redirect_stdout(log_file):
print(f"Writing result to {output[0]}")
with open(output[0], "w") as out_file:
out_file.write("result\n")
Running it:
$ snakemake -s test_run_log.snakefile
Results:
$ cat test_run_log.log
Writing result to test_run_log.txt
$ cat test_run_log.txt
result
My solution was the following. This is usefull both for normal log and logging exceptions with traceback. You can then wrap logger setup in a function to make it more organized. It's not very pretty though. Would be much nicer if snakemake could do it by itself.
import logging
# some stuff
rule logging_test:
input: 'input.json'
output: 'output.json'
log: 'rules_logs/logging_test.log'
run:
logger = logging.getLogger('logging_test')
fh = logging.FileHandler(str(log))
fh.setLevel(logging.INFO)
formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
fh.setFormatter(formatter)
logger.addHandler(fh)
try:
logger.info('Starting operation!')
# do something
with open(str(output), 'w') as f:
f.write('success!')
logger.info('Ended!')
except Exception as e:
logger.error(e, exc_info=True)
I'm playing with slim.learning.train and want to display the log in the console. According to the source code this is done using tf_logging module :
if 'should_log' in train_step_kwargs:
if sess.run(train_step_kwargs['should_log']):
logging.info('global step %d: loss = %.4f (%.2f sec)',
np_global_step, total_loss, time_elapsed)
I can run my training loop but there's no logs in the console. How can I enable it ?
tf.logging.info() goes to stderr, not stdout, as mentioned here:
https://groups.google.com/a/tensorflow.org/forum/#!msg/discuss/SO_JRts-VIs/JG1x8vOLDAAJ
and i can verify this from my personal experience, having spent several hours twiddling versions of subprocess.Popen()'s parameters, and not capturing the logging. a simple change to stderr=PIPE worked, as in my specific example, which you should be able to generalize to your problem.
training_results = Popen(cmds,shell=False,stderr=PIPE,bufsize=1,executable="python")
for line in iter(training_results.stderr.readline, b''):
print line
if line.startswith("INFO:tensorflow:Final test accuracy"):
tf_final_acc = line
training_results.wait() # wait for the subprocess to exit
I have read about phantomjs and rasterizejs as well. But my link is this:
http://localhost:5601/#/dashboard/External?_g=(time:(from:'2014-12-31T16:00:00.000Z',mode:absolute,to:'2015-01-01T16:00:00.000Z'))&_a=(filters:!(),panels:!((col:10,id:'Count-of-Source-IPs-(External)',row:1,size_x:3,size_y:3,type:visualization),(col:4,id:'Protocols-(External)',row:4,size_x:3,size_y:2,type:visualization),(col:7,id:'Top-5-Source-IPs-with-Protocols-and-Source-Port-(External)',row:4,size_x:6,size_y:6,type:visualization),(col:1,id:'Top-5-Source-IPs-(External)',row:4,size_x:3,size_y:2,type:visualization),(col:1,id:'Top-5-Countries-with-Protocols-(External)',row:1,size_x:6,size_y:3,type:visualization),(col:1,id:'Geographical-of-External-(Source)',row:6,size_x:6,size_y:4,type:visualization),(col:7,id:'Action-(External)',row:1,size_x:3,size_y:3,type:visualization)),query:(query_string:(analyze_wildcard:!t,query:'*')),title:External)
How do I make it such that it works with this command:
phantom.js rasterize.js "http://localhost:5601/#/dashboard/External?_g=(time:(from:'2014-12-31T16:00:00.000Z',mode:absolute,to:'2015-01-01T16:00:00.000Z'))&_a=(filters:!(),panels:!((col:10,id:'Count-of-Source-IPs-(External)',row:1,size_x:3,size_y:3,type:visualization),(col:4,id:'Protocols-(External)',row:4,size_x:3,size_y:2,type:visualization),(col:7,id:'Top-5-Source-IPs-with-Protocols-and-Source-Port-(External)',row:4,size_x:6,size_y:6,type:visualization),(col:1,id:'Top-5-Source-IPs-(External)',row:4,size_x:3,size_y:2,type:visualization),(col:1,id:'Top-5-Countries-with-Protocols-(External)',row:1,size_x:6,size_y:3,type:visualization),(col:1,id:'Geographical-of-External-(Source)',row:6,size_x:6,size_y:4,type:visualization),(col:7,id:'Action-(External)',row:1,size_x:3,size_y:3,type:visualization)),query:(query_string:(analyze_wildcard:!t,query:'*')),title:External)" external.pdf
I have been getting syntax error because of that.
The problem is probably that the command is too long for your terminal and some of it is cut off.
You can either directly put it into the script or read it from stdin. For that you need to edit rasterize.js.
First you need to reduce the x in all system.args[x] where x is above 1 by 1. If you've done that, then you can call the script as
phantom.js rasterize.js external.pdf
or
cat file.url | phantom.js rasterize.js external.pdf
in the second case.
Put URL into script
Change
address = system.args[1];
to
address = "http://localhost....";
Read from pipe
You can put your long URL into some file and pass that file to stdin of the PhantomJS script.
Change
address = system.args[1];
to
address = system.stdin.read();
I need to be able to read in a path file from my simple_switch.py application.I have added the following code to my simple_switch.py in python.
LOG = logging.getLogger(__name__)
CONF = cfg.CONF
CONF.register_cli_opts([
cfg.StrOpt('path-file', default='test.txt',
help='path-file')
])
I attempt to start the application as follows.
bin/ryu-manager --observe-links --path-file test.txt ryu/app/simple_switch.py
However I get the following error.
usage: ryu-manager [-h] [--app-lists APP_LISTS] [--ca-certs CA_CERTS]
[--config-dir DIR] [--config-file PATH]
[--ctl-cert CTL_CERT] [--ctl-privkey CTL_PRIVKEY]
[--default-log-level DEFAULT_LOG_LEVEL] [--explicit-drop]
[--install-lldp-flow] [--log-config-file LOG_CONFIG_FILE]
[--log-dir LOG_DIR] [--log-file LOG_FILE]
[--log-file-mode LOG_FILE_MODE]
[--neutron-admin-auth-url NEUTRON_ADMIN_AUTH_URL]
[--neutron-admin-password NEUTRON_ADMIN_PASSWORD]
[--neutron-admin-tenant-name NEUTRON_ADMIN_TENANT_NAME]
[--neutron-admin-username NEUTRON_ADMIN_USERNAME]
[--neutron-auth-strategy NEUTRON_AUTH_STRATEGY]
[--neutron-controller-addr NEUTRON_CONTROLLER_ADDR]
[--neutron-url NEUTRON_URL]
[--neutron-url-timeout NEUTRON_URL_TIMEOUT]
[--noexplicit-drop] [--noinstall-lldp-flow]
[--noobserve-links] [--nouse-stderr] [--nouse-syslog]
[--noverbose] [--observe-links]
[--ofp-listen-host OFP_LISTEN_HOST]
[--ofp-ssl-listen-port OFP_SSL_LISTEN_PORT]
[--ofp-tcp-listen-port OFP_TCP_LISTEN_PORT] [--use-stderr]
[--use-syslog] [--verbose] [--version]
[--wsapi-host WSAPI_HOST] [--wsapi-port WSAPI_PORT]
[--test-switch-dir TEST-SWITCH_DIR]
[--test-switch-target TEST-SWITCH_TARGET]
[--test-switch-tester TEST-SWITCH_TESTER]
[app [app ...]]
ryu-manager: error: unrecognized arguments: --path-file
It does look like I need to register a new command line option somewhere before I can use it.Can some-one point out to me how to do that? Also can someone explain how to access the file(text.txt) inside the program?
You're on the right track, however the CONF entry that you are creating actually needs to be loaded before your app is loaded, otherwise ryu-manager has no way of knowing it exists!
The file you are looking for is flags.py, under the ryu directory of the source tree (or under the root installation directory).
This is how the ryu/tests/switch/tester.py Ryu app defines it's own arguments, so you might use that as your reference:
CONF.register_cli_opts([
# tests/switch/tester
cfg.StrOpt('target', default='0000000000000001', help='target sw dp-id'),
cfg.StrOpt('tester', default='0000000000000002', help='tester sw dp-id'),
cfg.StrOpt('dir', default='ryu/tests/switch/of13',
help='test files directory')
], group='test-switch')
Following this format, the CONF.register_cli_opts takes an array of config types exactly as you have done it (see ryu/cfg.py for the different types available).
You'll notice that when you run the ryu-manager help, i.e.
ryu-manager --help
the list that comes up is sorted by application (e.g. the group of arguments under 'test-switch options'). For that reason, you will want to specify a group name for your set of commands.
Now let us say that you used the group name 'my-app' and have an argument named 'path-file' in that group, the command line argument will be --my-app-path-file (this can get a little long), while you can access it in your application like this:
from ryu import cfg
CONF = cfg.CONF
path_file = CONF['my-app']['path_file']
Note the use of dash versus the use of underscores.
Cheers!
I recently started using MonkeyRunner to test the UI of my Android application (I am also using Espresso but wanted to play around with MonkeyRunner). The problem that I am having is that I am unable to enter text into EditText fields using the automation script.
The script navigates through my app perfectly but it doesn't seem to actually enter any text on call of the MonkeyRunner.type() command.
Please find my script below.
from com.android.monkeyrunner import MonkeyRunner, MonkeyDevice
from com.android.monkeyrunner.easy import EasyMonkeyDevice, By
import commands
import sys
import os
# starting the application and test
print "Starting the monkeyrunner script"
# connection to the current device, and return a MonkeyDevice object
device = MonkeyRunner.waitForConnection()
easy_device = EasyMonkeyDevice(device)
apk_path = device.shell('pm path com.mysample
if apk_path.startswith('package:'):
print "application installed."
else:
print "not installed, install APK"
device.installPackage('/MySample/MySample.apk')')
package ="com.mysample"
activity = ".SampleActivity"
print "Package: " + package + "Activity: " + activity
print "starting application...."
device.startActivity(component=package + '/' + activity)
print "...component started"
device.touch(205,361, "DOWN_AND_UP")
device.type("This is sample text")
MonkeyRunner.sleep(1)
result = device.takeSnapshot()
result.writeToFile("images/testimage.png",'png')
As you can see from the script above the text This is sample text should be placed in the EditText box. Both the emulator and screenshot that is taken show no text in the text field.
Am I missing a step or just doing something incorrectly?
Any help would be greatly appreciated!
I would rather use AndroidViewClient/culebra to simplify the task.
Basically, you can connect your device with adb and then run
culebra -VC -d on -t on -o myscript.py
The script obtains references to all of the visible Views. Edit the script and add at the end
no_id10.type('This is sample text')
no_id10.writeImageToFile('/tmp/image.png')
No need to worry about View coordinates, no need to touch and type, no need to add sleeps, etc.
NOTE: this is using no_id10 as an example, the id for your EditText could be different
First of all, I would not use the MonkeyRunner.sleep command, but I would rather use the time package and the time.sleep command. Just import the package
import time
and you should be good to go.
Moreover, I suggest you should wait some time between device.touch and device.type. Try with
device.touch(205,361, "DOWN_AND_UP")
time.sleep(1)
device.type("This is sample text")