Directly after any proxy_pass line add
proxy_set_header X-Forwarded-Proto $scheme;
Typically X-Forwarded-Proto is used together with X-Forwarded-Host like this:
proxy_set_header X-Forwarded-Host $host; proxy_set_header X-Forwarded-Proto $scheme;
I prefer this method to the GUI docker method because:
--net=host and therefore doesn’t involve additional routing, bridging or forwarding of packets which might impact performanceLogin to the Synology NAS over SSH using a user with admin privileges, then sudo su.
For using iperf3 as a serve, use
docker run -it --rm --name=iperf3-server --net=host networkstatic/iperf3 -s
For using iperf3 as a client, use
docker run -it --rm --name=iperf3-client --net=host networkstatic/iperf3 -c 10.1.2.3
We tested iperf3 performance using our network based on the following devices:
Tailscale version was
1.24.1 tailscale commit: 1a9302b1edba91d0f638e775faeaa0ce2a6a25f8 other commit: 1331ed5836e1a0ab32b10e6ce8748e17ba2c7598 go version: go1.18.1-ts710a0d8610
The network is completely switched, not routed and we took care that tailscale actually used the switched connection using tailscale ping.
Desktop running iperf -s, VM running iperf -c 10.9.2.10:
Connecting to host 10.9.2.10, port 5201 [ 5] local 10.9.2.103 port 52944 connected to 10.9.2.10 port 5201 [ ID] Interval Transfer Bitrate Retr Cwnd [ 5] 0.00-1.00 sec 94.7 MBytes 794 Mbits/sec 338 109 KBytes [ 5] 1.00-2.00 sec 98.0 MBytes 822 Mbits/sec 353 148 KBytes [ 5] 2.00-3.00 sec 96.6 MBytes 811 Mbits/sec 382 117 KBytes [ 5] 3.00-4.00 sec 103 MBytes 862 Mbits/sec 334 116 KBytes [ 5] 4.00-5.00 sec 101 MBytes 851 Mbits/sec 483 102 KBytes [ 5] 5.00-6.00 sec 104 MBytes 874 Mbits/sec 503 126 KBytes [ 5] 6.00-7.00 sec 105 MBytes 883 Mbits/sec 527 119 KBytes [ 5] 7.00-8.00 sec 108 MBytes 906 Mbits/sec 451 105 KBytes [ 5] 8.00-9.00 sec 108 MBytes 903 Mbits/sec 442 117 KBytes [ 5] 9.00-10.00 sec 107 MBytes 900 Mbits/sec 461 123 KBytes - - - - - - - - - - - - - - - - - - - - - - - - - [ ID] Interval Transfer Bitrate Retr [ 5] 0.00-10.00 sec 1.00 GBytes 861 Mbits/sec 4274 sender [ 5] 0.00-10.00 sec 1.00 GBytes 860 Mbits/sec receiver iperf Done.
VM running iperf -s, Desktop running iperf -c 10.9.2.103
Connecting to host 10.9.2.103, port 5201 [ 5] local 10.9.2.10 port 42630 connected to 10.9.2.103 port 5201 [ ID] Interval Transfer Bitrate Retr Cwnd [ 5] 0.00-1.00 sec 88.5 MBytes 742 Mbits/sec 0 966 KBytes [ 5] 1.00-2.00 sec 90.0 MBytes 755 Mbits/sec 0 1.12 MBytes [ 5] 2.00-3.00 sec 87.5 MBytes 734 Mbits/sec 33 833 KBytes [ 5] 3.00-4.00 sec 90.0 MBytes 755 Mbits/sec 0 833 KBytes [ 5] 4.00-5.00 sec 88.8 MBytes 745 Mbits/sec 0 1.00 MBytes [ 5] 5.00-6.00 sec 88.8 MBytes 744 Mbits/sec 0 1.00 MBytes [ 5] 6.00-7.00 sec 87.5 MBytes 734 Mbits/sec 0 1.09 MBytes [ 5] 7.00-8.00 sec 90.0 MBytes 755 Mbits/sec 0 1.09 MBytes [ 5] 8.00-9.00 sec 90.0 MBytes 755 Mbits/sec 0 1.09 MBytes [ 5] 9.00-10.00 sec 90.0 MBytes 755 Mbits/sec 13 863 KBytes - - - - - - - - - - - - - - - - - - - - - - - - - [ ID] Interval Transfer Bitrate Retr [ 5] 0.00-10.00 sec 891 MBytes 747 Mbits/sec 46 sender [ 5] 0.00-10.00 sec 888 MBytes 745 Mbits/sec receiver iperf Done.
The direction where the VM hosts the iperf -s server i.e. sends the data shows a slight degradation of performance
iperf -s, VM running iperf -cConnecting to host 100.64.0.2, port 5201 [ 5] local 100.64.0.3 port 37466 connected to 100.64.0.2 port 5201 [ ID] Interval Transfer Bitrate Retr Cwnd [ 5] 0.00-1.00 sec 39.4 MBytes 330 Mbits/sec 62 149 KBytes [ 5] 1.00-2.00 sec 45.8 MBytes 385 Mbits/sec 44 150 KBytes [ 5] 2.00-3.00 sec 38.9 MBytes 326 Mbits/sec 97 122 KBytes [ 5] 3.00-4.00 sec 47.9 MBytes 401 Mbits/sec 7 242 KBytes [ 5] 4.00-5.00 sec 39.5 MBytes 332 Mbits/sec 118 110 KBytes [ 5] 5.00-6.00 sec 46.6 MBytes 391 Mbits/sec 32 136 KBytes [ 5] 6.00-7.00 sec 41.8 MBytes 351 Mbits/sec 42 159 KBytes [ 5] 7.00-8.00 sec 44.3 MBytes 372 Mbits/sec 91 104 KBytes [ 5] 8.00-9.00 sec 36.1 MBytes 303 Mbits/sec 72 133 KBytes [ 5] 9.00-10.00 sec 41.5 MBytes 348 Mbits/sec 39 139 KBytes - - - - - - - - - - - - - - - - - - - - - - - - - [ ID] Interval Transfer Bitrate Retr [ 5] 0.00-10.00 sec 422 MBytes 354 Mbits/sec 604 sender [ 5] 0.00-10.00 sec 421 MBytes 353 Mbits/sec receiver iperf Done.
iperf -s, Desktop running iperf -cConnecting to host 100.64.0.3, port 5201 [ 5] local 100.64.0.2 port 36744 connected to 100.64.0.3 port 5201 [ ID] Interval Transfer Bitrate Retr Cwnd [ 5] 0.00-1.00 sec 23.7 MBytes 199 Mbits/sec 104 89.9 KBytes [ 5] 1.00-2.00 sec 23.6 MBytes 198 Mbits/sec 80 49.2 KBytes [ 5] 2.00-3.00 sec 21.1 MBytes 177 Mbits/sec 59 54.0 KBytes [ 5] 3.00-4.00 sec 23.6 MBytes 198 Mbits/sec 68 69.6 KBytes [ 5] 4.00-5.00 sec 19.1 MBytes 160 Mbits/sec 77 48.0 KBytes [ 5] 5.00-6.00 sec 25.3 MBytes 212 Mbits/sec 76 62.4 KBytes [ 5] 6.00-7.00 sec 21.4 MBytes 179 Mbits/sec 50 107 KBytes [ 5] 7.00-8.00 sec 25.6 MBytes 215 Mbits/sec 35 124 KBytes [ 5] 8.00-9.00 sec 22.5 MBytes 188 Mbits/sec 71 48.0 KBytes [ 5] 9.00-10.00 sec 25.0 MBytes 209 Mbits/sec 42 64.8 KBytes - - - - - - - - - - - - - - - - - - - - - - - - - [ ID] Interval Transfer Bitrate Retr [ 5] 0.00-10.00 sec 231 MBytes 194 Mbits/sec 662 sender [ 5] 0.00-10.01 sec 230 MBytes 193 Mbits/sec receiver
UDP tests were mostly similar to TCP tests (albeit slightly higher throughput at up to 400 Mbit/s), including the sensitivity to the direction of the connection.
Tailscale has significant impact on network speeds and will not regularly be able to achieve near-Gigabit iperf3 speeds given typical setup with Desktop that are a couple of years old, and virtual machines. However, achieving a throughput of 200-400 Mbit/s is more than enough for most applications.
Interestingly, the speed is highly dependent on the direction of transfer between a less powerful VM and a more powerful Desktop, with a factor of x1.5 … x2 between the two directions. This might be attributed to the amount of computation required to encrypt or decrypt the data.
I recommend using invoke instead of the built-in subprocess to handle executing any shell command in Python.
Not only does invoke‘s run() it provide a more user friendly syntax compared to e.g. subprocess.check_output():
run('make')but it also tends to act more like you’d expect especially regarding the output of the command and has easy-to-use parameters such as hide=True to hide the output of shell commands.
Furthermore, it provides a buch of really useful features such as automatically responding to prompts from the shell command.
If you want to connect an USB device such as a 3D printer mainboard to your Raspberry Pi 4 using the USB-C connector as opposed to the larger USB-A connector, you need to first configure the Raspberry Pi kernel to use host mode for the USB-C connector.
sudo modprobe -r dwc2 && sudo dtoverlay dwc2 dr_mode=host && sudo modprobe dwc2
This method has the advantage of not requiring a reboot.
Edit /boot/config.txt and add
dtoverlay=dwc2,dr_mode=host
at the end of the file (in the [all] section). Then
reboot
To enable the WireGuard peer called MyPeer:
/interface/wireguard/peers/enable [find comment="MyPeer"]
To disable the WireGuard peer called MyPeer:
/interface/wireguard/peers/disable [find comment="MyPeer"]
Use this command to test if a given MongoDB database exists:
mongo --quiet --eval 'db.getMongo().getDBNames().indexOf("mydb")'This will return an index such as 0 or 241 if the database is found. On the other hand, it will return -1 if the database does not exist.
docker-compose version:
docker-compose exec mongodb mongo --quiet --eval 'db.getMongo().getDBNames().indexOf("mydb")'where mongodb is the name of your container.
Now we can put it together in a bash script to test if the database exists:
# Query if DB exists in MongoDB
mongo_indexof_db=$(mongo --quiet --eval 'db.getMongo().getDBNames().indexOf("mydb")')
if [ $mongo_indexof_db -ne "-1" ]; then
echo "MongoDB database exists"
else
echo "MongoDB database does not exist"
fi
docker-compose variant:
# Query if DB exists in MongoDB
mongo_indexof_db=$(docker-compose -f inspect.yml exec -T mongodb mongo --quiet --eval 'db.getMongo().getDBNames().indexOf("mydb")')
if [ $mongo_indexof_db -ne "-1" ]; then
echo "MongoDB database exists"
else
echo "MongoDB database does not exist"
fi
When trying to install pyarrow such as using
pip install pyarrow
you see an error log like
-- Found Python3Alt: /home/uli/.pypy3-virtualenv/bin/pypy3
CMake Warning (dev) at /usr/share/cmake-3.18/Modules/FindPackageHandleStandardArgs.cmake:273 (message):
The package name passed to `find_package_handle_standard_args` (PkgConfig)
does not match the name of the calling package (Arrow). This can lead to
problems in calling code that expects `find_package` result variables
(e.g., `_FOUND`) to follow a certain pattern.
Call Stack (most recent call first):
/usr/share/cmake-3.18/Modules/FindPkgConfig.cmake:59 (find_package_handle_standard_args)
cmake_modules/FindArrow.cmake:39 (include)
cmake_modules/FindArrowPython.cmake:46 (find_package)
CMakeLists.txt:229 (find_package)
This warning is for project developers. Use -Wno-dev to suppress it.
-- Found PkgConfig: /usr/bin/pkg-config (found version "0.29.2")
-- Could NOT find Arrow (missing: Arrow_DIR)
-- Checking for module 'arrow'
-- No package 'arrow' found
CMake Error at /usr/share/cmake-3.18/Modules/FindPackageHandleStandardArgs.cmake:165 (message):
Could NOT find Arrow (missing: ARROW_INCLUDE_DIR ARROW_LIB_DIR
ARROW_FULL_SO_VERSION ARROW_SO_VERSION)
Call Stack (most recent call first):
/usr/share/cmake-3.18/Modules/FindPackageHandleStandardArgs.cmake:458 (_FPHSA_FAILURE_MESSAGE)
cmake_modules/FindArrow.cmake:450 (find_package_handle_standard_args)
cmake_modules/FindArrowPython.cmake:46 (find_package)
CMakeLists.txt:229 (find_package)
-- Configuring incomplete, errors occurred!
See also "/tmp/pip-install-409dctif/pyarrow_b70cde6894c3469483f7360493fc2e65/build/temp.linux-x86_64-pypy39/CMakeFiles/CMakeOutput.log".
error: command '/usr/bin/cmake' failed with exit code 1
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for pyarrow
Failed to build pyarrow
ERROR: Could not build wheels for pyarrow, which is required to install pyproject.toml-based projects
You need to install the arrow library in order to be able to compile pyarrow from source. On Ubuntu, this can be done using
sudo apt install -y -V ca-certificates lsb-release wget wget https://apache.jfrog.io/artifactory/arrow/$(lsb_release --id --short | tr 'A-Z' 'a-z')/apache-arrow-apt-source-latest-$(lsb_release --codename --short).deb -O /tmp/apache-arrow.deb sudo apt -y install /tmp/apache-arrow.deb sudo apt -y update sudo apt -y install libarrow-dev libarrow-python-dev
When trying to install pillow such as using
pip install Pillow
you see an error log like
running build_ext
The headers or library files could not be found for jpeg,
a required dependency when compiling Pillow from source.
Please see the install instructions at:
https://pillow.readthedocs.io/en/latest/installation.html
Traceback (most recent call last):
File "/tmp/pip-install-_g5fa7ox/pillow_7cb18c0d6bec468e8844184b98c8bf45/setup.py", line 989, in <module>
setup(
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/__init__.py", line 87, in setup
return distutils.core.setup(**attrs)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/core.py", line 148, in setup
return run_commands(dist)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/core.py", line 163, in run_commands
dist.run_commands()
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/dist.py", line 967, in run_commands
self.run_command(cmd)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/dist.py", line 1214, in run_command
super().run_command(command)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/dist.py", line 986, in run_command
cmd_obj.run()
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/command/install.py", line 68, in run
return orig.install.run(self)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/command/install.py", line 670, in run
self.run_command('build')
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/dist.py", line 1214, in run_command
super().run_command(command)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/dist.py", line 986, in run_command
cmd_obj.run()
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/command/build.py", line 136, in run
self.run_command(cmd_name)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/dist.py", line 1214, in run_command
super().run_command(command)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/dist.py", line 986, in run_command
cmd_obj.run()
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/command/build_ext.py", line 79, in run
_build_ext.run(self)
File "/home/uli/.pypy3-virtualenv/lib/pypy3.9/site-packages/setuptools/_distutils/command/build_ext.py", line 339, in run
self.build_extensions()
File "/tmp/pip-install-_g5fa7ox/pillow_7cb18c0d6bec468e8844184b98c8bf45/setup.py", line 804, in build_extensions
raise RequiredDependencyException(f)
RequiredDependencyException: jpeg
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<string>", line 2, in <module>
File "<pip-setuptools-caller>", line 34, in <module>
File "/tmp/pip-install-_g5fa7ox/pillow_7cb18c0d6bec468e8844184b98c8bf45/setup.py", line 1009, in <module>
raise RequiredDependencyException(msg)
RequiredDependencyException:
The headers or library files could not be found for jpeg,
a required dependency when compiling Pillow from source.
Please see the install instructions at:
https://pillow.readthedocs.io/en/latest/installation.html
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: legacy-install-failure
× Encountered error while trying to install package.
╰─> PillowPillow needs a buch of libraries to be installed in order to work properly. Use the following command from the official Pillow website on Ubuntu:
sudo apt-get install cmake libtiff5-dev libjpeg8-dev libopenjp2-7-dev zlib1g-dev libfreetype6-dev liblcms2-dev libwebp-dev tcl8.6-dev tk8.6-dev python3-tk libharfbuzz-dev libfribidi-dev libxcb1-dev
or check out the installation guide for commands for other operating systems.
In order to install tailscale, on Fedora CoreOS (this post has been tested on Fedora CoreOS 35), you can use this sequence of commands:
sudo curl -o /etc/yum.repos.d/tailscale.repo https://pkgs.tailscale.com/stable/fedora/tailscale.repo sudo rpm-ostree install tailscale
Now reboot using
sudo systemctl reboot
Once rebooted, you can enable the service using
sudo systemctl enable --now tailscaled
and then configure tailscale as usual:
sudo tailscale up --login-server .... --authkey ...
Also see our post on How to connect tailscale to headscale server on Linux
When trying to export data as JSON that has originally been queried from MongoDB using code like
with open("alle.json", "w") as outfile:
json.dump(alle, outfile)you see the following error message:
File /usr/lib/python3.9/json/__init__.py:179, in dump(obj, fp, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
173 iterable = cls(skipkeys=skipkeys, ensure_ascii=ensure_ascii,
174 check_circular=check_circular, allow_nan=allow_nan, indent=indent,
175 separators=separators,
176 default=default, sort_keys=sort_keys, **kw).iterencode(obj)
177 # could accelerate with writelines in some versions of Python, at
178 # a debuggability cost
--> 179 for chunk in iterable:
180 fp.write(chunk)
File /usr/lib/python3.9/json/encoder.py:429, in _make_iterencode.<locals>._iterencode(o, _current_indent_level)
427 yield _floatstr(o)
428 elif isinstance(o, (list, tuple)):
--> 429 yield from _iterencode_list(o, _current_indent_level)
430 elif isinstance(o, dict):
431 yield from _iterencode_dict(o, _current_indent_level)
File /usr/lib/python3.9/json/encoder.py:325, in _make_iterencode.<locals>._iterencode_list(lst, _current_indent_level)
323 else:
324 chunks = _iterencode(value, _current_indent_level)
--> 325 yield from chunks
326 if newline_indent is not None:
327 _current_indent_level -= 1
File /usr/lib/python3.9/json/encoder.py:405, in _make_iterencode.<locals>._iterencode_dict(dct, _current_indent_level)
403 else:
404 chunks = _iterencode(value, _current_indent_level)
--> 405 yield from chunks
406 if newline_indent is not None:
407 _current_indent_level -= 1
File /usr/lib/python3.9/json/encoder.py:438, in _make_iterencode.<locals>._iterencode(o, _current_indent_level)
436 raise ValueError("Circular reference detected")
437 markers[markerid] = o
--> 438 o = _default(o)
439 yield from _iterencode(o, _current_indent_level)
440 if markers is not None:
File /usr/lib/python3.9/json/encoder.py:179, in JSONEncoder.default(self, o)
160 def default(self, o):
161 """Implement this method in a subclass such that it returns
162 a serializable object for ``o``, or calls the base implementation
163 (to raise a ``TypeError``).
(...)
177
178 """
--> 179 raise TypeError(f'Object of type {o.__class__.__name__} '
180 f'is not JSON serializable')
TypeError: Object of type ObjectId is not JSON serializableThis error occurs because objects queried from PyMongo always contain _id which is of type ObjectId and the normal JSON library (or drop-in replacements like simplejson do not know how to create JSON representations of Objects of type ObjectId).
In order to fix this, use pymongo‘s json_util instead of json. Note that the bson.json_util package contains dumps but does not contain dump, so use the following snippet to write to a file:
import bson.json_util as json_util
with open("alle.json", "w") as outfile:
outfile.write(json_util.dumps(alle))
While trying to install RcppGSL using
BiocManager::install("RcppGSL")
you see the following error message:
checking for gcc option to accept ISO C89... none needed
checking for gsl-config... no
configure: error: gsl-config not found, is GSL installed?
ERROR: configuration failed for package ‘RcppGSL’
* removing ‘/usr/local/lib/R/site-library/RcppGSL’
The downloaded source packages are in
‘/tmp/RtmpqSzFab/downloaded_packages’
Warning message:
In .inet_warning(msg) :
installation of package ‘RcppGSL’ had non-zero exit status
You need to install the libgsl2 development headers which include the gsl-config executable.
On Ubuntu, you can install it using
sudo apt -y install libgsl2-dev
This short example shows how to iterate all databases or list all database names for a MongoDB in Python using pymongo:
from pymongo import MongoClient
client = MongoClient("mongodb://localhost")
for database in client.list_databases():
print(database['name'])s
This will start Jupyter listening on all network interfaces / bind to all IP addresses in order to make direct browser access possible not only from localhost but any remote host that has network access to the host where you’re running Jupyter:
jupyter lab --ip=0.0.0.0
You can remove all the files / objects in a Google Cloud Storage bucket using gsutil like this:
gsutil -m rm -r gs://my-bucket/\*
This will delete all the data in the bucket and there is usually no way to recover the data!
export GCSFUSE_REPO=gcsfuse-`lsb_release -c -s` echo "deb http://packages.cloud.google.com/apt $GCSFUSE_REPO main" | sudo tee /etc/apt/sources.list.d/gcsfuse.list curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add - sudo apt-get update sudo apt-get install gcsfuse
If that doesn’t work (such as for Ubuntu 21.10 impish at the time of writing this post), use the following method:
curl -L -O https://github.com/GoogleCloudPlatform/gcsfuse/releases/download/v0.39.2/gcsfuse_0.39.2_amd64.deb sudo dpkg --install gcsfuse_0.39.2_amd64.deb rm gcsfuse_0.39.2_amd64.deb
This is a summary from the official docs.
While running a command like
gsutil rsync my-folder gs://my-bucket
you see an error message like
Building synchronization state... Caught non-retryable exception while listing gs://mfwh-backups/: ServiceException: 401 Anonymous caller does not have storage.objects.list access to the Google Cloud Storage bucket. CommandException: Caught non-retryable exception - aborting rsync
This error is basically telling you that you are not logged in !
First, create a service account for the project on Google cloud: Direct link to service account page. You need to figure out depending on your setup what roles you want to assign to the service account. If you are lost and don’t know what to select, just assign it admin rights on the storage, but be aware that this might have security implications, as this account may also delete or create storage buckets etc.
Then open the page for that service account and create a new key!
This will give you a JSON file such as my-project-4d267a915c4e.json. Save it on the server or computer where you want to run gsutil. I recommend to save it in ~ (the user’s home folder) with the original filename, for example ~/my-project-4d267a915c4e.json.
Then you need to activate that service account using
gcloud auth activate-service-account --key-file [path to JSON file]
such as
gcloud auth activate-service-account --key-file [path to JSON file]
sudo snap install google-cloud-cli --classic
This is the summary from the official docs. I recommend to install it as snap package as opposed to a deb package since it will auto-update, it’s much easier to use and just works better out of the box in my experience.
This is useful for cleaning up sensitive data even if you don’t know the specific filename:
git log --pretty=format: --name-only --diff-filter=A | sort -u
Original source: Dustin on StackOverflow
I analyzed a couple of different .gitignore files for LaTeX floating around the internet.
Clearly, the best one is TeX.gitignore by Brian Douglas which you can check out here on Github.