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Simulate delayed and dropped packets on Linux
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There is a high-level interface written in Python: github.com/thombashi/tcconfig It simplifies the usage of tc. It can also show the currently active filters in JSON style.
– John
Apr 17 '19 at 18:21
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Pandas timeseries plot setting x-axis major and minor ticks and labels
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Way to read first few lines for pandas dataframe
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Check if two unordered lists are equal [duplicate]
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Python has a built-in datatype for an unordered collection of (hashable) things, called a set. If you convert both lists to sets, the comparison will be unordered.
set(x) == set(y)
Documentation on set
EDIT: @mdwhatcott...
Detecting superfluous #includes in C/C++?
...use it ? The README isn't very clear about what contains the output of the python script.
– King's jester
Aug 10 '17 at 8:45
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Django rest framework nested self-referential objects
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I wrote a recursive field for DRF3.0 and packaged it for pip
https://pypi.python.org/pypi/djangorestframework-recursive/
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How can I find out the total physical memory (RAM) of my linux box suitable to be parsed by a shell
...is a much more universal pattern matching language (i.e. you can use it in Python or Perl as well). If you learn awk, all you've already is awk. If you lean grep + PCRE on the other hand... grep -oP '^MemTotal:\s+\K.*' /proc/meminfo
– Gabriel Totusek
Aug 10 '1...
What is RPC framework and Apache Thrift?
...tocol over HTTP. This service may be called by a client program written in Python, running on a Windows machine. The code for both server and client is generated from a Thrift IDL file. To get it running, you basically have to add only the intended program logic and put all the pieces together.
The...
Read specific columns from a csv file with csv module?
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Context: For this type of work you should use the amazing python petl library. That will save you a lot of work and potential frustration from doing things 'manually' with the standard csv module. AFAIK, the only people who still use the csv module are those who have not yet discove...
How to remove all rows in a numpy.ndarray that contain non-numeric values
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