pyjulia | python interface to julia | Dataset library
kandi X-RAY | pyjulia Summary
kandi X-RAY | pyjulia Summary
[DOI] Experimenting with developing a better interface to [Julia language] that works with [Python] 2 & 3 and Julia v1.0+.
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Top functions reviewed by kandi - BETA
- Initialize the Library .
- Initialize the library .
- Install java .
- Setup libjulia
- Loads the java module .
- Generate a list of paths to shared library paths .
- Add an argument .
- Find a jul - py executable .
- Parse command line arguments .
- Parse Python arguments .
pyjulia Key Features
pyjulia Examples and Code Snippets
Lines of Code : 2License : Strong Copyleft (CC BY-SA 4.0)
Copyfoo(itr) = maximum(x for x in itr if !isnan(x))
pd.pivot_table(df, index=['Name', 'Owner'], columns=['Role'],
values=['Can Edit','Can Read','Can Delete','Can download'],
aggfunc=np.sum)
pd.pivot_table(df, index=['Name', 'Owner'], cojl.eval("Float64(::Num) = NaN")
>>> jl.eval("@variables x y")
[nan, nan]
>>> jl.eval("@show simplify((x+y)^2 - (x-y)^2; expand=true)")
simplify((x + y) ^ 2 - (x - y) ^ 2; expand = true) = 4x*y
nanjulia> X = [1.1,2.2,3.3]
3-element Vector{Float64}:
1.1
2.2
3.3
julia> Y = [1.1,2.2,3.3]
3-element Vector{Float64}:
1.1
2.2
3.3
julia> X = reshape(X,3,1) # reshape to a single column **matrix**
3×1 Matrix{Float64}:
1.1
2var_python = 10
%%julia
py"var_python"
var_julia = 20
new_var = %julia var_julia
print(new_var)
Cp(ϕ) = 2 * (A + B sin ϕ - C cos ϕ)^2
# t is parameter in WS
-B ± sqrt(B^2 - (A^2 - C^2))
t₁ and t₂ = ----------------------------
A + C
ϕ₁ = 2atan(t₁)
ϕ₂ = 2atan(t₂)
x = [0,1,2]
y = [3,4,5]
function f()
z = vcat(x, y)
a = z*2
b = z*3
return a, b # here it is not needed, but typically in such cases it is dropped to return a tuple
end
function g()
n, m = f() # here it is needed
correct_values = torch.isclose(prediction, target, atol=tolerance, rtol=0).sum()
data = {"student": ["Anayo","Brandon","Claudia","Dave","Evelyn","Finn","Gloria","Hank","Isla", "Julia" ],
"test_one": [84, 90, 50, 29, 49, 44, 30, 98, 31, 66],
"test_two": [68, 78, 28, 80, 45, 56, 53, 93, 31, 66],
"pd.concat([df1, df1.assign(Project="Admin")],
ignore_index=True).sort_values(["Name", "Project"])
# Name Project Task Hours
# 1 David
# 3 David Admin
# 0 Julia
# 2 Julia Community Discussions
Trending Discussions on pyjulia
QUESTION
The python3 -m julia.sysimage sys_py.so builds the image.
But when applying this image to the file, I do not observe any acceleration. Most likely this is due to the fact that my library is not in the image. How to fix it?
For example my main Julia file main.jl.
ANSWER
Answered 2021-Dec-14 at 13:42I was unable to start PyJulya.
But I found an interesting JuliaCall library.
It has not yet implemented the connection of the system image, but this is not a big deal.
I replaced the system image generated by the PackageCompiler with the default one by simple copying.
I use docker, so I don't have to worry about the system Julia changing. In this case, the python library works great.
However, do not put pythoncall libraries in this image.
Suddenly it will help someone.
QUESTION
I tried to follow the instructions at this page to build a custom Julia system image, in order to speed up the initialization phase when using PyJulia.
The command python3 -m julia.sysimage sys.so successfully builds a sys.so image, but then jl = Julia(sysimage="sys.so") seems to fail, since I still get:
ANSWER
Answered 2020-Oct-23 at 07:05It seems related to this issue, and the following workaround to load the custom image seems to work:
QUESTION
I want to use PyJulia to speed up some part of the code
ANSWER
Answered 2020-Sep-04 at 08:17You need to have Pandas.jl installed. This library will process your Python pandas data frame for sanity with Julia and than you can convert it to DataFrames.jl.
Here is the Julia code (assumes that dfj is your Python variable):
QUESTION
I want to use julia inside python to speed up some of the code that is slow. Therefore I installed the PyJulia package. As some Julia command are several lines long, I'm writing string of executable code that I pass to Julia. However, the strings are complex to read. Moreover, I would prefer to have as a string as I want to work in a Jupyter Notebook and want to have every piece of code visible in one file. Here is the code:
ANSWER
Answered 2020-Sep-03 at 19:36- I guess what you're looking for is multiline string declaration. This'll not simplify the string, rather makes it easier to read as a code snippet and fits well within the code.
- Using
"""you can declare a code snippet within your code and use it for execution.
QUESTION
I am trying to build PyJulia on my system but get the following error when trying to install via Python:
...ANSWER
Answered 2020-May-14 at 17:33I'm guessing PyJulia can't find your desired Julia environment. I too have had difficulties with getting PyJulia to work in the past. This was what worked for me:
pip install julia
Then in a python file or Jupyter notebook:
QUESTION
I have a scenario in my Python application where I have some work that needs to be done in the background, but in a fire-and-forget manner. There are two constraints I'm trying to satisfy:
- The background task uses PyJulia, which is not thread-safe and will fail if it is invoked from two different threads in the same process, even if these calls don't happen concurrently.
- It turns out PyJulia also has some heavy lifting to do the first time it is invoked in a given process. It takes a few seconds to initialize before the Julia code gets executed. I don't want to pay this cost every time I call it.
What's the simplest way of handling a situation like this? I imagine that I have to create a single long-lived worker thread or process to which I can continually queue tasks, but I don't want to write custom code to handle all of this if I don't have to.
...ANSWER
Answered 2020-May-10 at 13:15The simplest solution I've found, which is satisfactory for my needs, is to use Python's multiprocessing.Pool to create a pool containing exactly one process, keep that process pool around for the life of my application, and use apply_async to execute the task on that process pool in a fire-and-forget manner:
QUESTION
I am trying to convert a PyCall.jlwrap ('Julia') object to a Pandas dataframe. I'm using PyJulia to run an optimization algorithm in Julia, which spits out a dataframe object as a result. I would like to convert that object to a Pandas dataframe.
This is a similar question as posed 5 years ago here. However, there is not any code to suggest how to accomplish the transfer.
Any help would be useful!
Here is the code I currently have set-up. It's not that useful to know what is happening in the background of my 'optimization_program' but just to know that what is returned by the 'run_hybrid' and 'run_storage' commands returns a data frame:
...ANSWER
Answered 2020-Mar-05 at 13:08I get an error (reading a Julia DataFrame in Python), if I use the DataFrames.jl package. However, it seems to work nicely with the Pandas.jl package:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
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Install pyjulia
You can use pyjulia like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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