I recently added the package typepigeon to conda-forge. On conda-forge it is currently at version 1.0.9; however, when installing typepigeon via conda install, the output of pip list shows its version to be 0.0.0.post2.dev0+a27ab2a instead of 1.0.9.
conda list:
typepigeon 1.0.9 pyhd8ed1ab_0 conda-forge
pip list:
typepigeon 0.0.0.post2.dev0+a27ab2a
I think the issue arises from the way I am assigning the version (I am using dunamai to extract the Git tag as the version number). This version extraction is done within setup.py of typepigeon.
try:
__version__ = Version.from_any_vcs().serialize()
except RuntimeError as error:
warnings.warn(f'{error.__class__.__name__} - {error}')
__version__ = '0.0.0'
When conda-forge builds the feedstock, I think it might be looking at the Git tag of the feedstock repository instead of the version from PyPI (as it is locally executing setup.py).
How can I modify the Conda Forge recipe to force the PyPI version?
I've figured out a solution; it might not be the best possible way to do this, but it works for my workflow.
I injected the version into the setup.py by looking for an environment variable (that I called __version__):
if '__version__' in os.environ:
__version__ = os.environ['__version__']
else:
from dunamai import Version
try:
__version__ = Version.from_any_vcs().serialize()
except RuntimeError as error:
warnings.warn(f'{error.__class__.__name__} - {error}')
__version__ = '0.0.0'
Then, in the conda-forge recipe, I added an environment variable (__version__) to the build step:
build:
noarch: python
script: export __version__={{ version }} && {{ PYTHON }} -m pip install . -vv
Related
Using pip, is it possible to figure out which version of a package is currently installed?
I know about pip install XYZ --upgrade but I am wondering if there is anything like pip info XYZ. If not what would be the best way to tell what version I am currently using.
As of pip 1.3, there is a pip show command.
$ pip show Jinja2
---
Name: Jinja2
Version: 2.7.3
Location: /path/to/virtualenv/lib/python2.7/site-packages
Requires: markupsafe
In older versions, pip freeze and grep should do the job nicely.
$ pip freeze | grep Jinja2
Jinja2==2.7.3
I just sent a pull request in pip with the enhancement Hugo Tavares said:
(specloud as example)
$ pip show specloud
Package: specloud
Version: 0.4.4
Requires:
nose
figleaf
pinocchio
Pip 1.3 now also has a list command:
$ pip list
argparse (1.2.1)
pip (1.5.1)
setuptools (2.1)
wsgiref (0.1.2)
and with --outdated as an extra argument, you will get the Current and Latest versions of the packages you are using :
$ pip list --outdated
distribute (Current: 0.6.34 Latest: 0.7.3)
django-bootstrap3 (Current: 1.1.0 Latest: 4.3.0)
Django (Current: 1.5.4 Latest: 1.6.4)
Jinja2 (Current: 2.6 Latest: 2.8)
So combining with AdamKG 's answer :
$ pip list --outdated | grep Jinja2
Jinja2 (Current: 2.6 Latest: 2.8)
Check pip-tools too : https://github.com/nvie/pip-tools
You can also install yolk and then run yolk -l which also gives some nice output. Here is what I get for my little virtualenv:
(venv)CWD> /space/vhosts/pyramid.xcode.com/venv/build/unittest
project#pyramid 43> yolk -l
Chameleon - 2.8.2 - active
Jinja2 - 2.6 - active
Mako - 0.7.0 - active
MarkupSafe - 0.15 - active
PasteDeploy - 1.5.0 - active
Pygments - 1.5 - active
Python - 2.7.3 - active development (/usr/lib/python2.7/lib-dynload)
SQLAlchemy - 0.7.6 - active
WebOb - 1.2b3 - active
account - 0.0 - active development (/space/vhosts/pyramid.xcode.com/project/account)
distribute - 0.6.19 - active
egenix-mx-base - 3.2.3 - active
ipython - 0.12 - active
logilab-astng - 0.23.1 - active
logilab-common - 0.57.1 - active
nose - 1.1.2 - active
pbkdf2 - 1.3 - active
pip - 1.0.2 - active
pyScss - 1.1.3 - active
pycrypto - 2.5 - active
pylint - 0.25.1 - active
pyramid-debugtoolbar - 1.0.1 - active
pyramid-tm - 0.4 - active
pyramid - 1.3 - active
repoze.lru - 0.5 - active
simplejson - 2.5.0 - active
transaction - 1.2.0 - active
translationstring - 1.1 - active
venusian - 1.0a3 - active
waitress - 0.8.1 - active
wsgiref - 0.1.2 - active development (/usr/lib/python2.7)
yolk - 0.4.3 - active
zope.deprecation - 3.5.1 - active
zope.interface - 3.8.0 - active
zope.sqlalchemy - 0.7 - active
The python function returning just the package version in a machine-readable format:
from importlib.metadata import version
version('numpy')
Prior to python 3.8:
pip install importlib-metadata
from importlib_metadata import version
version('numpy')
The bash equivalent (here also invoked from python) would be much more complex (but more robust - see caution below):
import subprocess
def get_installed_ver(pkg_name):
bash_str="pip freeze | grep -w %s= | awk -F '==' {'print $2'} | tr -d '\n'" %(pkg_name)
return(subprocess.check_output(bash_str, shell=True).decode())
Sample usage:
# pkg_name="xgboost"
# pkg_name="Flask"
# pkg_name="Flask-Caching"
pkg_name="scikit-learn"
print(get_installed_ver(pkg_name))
>>> 0.22
Note that in both cases pkg_name parameter should contain package name in the format as returned by pip freeze and not as used during import, e.g. scikit-learn not sklearn or Flask-Caching, not flask_caching.
Note that while invoking pip freeze in bash version may seem inefficient, only this method proves to be sufficiently robust to package naming peculiarities and inconsistencies (e.g. underscores vs dashes, small vs large caps, and abbreviations such as sklearn vs scikit-learn).
Caution: in complex environments both variants can return surprise version numbers, inconsistent with what you can actually get during import.
One such problem arises when there are other versions of the package hidden in a user site-packages subfolder. As an illustration of the perils of using version() here's a situation I encountered:
$ pip freeze | grep lightgbm
lightgbm==2.3.1
and
$ python -c "import lightgbm; print(lightgbm.__version__)"
2.3.1
vs.
$ python -c "from importlib_metadata import version; print(version(\"lightgbm\"))"
2.2.3
until you delete the subfolder with the old version (here 2.2.3) from the user folder (only one would normally be preserved by `pip` - the one installed as last with the `--user` switch):
$ ls /home/jovyan/.local/lib/python3.7/site-packages/lightgbm*
/home/jovyan/.local/lib/python3.7/site-packages/lightgbm-2.2.3.dist-info
/home/jovyan/.local/lib/python3.7/site-packages/lightgbm-2.3.1.dist-info
Another problem is having some conda-installed packages in the same environment. If they share dependencies with your pip-installed packages, and versions of these dependencies differ, you may get downgrades of your pip-installed dependencies.
To illustrate, the latest version of numpy available in PyPI on 04-01-2020 was 1.18.0, while at the same time Anaconda's conda-forge channel had only 1.17.3 version on numpy as their latest. So when you installed a basemap package with conda (as second), your previously pip-installed numpy would get downgraded by conda to 1.17.3, and version 1.18.0 would become unavailable to the import function. In this case version() would be right, and pip freeze/conda list wrong:
$ python -c "from importlib_metadata import version; print(version(\"numpy\"))"
1.17.3
$ python -c "import numpy; print(numpy.__version__)"
1.17.3
$ pip freeze | grep numpy
numpy==1.18.0
$ conda list | grep numpy
numpy 1.18.0 pypi_0 pypi
You can use the grep command to find out.
pip show <package_name>|grep Version
Example:
pip show urllib3|grep Version
will show only the versions.
Metadata-Version: 2.0
Version: 1.12
There's also a tool called pip-check which gives you a quick overview of all installed packages and their update status:
Haven't used it myself; just stumbled upon it and this SO question in quick succession, and since it wasn't mentioned...
pip show works in python 3.7:
pip show selenium
Name: selenium
Version: 4.0.0a3
Summary: Python bindings for Selenium
Home-page: https://github.com/SeleniumHQ/selenium/
Author: UNKNOWN
Author-email: UNKNOWN
License: Apache 2.0
Location: c:\python3.7\lib\site-packages\selenium-4.0.0a3-py3.7.egg
Requires: urllib3
Required-by:
The easiest way is this:
import jinja2
print jinja2.__version__
pip list can also be told to format its output as json.
It could be a safer approach to parse the version.
pip list --no-index --format=json | \
jq -r '.[] | select(.name=="Jinja2").version'
# 2.10.1
On windows, you can issue command such as:
pip show setuptools | findstr "Version"
Output:
Version: 34.1.1
To do this using Python code:
Using importlib.metadata.version
Python ≥3.8
import importlib.metadata
importlib.metadata.version('beautifulsoup4')
'4.9.1'
Python ≤3.7
(using importlib_metadata.version)
!pip install importlib-metadata
import importlib_metadata
importlib_metadata.version('beautifulsoup4')
'4.9.1'
Using pkg_resources.Distribution
import pkg_resources
pkg_resources.get_distribution('beautifulsoup4').version
'4.9.1'
pkg_resources.get_distribution('beautifulsoup4').parsed_version
<Version('4.9.1')>
Credited to comments by sinoroc and mirekphd.
For Windows you can
open cmd and type python, press enter.
type the import and press enter.
type ._version__ and press enter.
As you can see in screen shot here I am using this method for checking the version of serial module.
In question, it is not mentioned which OS user is using (Windows/Linux/Mac)
As there are couple of answers which will work flawlessly on Mac and Linux.
Below command can be used in case the user is trying to find the version of a python package on windows.
In PowerShell use below command :
pip list | findstr <PackageName>
Example:- pip list | findstr requests
Output : requests 2.18.4
import pkg_resources
packages = [dist.project_name for dist in pkg_resources.working_set]
try:
for count, item in enumerate(packages):
print(item, pkg_resources.get_distribution(item).version)
except:
pass here
The indentations might not be perfect. The reason I am using a Try- Except block is that few library names will throw errors because of parsing the library names to process the versions. even though packages variable will contain all the libraries install in your environment.
How can I update xarray? I tried:
>>> import xarray
>>> xarray.show_versions
<function show_versions at 0x7fcfaf2aa820>
But I cannot find any documentation how to read this, or how to update to a new version of xarray.
I was not the person to install it on the computer, so I do not know if it was through anaconda or something else. Is there a way to find this out?
xarray.show_versions is a function, which prints the versions of xarray and its dependencies.
To get just the version of xarray, you can check the __version__ property of the module.
Updating xarray is best done with pip or conda, depending on how you installed it in the first place.
import xarray as xr
print(xr.__version__)
# '0.18.2'
xr.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.8.8 (default, Feb 19 2021, 18:07:06)
[GCC 8.3.0]
python-bits: 64
OS: Linux
OS-release: 5.11.0-27-generic
machine: x86_64
processor:
byteorder: little
LC_ALL: C.UTF-8
LANG: C.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.0
libnetcdf: 4.7.4
xarray: 0.18.2
pandas: 1.2.4
numpy: 1.20.3
scipy: 1.6.3
netCDF4: 1.5.6
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.8.3
cftime: 1.5.0
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.2.3
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2021.05.0
distributed: 2021.05.0
matplotlib: 3.4.2
cartopy: None
seaborn: None
numbagg: None
pint: None
setuptools: 53.0.0
pip: 21.1.1
conda: None
pytest: None
IPython: 7.23.1
sphinx: None
To update xarray:
pip install --upgrade xarray
or
conda update xarray
To see if it was installed using conda or pip, run conda list xarray. If it was installed using pip, it should state pypi in the Channel column.
This is for those who want to do through GUI and who use software like pycharm, spyder, or other similar softwares.
SO, try finding 'python interpreter' in the settings. Most softwares shows the existing packages, current version,latest version(for example see the image of pycharm)
There is option to select the version that you want. for example there are times, when a module is in its beta phase and is not stable in usage. so, you can specify the latest stable version too. It is applicable for any module and not limited to xarray.
I'm struggling to figure out conda virtual environments on windows. All I want is to be able to have different versions of h2o installed at the same time because of their insane decision to not allow you to be able to load files saved in even the most minor different version.
I created a virtual environment by cloning my base anaconda:
conda create -n h203_14_0_7 --clone base
I then activated the virtual environment like so:
C:\ProgramData\Anaconda3\Scripts\activate h203_14_0_7
Now that I'm in the virtual environment (I see the (h203_14_0_7) at the beginning of the prompt), i want to uninstall the version of h2o in this virtual environment so I tried:
pip uninstall h2o
But this output
which to me looks like it's going to uninstall the global h2o rather than the virtual environment h2o. So I think it's using the global pip instead of the pip it should have cloned off the base. So how to I use the virtual environment pip to uninstall h2o just for my virtual environment and how can I be sure that it's doing the right thing?
I then ran
conda intall pip
and it seems that after that I was able to use pip to uninstall h2o only from the virtual environment (I hope). I then downloaded the older h2o version from here: https://github.com/h2oai/h2o-3/releases/tag/jenkins-rel-weierstrass-7
but when I try install it I get
(h203_14_0_7) C:\ProgramData\Anaconda3\envs\h203_14_0_7>pip install C:\Users\dan25\Downloads\h2o-3-jenkins-rel-weierstrass-7.tar.gz
Processing c:\users\dan25\downloads\h2o-3-jenkins-rel-weierstrass-7.tar.gz
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\ProgramData\Anaconda3\envs\h203_14_0_7\lib\tokenize.py", line 452, in open
buffer = _builtin_open(filename, 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\dan25\\AppData\\Local\\Temp\\pip-sf7r_6pm-build\\setup.py'
So what now?
I had trouble (e.g. https://0xdata.atlassian.net/browse/PUBDEV-3370 ) getting that approach to ever work. It felt like some kind of global dependency was in there, somewhere.
So, I personally just uninstall, and install the desired version, as I need to move between versions. (Actually, I am more likely to use a different VirtualBox or AWS image for each.)
However I noticed searching for conda on the H2O jira that there is a lot of activity recently. They might all be pointing out the same bug you have found, but if so it sounds like it is something getting enough attention to get fixed.
Aside: finding old versions (and your edit showing install problems)
To find, e.g. 3.14.0.7, google it with "h2o". The top hit is http://h2o-release.s3.amazonaws.com/h2o/rel-weierstrass/7/index.html
The "rel-weierstrass" represents 3.14.0, and the 7 is in the URL. (I've yet to see a full list of all the rel-XXX names, but google will always find at least one in the series, even if it won't find the exact minor version.)
Download the zip file you find there. Inside you will find both an R package, and a whl package for Python. So unzip it, extract the one you want, then pip install it.
These zip files are always on S3 (AFAIK). The link you showed was a source snapshot, on github.
Install requirements:
pip install requests tabulate numpy scikit-learn
Extract the archive:
zcat h2o-3-jenkins-rel-weierstrass-7.tar.gz | tar xvf -
cd into Python directory and build:
cd h2o-py
../gradlew build
I have this working now. I think the trick is to make sure you do NOT have h2o installed on your base python. I did the following:
pip uninstall h2o
conda create --name h2o-base pip
conda activate h2o-base
conda install numpy
conda install pandas
conda install requests
conda install tabulate
conda install colorama
conda install future
conda install jupyter
python -m pip install ipykernel
conda deactivate
And now to install specific versions of h2o, you need to URL of the .whl file for that version and you can find a list of the URLs of all the old versions here: https://github.com/h2oai/h2o-3/blob/master/Changes.md
So for example to install version 3.18.0.8:
conda create --name h2o-3-18-0-8 --clone h2o-base
conda activate h2o-3-18-0-8
pip install http://h2o-release.s3.amazonaws.com/h2o/rel-wolpert/8/Python/h2o-3.18.0.8-py2.py3-none-any.whl
python -m ipykernel install --user --name h2o-3-18-0-8 --display-name "Python (h2o-3-18-0-8)"
or version 3.20.0.2 (make sure to conda deactivate first):
conda create --name h2o-3-20-0-2 --clone h2o-base
conda activate h2o-3-20-0-2
pip install http://h2o-release.s3.amazonaws.com/h2o/rel-wright/2/Python/h2o-3.20.0.2-py2.py3-none-any.whl
python -m ipykernel install --user --name h2o-3-20-0-2 --display-name "Python (h2o-3-20-0-2)"
This set-up allows me to have multiple versions of h2o installed on the same computer and if I have to use serialized models I just have to run python from the virtual environment with the correct version of h2o installed. I think this is preferable to uninstalling and reinstalling h2o each time.
Here is the environments.yml file if you want to skip all the manual installs above:
name: h2o-base
channels:
- conda-forge
- defaults
dependencies:
- asn1crypto=0.24.0=py37_1003
- backcall=0.1.0=py_0
- bleach=3.0.2=py_0
- ca-certificates=2018.10.15=ha4d7672_0
- certifi=2018.10.15=py37_1000
- cffi=1.11.5=py37hfa6e2cd_1001
- chardet=3.0.4=py37_1003
- colorama=0.4.0=py_0
- cryptography=2.3=py37h74b6da3_0
- cryptography-vectors=2.3.1=py37_1000
- decorator=4.3.0=py_0
- entrypoints=0.2.3=py37_1002
- future=0.16.0=py37_1002
- icu=58.2=vc14_0
- idna=2.7=py37_1002
- ipykernel=5.1.0=pyh24bf2e0_0
- ipython=7.0.1=py37h39e3cac_1000
- ipython_genutils=0.2.0=py_1
- ipywidgets=7.4.2=py_0
- jedi=0.13.1=py37_1000
- jinja2=2.10=py_1
- jpeg=9b=vc14_2
- jsonschema=2.6.0=py37_1002
- jupyter=1.0.0=py_1
- jupyter_client=5.2.3=py_1
- jupyter_console=6.0.0=py_0
- jupyter_core=4.4.0=py_0
- libflang=5.0.0=vc14_20180208
- libpng=1.6.34=vc14_0
- libsodium=1.0.16=vc14_0
- llvm-meta=5.0.0=0
- markupsafe=1.0=py37hfa6e2cd_1001
- mistune=0.8.4=py37hfa6e2cd_1000
- nbconvert=5.3.1=py_1
- nbformat=4.4.0=py_1
- notebook=5.7.0=py37_1000
- openblas=0.2.20=vc14_8
- openmp=5.0.0=vc14_1
- openssl=1.0.2p=hfa6e2cd_1001
- pandas=0.23.4=py37h830ac7b_1000
- pandoc=2.3.1=0
- pandocfilters=1.4.2=py_1
- parso=0.3.1=py_0
- pickleshare=0.7.5=py37_1000
- pip=18.1=py37_1000
- prometheus_client=0.4.2=py_0
- prompt_toolkit=2.0.6=py_0
- pycparser=2.19=py_0
- pygments=2.2.0=py_1
- pyopenssl=18.0.0=py37_1000
- pyqt=5.6.0=py37h764d66f_7
- pysocks=1.6.8=py37_1002
- python=3.7.0=hc182675_1005
- python-dateutil=2.7.3=py_0
- pytz=2018.5=py_0
- pywinpty=0.5.4=py37_1002
- pyzmq=17.1.2=py37hf576995_1001
- qt=5.6.2=vc14_1
- qtconsole=4.4.2=py_1
- requests=2.19.1=py37_1001
- send2trash=1.5.0=py_0
- setuptools=40.4.3=py37_0
- simplegeneric=0.8.1=py_1
- sip=4.18.1=py37h6538335_0
- six=1.11.0=py37_1001
- tabulate=0.8.2=py_0
- terminado=0.8.1=py37_1001
- testpath=0.4.2=py37_1000
- tornado=5.1.1=py37hfa6e2cd_1000
- traitlets=4.3.2=py37_1000
- urllib3=1.23=py37_1001
- vc=14=0
- vs2015_runtime=14.0.25420=0
- wcwidth=0.1.7=py_1
- webencodings=0.5.1=py_1
- wheel=0.32.1=py37_0
- widgetsnbextension=3.4.2=py37_1000
- win_inet_pton=1.0.1=py37_1002
- wincertstore=0.2=py37_1002
- winpty=0.4.3=4
- zeromq=4.2.5=vc14_2
- zlib=1.2.11=vc14_0
- blas=1.0=mkl
- icc_rt=2017.0.4=h97af966_0
- intel-openmp=2019.0=118
- m2w64-gcc-libgfortran=5.3.0=6
- m2w64-gcc-libs=5.3.0=7
- m2w64-gcc-libs-core=5.3.0=7
- m2w64-gmp=6.1.0=2
- m2w64-libwinpthread-git=5.0.0.4634.697f757=2
- mkl=2019.0=118
- mkl_fft=1.0.6=py37hdbbee80_0
- mkl_random=1.0.1=py37h77b88f5_1
- msys2-conda-epoch=20160418=1
- numpy=1.15.2=py37ha559c80_0
- numpy-base=1.15.2=py37h8128ebf_0
I need the sacred package for a new code base I downloaded. It requires sacred.
https://pypi.python.org/pypi/sacred
conda install sacred fails with
PackageNotFoundError: Package missing in current osx-64 channels:
- sacred
The instruction on the package site only explains how to install with pip. What do you do in this case?
That package is not available as a conda package at all. You can search for packages on anaconda.org: https://anaconda.org/search?q=sacred You can see the type of package in the 4th column. Other Python packages may be available as conda packages, for instance, NumPy: https://anaconda.org/search?q=numpy
As you can see, the conda package numpy is available from a number of different channels (the channel is the name before the slash). If you wanted to install a package from a different channel, you can add the option to the install/create command with the -c/--channel option, or you can add the channel to your configuration conda config --add channels channel-name.
If no conda package exists for a Python package, you can either install via pip (if available) or build your own conda package. This isn't usually too difficult to do for pure Python packages, especially if one can use skeleton to build a recipe from a package on PyPI.
It happens some issue to me before. If your system default Python environment is Conda, then you could download those files from https://pypi.python.org/pypi/sacred#downloads
and manually install by
pip install C:/Destop/some-file.whl
I need to make use of python's mitmproxy. I have installed it successfully. However when I run mitmproxy command on my terminal it gives me a stack trace like the below :
File "/usr/local/bin/mitmproxy", line 9, in load_entry_point('mitmproxy==0.13', 'console_scripts','mitmproxy'()
File "/Library/Python/2.7/site-packages/pkg_resources/init.py", line 558, in load_entry_pointreturn get_distribution(dist).load_entry_point(group, name)
File "/Library/Python/2.7/site-packages/pkg_resources/init.py", line 2682, in load_entry_point return ep.load()
File "/Library/Python/2.7/site-packages/pkg_resources/init.py", line 2355, in load return self.resolve()
File "/Library/Python/2.7/site-packages/pkg_resources/init.py", line 2361, in resolve module = import(self.module_name, fromlist=['name'], level=0)
File "/Library/Python/2.7/site-packages/libmproxy/main.py", line 7, in from . import version, cmdline
File "/Library/Python/2.7/site-packages/libmproxy/cmdline.py", line 5, in from netlib import http
File "/Library/Python/2.7/site-packages/netlib/http.py", line 7, in from . import odict, utils, tcp, http_status
File "/Library/Python/2.7/site-packages/netlib/tcp.py", line 26, in 'TLSv1.2': SSL.TLSv1_2_METHOD, AttributeError: 'module' object has no attribute 'TLSv1_2_METHOD'
I tried debugging the issue through some Googling and looks like I needed to upgrade my pyOpenSSL.
To know the current version of my PyOpen SSL I did the following on the Python prompt and got the ouptut as shown below to be 0.13:
>>> import OpenSSL
>>> print OpenSSL.__version__
0.13
So I tried upgrading the my pyOpenSSL using the below :
sudo pip install --upgrade pyOpenSSL
ans successfully did so, as when I ran the above again I received the following in the first line of the output :
Requirement already up-to-date: pyOpenSSL in /Library/Python/2.7/site-packages
Just to cross verify I went to the above path and found the PyOpenSSL dir as PyOpenSSL-0.15.1.dist-info. So am guessing PyOpenSSL was actually upgraded to the latest version.
However, when I ran the below on Python prompt again I received the version again as 0.13. Ideally I was expecting it to give the updated version now.
>>> import OpenSSL
>>> print OpenSSL.__version__
0.13
Some blogs suggested that if I have a virtualevn installed, it might interfere with the above. So I uninstalled virtualenv as well using
sudo pip uninstall virtualenv
I am still not able to get mitmproxy running. And when I run mitmproxy, I still get the same error as above.
Please let me know what am I missing and how to get mitmproxy running.
So it happens yet again. :P I could figure out the problem with the above approach and the solution to it as well on my own - OF COURSE - with the help of some friends and blogs !
So appears that the problem was actually because of MANY out-dated dependencies : -
Outdated OpenSSL -
current version displayed using OpenSSL version -a
Awesome help found # http://javigon.com/2014/04/09/update-openssl-in-osx/ to update OpenSSL and from a friend (https://anantshri.info/) who pointed out the issue itself initially.
Outdated pyOpenSSL - upgraded using the below which of course upgraded the same.
sudo pip install --upgrade pyOpenSSL
Then why was the below still showing an outdated version ?
import OpenSSL
print OpenSSL.version
0.13
because there were 2 different OpenSSLs in the system. One that was installed by pip and the other that was by default present in OSX. Again awesome help found # https://github.com/pyca/pyopenssl/issues/128
some useful commands that helper were :
pip show pyOpenSSL - gives as output :
Name: pyOpenSSL
Version: 0.15.1
Location: /Library/Python/2.7/site-packages
as part of the output - indicating that the OpenSSL installed using pip is actually 0.15.1
cross verify using :
ls /Library/Python/2.7/site-packages/ | grep OpenSSL - gives as output:
pyOpenSSL-0.15.1.dist-info
Now the path below also had another copy of OpenSSL :
/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/OpenSSL and cat version.py in the above dir gave the below as part of output :
version = '0.13.1'
indicating that the cause of the issue with the import statement showing the outdated python version.
And the above itself was the root cause for mitmproxy also not working
because mitmproxy was unable to use the latest version on OpenSSL.
So solved the problem by just replacing the OpenSSL in the above path (which was outdated) with the updated one from /Library/Python/2.7/site-packages/
where
cat ./OpenSSL/version.py gave as output (once again just to cross-verify)
version = '0.15.1'
And now the import statement reported the right version of OpenSSL.
Uninstalled mitmproxy using sudo pip uninstall mitmproxy - successfully uninstalled. Also uninstalled virtualenv. (not sure of the above 2 was required !)
Reinstalled mitmproxy as sudo pip install mitmproxy - Successfully done !
And ran mitmproxy now from the terminal wihtout a glitch ! :)