This error raised while installing geopandas. I've looking for its solution on the web, but none of them really explain what happened and how to solve it..
This is the full error:
Collecting geopandas
Using cached https://files.pythonhosted.org/packages/24/11/d77c157c16909bd77557d00798b05a5b6615ed60acb5900fbe6a65d35e93/geopandas-0.4.0-py2.py3-none-any.whl
Requirement already satisfied: shapely in c:\users\alvaro\anaconda3\envs\tfdeeplearning\lib\site-packages (from geopandas) (1.6.4.post2)
Requirement already satisfied: pandas in c:\users\alvaro\anaconda3\envs\tfdeeplearning\lib\site-packages (from geopandas) (0.20.3)
Collecting fiona (from geopandas)
Using cached https://files.pythonhosted.org/packages/3a/16/84960540e9fce61d767fd2f0f1d95f4c63e99ab5d8fddc308e8b51b059b8/Fiona-1.8.4.tar.gz
Complete output from command python setup.py egg_info:
A GDAL API version must be specified. Provide a path to gdal-config using a GDAL_CONFIG environment variable or use a GDAL_VERSION environment variable.
----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in C:\Users\Alvaro\AppData\Local\Temp\pip-install-oxgkjg8l\fiona\
pip install wheel
pip install pipwin
pipwin install numpy
pipwin install pandas
pipwin install shapely
pipwin install gdal
pipwin install fiona
pipwin install pyproj
pipwin install six
pipwin install rtree
pipwin install geopandas
here are the source links:
http://geopandas.org/install.html#installation
https://pip.pypa.io/en/latest/user_guide/#installing-from-wheels
https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy
If you still have problems, consider uninstalling the above (pip uninstall) and reinstalling.
I solved this problem by running the following commands:
pip install pipwin
pipwin install gdal
pipwin install fiona
pip install geopandas
Works successfully on Windows.
Geospatial Data Abstraction Library (GDAL) is a library designed for vector geospatial data formats. It's a prerequisite for installing Fiona, the Python API for OGR (which doesn't really stand for anything), which is in turn a prerequisite for Geopandas. On UNIX-like systems the gdal-config script tells Fiona stuff about your particular gdal installation.
It seems that your gdal-config is not in one of the usual places on your PATH, so Fiona was unable to find it.
If you're using Anaconda, best is to remove gdal with conda remove gdal and then do a fresh conda install geopandas.
As a general rule, if you're using Conda you should never use pip to install something inside it unless you're absolutely sure conda offers no support for it. (Many package can be found on conda by specifying the right channel - -c argument.) And specifically in the case of geopandas, the maintainers recommend using conda over pip, since pip requires you to install the dependencies correctly.
I had a lot of issues myself installing geopandas, mostly showing error when downloading fiona and gdal. I did every step above and did a conda install geopandas but failed. The only thing worked for me is to install fiona and gdal wheel separately.
go to the link by Christoph: gohlke:https://www.lfd.uci.edu/~gohlke/pythonlibs/#fiona
You can search for fiona and gdal wheel files. Make sure you choose the file as per your python version, if it is 3.7 then there would be cp37.
Download the file
go to command prompt, put cd and then pip install , install GDAL wheel file, then fiona, then just do pip install geopandas.
This solution worked for me.
To install gdal, I followed the following steps:
downloaded the version that satisfies my computer (64 bit) from
https://www.lfd.uci.edu/~gohlke/pythonlibs/ . The file was GDAL-3.1.4-cp37-cp37m-win_amd64.whl
Put the file in a folder on the desktop.
From cmd, i moved to that directory and executed python -m pip install GDAL-3.1.4-cp37-cp37m-win_amd64.whl
This is followed by installing fiona the same way: python -m pip install Fiona-1.8.18-cp37-cp37m-win_amd64.whl
For shapely, i executed conda install -c conda-forge shapely
After that, i was able to install keplergl as usual: pip install keplergl
install descartes: conda install -c conda-forge descartes (or python -m pip install descartes).
In this way, i didn't have to play around with the 'Environmental Variables' as this may affect other programs
Cheers..
Installing geopandas
Geopandas has very complex multi-language dependencies, some of which need to be built with consistent compiler versions across packages. Because of this, the geopandas docs recommend installing using conda in a new environment using conda-forge only. Here are some general best practices to keep in mind:
conda is the recommended installation method. You can install geopandas from pip or source, but it's going to be a bumpy ride and it's not recommended. If you're installing conda for the first time, I recommend you start with miniconda (or better yet miniforge, a conda-forge-first miniconda variant), not anaconda, to keep your base env lean.
When using conda, you should not mix and match conda channels.
When installing geopandas, try creating a fresh environment rather than installing into your base environment. If you have anaconda installed, it comes with a large number of packages from the "defaults" channel installed in your base environment. I recommend deleting anaconda and installing miniconda, then installing into a new environment.
Try to create a new environment with everything you plan to use all at once rather than iteratively modifying the environment. In other words, if you want to use geopandas with scikit_learn, folium, and rasterio, install them together with a single conda create command
As a last resort, delete your conda installation and re-install miniconda. Desperate times call for desperate measures, and this usually resolves gnarly installation nightmares.
To create a fresh conda environment in which you install all necessary dependencies at the same time, using the conda-forge channel:
conda create -n my-geopandas-env -c conda-forge geopandas [all other packages you need]
For example, I might set up an environment with something along the lines of...
conda create -n my-geopandas-env -c conda-forge python=3.9 \
ipython ipykernel geopandas scipy seaborn fiona matplotlib cartopy
Bundling your installations into a single environment creation step like this reduces the chance of packages falling out of sync. To speed this process up, you could first install mamba or mambaforge, a faster drop-in replacement for conda, into your base environment and then run the above commands with mamba instead of conda.
Generally, it's best to avoid installing much of anything in your base environment (cross-environment system utilities like mamba are some of the few exceptions). If you already have a complex base environment (maybe you started with anaconda rather than miniconda) this may be the time to delete your entire conda installation and start from scratch (I know that's terrifying... sorry! but it'll save you heartache in the future). mamba is great for speeding this process up.
Connecting your editor to the conda environment
Once you have installed all of the packages you need, activate your environment with conda activate my-geopandas-env. See the conda guide to managing environments for more info.
Jupyter/ipython
Some editors/IDEs including jupyter require additional packages - jupyter requires that ipython and ipykernel be installed in order to load the environment within the notebook or editor - that's why I included ipykernel in my list above. See the ipykernel docs for more info.
Other IDES
To link this environment to an IDE such as VSCODE, spider, etc., find the location of this python version with conda run -n my-geopandas-env which python then point your editor to this python executable. Check the docs of your specific editor to get more targeted info about how to set up a conda environment for use with your editor:
Spider: FAQ on using an existing environment and Spider wiki guide to working with packages and environments
VSCode: Using python environments in vscode
PyCharm: Configure a conda virtual environment
I don't have conda installed, then using just pip I followed these steps:
Download GDAL and Fiona wheels directly on:
GDAL: https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal
FIONA: https://www.lfd.uci.edu/~gohlke/pythonlibs/#fiona
Then:
pip install <gdal.whl>
pip install <fiona.whl>
In my case I did pip install GDAL-3.4.1-cp38-cp38-win_amd64.whl and Fiona-1.8.21-cp38-cp38-win_amd64.whl. Where cp38 stands for python 3.8.
After that you are able to install geopandas with pip as well.
pip install geo pandas
For me, the only solution was to install the ready binaries from here
https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal
Then just install locally
pip install GDAL-3.1.4-cp38-cp38-win_amd64.whl
One way in which I could install geopandas was through the Anaconda Navigator. Get into the environment and install the package 'geopandas'. After that I could import the geopandas package in spyder
I will add
!pip install descartes
to #JDOaktown list.
I started with pip install geopandas and got the error, but later tried with conda install --channel conda-forge geopandas and the error disappeared.
Successfully installed in RHEL 7.8.
It automatically downloaded the required packages. This might be helpful
Installing collected packages: certifi, pyproj, shapely, attrs, click, click-plugins, munch, cligj, fiona, geopandas
Successfully installed attrs-20.3.0 certifi-2020.11.8 click-7.1.2 click-plugins-1.1.1 cligj-0.7.0 fiona-1.8.17 geopandas-0.8.1 munch-2.5.0 pyproj-3.0.0.post1 shapely-1.7.1
If you want to install GDAL, Geopandas, Shapely, Fiona etc in a windows Virtual Environment download .whl files for all of them and first install GDAL using
pip install gdal-.whl
Following this command edit the activate.bat file in you venv\Scripts folder and add
GDAL_CONFIG = \venv\Lib\site-packages\osgeo
Then you can install rest using pip install
I started off with a clean environment gdal_test in Conda environments, but made the mistake of using the old activate gdal_test instead of conda activate gdal_test. This made Conda Environment resolving take forever, which is why I resolved to other methods at first.
Takeaway: let conda handle it, with a proper new environment.
I ran into this problem not with anaconda/windows, but with python:3.6 Docker image. Google search always led me to this question, so I think I will share how I resolve my issue in case others also end up here.
Based on here, you need to install system relevant packages in the Dockerfile before running pip install geopandas or pip install requirements.txt:
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
libatlas-base-dev \
libgdal-dev \
gfortran
The following worked on macOS:
brew install gdal --HEAD
Verify the installation by running gdal-config --version
Following that pip installation as normal worked without a problem.
I used VirtualEnv to create a python2 environment without system site packages like this:
virtualenv -p /usr/bin/python2.7 --no-site-packages ENV2.7
And I want to install packages in this environment.
However, I found that my python code is still trying to look for packages out of this environment.
For example, after activate this env, I used:
pip install matplotlib
And in my demo.py, there is
import matplotlib
But this raised an error, and can not find this package
However, when I use python in the terminal and enter the interactive python, import matplotlib dose not raise an error.
Then I started another terminal and tried to install this package out of the environment by pip3:
pip3 install matplotlib
It turned out that my demo.py just work well.
Any idea? Many Thanks!
It sounds like your virtualenv pip version may be using pip3 instead of pip2:
Make sure you are using the correct python version in your project that you mean to, and using the same version of pip in your virtualenv. (Note that you use pip above once, then you used pip3 outside your virtualenv.)
Check your pip version from inside the virtualenv:
workon (your env name)
which pip
pip -V
Output should look something like:
$ which pip
/home/yourname/.virtualenvs/testenv/bin/pip
$ pip -V
pip 9.0.1 from /home/yourname/.virtualenvs/testenv/local/lib/python2.7/site-packages (python 2.7)
It should tell you you're using pip inside your virtualenv, and the correct python version.
If that looks correct, install your packages.
pip install (whatever)
Check they are installed with pip freeze.
Run your project. :)
Python2.6 was installed by default in my old centos server. Now I want to create a Python3 environment to install python3 specific module by conda
conda create -n py3 python=3.5.3
source activate py3
After activate the py3, I try to install hovercraft by pip3 install hovercraft, the shell tells "command not found: pip3". At first I thought pip3 was installed with Python3, but the result was not the case.
So I think I can install it manually. The package gzip file was downloaded from python package index, and install by conda install --file hovercraft-2.3.tar.gz. But it doesn't work.
Now I have two problems:
how to install pip3 for virtual-env create by conda?
Is it possible to install python package index downloaded package locally in conda?
pip3 and pip would make a difference only when you are not using any environment managers like virualenv (or) conda. Now as you are creating a conda environment which has python==3.x, pip would be equivalent to pip3.
I used sudo apt-get install python-scipy to install scipy. This put all the files in /usr/lib/python2.7.dist-packages/scipy. My best guess is it chose that location because python 2.7 was the default version of python. I also want to use scipy with python 3 however. Does the package need to be rebuilt for python 3 or can I just point python 3 to the existing version?
I've tried using pip to install two parallel version, but I can't get the dependency libblas3 installed for my system.
What's the best way to do this?
I'm on Debian Jessie.
To install scipy for python3.x the on a debian-based distribution:
sudo apt-get install python3-scipy
This corresponds to the python2.x equivalent:
sudo apt-get install python-scipy
On a more platform-independent note, pip is the more standard way of installing python packages:
pip install --user scipy #pip install using default python version
To make sure you are using the right pip version you can always be more explicit:
pip2 install --user scipy # install using python2
pip3 install --user scipy # install using python3
Also, I believe anaconda or the more lightweight miniconda were intended to make installation of python packages with complex dependencies more easy, plus it allows for using an environment, making it easier to have several configurations with non-compatible versions etc. This would create+use a python binary different from the one on your system though.
One would then install scipy using the command conda:
conda install scipy
If installing scipy for a specific version you would create an environment with that python version:
conda create -n my_environment_name python=3 scipy
One could also use pip inside a conda environment alongside conda python packages, but I would make sure that you are using pip installed using conda to avoid conflicts. An added benefit when installing conda for a user, is that you don't have to add the --user flag when installing with pip.
If you can't find python3-scipy using apt-get you can use pip to install it for python3, you just have to make sure you use pip3 (if you don't have it apt install python3-pip
pip3 install --user scipy
You may want to try with pip3 install scipy
Is there anyway I can use homewbrew to install packages (like numpy or matplotlib) into isolated virtual environments created using virtualenv, without having the packaged installed system wide.
Use pip inside of the virtualenv and it will isolate the packages to just that virtualenv. Each virtualenv has a local version of pip and will install the packages locally.
You can install numpy with pip.
Your problem will probably solved by issuing the following commands:
$ export CFLAGS=-Qunused-arguments
$ export CPPFLAGS=-Qunused-arguments
$ pip install numpy
You can test with
$ python -c 'import numpy'
There are several packages which have this problem at the moment. PIL is another example.