Trying to install quandl and need pandas, so I tried pip install pandas and get:
Could not find a version that satisfies the requirement numpy==1.9.3 (from versions: 1.10.4, 1.11.0, 1.11.1rc1, 1.11.1, 1.11.2rc1, 1.11.2, 1.11.3, 1.12.0b1, 1.12.0rc1, 1.12.0rc2, 1.12.0, 1.12.1rc1, 1.12.1, 1.13.0rc1, 1.13.0rc2, 1.13.0, 1.13.1, 1.13.3, 1.14.0rc1, 1.14.0, 1.14.1, 1.14.2) No matching distribution found for numpy==1.9.3.
I'm using python 3.4, win32
https://pypi.org/project/numpy/1.22.1/#files
Latest numpy does not support python 3.7 anymore.
The current quandl is more generous in its requirements:
https://pypi.python.org/pypi/Quandl
Requires Distributions
pandas (>=0.14)
numpy (>=1.8)
It's github setup is the same: https://github.com/quandl/quandl-python/blob/master/setup.py
pandas (rather than quandl itself). –
Fluctuation Just use this command :
pip install pandas==0.19.0 .
An older version which will not cry with this error !!
I had a similar problem, with installed python 3.6.9. Trying to install requirements with "pip install -r requirements.txt" gave me a similar error (can't find numpy version, in my case, it was 1.9.6). I triedpython3 -m pip install -r requirements.txt but it seems, for some reason the pip module for python3 hasn't been installed in my case. So, I installed it manually and repeated the command, and the requirements has been installed.
Manually installing pip module for python3:
Securely Download get-pip.py
Run python3 get-pip.py
Run sudo apt install python3-testresources
This will install or upgrade pip. Additionally, it will install setuptools and wheel if they’re not installed already.
"Warning: Be cautious if you’re using a Python install that’s managed by your operating system or another package manager. get-pip.py does not coordinate with those tools, and may leave your system in an inconsistent state. You can use python get-pip.py --prefix=/usr/local/ to install in /usr/local which is designed for locally-installed software."
And, finally, run python3 -m pip install -r requirements.txt
I changed the LASTEST VERSION into requirements.txt by pandas == 0.23.1 - at that time was the latest release of released - You can check in pandas
Just Install Python 3.5 or higher.
In my case, we wanted to get pip modules installed from requirement*.txt files, which had locked-in module's versions defined in the file and fetched from an internal Artifactory server (rather than going to online i.e. pypi.org)
Ex: requirements.txt file(s)
numpy==1.16.2
pandas==1.0.3
..
...
To fix the issue: I had to use NO_PROXY=<value> available as an environment variable.
Let's say, if you artifactory server is: my-artifactory.company.local or my-artifactory.company.com, then all we need to ensure is that NO_PROXY variable has that hostname's "domain" part listed in its value.
i.e. for my-artifactory.company.com or my-artifactory.company.local, value inside
NO_PROXY variable must have: ,.company.com,.company.local,... in it.
Sample exported variable (at command line $ prompt):
export NO_PROXY=localhost,127.0.0.1,169.254.169.254,169.254.169.123,.somecompany.com,.company.com,.company.local,pki.company.com,s3-us-gov-west-1.amazonaws.com,s3-fips-us-gov-west-1.amazonaws.com,rds.amazonaws.com,10.201.12.244,10.201.44.62,10.201.32.261
====
If you are using a Dockerfile, then, ensure you have ARG/ENV variable are set correctly.
ARG is used during build time (can be overridden at command line using --build-arg option sent to docker build -t tag . where it'll search current directory for a Dockerfile and create an image. ENV is used at run time (docker run) and can be overridden as well.
Sample Dockerfile is:
FROM python:3.7
MAINTAINER [email protected]
ARG PYTHONBUFFERED=0
ARG HTTPS_PROXY=http://proxy.ext.company.com:80
ARG HTTP_PROXY=http://proxy.ext.company.com:80
ARG NO_PROXY=localhost,127.0.0.1,169.254.169.254,.company.com,.company.local,pki.company.com,s3-us-gov-west-1.amazonaws.com,s3-fips-us-gov-west-1.amazonaws.com,rds.amazonaws.com
ENV PYTHONBUFFERED=${PYTHONBUFFERED}
ENV HTTPS_PROXY=${HTTPS_PROXY}
ENV HTTP_PROXY=${HTTP_PROXY}
ENV NO_PROXY=${NO_PROXY}
# If there are 3 requirements files in source control, I'm copy all for pip install, you don't have to. Use what modules you want / file you want.
RUN mkdir -p code
COPY requirements.txt /code
COPY requirements-test.txt /code
COPY requirements-dev.txt /code
WORKDIR /code
# You can fetch from pypi.org but in my case, this was a security issue.
# RUN pip install --trusted-host pypi.org -r requirements.txt
RUN pip install --no-cache-dir --trusted-host my-artifactory.company.local -r requirements.txt -r requirements-test.txt -r requirements-dev.txt --index-url http://my-artifactory.company.local:8081/artifactory/api/pypi/pypi-local-deps/simple --disable-pip-version-check
The main line, which solved the issue in my case, was using the NO_PROXY (as listed above).
Any issues related to pip module not found, or module version not found, or any SSL errors SSLError(SSLCertVerificationError like errors, went away after applying the above NO_PROXY at cmd line or in Dockerfile:
WARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1091)'))': /simple/requests/
or
ERROR: Could not find a version that satisfies the requirement requests
ERROR: No matching distribution found for requests
or
ERROR: Could not find a version that satisfies the requirement numpy==1.16.2
ERROR: No matching distribution found for numpy==1.16.2
You can also follow this steps here
Select: Workloads → Desktop development with C++, then for Individual Components, select only:
Can also achieve the same automatically using the following command:
vs_buildtools.exe --norestart --passive --downloadThenInstall --includeRecommended --add Microsoft.VisualStudio.Workload.NativeDesktop --add Microsoft.VisualStudio.Workload.VCTools --add Microsoft.VisualStudio.Workload.MSBuildTools
Go to the link and download vs_buildtools.exe
I did that and it worked. Good Luck!
I had the same error with OpenCV, upgrading the pip version solved the issue:
python -m pip install --upgrade pip
After the update the error is gone.
I had a similar issue and was told that Pandas no longer supports Python 3.4 so you will need to install an older version of Pandas (and perhaps an older version of numpy) to work with Python 3.4.
Not terribly satisfying I know but there it is.
I had the same issue installing pandas from source, branch 0.22.x. I followed these steps and obtained this error:
$ python -m pip install -e .
Obtaining file:///Users/mmorin/Software/pandas
Could not find a version that satisfies the requirement numpy==1.9.3 (from versions: 1.11.3, 1.12.0rc2, 1.12.0, 1.12.1rc1, 1.12.1, 1.13.0rc1, 1.13.0rc2, 1.13.0, 1.13.1, 1.13.3, 1.14.0rc1, 1.14.0, 1.14.1, 1.14.2, 1.14.3)
No matching distribution found for numpy==1.9.3
I found this issue on GitHub where @djhoese suggested using version 9.0.3 of pip instead of version 10.0.1. I added this line in ci/environment-dev.yaml:
- pip==9.0.3
I gave the environment a new name for clarity, so the whole file is:
name: pandas-dev-pip9
channels:
- defaults
- conda-forge
dependencies:
- Cython
- NumPy
- moto
- pytest
- python-dateutil
- python=3
- pytz
- setuptools
- sphinx
- pip==9.0.3
Numpy is notoriously difficult to install as it contains dependencies (optional or selectable) on various non-Python packages. I would suggest to use a different environment manager such as Enthought or Anaconda (which I would recommend).
If you want to do a quick start, use the full-blown anaconda distribution. If you need more explicit control, use miniconda.
Once you have anaconda installed, all you need to do to create a new conda environment (similar to a virtual environment, but with non-python packages included in the environment itself) is
conda create -n my_shining_environment quandl
The above will include quandl (at the time of writing v3.3.0), numpy and all other dependencies for quandl.
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import numpy; print(numpy.__version__)? – Crucialnumpyand it doesn't seem to be available in pip anymore. Is there a reason for that specific requirement? You could search for an archive of the old version, but you might have better luck finding a newer version ofquandlthat works with current versions ofnumpy– Lammastidequandl. A well written package shouldn't depend on a subversion like that. It's ok to expect something newer than 1.9.3 but not exactly that. That's too fragile. – Fluctuationpip/pip3issue? – Crucial