I'd like to install the pymongo library but I'm getting the following error:
(C:\Users\xxxxxxx\AppData\Local\Continuum\anaconda3) C:\Users\xxxxxxx>
conda install -c anaconda pymongo
Fetching package metadata ...
CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://conda.anaconda.org/a
naconda/win-64/repodata.json>
Elapsed: -
An HTTP error occurred when trying to retrieve this URL.
HTTP errors are often intermittent, and a simple retry will get you on your way.
ConnectTimeout(MaxRetryError("HTTPSConnectionPool(host='conda.anaconda.org', por
t=443): Max retries exceeded with url: /anaconda/win-64/repodata.json (Caused by
ConnectTimeoutError(<urllib3.connection.VerifiedHTTPSConnection object at 0x000
00000054D6128>, 'Connection to conda.anaconda.org timed out. (connect timeout=9.
15)'))",),)
Steps taken to resolve:
1. Update C:\Users\\xxxxxxx\.condarc file with the following:
channels:
- defaults
ssl_verify: false
proxy_servers:
http: http://sproxy.fg.xxx.com:1000
https: https://sproxy.fg.xxx.com:1000
2. (C:\Users\xxxxxxx\AppData\Local\Continuum\anaconda3) C:\Users\xxxxxxx>
conda config --set ssl_verify False
Additional Info:
(C:\Users\xxxxxxx\AppData\Local\Continuum\anaconda3) C:\Users\xxxxxxx>
conda info
Current conda install:
platform : win-64
conda version : 4.3.27
conda is private : False
conda-env version : 4.3.27
conda-build version : 3.0.22
python version : 3.6.2.final.0
requests version : 2.18.4
config file : C:\Users\xxxxxxx\.condarc
netrc file : None
offline mode : False
user-agent : conda/4.3.27 requests/2.18.4 CPython/3.6.2 Windows/7 W
indows/6.1.7601
administrator : False
A number of posts online simply reinstalled Anaconda, any other options apart from a fresh install?
This works a charm:-
Just copy these:-
libcrypto-1_1-x64.dll
libssl-1_1-x64.dll
from D:\Anaconda3\Library\bin to D:\Anaconda3\DLLs.
Execute the following command in the cmd prompt/terminal:
conda config --set ssl_verify no
I try to create a virtual env with python 2.7 with anaconda, the base env is python 3.7. I encounter the exactly same problem. It turns out that there isn't such problem with other virtual envs with python 3.7 or 3.6.
This post works perfectly to solve my problem on win7 with anaconda prompt.
It basically says you need to add the following directories into your user environment path in windows (go to Start and type in: View Advanced System Settings, then select Environmental Variables: then select Path and click Edit: finally you can click New and add a path):
C:\your_directory_to_anaconda3\Anaconda3\Scripts
C:\your_directory_to_anaconda3\Anaconda3\
C:\your_directory_to_anaconda3\Anaconda3\Library\bin -- This is the directory for openssl
If you added conda to your PATH variables, remove it and use the "Anaconda Prompt". This solved the problem for me.
See: https://github.com/conda/conda/issues/8046#issuecomment-450582208
I faced this issue when I tried to create environment. I solved it by first activating conda base environment by using:
conda activate base
then I created the environment
conda create -n myenv python=3.7
Check the proxy URL
Verify .condarc file
For me, the problem was with the indentation in the .condarc file.
proxy_servers:
http: http://testproxy:8080
https: https://testproxy:8080
My authenticated proxy server is configured with a domain whitelist for massive and repeated downloads so root or local sudoer doesn't need to be authenticated.
Adding conda.anaconda.org is not enough as this repo redirect its traffic to amazonaws.com.
In my case, adding ".amazonaws.com" to the whitelist solved the issue.
The issue was resolved by adding a username and password to file C:\Users\xxxxx.condarc
channels:
- defaults
ssl_verify: false
proxy_servers:
http: http://xxxxx:password#sproxy.fg.abc.com:yyyy
https: https://xxxxx:password#sproxy.fg.abc.com:yyyy
I had the same problem on Windows 10-64 bit and intuitively installed the 64-bit version of miniconda. However, it results in exactly the same error above. Installing 32 bit conda installer has resolved the issue
Before installing some package (pydicom) the installation run just fine. After
it I tried to install matplotlib, but I got the same error as yours.
I tried conda config --set ssl_verify no but it didn't solve the problem so I set it again to true.
Fortunately, I had a virtual environment where I installed my packages. I closed all Anaconda prompts and tried in a new test environment. Magically, the install worked. I came back to my original virtual env and run the install again, and it worked!.
It might be that I just had to wait for some time before I could use conda install again.
One other thing I could do is remove the package that caused the problem, but I didn't have the chance to try it. If it has anything to do with some virtual environments not being affected, then one possible way to guard against this is to clone the environment before installing any new package.
Edit: I tried the same solution but It did not work. But instead of showing the error immediately, it asks me whether I want to proceed. I deactivated the env, and re-opened anaconda prompt, then did the same steps as above and worked again.
I also had the Same Issue, I resolved by installing 32 bit Anaconda Installer.
Which resolved the CondaHTTPError: HTTP 000 CONNECTION, on Windows 64 bit.
I faced this issues after "conda clean -a" on win-64.
Activating and deactivating existing conda env resolved the issue.
You might need to upgrade your openssl installation
You can download it here (Try the latest version):
https://slproweb.com/products/Win32OpenSSL.html
Source:
https://github.com/ContinuumIO/anaconda-issues/issues/6424#issuecomment-464660808
My issue was simply not running the conda init command prior to attempting to create an environment.
Came across the CondaHTTP Connection error after installing Anaconda environment on a new Windows 10 computer. I tried virtually all the recommendations above unsuccessfully! Looking up the Anaconda archives ( https://repo.continuum.io/archive/ ), I downloaded the immediate previous release .... and on installation and rebooting my PC, all is now wellscreenshot of release
In short - installing Microsoft Visual C++ Redistributable for Visual Studio solved my problem.
In more detail: upon trying a suggested solution of installing a new version of OpenSSL, the installation process told me I was missing a dependency - the Visual Studio Redistributable package. The installer led me to a direct download page of the 2017 version. I can't find that page now, but the official release of 2019 can be found here, and should work as well (found under Other Tools and Frameworks).
Uninstalling and reinstalling anaconda for all users (instead, of current user only, requires admin privileges) and activating the option to add Anaconda to PATH during the installation process, fixed the issues for me.
Thank you everyone for your responses. In my case, I found out that my Kaspersky Internet Security was blocking it the whole time. The moment I quit the application all applications were downloaded. Please check your firewall settings before trying all the above options.
I tried all of these solutions and none worked for me. After running the command
conda config --remove-key channels
in the Anaconda Prompt, everything started working for me on my next attempt.
Adding that I had the same problem on ubuntu on WSL. None of the solutions worked for me, until I realized I was working on WSL version 1 (I thought I'd already upgraded). Upgrading from WSL 1 to WSL 2 solved the problem for me.
Running following these two commands worked for me.
conda config --remove-key proxy_servers
conda clean --source-cache
I'd tried all of the advice on this and many other webpages.
In the end I broadcast a "help me Obiwan Kenobi, you're my only hope message" to a large group of people at work and one of them who used python all the time was able to help me
The trick was to set several windows environmental variables
CURL_CA_BUNDLE
REQUESTS_CA_BUNDLE
SSL_CERT_FILE
To my company's root certificate (a .cer or .crt) which I had downloaded to a spot on my disk
You may also need to add (in my case)
C:\Users\kdalbey\Anaconda3\Scripts
(or your particular \Anaconda3\Scripts) to your path.
And then I set proxies just for good measure
note I previously copied libcrypto-1_1-x64.dll, libcrypto-1_1-x64.pdb, libssl-1_1-x64.dll, libssl-1_1-x64.pdb from anaconda3\Library\bin to anaconda3\DLLs so that could be part of the secret sauce
and it didn't work until I killed and restarted anaconda-navigator
Two steps to deal with this error.
The Anaconda prompt configures the path, to include all the necessary executable files (for instance Library\bin - On Windows, launch it with admin permission). So that you need to use it to execute conda :
Update conda with conda update conda
Exit my proxy software which solved the issue.
I would like summarize some of the proposed answers in this post and propose my experience on that. As it can be understood from the error explanation, the error is related to the connection and I strongly believe that no need to uninstall and reinstall anything if the real cause of the problem be known. My problem gone away after the system powered off and powered on again one day later. So, some possible causes and their solutions (these solutions could be tested in order based on the written bulleted order) could be as follows:
Crash in anaconda prompt:
Probable solutions:
Deactivating and activating the environment, without removing all packages or …, or
Closing/reopening the prompt (Michael Heidelberg) or
Using cmd.exe instead, perhaps
Non-responsiveness of the anaconda site:
Massive site traffics related probable issues, that could be the reason of non-responsiveness or to temporary block some IPs
Probable solutions:
Retying as recommended in the error: HTTP errors are often intermittent, and a simple retry will get you on your way. It solves my problem sometimes. or
Activate or deactivate VPNs or Proxies (like use in .condarc; see: Github sroder, Nandhan Thiravia, Vinod Sangale, Peter Lucas, Sunding Wei).
Try after a while if you have time
System firewall block the site:
That might be happened by activating and deactivating of VPNs, repeatedly or by some other works
Probable solutions:
Finding the issue in system firewall and allowing the connection in the firewall settings (ScienceJedi, Github)
Reboot, perhaps
If the aforementioned ways didn't solve the problem, testing the related answers in the following order:
Add ...\Anaconda3\Scripts, ...\Anaconda3\, and ...\Anaconda3\Library\bin to the path (talentcat, skerjj, Victor Ochieng, jankap), perhaps need a reboot after (lightarrow)
Copying libcrypto-1_1-x64.dll and libssl-1_1-x64.dll from D:\Anaconda3\Library\bin into D:\Anaconda3\DLLs (Swapnil)
I think it could be used in the first step because It is unlikely to be cause of any other problem. The reason I didn't mention this at the beginning is that the developers could placed these files in that directory during installation, too, in default, but they didn't; perhaps it had some reasons (Github).
Note: these files are for Python >3, and I didn't find them for Python 2. Perhaps they have another names.
It must be said that my problem didn't solve by this solution.
Keep your SSL stack up-to-date (kamal dua, Anaconda troubleshooting, update openssl, Abdulrahman Bres, Update to openssl 1.1.1)
I didn't recommend it at first because Its not a good idea to unset ssl verification unless you know what you are doing (Pratyush comment) and somewhere I read that it couldn't return to True again.
It must be said that my problem didn't solve by this solution, too.
conda config --set ssl_verify false
conda update openssl ca-certificates certifi
my first posting on setting up Yocto development environment
on my Ubuntu system (Ubuntu 18.04.3 LTS/bionic), based on the information enclosed in the document from
this web link (https://www.yoctoproject.org/docs/current/brief-yoctoprojectqs/brief-yoctoprojectqs.html).
All is well until... ~/poky/build$ bitbake core-image-sato
which results in this error:
File "/usr/local/lib/python3.5/sqlite3/dbapi2.py", line 27, in <module>
from _sqlite3 import *
ImportError: No module named '_sqlite3'
Below is my effort to proceed past this error, which didn't resolve the
error above. Please be generous and provide some guidance. I searched for
relevant posting locations; any advice on a better place is appreciated.
Thank you.
------------------------------------------------
A web search on this error () results in:
How to Use SQLite in Ubuntu | Chron.com
with
~/poky/build$ sudo apt-get install sqlite3 libsqlite3-dev
which tells me this:
Reading package lists... Done
Building dependency tree
Reading state information... Done
libsqlite3-dev is already the newest version (3.22.0-1ubuntu0.1).
sqlite3 is already the newest version (3.22.0-1ubuntu0.1).
The following packages were automatically installed and are no longer
required:
linux-headers-5.0.0-23 linux-headers-5.0.0-23-generic linux-image-5.0.0-23-generic linux-modules-5.0.0-23-generic
linux-modules-extra-5.0.0-23-generic
Use 'sudo apt autoremove' to remove them.
0 upgraded, 0 newly installed, 0 to remove and 12 not upgraded.
So, evidently sqlite3 exists on my system. Here are the SO references that I checked:
[ImportError: No module named '_sqlite3' in python3.3][1]
[importerror no module named '_sqlite3' python3.4][2]
[ImportError: No module named _sqlite3 (even after doing eveything)][3]
[ImportError: No module named _sqlite3][4]
[1]: https://stackoverflow.com/questions/20126475/importerror-no-module-named-sqlite3-in-python3-3
[2]: https://stackoverflow.com/questions/24052137/importerror-no-module-named-sqlite3-python3-4
[3]: https://stackoverflow.com/questions/35889383/importerror-no-module-named-sqlite3-even-after-doing-eveything
[4]: https://stackoverflow.com/questions/2665337/importerror-no-module-named-sqlite3
I have just kicked off a build verifying the Brief-Quickstart steps verbatim on an otherwise fresh Ubuntu 18.04 install. There is not even SQLite installed at all, yet the build proceeds nicely. So the chances are pretty high the python installation in your development host is busted in some way or the other. Yet, there might be reasons for it:
you maybe selected python 3.5 explicitly because some other thing you did requires it
you maybe selected python 3.5 implicitly because you forwarded from on old installation, installed something that depended on it, or similar.
In any case, I'd guess that now tinkering with the link might break things somewhere else on your machine, which should be avoided IMHO.
So what are your options now? My advice would be to start building in a container, in the simplest for that requires no more than installing docker and kicking off docker run -it ubuntu:bionic /bin/bash - at least to verify things are generally working.
In the longer term you might want to make a specialized container for this with one or two additions:
1) have all the needed packages set up already
2) using a standard user instead of root.
This is the way I do things personally. An alternative would be to use the prepared things by CROPS as it is a known good solution, and it significantly reduces problems originating from host system pecularities.
I'm trying to make julia language available through jupyterhub on an ubuntu server.
I already have installed and configured the jupyterhub. Its working fine with python3.5.
And the authentication method is Regular Unix users and PAM.
I installed the julia language in /usr/local/julia-1.0.2/ and it is available for all users globally.
then with the root user I set the JULIA_DEPOT_PATH="/usr/share/juliapackages/
then again with the root user, I run the julia and run the
using Pkg
Pkg.add("IJulia")
it installs the IJulia in the specified path.
from this point, I didn't find any further useful instructions on the internet over the subject of installing julia kernel for jupyterhub, so I don't know how to proceed.
does anybody have a good step by step document to find the solution?
I followed the instruction proposed here but it seems doesn't work for me.
As you are using Jupyterhub, the best way would be to use a docker spawner and use the data science docker image which has Julia already installed and configured.
https://github.com/jupyter/docker-stacks/blob/master/datascience-notebook/Dockerfile
I'd like to discover the guile ecosystem. I looked at how to install a library and I didn't find a package manager, like python's pip. Does such a thing exist for guile ?
Looks like guildhall is the closest thing to pip out there. There has been some discussion on the Guile mailing lists recently around it. The posts by Wingo, Boubekki, Zaretskii, and a few others who are heavily involved with Guile development indicate a push towards making guildhall an upstream source for something called Guix that is a more general package manager intended to be independent of platform.
If you consult the Guix list of packages you will see guile there and a number of other guile related items (e.g. guile-json, guile-ncurses, etc..). I'd give that a shot. Otherwise you're on your own and you'll have to either fall back to the OS package manager or pull down the source yourself, build, and install.
Full disclosure: I haven't tried Guix myself but I've been meaning to. I'd be very interested to see how it turns out for you so if you do go this route it'd be awesome if you could provide an update with your Guix experience.
There's also been a recent call to update the libraries page and from a quick inspection there's been some small number of updates that you may find useful.
#unclejamil This is an update of my attempt to install the guix package manager.
Documentation
First of all, the links:
the official page: https://www.gnu.org/software/guix/
the download page: http://alpha.gnu.org/gnu/guix/ (guix-the-system and guix the package manager are listed together)
Installation (Debian)
Guix needs Guile-2.0-dev and more dependencies, which are present in Debian's repositories:
apt-get install guile-2.0-dev guile-2.0 libgcrypt20-dev libbz2-dev libsqlite3-dev autopoint
Download guix. See the above links to download a binary. Or get the sources:
git clone git://git.savannah.gnu.org/guix.git
The installation goes with a classical ./configure && make && make install.
make will take several minutes and make install needs root access. If you install from source, make will build guile objects of the 346 base packages (python, zsh, abiword,…) so it'll take a long time (the database is included into guix-the-program, so we must do that. You can still tweak this list in the Makefile, at MODULES) .
Note: Your current directory must not contain non ascii characters.
Note: see also this complete tutorial, with the focus on how to install guix locally, i.e. not to run make install: http://dustycloud.org/blog/guix-package-manager-without-make-install/
Usage
To install packages with guix, we need a running server.
The first method, for testing purposes, is simply to run the server in a terminal:
sudo guix-daemon
and the client in another one:
guix package -s "guile.*curses" # search with regexps
sudo guix package -i guile-ncurses # install. All start with the "package" command.
For the proper method, see https://www.gnu.org/software/guix/manual/html_node/Build-Environment-Setup.html#Build-Environment-Setup
To be continued.
This answer is a community wiki, feel free to complete it, thanks !
I am building Guix right now and encountered the same error about not finding guile-2.0. I managed to fix it by installing the development files for guile-2.0
sudo apt-get install guile-2.0-dev
I encountered some more errors later on and it just meant I needed to install the development files for it.
I'm new to R and I decided to put R on a machine I have and see if I can remotely run code that is on my desktop computer.
While searching for "how to do" that, I came across the names "Rserve" and "RStudio". As far as I could tell, RServe is a package (actually, it seems to be the package) which I can use to configure the server, while RStudio is an IDE.
My question is: does RStudio use RServe "under the hood"? And, if it doesn't, then how does RStudio compare to RServe? (I.e., which one is better and why?)
[I figured out that this question could possibly be a duplicate, but I couldn't find any similar question]
Rserve is a client server implemenation written in pure c that starts a server and spawns multiple processes each with it's own R workspace. This is not threads but processes due to R's limitation on multithreading. It uses a QAP packing protocol as it's primary form of transport between the client and the server. You execute commands via the client (PHP, Java, C++) to the server and it returns you REXP objects that are essentially mappings to R's underlying SEXP data objects. Rserve also offers a websockets version that does will can transmit data through websockets but the api is not well documented. It also supports basic authentication through a configuration file.
Rstudio is a C++ and gwt application that provides a web based front end to R. AFAIK it uses json as it's primary transport and supports authentication through pam. Each user has a workspace configured in their home directory. It runs a server very similar but not the same as Rserve to communicate with R using RCPP. It also has it's own plotting driver used to wrap the plot device so that it can pickup the plots to be served to the ui. It has much more functionality such as stepping through your code from the ui and viewing workspace variables.
Functionally they are similar in that they provide a client/server connection to R but IMHO the comparison stops there.
I believe they are separate projects (though I could be wrong). I've never heard of RServe and there does not appear to be any mention of it in the documentation for RStudio. I have used and would recommend RStudio Server. It is relatively easy to set up and super easy to use once it is set up. This is a helpful guide to setting up a server on Amazon EC2:
#Create a user, home directory and set password
sudo useradd rstudio
sudo mkdir /home/rstudio
sudo passwd rstudio
#Enter Password
sudo chmod -R 0777 /home/rstudio
#Update all files from the default state
sudo apt-get update
sudo apt-get upgrade
#Be Able to get R 3.0
sudo add-apt-repository 'deb http://cran.rstudio.com/bin/linux/ubuntu precise/'
#Update files to use CRAN mirror
#Don't worry about error message
sudo apt-get update
#Install latest version of R
#Install without verification
sudo apt-get install r-base
#Install a few background files
sudo apt-get install gdebi-core
sudo apt-get install libapparmor1
#Change to a writeable directory
#Download & Install RStudio Server
cd /tmp
wget http://download2.rstudio.org/rstudio-server-0.97.551-amd64.deb
sudo gdebi rstudio-server-0.97.551-amd64.deb
#Once you’ve installed the above commands, you can now access RStudio through your local browser. Navigate to the Public DNS of your image on port 8787, similar to:
#http://ec2-50-19-18-120.compute-1.amazonaws.com:8787
The earlier answer about 3 years old provide old information, such as here.
Updated correction
RStudio is a firm that provides the open source RStudio IDE for R. They also sell commercial services such as RStudio Server Pro that markets itself with load balancing and related things. Apparently, the successuful open source project has lead the way to markets.
You may also mean Microsoft R Server, which is now called Microsoft Machine Learning Server?
There is also RServer by RStudio.
Anyway how to install both can be found here.