Running µGFX on ESP32 and Arduino IDE
Problem bringing up ESP32 ILI9488
LinkedIn: Joel Bodenmann
github.com/Tectu
Blog Post: QtitanRibbon cmake integration
uGFX by Joel Bodenmann
Leave a reply
YouTube: Bert Huang’s Machine Learning and AI
Fall 2015 Machine Learning
- 1.1 Machine Learning
- Types of Machine Learning
- Model Selection in Machine Learning
- 2 Probability and Naive Bayes
- 3 Decision Trees
- 4 Logistic Regression
- 5 Perceptron
- Neural Networks
- 7 Learning Objective Functions
- Back Propagation
- 9 Support Vector Machines
- 10 Dual SVM and Kernels
- 11 Feature Maps and Kernels
- 12 SMO and Stochastic SVM
- 13 Regression
- 14 Principal Component Analysis
- 15 Clustering and Mixture Models
- 16 Variational EM and K Means
- 15.1 GMM Degeneracy
- 17 Probabilistic Graphical Models and Bayesian Networks
- Markov Models
- Hidden Markov Models
- Undirected Graphical Models
- Belief Propagation
- Graphical Models Wrap up
- What is Learning Theory?
- Model Complexity and VC Dimension
- Fairness in Machine Learning
- The Queen is King | Magnus Carlsen vs Fabiano Caruana | Norway Chess 2018
CS4804 Intro to AI, Fall 2016
- Intelligent Agents
- Intro to Search
- Informed Search
- A* Optimality
- Pruning (Alpha-Beta)
- Probability Basics
- More Realistic Adversarial Settings
- Markov Decision Processes
- Passive Reinforcement Learning
- Active Reinforcement Learning
- Logic
- First Order Logic Overview
- Bayesian Networks
- Markov Models
- Hidden Markov Models
- Particle Filters
- Types of Machine Learning
- Model Selection in Machine Learning
- Neural Networks
- Back Propagation
YouTube: Leo Isikdogan’s Image Processing, Deep Learning and CNN
Image and Video Processing
- How Digital Cameras Process Images
- How Image Compression Works
- How Video Compression Works
- Computer Vision vs Image Processing
- How Super Resolution Works
Deep Learning Crash Course
- Deep Learning Crash Course: Introduction | Lecture 1
- Artificial Neural Networks Demystified | Lecture 2
- Artificial Neural Networks: Going Deeper | Lecture 3
- Overfitting, Underfitting, and Model Capacity | Lecture 4
- Regularization | Lecture 5
- Data Collection and Preprocessing | Lecture 6
- Convolutional Neural Networks Explained | Lecture 7
- How to Design a Convolutional Neural Network | Lecture 8
- Transfer Learning | Lecture 9
- Optimization Tricks: momentum, batch-norm, and more | Lecture 10
- Recurrent Neural Networks | Lecture 11
- Deep Unsupervised Learning | Lecture 12
- Generative Adversarial Networks | Lecture 13
- Practical Methodology in Deep Learning | Lecture 14
- Network Architecture Search: AutoML and others
- How to Design a Neural Network | 2020 Edition
- Fast and Efficient Training of Neural Networks (feat. CodeEmporium)
Hands-on Deep Learning: TensorFlow Coding Sessions
Hands-on Deep Learning: TensorFlow Coding Sessions
- TensorFlow Coding Session #1 Introduction
- TensorFlow Coding Session #2 Training a Model
- TensorFlow Coding Session #3 Training and Validation Sets
- TensorFlow Coding Session #4 Regularization, Checkpoints, and TensorBoard
- TensorFlow Coding Session #5 Convolutional Neural Networks
- TensorFlow Coding Session #6 TFRecords and Freezing Models
- TensorFlow Coding Session #7 Transfer Learning
- What is new in TensorFlow 2.0 | Tutorial
Keras: Regression
TensorFlow
Basic regression: Predict fuel efficiency
Adrian Rosebrock
Regression with Keras
Keras, Regression, and CNNs
Keras: Multiple Inputs and Mixed Data
Div
Regression Tutorial with the Keras Deep Learning Library in Python
Regression with Keras
A Convolutional Neural Network Tutorial in Keras and Tensorflow 2
Non Linear Regression Example with Keras and Tensorflow Backend
Deep Learning Nonlinear Regression
YouTube
TensorFlow
Get started with using TensorFlow to solve for regression problems (Coding TensorFlow)
Jeff Heaton
Keras Regression for Deep Neural Networks with RMSE (4.3)
5.3: Regression Neural Networks for Keras and TensorFlow (Module 5, Part 3)
Hello World HD
ESP32 TFT LCD with Touchscreen
- TFT: ILI9488
- Touchscreen: XPT2046
Hardware
3.5inch SPI Module ILI9488 SKU:MSP3520
Display- and Touch-Driver
TFT_eSPI
TFT_eSPI
github.com/Bodmer/TFT_eSPI, Arduino and PlatformIO IDE compatible TFT library optimised for the STM32, ESP8266 and ESP32 that supports different driver chips
github.com/Bodmer/TFT_eFEX, A support library for TFT_eSPI that adds commonly used extra functions
GUI Library
LittlevGL
by Gábor Kiss-Vámosi
LittlevGL
Espressif officially supports LittlevGL on ESP32! Let’s try it!
ESP32 LittlevGL Guide
Source
github.com/littlevgl/lvgl, Powerful and easy-to-use embedded GUI with many widgets, advanced visual effects (opacity, antialiasing, animations) and low memory requirements (16K RAM, 64K Flash)
github.com/littlevgl/lv_arduino, LittlevGL as Arduino Library + example sketch (also ESP32!!)
github.com/littlevgl/lv_port_esp32, LittlevGL ported to ESP32 including various display and touchpad drivers
github.com/littlevgl/lv_drivers, TFT and touch pad drivers for LittlevGL embedded GUI library
github.com/littlevgl/lv_examples/, Examples, tutorials and applications for the LittlevGL embedded GUI library
github.com/littlevgl/lv_binding_micropython, LittlevGL bindings to other languages
Documentation
FabGL
FabGL – ESP32 Display Controller and Graphics Library
github.com/fdivitto/fabgl, Display Controller (VGA, SSD1306), PS/2 Mouse and Keyboard Controller, Graphics Library, Sound Engine, Game Engine and ANSI/VT Terminal for the ESP32
AWind
AWind library
github.com/AndreiDegtiarev/AWind, Arduino window library for TFT and OLED displays
Showcase
Gábor Kiss-Vámosi
GUI on ESP32 with 30 FPS using LittlevGL
That Project
ESP32 | LittlevGL | Arduino IDE – [Part.0] Touch Display Setup for Simple Note App
ESP32 | LittlevGL | Arduino IDE – [Part.1] Basic LittlevGL for Simple Note App
ESP32 | LittlevGL | Arduino IDE – [Part.2] By LittlevGL for Simple Note App
Martin Harizanov
TFT32 – IoT gateway/control hub with TFT
ESP32 with ILI9488 TFT+touch (LittlevGL)
ScarsFun
github.com/ScarsFun/pc_simulator, Qt-Creator project to run LittlevGL PC Simulator for Windows
hackaday.io/ScarsFun
STM32f103 LittleVgl (V6.0) demo. ILI9341, XPT2046, no OS
github.com/ScarsFun/lvgl_STM32F103_ILI9341_XPT2046, Littlevgl test for STM32F103 with ILI9341 and XPT2046 no OS.
GUI on ESP32 with 30 FPS using LittlevGL
ESP32 Project – Fast Jpeg images in 3.2-inch TFT LCD (ILI9341)
Pi4IoT YouTube Video
Raspberry I2C Sensoric
- Web Control of Raspberry via WebSocket (3)
- Alarm Clock
- Atmega48 at Raspberry
- LED and button on GPIO
- Raspberry als Websever
- Web Control of Raspberry Pi (2)
- Backup
- Thermocouple at Raspberry Teil 5 (MCP3421)
- Raspberry PI I2C Teil 4 (PCF8591T)
- Raspberry PI I2C Teil 3 (TSL2561)
- Raspberry PI I2C Teil 2 (HIH-6130)
- Raspberry PI I2C Teil 1 (8574TS)
- Anschluss I2C am Raspberry PI
- Web Control of Raspberry Pi (1)
- 3D Printing a Raspberry Pi Case
- PI-TOP the Raspberry Pi Laptop
- Power consumption of Raspberry Pi A+ vs B+
Arduino / Raspberry / Bluetooth
Arduino / Raspberry / Bluetooth
- Raspberry & Arduino via Bluetooth Part #1 – Introduction and Overview
- Raspberry & Arduino via Bluetooth Part #2 – Install Teensy-LC
- Raspberry & Arduino via Bluetooth Part #3 – Use Nokia 5110 LCD
- Raspberry & Arduino via Bluetooth Part #4 – Use Humidity Sensor SHT75
- Raspberry & Arduino via Bluetooth Part #5 – RN-42 Bluetooth Module
- Raspberry & Arduino via Bluetooth Part #6 – SHT75 Data – Node-RED
- How to communicate between Raspberry and Arduino over Bluetooth
Python
- Python GUI Example Part#2 – Create a new Project
- Python GUI Example Part#3 – Control NeoPixel Digital RGB LED with sliders
- Python GUI Example Part#1 – Install Python IDE & Tools on Raspberry Pi
- Python GUI Example Part#4 – Advanced Python Graphical Application PyQt5
- Ethernet – MODBUS – WAGO 750-352 – Example with Python
- Making a start menu for the “Raspberry Game HAT” in Python.
- Making a start menu for the “Raspberry Game HAT” in Python.
ESP32
- ESP32 Module with OLED Part #1 – Install MicroPython
- ESP32 Module with OLED Part #2 – Use the OLED Display
- M5Stack Faces Kit Part#1 – Unboxing and First Test with ESPlorer IDE and PuTTY
- M5Stack Part#2 – Arduino IDE (install Board and Library)
- Water Consumption Meter with ESP8266
Control NeoPixel Digital RGB LED with sliders
github.com/Pi4IoT/WS2812-LED-Strips
Raspberry Pi & WS2812 LED-Strips
adafruit
NeoPixels on Raspberry Pi
CircuitPython on Linux and Raspberry Pi
DeepFakes: First Order Motion Model for Image Animation, Aliaksandr Siarohin
First Order Motion Model for Image Animation, Paper
First Order Motion Model for Image Animation, Website
github.com/AliaksandrSiarohin/first-order-model, This repository contains the source code for the paper First Order Motion Model for Image Animation
Aliaksandr Siarohin, PhD student, Doctoral programme – Information and Communication Technology
Everybody Can Make DeepFakes Now!, Two Minute Papers
Chip Marker: Finding pin 1
Keras
(base) C:\Users\andreas>conda env remove --name compvis
(base) C:\Users\andreas>conda create --name compvis python=3.7
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: C:\Users\andreas\Miniconda3\envs\compvis
added / updated specs:
- python=3.7
The following packages will be downloaded:
package | build
---------------------------|-----------------
python-3.7.7 |h60c2a47_0_cpython 14.8 MB
------------------------------------------------------------
Total: 14.8 MB
The following NEW packages will be INSTALLED:
ca-certificates pkgs/main/win-64::ca-certificates-2020.1.1-0
certifi pkgs/main/win-64::certifi-2019.11.28-py37_1
openssl pkgs/main/win-64::openssl-1.1.1e-he774522_0
pip pkgs/main/win-64::pip-20.0.2-py37_1
python pkgs/main/win-64::python-3.7.7-h60c2a47_0_cpython
setuptools pkgs/main/win-64::setuptools-46.1.3-py37_0
sqlite pkgs/main/win-64::sqlite-3.31.1-he774522_0
vc pkgs/main/win-64::vc-14.1-h0510ff6_4
vs2015_runtime pkgs/main/win-64::vs2015_runtime-14.16.27012-hf0eaf9b_1
wheel pkgs/main/win-64::wheel-0.34.2-py37_0
wincertstore pkgs/main/win-64::wincertstore-0.2-py37_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
python-3.7.7 | 14.8 MB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate compvis
#
# To deactivate an active environment, use
#
# $ conda deactivate
(base) C:\Users\andreas>conda activate compvis (compvis) C:\Users\andreas>conda install -c conda-forge jupyter scikit-learn scikit-image matplotlib ipywidgets tqdm keras notebook seaborn pandas opencv
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: C:\Users\andreas\Miniconda3\envs\compvis
added / updated specs:
- ipywidgets
- jupyter
- keras
- matplotlib
- notebook
- scikit-image
- scikit-learn
- tqdm
The following packages will be downloaded:
package | build
---------------------------|-----------------
_tflow_select-2.2.0 | eigen 3 KB
absl-py-0.9.0 | py37hc8dfbb8_1 162 KB conda-forge
bleach-3.1.4 | pyh9f0ad1d_0 111 KB conda-forge
blinker-1.4 | py_1 13 KB conda-forge
cachetools-3.1.1 | py_0 11 KB conda-forge
certifi-2019.11.28 | py37hc8dfbb8_1 149 KB conda-forge
cffi-1.14.0 | py37ha419a9e_0 222 KB conda-forge
chardet-3.0.4 |py37hc8dfbb8_1006 189 KB conda-forge
click-7.1.1 | pyh8c360ce_0 64 KB conda-forge
cryptography-2.8 | py37hb32ad35_1 564 KB conda-forge
cytoolz-0.10.1 | py37hfa6e2cd_0 336 KB conda-forge
dask-core-2.13.0 | py_0 596 KB conda-forge
entrypoints-0.3 |py37hc8dfbb8_1001 12 KB conda-forge
freetype-2.10.1 | ha9979f8_0 481 KB conda-forge
gast-0.2.2 | py_0 10 KB conda-forge
google-auth-1.12.0 | pyh9f0ad1d_0 52 KB conda-forge
google-auth-oauthlib-0.4.1 | py_2 18 KB conda-forge
google-pasta-0.2.0 | pyh8c360ce_0 42 KB conda-forge
grpcio-1.27.2 | py37h351948d_0 1.2 MB
h5py-2.10.0 |nompi_py37h422b98e_102 950 KB conda-forge
idna-2.9 | py_1 52 KB conda-forge
importlib-metadata-1.6.0 | py37hc8dfbb8_0 42 KB conda-forge
importlib_metadata-1.6.0 | 0 3 KB conda-forge
ipykernel-5.2.0 | py37h5ca1d4c_1 161 KB conda-forge
ipython-7.13.0 | py37hc8dfbb8_2 1.1 MB conda-forge
jedi-0.16.0 | py37hc8dfbb8_1 772 KB conda-forge
jsonschema-3.2.0 | py37hc8dfbb8_1 108 KB conda-forge
jupyter_client-6.1.2 | py_0 74 KB conda-forge
jupyter_console-6.1.0 | py_1 21 KB conda-forge
jupyter_core-4.6.3 | py37hc8dfbb8_1 94 KB conda-forge
keras-2.3.1 | py37h21ff451_0 591 KB conda-forge
kiwisolver-1.1.0 | py37heaa310e_1 61 KB conda-forge
libpng-1.6.37 | hfe6a214_1 1.4 MB conda-forge
libtiff-4.1.0 | h885aae3_6 1020 KB conda-forge
markupsafe-1.1.1 | py37h8055547_1 28 KB conda-forge
matplotlib-3.2.1 | 0 6 KB conda-forge
matplotlib-base-3.2.1 | py37h911224e_0 7.1 MB conda-forge
mistune-0.8.4 |py37hfa6e2cd_1000 53 KB conda-forge
mkl-service-2.3.0 | py37hb782905_0 210 KB
nbconvert-5.6.1 | py37_0 506 KB conda-forge
notebook-6.0.3 | py37_0 7.7 MB conda-forge
numpy-1.18.1 | py37h90d3380_1 4.7 MB conda-forge
oauthlib-3.0.1 | py_0 82 KB conda-forge
opt_einsum-3.2.0 | py_0 49 KB conda-forge
pickleshare-0.7.5 |py37hc8dfbb8_1001 12 KB conda-forge
pillow-7.0.0 | py37h91e7a8d_1 700 KB conda-forge
prompt-toolkit-3.0.5 | py_0 232 KB conda-forge
prompt_toolkit-3.0.5 | 0 4 KB conda-forge
protobuf-3.11.4 | py37he025d50_0 583 KB conda-forge
pyasn1-0.4.8 | py_0 53 KB conda-forge
pyasn1-modules-0.2.7 | py_0 60 KB conda-forge
pycparser-2.20 | py_0 89 KB conda-forge
pygpu-0.7.6 |py37hc8d92b1_1000 600 KB conda-forge
pyjwt-1.7.1 | py_0 17 KB conda-forge
pyopenssl-19.1.0 | py_1 47 KB conda-forge
pyqt-5.12.3 | py37h6538335_1 4.7 MB conda-forge
pyreadline-2.1 | py37_1001 141 KB conda-forge
pyrsistent-0.16.0 | py37h8055547_0 91 KB conda-forge
pysocks-1.7.1 | py37hc8dfbb8_1 27 KB conda-forge
python_abi-3.7 | 1_cp37m 4 KB conda-forge
pywavelets-1.1.1 | py37hc8d92b1_0 4.3 MB conda-forge
pywin32-227 | py37hfa6e2cd_0 7.0 MB conda-forge
pywinpty-0.5.7 | py37_0 48 KB conda-forge
pyyaml-5.3.1 | py37h8055547_0 155 KB conda-forge
pyzmq-19.0.0 | py37h8c16cda_1 428 KB conda-forge
qtconsole-4.7.2 | pyh9f0ad1d_0 87 KB conda-forge
requests-2.23.0 | pyh8c360ce_2 47 KB conda-forge
requests-oauthlib-1.2.0 | py_0 19 KB conda-forge
rsa-4.0 | py_0 27 KB conda-forge
scikit-image-0.16.2 | py37he350917_0 24.1 MB conda-forge
scikit-learn-0.22.2.post1 | py37h7208079_0 6.1 MB conda-forge
scipy-1.4.1 | py37h9439919_0 11.9 MB
six-1.14.0 | py_1 13 KB conda-forge
tensorboard-2.1.0 | py3_0 3.3 MB
tensorflow-2.1.0 |eigen_py37hd727fc0_0 4 KB
tensorflow-base-2.1.0 |eigen_py37h49b2757_0 35.4 MB
tensorflow-estimator-2.1.0 | pyhd54b08b_0 251 KB
terminado-0.8.3 | py37hc8dfbb8_1 23 KB conda-forge
theano-1.0.4 |py37h6538335_1001 3.7 MB conda-forge
tornado-6.0.4 | py37hfa6e2cd_0 643 KB conda-forge
traitlets-4.3.3 | py37hc8dfbb8_1 133 KB conda-forge
urllib3-1.25.7 | py37hc8dfbb8_1 160 KB conda-forge
wcwidth-0.1.9 | pyh9f0ad1d_0 20 KB conda-forge
werkzeug-0.16.1 | py_0 255 KB conda-forge
widgetsnbextension-3.5.1 | py37_0 1.8 MB conda-forge
win_inet_pton-1.1.0 | py37_0 7 KB conda-forge
wrapt-1.12.1 | py37h8055547_1 45 KB conda-forge
xz-5.2.4 | h2fa13f4_1002 815 KB conda-forge
zstd-1.4.4 | hd8a0e53_2 1.7 MB conda-forge
------------------------------------------------------------
Total: 140.6 MB
The following NEW packages will be INSTALLED:
_tflow_select pkgs/main/win-64::_tflow_select-2.2.0-eigen
absl-py conda-forge/win-64::absl-py-0.9.0-py37hc8dfbb8_1
astor conda-forge/noarch::astor-0.7.1-py_0
attrs conda-forge/noarch::attrs-19.3.0-py_0
backcall conda-forge/noarch::backcall-0.1.0-py_0
blas pkgs/main/win-64::blas-1.0-mkl
bleach conda-forge/noarch::bleach-3.1.4-pyh9f0ad1d_0
blinker conda-forge/noarch::blinker-1.4-py_1
cachetools conda-forge/noarch::cachetools-3.1.1-py_0
cffi conda-forge/win-64::cffi-1.14.0-py37ha419a9e_0
chardet conda-forge/win-64::chardet-3.0.4-py37hc8dfbb8_1006
click conda-forge/noarch::click-7.1.1-pyh8c360ce_0
cloudpickle conda-forge/noarch::cloudpickle-1.3.0-py_0
colorama conda-forge/noarch::colorama-0.4.3-py_0
cryptography conda-forge/win-64::cryptography-2.8-py37hb32ad35_1
cycler conda-forge/noarch::cycler-0.10.0-py_2
cytoolz conda-forge/win-64::cytoolz-0.10.1-py37hfa6e2cd_0
dask-core conda-forge/noarch::dask-core-2.13.0-py_0
decorator conda-forge/noarch::decorator-4.4.2-py_0
defusedxml conda-forge/noarch::defusedxml-0.6.0-py_0
entrypoints conda-forge/win-64::entrypoints-0.3-py37hc8dfbb8_1001
freetype conda-forge/win-64::freetype-2.10.1-ha9979f8_0
gast conda-forge/noarch::gast-0.2.2-py_0
google-auth conda-forge/noarch::google-auth-1.12.0-pyh9f0ad1d_0
google-auth-oauth~ conda-forge/noarch::google-auth-oauthlib-0.4.1-py_2
google-pasta conda-forge/noarch::google-pasta-0.2.0-pyh8c360ce_0
grpcio pkgs/main/win-64::grpcio-1.27.2-py37h351948d_0
h5py conda-forge/win-64::h5py-2.10.0-nompi_py37h422b98e_102
hdf5 conda-forge/win-64::hdf5-1.10.5-nompi_ha405e13_1104
icc_rt pkgs/main/win-64::icc_rt-2019.0.0-h0cc432a_1
icu conda-forge/win-64::icu-64.2-he025d50_1
idna conda-forge/noarch::idna-2.9-py_1
imageio conda-forge/noarch::imageio-2.8.0-py_0
importlib-metadata conda-forge/win-64::importlib-metadata-1.6.0-py37hc8dfbb8_0
importlib_metadata conda-forge/noarch::importlib_metadata-1.6.0-0
intel-openmp pkgs/main/win-64::intel-openmp-2020.0-166
ipykernel conda-forge/win-64::ipykernel-5.2.0-py37h5ca1d4c_1
ipython conda-forge/win-64::ipython-7.13.0-py37hc8dfbb8_2
ipython_genutils conda-forge/noarch::ipython_genutils-0.2.0-py_1
ipywidgets conda-forge/noarch::ipywidgets-7.5.1-py_0
jedi conda-forge/win-64::jedi-0.16.0-py37hc8dfbb8_1
jinja2 conda-forge/noarch::jinja2-2.11.1-py_0
joblib conda-forge/noarch::joblib-0.14.1-py_0
jpeg conda-forge/win-64::jpeg-9c-hfa6e2cd_1001
jsonschema conda-forge/win-64::jsonschema-3.2.0-py37hc8dfbb8_1
jupyter conda-forge/noarch::jupyter-1.0.0-py_2
jupyter_client conda-forge/noarch::jupyter_client-6.1.2-py_0
jupyter_console conda-forge/noarch::jupyter_console-6.1.0-py_1
jupyter_core conda-forge/win-64::jupyter_core-4.6.3-py37hc8dfbb8_1
keras conda-forge/win-64::keras-2.3.1-py37h21ff451_0
keras-applications conda-forge/noarch::keras-applications-1.0.8-py_1
keras-preprocessi~ conda-forge/noarch::keras-preprocessing-1.1.0-py_0
kiwisolver conda-forge/win-64::kiwisolver-1.1.0-py37heaa310e_1
libblas conda-forge/win-64::libblas-3.8.0-15_mkl
libcblas conda-forge/win-64::libcblas-3.8.0-15_mkl
libclang conda-forge/win-64::libclang-9.0.1-default_hf44288c_0
libgpuarray conda-forge/win-64::libgpuarray-0.7.6-hfa6e2cd_1003
liblapack conda-forge/win-64::liblapack-3.8.0-15_mkl
libpng conda-forge/win-64::libpng-1.6.37-hfe6a214_1
libprotobuf conda-forge/win-64::libprotobuf-3.11.4-h1a1b453_0
libsodium conda-forge/win-64::libsodium-1.0.17-h2fa13f4_0
libtiff conda-forge/win-64::libtiff-4.1.0-h885aae3_6
lz4-c conda-forge/win-64::lz4-c-1.8.3-he025d50_1001
m2w64-gcc-libgfor~ pkgs/msys2/win-64::m2w64-gcc-libgfortran-5.3.0-6
m2w64-gcc-libs pkgs/msys2/win-64::m2w64-gcc-libs-5.3.0-7
m2w64-gcc-libs-co~ pkgs/msys2/win-64::m2w64-gcc-libs-core-5.3.0-7
m2w64-gmp pkgs/msys2/win-64::m2w64-gmp-6.1.0-2
m2w64-libwinpthre~ pkgs/msys2/win-64::m2w64-libwinpthread-git-5.0.0.4634.697f757-2
mako conda-forge/noarch::mako-1.1.0-py_0
markdown conda-forge/noarch::markdown-3.2.1-py_0
markupsafe conda-forge/win-64::markupsafe-1.1.1-py37h8055547_1
matplotlib conda-forge/win-64::matplotlib-3.2.1-0
matplotlib-base conda-forge/win-64::matplotlib-base-3.2.1-py37h911224e_0
mistune conda-forge/win-64::mistune-0.8.4-py37hfa6e2cd_1000
mkl pkgs/main/win-64::mkl-2020.0-166
mkl-service pkgs/main/win-64::mkl-service-2.3.0-py37hb782905_0
msys2-conda-epoch pkgs/msys2/win-64::msys2-conda-epoch-20160418-1
nbconvert conda-forge/win-64::nbconvert-5.6.1-py37_0
nbformat conda-forge/noarch::nbformat-5.0.4-py_0
networkx conda-forge/noarch::networkx-2.4-py_1
notebook conda-forge/win-64::notebook-6.0.3-py37_0
numpy conda-forge/win-64::numpy-1.18.1-py37h90d3380_1
oauthlib conda-forge/noarch::oauthlib-3.0.1-py_0
olefile conda-forge/noarch::olefile-0.46-py_0
opt_einsum conda-forge/noarch::opt_einsum-3.2.0-py_0
pandoc conda-forge/win-64::pandoc-2.9.2-0
pandocfilters conda-forge/noarch::pandocfilters-1.4.2-py_1
parso conda-forge/noarch::parso-0.6.2-py_0
pickleshare conda-forge/win-64::pickleshare-0.7.5-py37hc8dfbb8_1001
pillow conda-forge/win-64::pillow-7.0.0-py37h91e7a8d_1
prometheus_client conda-forge/noarch::prometheus_client-0.7.1-py_0
prompt-toolkit conda-forge/noarch::prompt-toolkit-3.0.5-py_0
prompt_toolkit conda-forge/noarch::prompt_toolkit-3.0.5-0
protobuf conda-forge/win-64::protobuf-3.11.4-py37he025d50_0
pyasn1 conda-forge/noarch::pyasn1-0.4.8-py_0
pyasn1-modules conda-forge/noarch::pyasn1-modules-0.2.7-py_0
pycparser conda-forge/noarch::pycparser-2.20-py_0
pygments conda-forge/noarch::pygments-2.6.1-py_0
pygpu conda-forge/win-64::pygpu-0.7.6-py37hc8d92b1_1000
pyjwt conda-forge/noarch::pyjwt-1.7.1-py_0
pyopenssl conda-forge/noarch::pyopenssl-19.1.0-py_1
pyparsing conda-forge/noarch::pyparsing-2.4.6-py_0
pyqt conda-forge/win-64::pyqt-5.12.3-py37h6538335_1
pyreadline conda-forge/win-64::pyreadline-2.1-py37_1001
pyrsistent conda-forge/win-64::pyrsistent-0.16.0-py37h8055547_0
pysocks conda-forge/win-64::pysocks-1.7.1-py37hc8dfbb8_1
python-dateutil conda-forge/noarch::python-dateutil-2.8.1-py_0
python_abi conda-forge/win-64::python_abi-3.7-1_cp37m
pywavelets conda-forge/win-64::pywavelets-1.1.1-py37hc8d92b1_0
pywin32 conda-forge/win-64::pywin32-227-py37hfa6e2cd_0
pywinpty conda-forge/win-64::pywinpty-0.5.7-py37_0
pyyaml conda-forge/win-64::pyyaml-5.3.1-py37h8055547_0
pyzmq conda-forge/win-64::pyzmq-19.0.0-py37h8c16cda_1
qt conda-forge/win-64::qt-5.12.5-h7ef1ec2_0
qtconsole conda-forge/noarch::qtconsole-4.7.2-pyh9f0ad1d_0
qtpy conda-forge/noarch::qtpy-1.9.0-py_0
requests conda-forge/noarch::requests-2.23.0-pyh8c360ce_2
requests-oauthlib conda-forge/noarch::requests-oauthlib-1.2.0-py_0
rsa conda-forge/noarch::rsa-4.0-py_0
scikit-image conda-forge/win-64::scikit-image-0.16.2-py37he350917_0
scikit-learn conda-forge/win-64::scikit-learn-0.22.2.post1-py37h7208079_0
scipy pkgs/main/win-64::scipy-1.4.1-py37h9439919_0
send2trash conda-forge/noarch::send2trash-1.5.0-py_0
six conda-forge/noarch::six-1.14.0-py_1
tensorboard pkgs/main/noarch::tensorboard-2.1.0-py3_0
tensorflow pkgs/main/win-64::tensorflow-2.1.0-eigen_py37hd727fc0_0
tensorflow-base pkgs/main/win-64::tensorflow-base-2.1.0-eigen_py37h49b2757_0
tensorflow-estima~ pkgs/main/noarch::tensorflow-estimator-2.1.0-pyhd54b08b_0
termcolor conda-forge/noarch::termcolor-1.1.0-py_2
terminado conda-forge/win-64::terminado-0.8.3-py37hc8dfbb8_1
testpath conda-forge/noarch::testpath-0.4.4-py_0
theano conda-forge/win-64::theano-1.0.4-py37h6538335_1001
tk conda-forge/win-64::tk-8.6.10-hfa6e2cd_0
toolz conda-forge/noarch::toolz-0.10.0-py_0
tornado conda-forge/win-64::tornado-6.0.4-py37hfa6e2cd_0
tqdm conda-forge/noarch::tqdm-4.44.1-pyh9f0ad1d_0
traitlets conda-forge/win-64::traitlets-4.3.3-py37hc8dfbb8_1
urllib3 conda-forge/win-64::urllib3-1.25.7-py37hc8dfbb8_1
vs2015_win-64 pkgs/main/win-64::vs2015_win-64-14.0.25420-h55c1224_11
wcwidth conda-forge/noarch::wcwidth-0.1.9-pyh9f0ad1d_0
webencodings conda-forge/noarch::webencodings-0.5.1-py_1
werkzeug conda-forge/noarch::werkzeug-0.16.1-py_0
widgetsnbextension conda-forge/win-64::widgetsnbextension-3.5.1-py37_0
win_inet_pton conda-forge/win-64::win_inet_pton-1.1.0-py37_0
winpty conda-forge/win-64::winpty-0.4.3-4
wrapt conda-forge/win-64::wrapt-1.12.1-py37h8055547_1
xz conda-forge/win-64::xz-5.2.4-h2fa13f4_1002
yaml conda-forge/win-64::yaml-0.2.2-hfa6e2cd_1
zeromq conda-forge/win-64::zeromq-4.3.2-h6538335_2
zipp conda-forge/noarch::zipp-3.1.0-py_0
zlib conda-forge/win-64::zlib-1.2.11-h2fa13f4_1006
zstd conda-forge/win-64::zstd-1.4.4-hd8a0e53_2
The following packages will be SUPERSEDED by a higher-priority channel:
ca-certificates pkgs/main::ca-certificates-2020.1.1-0 --> conda-forge::ca-certificates-2019.11.28-hecc5488_0
certifi pkgs/main::certifi-2019.11.28-py37_1 --> conda-forge::certifi-2019.11.28-py37hc8dfbb8_1
openssl pkgs/main::openssl-1.1.1e-he774522_0 --> conda-forge::openssl-1.1.1e-hfa6e2cd_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
python_abi-3.7 | 4 KB | ################### | 100%
ipython-7.13.0 | 1.1 MB | ################### | 100%
pyzmq-19.0.0 | 428 KB | ################### | 100%
werkzeug-0.16.1 | 255 KB | ################### | 100%
google-pasta-0.2.0 | 42 KB | ################### | 100%
matplotlib-base-3.2. | 7.1 MB | ################### | 100%
urllib3-1.25.7 | 160 KB | ################### | 100%
importlib_metadata-1 | 3 KB | ################### | 100%
h5py-2.10.0 | 950 KB | ################### | 100%
jupyter_core-4.6.3 | 94 KB | ################### | 100%
six-1.14.0 | 13 KB | ################### | 100%
matplotlib-3.2.1 | 6 KB | ################### | 100%
idna-2.9 | 52 KB | ################### | 100%
libtiff-4.1.0 | 1020 KB | ################### | 100%
scipy-1.4.1 | 11.9 MB | ################### | 100%
pyasn1-0.4.8 | 53 KB | ################### | 100%
tensorflow-base-2.1. | 35.4 MB | ################### | 100%
prompt_toolkit-3.0.5 | 4 KB | ################### | 100%
certifi-2019.11.28 | 149 KB | ################### | 100%
ipykernel-5.2.0 | 161 KB | ################### | 100%
oauthlib-3.0.1 | 82 KB | ################### | 100%
jupyter_console-6.1. | 21 KB | ################### | 100%
tensorboard-2.1.0 | 3.3 MB | ################### | 100%
traitlets-4.3.3 | 133 KB | ################### | 100%
pyqt-5.12.3 | 4.7 MB | ################### | 100%
pickleshare-0.7.5 | 12 KB | ################### | 100%
mkl-service-2.3.0 | 210 KB | ################### | 100%
kiwisolver-1.1.0 | 61 KB | ################### | 100%
prompt-toolkit-3.0.5 | 232 KB | ################### | 100%
tornado-6.0.4 | 643 KB | ################### | 100%
numpy-1.18.1 | 4.7 MB | ################### | 100%
protobuf-3.11.4 | 583 KB | ################### | 100%
jsonschema-3.2.0 | 108 KB | ################### | 100%
rsa-4.0 | 27 KB | ################### | 100%
wcwidth-0.1.9 | 20 KB | ################### | 100%
grpcio-1.27.2 | 1.2 MB | ################### | 100%
dask-core-2.13.0 | 596 KB | ################### | 100%
tensorflow-estimator | 251 KB | ################### | 100%
qtconsole-4.7.2 | 87 KB | ################### | 100%
terminado-0.8.3 | 23 KB | ################### | 100%
_tflow_select-2.2.0 | 3 KB | ################### | 100%
blinker-1.4 | 13 KB | ################### | 100%
pillow-7.0.0 | 700 KB | ################### | 100%
cryptography-2.8 | 564 KB | ################### | 100%
notebook-6.0.3 | 7.7 MB | ################### | 100%
jupyter_client-6.1.2 | 74 KB | ################### | 100%
xz-5.2.4 | 815 KB | ################### | 100%
wrapt-1.12.1 | 45 KB | ################### | 100%
google-auth-1.12.0 | 52 KB | ################### | 100%
jedi-0.16.0 | 772 KB | ################### | 100%
theano-1.0.4 | 3.7 MB | ################### | 100%
libpng-1.6.37 | 1.4 MB | ################### | 100%
markupsafe-1.1.1 | 28 KB | ################### | 100%
cffi-1.14.0 | 222 KB | ################### | 100%
chardet-3.0.4 | 189 KB | ################### | 100%
widgetsnbextension-3 | 1.8 MB | ################### | 100%
cachetools-3.1.1 | 11 KB | ################### | 100%
cytoolz-0.10.1 | 336 KB | ################### | 100%
pyasn1-modules-0.2.7 | 60 KB | ################### | 100%
pyrsistent-0.16.0 | 91 KB | ################### | 100%
pyjwt-1.7.1 | 17 KB | ################### | 100%
tensorflow-2.1.0 | 4 KB | ################### | 100%
bleach-3.1.4 | 111 KB | ################### | 100%
click-7.1.1 | 64 KB | ################### | 100%
pyyaml-5.3.1 | 155 KB | ################### | 100%
pysocks-1.7.1 | 27 KB | ################### | 100%
keras-2.3.1 | 591 KB | ################### | 100%
entrypoints-0.3 | 12 KB | ################### | 100%
freetype-2.10.1 | 481 KB | ################### | 100%
pywin32-227 | 7.0 MB | ################### | 100%
nbconvert-5.6.1 | 506 KB | ################### | 100%
gast-0.2.2 | 10 KB | ################### | 100%
pygpu-0.7.6 | 600 KB | ################### | 100%
pyreadline-2.1 | 141 KB | ################### | 100%
pycparser-2.20 | 89 KB | ################### | 100%
mistune-0.8.4 | 53 KB | ################### | 100%
pywavelets-1.1.1 | 4.3 MB | ################### | 100%
zstd-1.4.4 | 1.7 MB | ################### | 100%
pywinpty-0.5.7 | 48 KB | ################### | 100%
google-auth-oauthlib | 18 KB | ################### | 100%
absl-py-0.9.0 | 162 KB | ################### | 100%
scikit-learn-0.22.2. | 6.1 MB | ################### | 100%
importlib-metadata-1 | 42 KB | ################### | 100%
requests-oauthlib-1. | 19 KB | ################### | 100%
win_inet_pton-1.1.0 | 7 KB | ################### | 100%
opt_einsum-3.2.0 | 49 KB | ################### | 100%
requests-2.23.0 | 47 KB | ################### | 100%
scikit-image-0.16.2 | 24.1 MB | ################### | 100%
pyopenssl-19.1.0 | 47 KB | ################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: | b'Enabling notebook extension jupyter-js-widgets/extension...\n - Validating: ok\n'
done
C:\Users\andreas>set "KERAS_BACKEND="
C:\Users\andreas>python C:\Users\andreas\Miniconda3\envs\compvis\etc\keras\load_config.py 1>temp.txt
C:\Users\andreas>set /p KERAS_BACKEND= 0<temp.txt
C:\Users\andreas>del temp.txt
C:\Users\andreas>python -c "import keras" 1>nul 2>&1
C:\Users\andreas>if errorlevel 1 (
ver 1>nul
set "KERAS_BACKEND=theano"
python -c "import keras" 1>nul 2>&1
)
C:\Users\andreas>SET DISTUTILS_USE_SDK=1
C:\Users\andreas>SET MSSdk=1
C:\Users\andreas>SET platform=
C:\Users\andreas>IF /I [AMD64] == [amd64] set "platform=true"
C:\Users\andreas>IF /I [] == [amd64] set "platform=true"
C:\Users\andreas>if defined platform (set "VSREGKEY=HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Microsoft\VisualStudio\14.0" ) ELSE (set "VSREGKEY=HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\VisualStudio\14.0" )
C:\Users\andreas>for /F "skip=2 tokens=2,*" %A in ('reg query "HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Microsoft\VisualStudio\14.0" /v InstallDir') do SET "VSINSTALLDIR=%B"
ERROR: The system was unable to find the specified registry key or value.
C:\Users\andreas>if "" == "" (set "VSINSTALLDIR=" )
C:\Users\andreas>if "" == "" (
ECHO "WARNING: Did not find VS in registry or in VS140COMNTOOLS env var - your compiler may not work"
GOTO End
)
"WARNING: Did not find VS in registry or in VS140COMNTOOLS env var - your compiler may not work"
The system cannot find the batch label specified - End
(base) C:\Users\andreas>conda activate compvis
(compvis) C:\Users\andreas>conda install -c conda-forge tqdm
Collecting package metadata (current_repodata.json): done
Solving environment: done
==> WARNING: A newer version of conda exists. <==
current version: 4.8.2
latest version: 4.8.3
Please update conda by running
$ conda update -n base -c defaults conda
## Package Plan ##
environment location: C:\Users\andreas\Miniconda3\envs\compvis
added / updated specs:
- tqdm
The following packages will be downloaded:
package | build
---------------------------|-----------------
certifi-2019.11.28 | py38h32f6830_1 149 KB conda-forge
openssl-1.1.1e | hfa6e2cd_0 4.7 MB conda-forge
tqdm-4.44.1 | pyh9f0ad1d_0 48 KB conda-forge
------------------------------------------------------------
Total: 4.9 MB
The following NEW packages will be INSTALLED:
tqdm conda-forge/noarch::tqdm-4.44.1-pyh9f0ad1d_0
The following packages will be UPDATED:
certifi 2019.11.28-py38h32f6830_0 --> 2019.11.28-py38h32f6830_1
openssl 1.1.1d-hfa6e2cd_0 --> 1.1.1e-hfa6e2cd_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
openssl-1.1.1e | 4.7 MB | ############################################################################ | 100%
tqdm-4.44.1 | 48 KB | ############################################################################ | 100%
certifi-2019.11.28 | 149 KB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(compvis) C:\Users\andreas>conda install -c conda-forge keras
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed
CondaError: KeyboardInterrupt
Terminate batch job (Y/N)? y
(compvis) C:\Users\andreas>conda install keras
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
CondaError: KeyboardInterrupt
Terminate batch job (Y/N)? y
(compvis) C:\Users\andreas>conda install -c anaconda keras
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
- keras -> python[version='>=3.5,<3.6.0a0|>=3.6,<3.7.0a0']
Your python: python=3.8
If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.
(compvis) C:\Users\andreas>conda install -c conda-forge keras
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: \
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
- keras -> python[version='2.7.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.5,<3.6.0a0|3.4.*']
Your python: python=3.8
If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.
(compvis) C:\Users\andreas>conda install python=3.6
Collecting package metadata (current_repodata.json): done
Solving environment: done
==> WARNING: A newer version of conda exists. <==
current version: 4.8.2
latest version: 4.8.3
Please update conda by running
$ conda update -n base -c defaults conda
## Package Plan ##
environment location: C:\Users\andreas\Miniconda3\envs\compvis
added / updated specs:
- python=3.6
The following packages will be downloaded:
package | build
---------------------------|-----------------
blas-1.0 | mkl 6 KB
certifi-2019.11.28 | py36_1 157 KB
cytoolz-0.10.1 | py36he774522_0 303 KB
entrypoints-0.3 | py36_0 12 KB
icu-58.2 | ha66f8fd_1 9.4 MB
ipykernel-5.1.4 | py36h39e3cac_0 172 KB
ipython-7.13.0 | py36h5ca1d4c_0 1010 KB
jedi-0.16.0 | py36_1 768 KB
jsonschema-2.6.0 | py36h7636477_0 102 KB
jupyter_core-4.6.1 | py36_0 86 KB
kiwisolver-1.1.0 | py36ha925a31_0 53 KB
markupsafe-1.1.1 | py36he774522_0 31 KB
matplotlib-3.1.3 | py36_0 22 KB
matplotlib-base-3.1.3 | py36h64f37c6_0 4.9 MB
mistune-0.8.4 | py36he774522_0 55 KB
mkl-service-2.3.0 | py36hb782905_0 210 KB
mkl_fft-1.0.15 | py36h14836fe_0 118 KB
mkl_random-1.1.0 | py36h675688f_0 233 KB
nbconvert-5.6.1 | py36_0 475 KB
notebook-6.0.3 | py36_0 4.3 MB
numpy-1.18.1 | py36h93ca92e_0 6 KB
numpy-base-1.18.1 | py36hc3f5095_1 3.8 MB
openssl-1.1.1e | he774522_0 4.8 MB
pickleshare-0.7.5 | py36_0 13 KB
pillow-7.0.0 | py36hcc1f983_0 652 KB
pyqt-5.9.2 | py36h6538335_2 3.3 MB
python-3.6.10 | h9f7ef89_0 15.9 MB
pywavelets-1.1.1 | py36he774522_0 3.4 MB
pywin32-227 | py36he774522_1 5.6 MB
pywinpty-0.5.7 | py36_0 50 KB
pyzmq-18.1.1 | py36ha925a31_0 399 KB
qt-5.9.7 | vc14h73c81de_0 72.5 MB
scikit-image-0.16.2 | py36h47e9c7a_0 22.6 MB
scikit-learn-0.22.1 | py36h6288b17_0 4.7 MB
scipy-1.4.1 | py36h9439919_0 11.9 MB
setuptools-46.1.3 | py36_0 527 KB
sip-4.19.8 | py36h6538335_0 262 KB
six-1.14.0 | py36_0 27 KB
terminado-0.8.3 | py36_0 26 KB
tornado-6.0.4 | py36he774522_1 604 KB
traitlets-4.3.3 | py36_0 140 KB
widgetsnbextension-3.5.1 | py36_0 868 KB
wincertstore-0.2 | py36h7fe50ca_0 14 KB
------------------------------------------------------------
Total: 174.3 MB
The following NEW packages will be INSTALLED:
blas pkgs/main/win-64::blas-1.0-mkl
mkl-service pkgs/main/win-64::mkl-service-2.3.0-py36hb782905_0
mkl_fft pkgs/main/win-64::mkl_fft-1.0.15-py36h14836fe_0
mkl_random pkgs/main/win-64::mkl_random-1.1.0-py36h675688f_0
numpy-base pkgs/main/win-64::numpy-base-1.18.1-py36hc3f5095_1
sip pkgs/main/win-64::sip-4.19.8-py36h6538335_0
The following packages will be REMOVED:
importlib_metadata-1.5.0-py38_0
pyrsistent-0.15.7-py38hfa6e2cd_0
python_abi-3.8-1_cp38
The following packages will be UPDATED:
ca-certificates conda-forge::ca-certificates-2019.11.~ --> pkgs/main::ca-certificates-2020.1.1-0
jedi conda-forge::jedi-0.16.0-py38_0 --> pkgs/main::jedi-0.16.0-py36_1
pywin32 conda-forge::pywin32-227-py38hfa6e2cd~ --> pkgs/main::pywin32-227-py36he774522_1
scipy conda-forge::scipy-1.3.2-py38h582fac2~ --> pkgs/main::scipy-1.4.1-py36h9439919_0
setuptools conda-forge::setuptools-46.0.0-py38_0 --> pkgs/main::setuptools-46.1.3-py36_0
tornado conda-forge::tornado-6.0.4-py38hfa6e2~ --> pkgs/main::tornado-6.0.4-py36he774522_1
The following packages will be SUPERSEDED by a higher-priority channel:
certifi conda-forge::certifi-2019.11.28-py38h~ --> pkgs/main::certifi-2019.11.28-py36_1
cytoolz conda-forge::cytoolz-0.10.1-py38hfa6e~ --> pkgs/main::cytoolz-0.10.1-py36he774522_0
entrypoints conda-forge::entrypoints-0.3-py38_1000 --> pkgs/main::entrypoints-0.3-py36_0
icu conda-forge::icu-64.2-he025d50_1 --> pkgs/main::icu-58.2-ha66f8fd_1
ipykernel conda-forge::ipykernel-5.1.4-py38h5ca~ --> pkgs/main::ipykernel-5.1.4-py36h39e3cac_0
ipython conda-forge::ipython-7.13.0-py38h5ca1~ --> pkgs/main::ipython-7.13.0-py36h5ca1d4c_0
jsonschema conda-forge::jsonschema-3.2.0-py38_0 --> pkgs/main::jsonschema-2.6.0-py36h7636477_0
jupyter_core conda-forge::jupyter_core-4.6.3-py38_0 --> pkgs/main::jupyter_core-4.6.1-py36_0
kiwisolver conda-forge::kiwisolver-1.1.0-py38he9~ --> pkgs/main::kiwisolver-1.1.0-py36ha925a31_0
markupsafe conda-forge::markupsafe-1.1.1-py38hfa~ --> pkgs/main::markupsafe-1.1.1-py36he774522_0
matplotlib conda-forge::matplotlib-3.2.0-1 --> pkgs/main::matplotlib-3.1.3-py36_0
matplotlib-base conda-forge::matplotlib-base-3.2.0-py~ --> pkgs/main::matplotlib-base-3.1.3-py36h64f37c6_0
mistune conda-forge::mistune-0.8.4-py38hfa6e2~ --> pkgs/main::mistune-0.8.4-py36he774522_0
nbconvert conda-forge::nbconvert-5.6.1-py38_0 --> pkgs/main::nbconvert-5.6.1-py36_0
notebook conda-forge::notebook-6.0.3-py38_0 --> pkgs/main::notebook-6.0.3-py36_0
numpy conda-forge::numpy-1.18.1-py38hc71023~ --> pkgs/main::numpy-1.18.1-py36h93ca92e_0
openssl conda-forge::openssl-1.1.1e-hfa6e2cd_0 --> pkgs/main::openssl-1.1.1e-he774522_0
pickleshare conda-forge::pickleshare-0.7.5-py38_1~ --> pkgs/main::pickleshare-0.7.5-py36_0
pillow conda-forge::pillow-7.0.0-py38h9ea1dd~ --> pkgs/main::pillow-7.0.0-py36hcc1f983_0
pyqt conda-forge::pyqt-5.12.3-py38h6538335~ --> pkgs/main::pyqt-5.9.2-py36h6538335_2
python conda-forge::python-3.8.2-h5fd99cc_4_~ --> pkgs/main::python-3.6.10-h9f7ef89_0
pywavelets conda-forge::pywavelets-1.1.1-py38hc8~ --> pkgs/main::pywavelets-1.1.1-py36he774522_0
pywinpty conda-forge::pywinpty-0.5.7-py38_0 --> pkgs/main::pywinpty-0.5.7-py36_0
pyzmq conda-forge::pyzmq-19.0.0-py38h16f901~ --> pkgs/main::pyzmq-18.1.1-py36ha925a31_0
qt conda-forge::qt-5.12.5-h7ef1ec2_0 --> pkgs/main::qt-5.9.7-vc14h73c81de_0
scikit-image conda-forge::scikit-image-0.16.2-py38~ --> pkgs/main::scikit-image-0.16.2-py36h47e9c7a_0
scikit-learn conda-forge::scikit-learn-0.22.2.post~ --> pkgs/main::scikit-learn-0.22.1-py36h6288b17_0
six conda-forge::six-1.14.0-py38_0 --> pkgs/main::six-1.14.0-py36_0
terminado conda-forge::terminado-0.8.3-py38_0 --> pkgs/main::terminado-0.8.3-py36_0
traitlets conda-forge::traitlets-4.3.3-py38_0 --> pkgs/main::traitlets-4.3.3-py36_0
widgetsnbextension conda-forge::widgetsnbextension-3.5.1~ --> pkgs/main::widgetsnbextension-3.5.1-py36_0
wincertstore conda-forge::wincertstore-0.2-py38_10~ --> pkgs/main::wincertstore-0.2-py36h7fe50ca_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
ipykernel-5.1.4 | 172 KB | ############################################################################ | 100%
numpy-base-1.18.1 | 3.8 MB | ############################################################################ | 100%
scikit-image-0.16.2 | 22.6 MB | ############################################################################ | 100%
widgetsnbextension-3 | 868 KB | ############################################################################ | 100%
pyqt-5.9.2 | 3.3 MB | ############################################################################ | 100%
jedi-0.16.0 | 768 KB | ############################################################################ | 100%
scipy-1.4.1 | 11.9 MB | ############################################################################ | 100%
matplotlib-base-3.1. | 4.9 MB | ############################################################################ | 100%
pickleshare-0.7.5 | 13 KB | ############################################################################ | 100%
blas-1.0 | 6 KB | ############################################################################ | 100%
kiwisolver-1.1.0 | 53 KB | ############################################################################ | 100%
six-1.14.0 | 27 KB | ############################################################################ | 100%
mkl-service-2.3.0 | 210 KB | ############################################################################ | 100%
scikit-learn-0.22.1 | 4.7 MB | ############################################################################ | 100%
entrypoints-0.3 | 12 KB | ############################################################################ | 100%
pywavelets-1.1.1 | 3.4 MB | ############################################################################ | 100%
certifi-2019.11.28 | 157 KB | ############################################################################ | 100%
openssl-1.1.1e | 4.8 MB | ############################################################################ | 100%
wincertstore-0.2 | 14 KB | ############################################################################ | 100%
pyzmq-18.1.1 | 399 KB | ############################################################################ | 100%
pywinpty-0.5.7 | 50 KB | ############################################################################ | 100%
pywin32-227 | 5.6 MB | ############################################################################ | 100%
mkl_fft-1.0.15 | 118 KB | ############################################################################ | 100%
terminado-0.8.3 | 26 KB | ############################################################################ | 100%
python-3.6.10 | 15.9 MB | ############################################################################ | 100%
jsonschema-2.6.0 | 102 KB | ############################################################################ | 100%
notebook-6.0.3 | 4.3 MB | ############################################################################ | 100%
jupyter_core-4.6.1 | 86 KB | ############################################################################ | 100%
cytoolz-0.10.1 | 303 KB | ############################################################################ | 100%
mistune-0.8.4 | 55 KB | ############################################################################ | 100%
sip-4.19.8 | 262 KB | ############################################################################ | 100%
mkl_random-1.1.0 | 233 KB | ############################################################################ | 100%
icu-58.2 | 9.4 MB | ############################################################################ | 100%
numpy-1.18.1 | 6 KB | ############################################################################ | 100%
setuptools-46.1.3 | 527 KB | ############################################################################ | 100%
matplotlib-3.1.3 | 22 KB | ############################################################################ | 100%
markupsafe-1.1.1 | 31 KB | ############################################################################ | 100%
traitlets-4.3.3 | 140 KB | ############################################################################ | 100%
tornado-6.0.4 | 604 KB | ############################################################################ | 100%
nbconvert-5.6.1 | 475 KB | ############################################################################ | 100%
ipython-7.13.0 | 1010 KB | ############################################################################ | 100%
qt-5.9.7 | 72.5 MB | ############################################################################ | 100%
pillow-7.0.0 | 652 KB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: / b'Uninstalling jupyter-js-widgets jupyter-js-widgets/extension\nRemoving: C:\\Users\\andreas\\Miniconda3\\envs\\compvis\\share\\jupyter\\nbextensions\\jupyter-js-widgets\n'
/ WARNING conda.gateways.disk.delete:unlink_or_rename_to_trash(140): Could not remove or rename C:\Users\andreas\Miniconda3\envs\compvis\Lib\site-packages\matplotlib\mpl-data\fonts\ttf\DejaVuSans.ttf. Please remove this file manually (you may need to reboot to free file handles)
| DEBUG menuinst_win32:__init__(199): Menu: name: 'Anaconda${PY_VER} ${PLATFORM}', prefix: 'C:\Users\andreas\Miniconda3\envs\compvis', env_name: 'compvis', mode: 'user', used_mode: 'user'
DEBUG menuinst_win32:create(323): Shortcut cmd is C:\Users\andreas\Miniconda3\python.exe, args are ['C:\\Users\\andreas\\Miniconda3\\cwp.py', 'C:\\Users\\andreas\\Miniconda3\\envs\\compvis', 'C:\\Users\\andreas\\Miniconda3\\envs\\compvis\\python.exe', 'C:\\Users\\andreas\\Miniconda3\\envs\\compvis\\Scripts\\jupyter-notebook-script.py', '"%USERPROFILE%/"']
done
(compvis) C:\Users\andreas>
(compvis) C:\Users\andreas>
(compvis) C:\Users\andreas>conda install python=3.6
Collecting package metadata (current_repodata.json): done
Solving environment: done
==> WARNING: A newer version of conda exists. <==
current version: 4.8.2
latest version: 4.8.3
Please update conda by running
$ conda update -n base -c defaults conda
# All requested packages already installed.
(compvis) C:\Users\andreas>conda update -n base -c defaults conda
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: C:\Users\andreas\Miniconda3
added / updated specs:
- conda
The following packages will be downloaded:
package | build
---------------------------|-----------------
certifi-2019.11.28 | py37_1 157 KB
conda-4.8.3 | py37_0 2.8 MB
idna-2.9 | py_1 49 KB
pycparser-2.20 | py_0 92 KB
requests-2.23.0 | py37_0 93 KB
setuptools-46.1.3 | py37_0 528 KB
tqdm-4.44.1 | py_0 57 KB
------------------------------------------------------------
Total: 3.8 MB
The following packages will be UPDATED:
certifi 2019.11.28-py37_0 --> 2019.11.28-py37_1
conda 4.8.2-py37_0 --> 4.8.3-py37_0
idna pkgs/main/win-64::idna-2.8-py37_0 --> pkgs/main/noarch::idna-2.9-py_1
openssl 1.1.1d-he774522_4 --> 1.1.1e-he774522_0
pycparser pkgs/main/win-64::pycparser-2.19-py37~ --> pkgs/main/noarch::pycparser-2.20-py_0
requests 2.22.0-py37_1 --> 2.23.0-py37_0
setuptools 45.2.0-py37_0 --> 46.1.3-py37_0
tqdm 4.42.1-py_0 --> 4.44.1-py_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
setuptools-46.1.3 | 528 KB | ############################################################################ | 100%
idna-2.9 | 49 KB | ############################################################################ | 100%
requests-2.23.0 | 93 KB | ############################################################################ | 100%
tqdm-4.44.1 | 57 KB | ############################################################################ | 100%
pycparser-2.20 | 92 KB | ############################################################################ | 100%
conda-4.8.3 | 2.8 MB | ############################################################################ | 100%
certifi-2019.11.28 | 157 KB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(compvis) C:\Users\andreas>conda install python=3.6
Collecting package metadata (current_repodata.json): done
Solving environment: done
# All requested packages already installed.
(compvis) C:\Users\andreas>conda install -c conda-forge keras
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: C:\Users\andreas\Miniconda3\envs\compvis
added / updated specs:
- keras
The following packages will be downloaded:
package | build
---------------------------|-----------------
absl-py-0.9.0 | py36h9f0ad1d_1 162 KB conda-forge
astor-0.7.1 | py_0 22 KB conda-forge
certifi-2019.11.28 | py36h9f0ad1d_1 149 KB conda-forge
gast-0.3.3 | py_0 12 KB conda-forge
grpcio-1.23.0 | py36hc6b9980_1 1.0 MB conda-forge
h5py-2.10.0 |nompi_py36h422b98e_102 936 KB conda-forge
hdf5-1.10.5 |nompi_ha405e13_1104 35.1 MB conda-forge
keras-2.3.1 | py36h21ff451_0 589 KB conda-forge
keras-applications-1.0.8 | py_1 30 KB conda-forge
keras-preprocessing-1.1.0 | py_0 33 KB conda-forge
libgpuarray-0.7.6 | hfa6e2cd_1003 314 KB conda-forge
libprotobuf-3.11.4 | h1a1b453_0 2.2 MB conda-forge
mako-1.1.0 | py_0 57 KB conda-forge
markdown-3.2.1 | py_0 61 KB conda-forge
protobuf-3.11.4 | py36he025d50_0 583 KB conda-forge
pygpu-0.7.6 |py36hc8d92b1_1000 594 KB conda-forge
pyreadline-2.1 | py36_1001 141 KB conda-forge
python_abi-3.6 | 1_cp36m 4 KB conda-forge
pyyaml-5.3.1 | py36h68a101e_0 155 KB conda-forge
tensorboard-1.13.1 | py36_0 3.3 MB conda-forge
tensorflow-1.13.2 | h21ff451_0 22 KB conda-forge
tensorflow-base-1.13.2 | py36_0 52.5 MB conda-forge
tensorflow-estimator-1.13.0| py36h39e3cac_0 475 KB conda-forge
termcolor-1.1.0 | py_2 6 KB conda-forge
theano-1.0.4 |py36h6538335_1001 3.7 MB conda-forge
vs2015_win-64-14.0.25420 | h55c1224_11 7 KB
werkzeug-1.0.0 | py_0 238 KB conda-forge
yaml-0.2.2 | hfa6e2cd_1 63 KB conda-forge
------------------------------------------------------------
Total: 102.4 MB
The following NEW packages will be INSTALLED:
absl-py conda-forge/win-64::absl-py-0.9.0-py36h9f0ad1d_1
astor conda-forge/noarch::astor-0.7.1-py_0
gast conda-forge/noarch::gast-0.3.3-py_0
grpcio conda-forge/win-64::grpcio-1.23.0-py36hc6b9980_1
h5py conda-forge/win-64::h5py-2.10.0-nompi_py36h422b98e_102
hdf5 conda-forge/win-64::hdf5-1.10.5-nompi_ha405e13_1104
keras conda-forge/win-64::keras-2.3.1-py36h21ff451_0
keras-applications conda-forge/noarch::keras-applications-1.0.8-py_1
keras-preprocessi~ conda-forge/noarch::keras-preprocessing-1.1.0-py_0
libgpuarray conda-forge/win-64::libgpuarray-0.7.6-hfa6e2cd_1003
libprotobuf conda-forge/win-64::libprotobuf-3.11.4-h1a1b453_0
mako conda-forge/noarch::mako-1.1.0-py_0
markdown conda-forge/noarch::markdown-3.2.1-py_0
protobuf conda-forge/win-64::protobuf-3.11.4-py36he025d50_0
pygpu conda-forge/win-64::pygpu-0.7.6-py36hc8d92b1_1000
pyreadline conda-forge/win-64::pyreadline-2.1-py36_1001
python_abi conda-forge/win-64::python_abi-3.6-1_cp36m
pyyaml conda-forge/win-64::pyyaml-5.3.1-py36h68a101e_0
tensorboard conda-forge/win-64::tensorboard-1.13.1-py36_0
tensorflow conda-forge/win-64::tensorflow-1.13.2-h21ff451_0
tensorflow-base conda-forge/win-64::tensorflow-base-1.13.2-py36_0
tensorflow-estima~ conda-forge/win-64::tensorflow-estimator-1.13.0-py36h39e3cac_0
termcolor conda-forge/noarch::termcolor-1.1.0-py_2
theano conda-forge/win-64::theano-1.0.4-py36h6538335_1001
vs2015_win-64 pkgs/main/win-64::vs2015_win-64-14.0.25420-h55c1224_11
werkzeug conda-forge/noarch::werkzeug-1.0.0-py_0
yaml conda-forge/win-64::yaml-0.2.2-hfa6e2cd_1
The following packages will be SUPERSEDED by a higher-priority channel:
ca-certificates pkgs/main::ca-certificates-2020.1.1-0 --> conda-forge::ca-certificates-2019.11.28-hecc5488_0
certifi pkgs/main::certifi-2019.11.28-py36_1 --> conda-forge::certifi-2019.11.28-py36h9f0ad1d_1
openssl pkgs/main::openssl-1.1.1e-he774522_0 --> conda-forge::openssl-1.1.1e-hfa6e2cd_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
gast-0.3.3 | 12 KB | ############################################################################ | 100%
grpcio-1.23.0 | 1.0 MB | ############################################################################ | 100%
keras-preprocessing- | 33 KB | ############################################################################ | 100%
absl-py-0.9.0 | 162 KB | ############################################################################ | 100%
pyyaml-5.3.1 | 155 KB | ############################################################################ | 100%
pygpu-0.7.6 | 594 KB | ############################################################################ | 100%
libgpuarray-0.7.6 | 314 KB | ############################################################################ | 100%
keras-2.3.1 | 589 KB | ############################################################################ | 100%
python_abi-3.6 | 4 KB | ############################################################################ | 100%
werkzeug-1.0.0 | 238 KB | ############################################################################ | 100%
hdf5-1.10.5 | 35.1 MB | ############################################################################ | 100%
protobuf-3.11.4 | 583 KB | ############################################################################ | 100%
keras-applications-1 | 30 KB | ############################################################################ | 100%
tensorflow-1.13.2 | 22 KB | ############################################################################ | 100%
mako-1.1.0 | 57 KB | ############################################################################ | 100%
tensorflow-estimator | 475 KB | ############################################################################ | 100%
yaml-0.2.2 | 63 KB | ############################################################################ | 100%
astor-0.7.1 | 22 KB | ############################################################################ | 100%
tensorflow-base-1.13 | 52.5 MB | ############################################################################ | 100%
theano-1.0.4 | 3.7 MB | ############################################################################ | 100%
tensorboard-1.13.1 | 3.3 MB | ############################################################################ | 100%
h5py-2.10.0 | 936 KB | ############################################################################ | 100%
vs2015_win-64-14.0.2 | 7 KB | ############################################################################ | 100%
markdown-3.2.1 | 61 KB | ############################################################################ | 100%
certifi-2019.11.28 | 149 KB | ############################################################################ | 100%
pyreadline-2.1 | 141 KB | ############################################################################ | 100%
termcolor-1.1.0 | 6 KB | ############################################################################ | 100%
libprotobuf-3.11.4 | 2.2 MB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
C:\Users\andreas>set "KERAS_BACKEND="
C:\Users\andreas>python C:\Users\andreas\Miniconda3\envs\compvis\etc\keras\load_config.py 1>temp.txt
C:\Users\andreas>set /p KERAS_BACKEND= 0<temp.txt
C:\Users\andreas>del temp.txt
C:\Users\andreas>python -c "import keras" 1>nul 2>&1
C:\Users\andreas>if errorlevel 1 (
ver 1>nul
set "KERAS_BACKEND=theano"
python -c "import keras" 1>nul 2>&1
)
C:\Users\andreas>SET DISTUTILS_USE_SDK=1
C:\Users\andreas>SET MSSdk=1
C:\Users\andreas>SET platform=
C:\Users\andreas>IF /I [AMD64] == [amd64] set "platform=true"
C:\Users\andreas>IF /I [] == [amd64] set "platform=true"
C:\Users\andreas>if defined platform (set "VSREGKEY=HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Microsoft\VisualStudio\14.0" ) ELSE (set "VSREGKEY=HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\VisualStudio\14.0" )
C:\Users\andreas>for /F "skip=2 tokens=2,*" %A in ('reg query "HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\Microsoft\VisualStudio\14.0" /v InstallDir') do SET "VSINSTALLDIR=%B"
ERROR: The system was unable to find the specified registry key or value.
C:\Users\andreas>if "" == "" (set "VSINSTALLDIR=" )
C:\Users\andreas>if "" == "" (
ECHO "WARNING: Did not find VS in registry or in VS140COMNTOOLS env var - your compiler may not work"
GOTO End
)
"WARNING: Did not find VS in registry or in VS140COMNTOOLS env var - your compiler may not work"
The system cannot find the batch label specified - End
(compvis) C:\Users\andreas>
(compvis) C:\Users\andreas>
(compvis) C:\Users\andreas>file
'file' is not recognized as an internal or external command,
operable program or batch file.
(compvis) C:\Users\andreas>conda install python=3.8
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: /
CALL "%VSINSTALLDIR%VC\vcvarsall.bat" amd64
Perl
perlintro – a brief introduction and overview of Perl
perlop – Perl operators and precedence
perlobj – Perl object reference
perldebug – Perl debugging
perlrequick – Perl regular expressions quick start
Perl Environment Include/Library Path
# perl -e "print qq(@INC)" /usr/local/lib/perl5/site_perl/mach/5.20 /usr/local/lib/perl5/site_perl /usr/local/lib/perl5/5.20/mach /usr/local/lib/perl5/5.20 /usr/local/lib/perl5/site_perl/5.20 /usr/local/lib/perl5/site_perl/5.20/mach # find /usr/local/lib/perl5 -name "*.pm" /usr/local/lib/perl5/5.20/AnyDBM_File.pm /usr/local/lib/perl5/5.20/App/Cpan.pm ...
Variable Type
Enum
Does Perl have an enumeration type?
RegEx
Regular Expressions and Matching
perl – strings comparison and regex
System Command-Line
perldoc: system
How can I store the result of a system command in a Perl variable?
How can I capture STDERR from an external command?
Name of the Perl script
How to get the name of Perl script that is running
print $0;
Command Line Arguments
- Use
$ARGV[n]to display argument. - Use
$#ARGVto get total number of passed argument to a perl script.
Processing command line arguments – @ARGV in Perl
Perl Display And Pass Command Line Arguments With @argv
How to read Perl command-line arguments
my $argc= $#ARGV + 1; my $name = $ARGV[0]; my $number = $ARGV[1]; # or my ($name, $number) = @ARGV;
Loops (for, foreach, etc.)
Perl for loop explained with examples
defined
Arrays
Note, when accessing a single element of an array the leading sigil changes from @ to $. This might cause confusion to some people, but if you think about it, it is quite obvious why.
@ marks plural and $ marks singular. When accessing a single element of an array it behaves just as a regular scalar variable.
# Declare an array
my @names;
# Declare and assign values:
my @names = ("Foo", "Bar", "Baz");
# Debugging of an array
use Data::Dumper qw(Dumper);
my @names = ("Foo", "Bar", "Baz");
say Dumper \@names;
# $VAR1 = [
# 'Foo',
# 'Bar',
# 'Baz'
# ];
# foreach loop and perl arrays
my @names = ("Foo", "Bar", "Baz");
foreach my $n (@names) {
say $n;
}
# Foo
# Bar
# Baz
# Accessing an element of an array
my @names = ("Foo", "Bar", "Baz");
say $names[0];
Indexing array
The indexes of an array start from 0. The largest index is always in the variable called $#name_of_the_array. So
my @names = ("Foo", "Bar", "Baz");
say $#names;
Will print 2 because the indexes are 0,1 and 2.
Length or size of an array
In Perl there is no special function to fetch the size of an array, but there are several ways to obtain that value. For one, the size of the array is one more than the largest index. In the above case $#names+1 is the size or length of the array.
In addition the scalar function can be used to to obtain the size of an array:
my @names = ("Foo", "Bar", "Baz");
say scalar @names;
Will print 3.
The scalar function is sort of a casting function that – among other things – converts an array to a scalar. Due to an arbitrary, but clever decision this conversion yields the size of the array.
Loop on the indexes of an array
There are cases when looping over the values of an array is not enough. We might need both the value and the index of that value. In that case we need to loop over the indexes, and obtain the values using the indexes:
my @names = ("Foo", "Bar", "Baz");
foreach my $i (0 .. $#names) {
say "$i - $names[$i]";
}
prints:
0 - Foo 1 - Bar 2 - Baz
String
Perl string concatenation – How to concatenate strings with Perl
- Perl string concatenation – Method #1 – Using ${name}
- Perl string concatenation – Method #2 – using Perl’s dot operator
- Perl string concatenation – Method #3 – using Perl’s join function
$name = 'foo';
$filename = "/tmp/${name}.tmp";
$name = checkbook';
$filename = '/tmp/' . $name . '.tmp';
# $filename now contains "/tmp/checkbook.tmp"
$name = 'checkbook';
$filename = join '', '/tmp/', $name, '.tmp';
# $filename now contains "/tmp/checkbook.tmp"
File I/O
How to tell perl to print to a file handle instead of printing the file handle? !!!
Writing to files with Perl
Perl – File I/O
How to remove one line from a file using Perl?
How do I delete a certain line from a file with Perl?
Insert a line at the beginning of a file
"<file.txt": read-only mode">file.txt": writing mode"+<file.txt": updating without truncating"+>file.txt": truncate the file first">>file.txt": append mode"+>>file.txt": append mode with read
use strict; use warnings; my $filename = 'report.txt'; open(my $fh, '>', $filename) or die "Could not open file '$filename' $!"; print $fh "My first report generated by perl\n"; close $fh; print "done\n";
Process List
Day 17: Checking process existence and listing processes (Proc::Find)
ps in perl?
Proc::Find – Find processes by name, PID, or some other attributes
Proc::ProcessTable – Perl extension to access the unix process table
# perl ... Can't locate Proc/Find.pm in @INC (you may need to install the Proc::Find module)