Pip install talib ошибка

Всем привет!

Пытаюсь поставить библиотеку ta-lib для python в 16.04(х64), но получаю ошибку:

pip install ta-lib
Collecting ta-lib
  Using cached https://files.pythonhosted.org/packages/90/05/d4c6a778d7a7de0be366bc4a850b4ffaeac2abad927f95fa8ba6f355a082/TA-Lib-0.4.17.tar.gz
Requirement already satisfied: numpy in ./.local/lib/python2.7/site-packages (from ta-lib) (1.15.0)
Building wheels for collected packages: ta-lib
  Running setup.py bdist_wheel for ta-lib ... error
  Complete output from command /usr/bin/python -u -c "import setuptools, tokenize;__file__='/tmp/pip-install-p7nQVn/ta-lib/setup.py';f=getattr(tokenize, 'open', open)(__file__);code=f.read().replace('rn', 'n');f.close();exec(compile(code, __file__, 'exec'))" bdist_wheel -d /tmp/pip-wheel-Qr_dyn --python-tag cp27:
  /tmp/pip-install-p7nQVn/ta-lib/setup.py:79: UserWarning: Cannot find ta-lib library, installation may fail.
    warnings.warn('Cannot find ta-lib library, installation may fail.')
  running bdist_wheel
  running build
  running build_py
  creating build
  creating build/lib.linux-x86_64-2.7
  creating build/lib.linux-x86_64-2.7/talib
  copying talib/abstract.py -> build/lib.linux-x86_64-2.7/talib
  copying talib/stream.py -> build/lib.linux-x86_64-2.7/talib
  copying talib/test_pandas.py -> build/lib.linux-x86_64-2.7/talib
  copying talib/__init__.py -> build/lib.linux-x86_64-2.7/talib
  copying talib/deprecated.py -> build/lib.linux-x86_64-2.7/talib
  copying talib/test_stream.py -> build/lib.linux-x86_64-2.7/talib
  copying talib/test_data.py -> build/lib.linux-x86_64-2.7/talib
  copying talib/test_func.py -> build/lib.linux-x86_64-2.7/talib
  copying talib/test_abstract.py -> build/lib.linux-x86_64-2.7/talib
  running build_ext
  building 'talib._ta_lib' extension
  creating build/temp.linux-x86_64-2.7
  creating build/temp.linux-x86_64-2.7/talib
  x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -I/home/sergey/.local/lib/python2.7/site-packages/numpy/core/include -I/usr/include -I/usr/local/include -I/opt/include -I/opt/local/include -I/usr/include/python2.7 -c talib/_ta_lib.c -o build/temp.linux-x86_64-2.7/talib/_ta_lib.o
  talib/_ta_lib.c:526:28: fatal error: ta-lib/ta_defs.h: Нет такого файла или каталога
  compilation terminated.
  error: command 'x86_64-linux-gnu-gcc' failed with exit status 1

Помогите решить проблему?

By Ishan Shah, Rekhit Pachanekar and Gaurav Singh

Technical indicators are calculated using historical price and volume data to predict the market direction. These indicators are added on charts using which you can set your entry and exit signals.

Won’t it be amazing if you can compute these technical indicators in python in a few lines of code and backtest the performance of it on many financial securities?

What started off as a hobby by Mario Fortier, Ta-Lib python library quickly rose to become one of the most famous libraries for technical analysis of stocks and other financial securities. Ta-lib includes 150+ indicators such as ADX, MACD, RSI and Bollinger Bands and candlestick pattern recognition.

However, it is difficult and sometimes frustrating to install Ta-Lib in your python. But don’t worry, in this article, we will simplify the installation for you so that you can focus on creating and backtesting strategies.

We will cover the following topics in this Ta-Lib installation tutorial.

Easiest Method

• The EASIEST way to install Ta-Lib

Alternate Methods

• Install Ta-Lib on Windows PC
• Install Ta-Lib on MacOS
• Install Ta-Lib on Linux
• Technical Indicators using Python Ta-Lib

Before we begin, why was Ta-Lib python library created in the first place? Let us think about the reason functions were made. It was realised that instead of writing the same code, we could create a function and reduce the code length by a huge margin.

It is the same logic we apply to Ta-Lib. Instead of writing a few lines of code to first find the upper and lower bands and then the Bollinger band, we use Ta-Lib and input just one line of code to get the result.

That is all! Keeping that in mind, let us begin with the tutorial on Ta-Lib python library.

The EASIEST way to install Ta-Lib

The following is the easiest and the best way to install Ta-Lib across platforms using Anaconda Prompt.

Anaconda is an open-source Python distribution platform that helps individuals, as well as commercial enterprises, implement their Python codes easily. It also makes life easier when it comes to installing various Python libraries.

To install Ta-Lib easily, you can follow these steps:

• Install Anaconda
• Open the Anaconda prompt
• Write the code: conda install -c conda-forge ta-lib
• Press the “Enter” key

et voilà! Ta-Lib is now installed!

After a few moments, the ta-lib package will be installed.

That’s all there is to it. Most of the time this method would help you install the package, but if you still face any problems, read on to find the installation instructions as per the operating system.

Note: The packages are first downloaded from the respective web location. You will then be prompted to confirm the installation process by pressing “y” on the keyboard. This acts as a confirmation for the installer to install the necessary files.

Install Ta-Lib on Windows PC

Step 0: We suggest the Anaconda installer for installing Python as it is easier to work with when it comes to programming in Python.

Step 1: Once you have installed Anaconda, you will use the Anaconda prompt window to install the relevant files.

Before we download the Python Ta-Lib files, we have to verify the Python version as well as the Windows System architecture (32-bit or 64-bit) on our computer.

You can find the version installed in your system by simply writing the following code in the Anaconda prompt window: python —version

You will get the output as shown below:

For the windows architecture, you can simply right-click on your «computer» (usually named as «This-PC» or «My Computer») icon and click properties and your system details will be displayed.

Step 2: We cannot directly use the «pip install» command when it comes to installing Ta-Lib. Thus, we will first install the «whl» file which can be found on this link: https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib

The website is a useful resource for a lot of Python extensions, but we are concerned about Ta-Lib installation for now.

You can scroll down to the section where we will find the relevant links, as shown below:

One should note that you should download the file keeping your Python version and Windows architecture (32 bit or 64 bit) in mind. E.g. Since we have the python version 3.7 installed and 64 bit Windows 7 system, we will download the file, “TA_Lib‑0.4.17‑cp37‑cp37m‑win_amd64.whl”.

As you might have guessed “cp37” implies Python version 3.7 and “win_amd64” implies Windows 64 bit operating system.

By default, the «whl» file gets downloaded in the «Downloads» folder. Since we have used Anaconda installer for Python, we will place the file in the same folder location which is shown on the Anaconda prompt.

For eg: C:Usersrekhit.p

And now comes the easy part.

In the Anaconda prompt, use the pip install command with the file name of the downloaded file.

Since we have downloaded the file, “TA_Lib‑0.4.17‑cp37‑cp37m‑win_amd64.whl”, the command would be, pip install TA_Lib-0.4.17-cp37-cp37m-win_amd64.whl

If there is no error, then it implies that we have successfully installed Ta-Lib. You should get a screen with the following messages.

Great! We have just finished installing the Ta-Lib Python library.

But how do we check if it is correctly installed?

On the Anaconda command prompt, you will first type “python” to interpret the program.

We will then type the following command, “import talib” and then press Enter.

If there are no errors, then it means that the python Ta-Lib library has been successfully installed on your computer.

Alternatively, you can also open Jupyter notebook (or Spyder) and try to run the same code to check if the Python Ta-Lib is installed correctly.

Install Ta-Lib on MacOS

In comparison to the windows installation, Python Ta-Lib installation is relatively straightforward and easy on the MacOS. But before we talk about the installation of Ta-Lib, we have to make sure the python environment is installed as well.

You can install Anaconda from here or download Python from here.

In our opinion, it is generally a good idea to install Anaconda as it helps build an environment for your python code to be executed seamlessly.

Note: During the Anaconda installation, you will be asked to install either Python 2.7 or 3.7. Since the support for Python 2.7 ended on January 1, 2020, it would be advisable to select the 3.7 version. For a seamless installation, choose the graphical installer.

You will then be greeted with the following dialog box.

Select “Continue” tab and choose the appropriate install destination and you will finish installation in a short time.

All right, now we move on to the main event, i.e. Ta-lib python library installation. Ok, there is one small step you need to do before the main install.

Check if you can use the ‘brew’ command. For this tutorial on how to install Ta-Lib, let us assume that the ‘brew’ command throws an error. To rectify this, we install the necessary package by using the following line of code in the MacOS shell:

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

If it is successful, you will see the following messages:

You might be asked to enter your password, which is part of the process.

Of course, you will get a prompt which asks you to press “Return” to continue the installation or any other key to cancel the installation.

If you are curious about the ‘brew’ command, you can always visit this website to know more.

Great! Now that the brew command is installed, use the following code to install the Ta-Lib operating system dependencies:

brew install ta-lib

You will see the following screen

Now, we use the familiar command i.e. “pip” to install Ta-Lib on our MacOS. The command is as follows:

pip install ta-lib

You see the following files being installed on your system.

Great! We have been successful in our quest to install Ta-Lib on MacOS.

But how do we check if it is correctly installed on the system? Simple, we use the following commands.

First, we call the python language by simply writing “python” in the terminal. We then use the following command to import the Ta-Lib library.

import talib

If there is no error, then we should be able to see the following screen

Install Ta-Lib on Linux

The Ta-lib installation in Linux can be a bit tricky. The libraries necessary for the Ta-lib installation should be installed first before you install the Python wrapper.

But don’t worry! We have provided comprehensive steps on how to install the Ta-lib library in your Linux system.

Step 0: Install Anaconda in your Linux system. You can follow the documentation or execute the commands as shared below.

The following command installs the Anaconda software and creates an environment named ‘quantra’. You can use this environment for your Quantra related coding projects!

• Install the prerequisites
• Install Anaconda on your system

Step 1: Install the Ta-lib dependencies and Python wrapper by executing the following command.

This will take a couple of minutes and install all the libraries necessary for using Ta-lib.

Step 2: Test the Ta-lib installation by executing a sample script. We take some data and try to find the moving average using the Ta-lib libraries.

• Install yfinance library if you do not have it already
• Run Python in the terminal
• Paste the following code lines to check if Ta-lib is working properly or not.
• You should see a Simple MA and EMA column similar to the screenshot below.

The Ta-lib library is now installed in the ‘quantra’ environment! To know how to activate and switch environments, please refer to the Conda resource.

Awesome! We have now been successful in installing Python Ta-Lib on Windows, MacOS and Linux. But can we really stop here?

In the next section, we try a simple code using the Ta-Lib library.

Technical Indicators using Python Ta-Lib

We will first import the Python Ta-Lib library since we are using it to work out different indicators. Along with that, we use the python matplotlib to draw their graphs for analysis. Since we are going to be working on the stock prices, we will import the data from Yahoo Finance.

Thus, the code will be as follows:

import talib as ta import matplotlib.pyplot as plt plt.style.use('bmh')
import yfinance as yf aapl = yf.download('AAPL', '2019-1-1','2019-12-27')

In the above example, we have imported the stock price data of Apple from 1 January 2019 to 27 December 2019.

Let us start off with something simple. We will find the Simple Moving Average and the Exponential Moving Average of Apple stock data. We will use the following code:

aapl['Simple MA'] = ta.SMA(aapl['Close'],14)
aapl['EMA'] = ta.EMA(aapl['Close'], timeperiod = 14)

# Plot aapl
[['Close','Simple MA','EMA']].plot(figsize=(15,15)) plt.show()

The output is as follows:

That was simple, wasn’t it?

Recall that at the start of this tutorial on Installing Python Ta-Lib, we talked about Bollinger Bands. Well, let’s try that one now.

# Bollinger Bands aapl['upper_band'], aapl['middle_band'], aapl['lower_band'] = ta.BBANDS(aapl['Close'], timeperiod =20)

# Plot aapl[['Close','upper_band','middle_band','lower_band']].plot(figsize=(15,15)) plt.show()

Wasn’t it easy? We are sure you are getting it but let us break down the line and see how Python Ta-Lib worked out the Bollinger Bands.

To create the Bollinger bands, we simply passed the Closing Price ie the “Close” column and defined a time period of 20 for the moving average. This is done using the “ta.BBANDS()” function.

As the Bollinger bands consist of three bands, we store the data in the following three columns, “upper_band”, “middle_band” and “lower_band.

aapl[‘upper_band’], aapl[‘middle_band’], aapl[‘lower_band’] = ta.BBANDS(aapl[‘Close’], timeperiod =20)

Now, can you figure out from the code below, what are the parameters passed?

aapl['RSI'] = ta.RSI(aapl['Close'],14) aapl['RSI'].plot(figsize=(15,15)) plt.show()

As a bonus, we plotted the Stochastic oscillators as well, the code is given below:

aapl['slowk'], aapl['slowd'] = ta.STOCH(aapl['High'], aapl['Low'], aapl['Close'], fastk_period=14, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0) aapl[['slowk','slowd']].plot(figsize=(15,15)) plt.show()

aapl['fastk'], aapl['fastd'] = ta.STOCHF(aapl['High'], aapl['Low'], aapl['Close'], fastk_period=14, fastd_period=3, fastd_matype=0) aapl[['fastk','fastd']].plot(figsize=(15,15)) plt.show()

Phew! You can go ahead and check out the other indicators on the following website as well.

You will find it very useful and knowledgeable to read through this curated compilation of some of our top blogs on:

Python for Trading
Machine Learning
Sentiment Trading
Algorithmic Trading
Options Trading
Technical Analysis

Conclusion

Thus, we have gone through the Tutorial on how to install Ta-Lib python library on Windows, MacOS as well as Linux. We have also found how to create a few technical indicators using Ta-Lib and plot them.

In case you are also interested in developing lifelong skills that will always assist you in improving your trading strategies. In this algo trading course, you will be trained in statistics & econometrics, programming, machine learning and quantitative trading methods, so you are proficient in every skill necessary to excel in quantitative & algorithmic trading. Know more about the EPAT course now!

Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis.

This is a Python wrapper for TA-LIB based on Cython
instead of SWIG. From the homepage:

TA-Lib is widely used by trading software developers requiring to perform
technical analysis of financial market data.

• Includes 150+ indicators such as ADX, MACD, RSI, Stochastic, Bollinger
  Bands, etc.
• Candlestick pattern recognition
• Open-source API for C/C++, Java, Perl, Python and 100% Managed .NET

The original Python bindings included with TA-Lib use
SWIG which unfortunately are difficult to install and
aren’t as efficient as they could be. Therefore this project uses
Cython and Numpy to efficiently
and cleanly bind to TA-Lib — producing results 2-4 times faster than the
SWIG interface.

In addition, this project also supports the use of the
Polars and Pandas
libraries.

Installation

You can install from PyPI:

$ python3 -m pip install TA-Lib

Or checkout the sources and run setup.py yourself:

$ python setup.py install

It also appears possible to install via
Conda Forge:

$ conda install -c conda-forge ta-lib

Dependencies

To use TA-Lib for python, you need to have the
TA-Lib already installed. You should
probably follow their installation directions for your platform, but some
suggestions are included below for reference.

Mac OS X

You can simply install using Homebrew:

$ brew install ta-lib

If you are using Apple Silicon, such as the M1 processors, and building mixed
architecture Homebrew projects, you might want to make sure it’s being built
for your architecture:

$ arch -arm64 brew install ta-lib

And perhaps you can set these before installing with pip:

$ export TA_INCLUDE_PATH="$(brew --prefix ta-lib)/include"
$ export TA_LIBRARY_PATH="$(brew --prefix ta-lib)/lib"

You might also find this helpful, particularly if you have tried several
different installations without success:

$ your-arm64-python -m pip install --no-cache-dir ta-lib

Windows

Download ta-lib-0.4.0-msvc.zip
and unzip to C:ta-lib.

This is a 32-bit binary release. If you want to use 64-bit Python, you will
need to build a 64-bit version of the library. Some unofficial (and
unsupported) instructions for building on 64-bit Windows 10, here for
reference:

1. Download and Unzip ta-lib-0.4.0-msvc.zip
2. Move the Unzipped Folder ta-lib to C:
3. Download and Install Visual Studio Community 2015
   • Remember to Select [Visual C++] Feature
4. Build TA-Lib Library
   • From Windows Start Menu, Start [VS2015 x64 Native Tools Command Prompt]
   • Move to C:ta-libcmakecdrwin32msvc
   • Build the Library nmake

You might also try these unofficial windows binaries for both 32-bit and
64-bit:

https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib

Linux

Download ta-lib-0.4.0-src.tar.gz and:

$ tar -xzf ta-lib-0.4.0-src.tar.gz
$ cd ta-lib/
$ ./configure --prefix=/usr
$ make
$ sudo make install

If you build TA-Lib using make -jX it will fail but that’s OK!
Simply rerun make -jX followed by [sudo] make install.

Note: if your directory path includes spaces, the installation will probably
fail with No such file or directory errors.

Troubleshooting

If you get a warning that looks like this:

setup.py:79: UserWarning: Cannot find ta-lib library, installation may fail.
warnings.warn('Cannot find ta-lib library, installation may fail.')

This typically means setup.py can’t find the underlying TA-Lib
library, a dependency which needs to be installed.

If you installed the underlying TA-Lib library with a custom prefix
(e.g., with ./configure --prefix=$PREFIX), then when you go to install
this python wrapper you can specify additional search paths to find the
library and include files for the underlying TA-Lib library using the
TA_LIBRARY_PATH and TA_INCLUDE_PATH environment variables:

$ export TA_LIBRARY_PATH=$PREFIX/lib
$ export TA_INCLUDE_PATH=$PREFIX/include
$ python setup.py install # or pip install ta-lib

Sometimes installation will produce build errors like this:

talib/_ta_lib.c:601:10: fatal error: ta-lib/ta_defs.h: No such file or directory
  601 | #include "ta-lib/ta_defs.h"
      |          ^~~~~~~~~~~~~~~~~~
compilation terminated.

or:

common.obj : error LNK2001: unresolved external symbol TA_SetUnstablePeriod
common.obj : error LNK2001: unresolved external symbol TA_Shutdown
common.obj : error LNK2001: unresolved external symbol TA_Initialize
common.obj : error LNK2001: unresolved external symbol TA_GetUnstablePeriod
common.obj : error LNK2001: unresolved external symbol TA_GetVersionString

This typically means that it can’t find the underlying TA-Lib library, a
dependency which needs to be installed. On Windows, this could be caused by
installing the 32-bit binary distribution of the underlying TA-Lib library,
but trying to use it with 64-bit Python.

Sometimes installation will fail with errors like this:

talib/common.c:8:22: fatal error: pyconfig.h: No such file or directory
 #include "pyconfig.h"
                      ^
compilation terminated.
error: command 'x86_64-linux-gnu-gcc' failed with exit status 1

This typically means that you need the Python headers, and should run
something like:

$ sudo apt-get install python3-dev

Sometimes building the underlying TA-Lib library has errors running
make that look like this:

../libtool: line 1717: cd: .libs/libta_lib.lax/libta_abstract.a: No such file or directory
make[2]: *** [libta_lib.la] Error 1
make[1]: *** [all-recursive] Error 1
make: *** [all-recursive] Error 1

This might mean that the directory path to the underlying TA-Lib library
has spaces in the directory names. Try putting it in a path that does not have
any spaces and trying again.

Sometimes you might get this error running setup.py:

/usr/include/limits.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
#include <bits/libc-header-start.h>
         ^~~~~~~~~~~~~~~~~~~~~~~~~~

This is likely an issue with trying to compile for 32-bit platform but
without the appropriate headers. You might find some success looking at the
first answer to this question.

If you wonder why STOCHRSI gives you different results than you expect,
probably you want STOCH applied to RSI, which is a little different
than the STOCHRSI which is STOCHF applied to RSI:

>>> import talib
>>> import numpy
>>> c = numpy.random.randn(100)

# this is the library function
>>> k, d = talib.STOCHRSI(c)

# this produces the same result, calling STOCHF
>>> rsi = talib.RSI(c)
>>> k, d = talib.STOCHF(rsi, rsi, rsi)

# you might want this instead, calling STOCH
>>> rsi = talib.RSI(c)
>>> k, d = talib.STOCH(rsi, rsi, rsi)

If the build appears to hang, you might be running on a VM with not enough
memory — try 1 GB or 2 GB.

Function API

Similar to TA-Lib, the Function API provides a lightweight wrapper of the
exposed TA-Lib indicators.

Each function returns an output array and have default values for their
parameters, unless specified as keyword arguments. Typically, these functions
will have an initial «lookback» period (a required number of observations
before an output is generated) set to NaN.

For convenience, the Function API supports both numpy.ndarray and
pandas.Series and polars.Series inputs.

All of the following examples use the Function API:

import numpy
import talib

close = numpy.random.random(100)

Calculate a simple moving average of the close prices:

output = talib.SMA(close)

Calculating bollinger bands, with triple exponential moving average:

from talib import MA_Type

upper, middle, lower = talib.BBANDS(close, matype=MA_Type.T3)

Calculating momentum of the close prices, with a time period of 5:

output = talib.MOM(close, timeperiod=5)

NaN’s

The underlying TA-Lib C library handles NaN’s in a sometimes surprising manner
by typically propagating NaN’s to the end of the output, for example:

>>> c = numpy.array([1.0, 2.0, 3.0, np.nan, 4.0, 5.0, 6.0])

>>> talib.SMA(c, 3)
array([nan, nan,  2., nan, nan, nan, nan])

You can compare that to a Pandas rolling mean, where their approach is to
output NaN until enough «lookback» values are observed to generate new outputs:

>>> c = pandas.Series([1.0, 2.0, 3.0, np.nan, 4.0, 5.0, 6.0])

>>> c.rolling(3).mean()
0    NaN
1    NaN
2    2.0
3    NaN
4    NaN
5    NaN
6    5.0
dtype: float64

Abstract API

If you’re already familiar with using the function API, you should feel right
at home using the Abstract API.

Every function takes a collection of named inputs, either a dict of
numpy.ndarray or pandas.Series or polars.Series, or a
pandas.DataFrame or polars.DataFrame. If a pandas.DataFrame or
polars.DataFrame is provided, the output is returned as the same type
with named output columns.

For example, inputs could be provided for the typical «OHLCV» data:

import numpy as np

# note that all ndarrays must be the same length!
inputs = {
    'open': np.random.random(100),
    'high': np.random.random(100),
    'low': np.random.random(100),
    'close': np.random.random(100),
    'volume': np.random.random(100)
}

Functions can either be imported directly or instantiated by name:

from talib import abstract

# directly
SMA = abstract.SMA

# or by name
SMA = abstract.Function('sma')

From there, calling functions is basically the same as the function API:

from talib.abstract import *

# uses close prices (default)
output = SMA(inputs, timeperiod=25)

# uses open prices
output = SMA(inputs, timeperiod=25, price='open')

# uses close prices (default)
upper, middle, lower = BBANDS(inputs, 20, 2, 2)

# uses high, low, close (default)
slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0) # uses high, low, close by default

# uses high, low, open instead
slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0, prices=['high', 'low', 'open'])

Streaming API

An experimental Streaming API was added that allows users to compute the latest
value of an indicator. This can be faster than using the Function API, for
example in an application that receives streaming data, and wants to know just
the most recent updated indicator value.

import talib
from talib import stream

close = np.random.random(100)

# the Function API
output = talib.SMA(close)

# the Streaming API
latest = stream.SMA(close)

# the latest value is the same as the last output value
assert (output[-1] - latest) < 0.00001

Supported Indicators and Functions

We can show all the TA functions supported by TA-Lib, either as a list or
as a dict sorted by group (e.g. «Overlap Studies», «Momentum Indicators»,
etc):

import talib

# list of functions
print talib.get_functions()

# dict of functions by group
print talib.get_function_groups()

Indicator Groups

• Overlap Studies
• Momentum Indicators
• Volume Indicators
• Volatility Indicators
• Price Transform
• Cycle Indicators
• Pattern Recognition

Overlap Studies

BBANDS               Bollinger Bands
DEMA                 Double Exponential Moving Average
EMA                  Exponential Moving Average
HT_TRENDLINE         Hilbert Transform - Instantaneous Trendline
KAMA                 Kaufman Adaptive Moving Average
MA                   Moving average
MAMA                 MESA Adaptive Moving Average
MAVP                 Moving average with variable period
MIDPOINT             MidPoint over period
MIDPRICE             Midpoint Price over period
SAR                  Parabolic SAR
SAREXT               Parabolic SAR - Extended
SMA                  Simple Moving Average
T3                   Triple Exponential Moving Average (T3)
TEMA                 Triple Exponential Moving Average
TRIMA                Triangular Moving Average
WMA                  Weighted Moving Average

Momentum Indicators

ADX                  Average Directional Movement Index
ADXR                 Average Directional Movement Index Rating
APO                  Absolute Price Oscillator
AROON                Aroon
AROONOSC             Aroon Oscillator
BOP                  Balance Of Power
CCI                  Commodity Channel Index
CMO                  Chande Momentum Oscillator
DX                   Directional Movement Index
MACD                 Moving Average Convergence/Divergence
MACDEXT              MACD with controllable MA type
MACDFIX              Moving Average Convergence/Divergence Fix 12/26
MFI                  Money Flow Index
MINUS_DI             Minus Directional Indicator
MINUS_DM             Minus Directional Movement
MOM                  Momentum
PLUS_DI              Plus Directional Indicator
PLUS_DM              Plus Directional Movement
PPO                  Percentage Price Oscillator
ROC                  Rate of change : ((price/prevPrice)-1)*100
ROCP                 Rate of change Percentage: (price-prevPrice)/prevPrice
ROCR                 Rate of change ratio: (price/prevPrice)
ROCR100              Rate of change ratio 100 scale: (price/prevPrice)*100
RSI                  Relative Strength Index
STOCH                Stochastic
STOCHF               Stochastic Fast
STOCHRSI             Stochastic Relative Strength Index
TRIX                 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA
ULTOSC               Ultimate Oscillator
WILLR                Williams' %R

Volume Indicators

AD                   Chaikin A/D Line
ADOSC                Chaikin A/D Oscillator
OBV                  On Balance Volume

Cycle Indicators

HT_DCPERIOD          Hilbert Transform - Dominant Cycle Period
HT_DCPHASE           Hilbert Transform - Dominant Cycle Phase
HT_PHASOR            Hilbert Transform - Phasor Components
HT_SINE              Hilbert Transform - SineWave
HT_TRENDMODE         Hilbert Transform - Trend vs Cycle Mode

Price Transform

AVGPRICE             Average Price
MEDPRICE             Median Price
TYPPRICE             Typical Price
WCLPRICE             Weighted Close Price

Volatility Indicators

ATR                  Average True Range
NATR                 Normalized Average True Range
TRANGE               True Range

Pattern Recognition

CDL2CROWS            Two Crows
CDL3BLACKCROWS       Three Black Crows
CDL3INSIDE           Three Inside Up/Down
CDL3LINESTRIKE       Three-Line Strike
CDL3OUTSIDE          Three Outside Up/Down
CDL3STARSINSOUTH     Three Stars In The South
CDL3WHITESOLDIERS    Three Advancing White Soldiers
CDLABANDONEDBABY     Abandoned Baby
CDLADVANCEBLOCK      Advance Block
CDLBELTHOLD          Belt-hold
CDLBREAKAWAY         Breakaway
CDLCLOSINGMARUBOZU   Closing Marubozu
CDLCONCEALBABYSWALL  Concealing Baby Swallow
CDLCOUNTERATTACK     Counterattack
CDLDARKCLOUDCOVER    Dark Cloud Cover
CDLDOJI              Doji
CDLDOJISTAR          Doji Star
CDLDRAGONFLYDOJI     Dragonfly Doji
CDLENGULFING         Engulfing Pattern
CDLEVENINGDOJISTAR   Evening Doji Star
CDLEVENINGSTAR       Evening Star
CDLGAPSIDESIDEWHITE  Up/Down-gap side-by-side white lines
CDLGRAVESTONEDOJI    Gravestone Doji
CDLHAMMER            Hammer
CDLHANGINGMAN        Hanging Man
CDLHARAMI            Harami Pattern
CDLHARAMICROSS       Harami Cross Pattern
CDLHIGHWAVE          High-Wave Candle
CDLHIKKAKE           Hikkake Pattern
CDLHIKKAKEMOD        Modified Hikkake Pattern
CDLHOMINGPIGEON      Homing Pigeon
CDLIDENTICAL3CROWS   Identical Three Crows
CDLINNECK            In-Neck Pattern
CDLINVERTEDHAMMER    Inverted Hammer
CDLKICKING           Kicking
CDLKICKINGBYLENGTH   Kicking - bull/bear determined by the longer marubozu
CDLLADDERBOTTOM      Ladder Bottom
CDLLONGLEGGEDDOJI    Long Legged Doji
CDLLONGLINE          Long Line Candle
CDLMARUBOZU          Marubozu
CDLMATCHINGLOW       Matching Low
CDLMATHOLD           Mat Hold
CDLMORNINGDOJISTAR   Morning Doji Star
CDLMORNINGSTAR       Morning Star
CDLONNECK            On-Neck Pattern
CDLPIERCING          Piercing Pattern
CDLRICKSHAWMAN       Rickshaw Man
CDLRISEFALL3METHODS  Rising/Falling Three Methods
CDLSEPARATINGLINES   Separating Lines
CDLSHOOTINGSTAR      Shooting Star
CDLSHORTLINE         Short Line Candle
CDLSPINNINGTOP       Spinning Top
CDLSTALLEDPATTERN    Stalled Pattern
CDLSTICKSANDWICH     Stick Sandwich
CDLTAKURI            Takuri (Dragonfly Doji with very long lower shadow)
CDLTASUKIGAP         Tasuki Gap
CDLTHRUSTING         Thrusting Pattern
CDLTRISTAR           Tristar Pattern
CDLUNIQUE3RIVER      Unique 3 River
CDLUPSIDEGAP2CROWS   Upside Gap Two Crows
CDLXSIDEGAP3METHODS  Upside/Downside Gap Three Methods

Statistic Functions

BETA                 Beta
CORREL               Pearson's Correlation Coefficient (r)
LINEARREG            Linear Regression
LINEARREG_ANGLE      Linear Regression Angle
LINEARREG_INTERCEPT  Linear Regression Intercept
LINEARREG_SLOPE      Linear Regression Slope
STDDEV               Standard Deviation
TSF                  Time Series Forecast
VAR                  Variance

Небольшая предыстория. Длительное время пользуюсь Visual studio, устанавливал через pip разные библиотеки и тут возникла проблема с библиотекой Ta-lib. Скорее всего проблема не конкретно в библиотеке, сколько в самом pip. Ниже полный код, что пишу в powershell (pip install TA-Lib==0.4.25 — версию указал в попытке решить проблему, но не помогло)

Как видно ошибка fatal error C1083: ЌҐ г¤ Ґвбп ®вЄалвм д ©« ўЄ«о祭ЁҐ: ta_libc.h: No such file or directory,
Но у меня нет такой директории. Проблема в Юникоде библиотеки? В PS (правее, где указана директория как я понимаю) теперь тоже отражается белиберда из символов ( скрин из вложения) .

Пжлст, добрые люди помогите.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47

pip install TA-Lib==0.4.25
Collecting TA-Lib==0.4.25
  Using cached TA-Lib-0.4.25.tar.gz (271 kB)
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Installing backend dependencies ... done
  Preparing metadata (pyproject.toml) ... done
Requirement already satisfied: numpy in c:usersняшаappdatalocalprogramspythonpython311libsite-packages (from TA-Lib==0.4.25) (1.23.4)
Building wheels for collected packages: TA-Lib
  Building wheel for TA-Lib (pyproject.toml) ... error
  error: subprocess-exited-with-error
  
  × Building wheel for TA-Lib (pyproject.toml) did not run successfully.
  │ exit code: 1
  ╰─> [26 lines of output]
      <string>:77: UserWarning: Cannot find ta-lib library, installation may fail.
      running bdist_wheel
      running build
      running build_py
      creating build
      creating buildlib.win-amd64-cpython-311
      creating buildlib.win-amd64-cpython-311talib
      copying talibabstract.py -> buildlib.win-amd64-cpython-311talib
      copying talibdeprecated.py -> buildlib.win-amd64-cpython-311talib        
      copying talibstream.py -> buildlib.win-amd64-cpython-311talib
      copying talibtest_abstract.py -> buildlib.win-amd64-cpython-311talib
      copying talibtest_data.py -> buildlib.win-amd64-cpython-311talib
      copying talibtest_func.py -> buildlib.win-amd64-cpython-311talib
      copying talibtest_pandas.py -> buildlib.win-amd64-cpython-311talib
      copying talibtest_polars.py -> buildlib.win-amd64-cpython-311talib
      copying talibtest_stream.py -> buildlib.win-amd64-cpython-311talib
      copying talib__init__.py -> buildlib.win-amd64-cpython-311talib
      running build_ext
      building 'talib._ta_lib' extension
      creating buildtemp.win-amd64-cpython-311
      creating buildtemp.win-amd64-cpython-311Release
      creating buildtemp.win-amd64-cpython-311Releasetalib
      "C:Program Files (x86)Microsoft Visual Studio2017BuildToolsVCToolsMSVC14.16.27023binHostX86x64cl.exe" /c /nologo /O2 /W3 /GL /DNDEBUG /MD -Ic:ta-libcinclude -IC:UsersНяшаAppDataLocalTemppip-build-env-vdqp76r7normalLibsite-packagesnumpycoreinclude -IC:UsersНяшаAppDataLocalProgramsPythonPython311include -IC:UsersНяшаAppDataLocalProgramsPythonPython311Include "-IC:Program Files (x86)Microsoft Visual Studio2017BuildToolsVCToolsMSVC14.16.27023include" "-IC:Program Files (x86)Windows Kits10include10.0.17763.0ucrt" "-IC:Program Files (x86)Windows Kits10include10.0.17763.0shared" "-IC:Program Files (x86)Windows Kits10include10.0.17763.0um" "-IC:Program Files (x86)Windows Kits10include10.0.17763.0winrt" "-IC:Program Files (x86)Windows Kits10include10.0.17763.0cppwinrt" /Tctalib/_ta_lib.c /Fobuildtemp.win-amd64-cpython-311Releasetalib/_ta_lib.obj
      _ta_lib.c
      talib/_ta_lib.c(745):[COLOR="Red"] fatal error C1083: ЌҐ г¤ Ґвбп ®вЄалвм д ©« ўЄ«о祭ЁҐ: ta_libc.h: No such file or directory,[/COLOR]
      error: command 'C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.16.27023\bin\HostX86\x64\cl.exe' failed with exit code 2
      [end of output]
 
  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for TA-Lib
Failed to build TA-Lib
ERROR: Could not build wheels for TA-Lib, which is required to install pyproject.toml-based projects

Although I had installed numpy and apparently have it up to date, I’ve spent several hours banging my head into a wall trying to

pip install talib
pip install ta-lib

and I got all sorts of cool errors, they look like big long blocks of garble, at the end rechecked pip install numpy and it still seems to work.

Error:
C:WINDOWSsystem32>pip install talib
Collecting talib
  Using cached talib-0.1.1.tar.gz (1.3 kB)
Building wheels for collected packages: talib
  Building wheel for talib (setup.py) ... error
  ERROR: Command errored out with exit status 1:
   command: 'c:usersm sanaconda3python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\Users\M S\AppData\Local\Temp\pip-install-chf6hp7j\talib_68b5a96fb6c24bf9bb216a856ab5c8f2\setup.py'"'"'; __file__='"'"'C:\Users\M S\AppData\Local\Temp\pip-install-chf6hp7j\talib_68b5a96fb6c24bf9bb216a856ab5c8f2\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'rn'"'"', '"'"'n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d 'C:UsersM SAppDataLocalTemppip-wheel-xkdrzdhz'
       cwd: C:UsersM SAppDataLocalTemppip-install-chf6hp7jtalib_68b5a96fb6c24bf9bb216a856ab5c8f2
  Complete output (29 lines):
  running bdist_wheel
  running build
  running build_py
  creating build
  creating buildlib
  creating buildlibtalib
  copying talibcli.py -> buildlibtalib
  copying talib__init__.py -> buildlibtalib
  installing to buildbdist.win-amd64wheel
  running install
  Traceback (most recent call last):
    File "<string>", line 1, in <module>
    File "C:UsersM SAppDataLocalTemppip-install-chf6hp7jtalib_68b5a96fb6c24bf9bb216a856ab5c8f2setup.py", line 32, in <module>
      setup(
    File "c:usersm sanaconda3libdistutilscore.py", line 148, in setup
      dist.run_commands()
    File "c:usersm sanaconda3libdistutilsdist.py", line 966, in run_commands
      self.run_command(cmd)
    File "c:usersm sanaconda3libdistutilsdist.py", line 985, in run_command
      cmd_obj.run()
    File "c:usersm sanaconda3libsite-packageswheelbdist_wheel.py", line 259, in run
      self.run_command('install')
    File "c:usersm sanaconda3libdistutilscmd.py", line 313, in run_command
      self.distribution.run_command(command)
    File "c:usersm sanaconda3libdistutilsdist.py", line 985, in run_command
      cmd_obj.run()
    File "C:UsersM SAppDataLocalTemppip-install-chf6hp7jtalib_68b5a96fb6c24bf9bb216a856ab5c8f2setup.py", line 20, in run
      raise Exception("You probably meant to install and run ta-lib")
  Exception: You probably meant to install and run ta-lib
  ----------------------------------------
  ERROR: Failed building wheel for talib
  Running setup.py clean for talib
Failed to build talib
Installing collected packages: talib
    Running setup.py install for talib ... error
    ERROR: Command errored out with exit status 1:
     command: 'c:usersm sanaconda3python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\Users\M S\AppData\Local\Temp\pip-install-chf6hp7j\talib_68b5a96fb6c24bf9bb216a856ab5c8f2\setup.py'"'"'; __file__='"'"'C:\Users\M S\AppData\Local\Temp\pip-install-chf6hp7j\talib_68b5a96fb6c24bf9bb216a856ab5c8f2\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'rn'"'"', '"'"'n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:UsersM SAppDataLocalTemppip-record-nl2y7qjqinstall-record.txt' --single-version-externally-managed --compile --install-headers 'c:usersm sanaconda3Includetalib'
         cwd: C:UsersM SAppDataLocalTemppip-install-chf6hp7jtalib_68b5a96fb6c24bf9bb216a856ab5c8f2
    Complete output (14 lines):
    running install
    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "C:UsersM SAppDataLocalTemppip-install-chf6hp7jtalib_68b5a96fb6c24bf9bb216a856ab5c8f2setup.py", line 32, in <module>
        setup(
      File "c:usersm sanaconda3libdistutilscore.py", line 148, in setup
        dist.run_commands()
      File "c:usersm sanaconda3libdistutilsdist.py", line 966, in run_commands
        self.run_command(cmd)
      File "c:usersm sanaconda3libdistutilsdist.py", line 985, in run_command
        cmd_obj.run()
      File "C:UsersM SAppDataLocalTemppip-install-chf6hp7jtalib_68b5a96fb6c24bf9bb216a856ab5c8f2setup.py", line 20, in run
        raise Exception("You probably meant to install and run ta-lib")
    Exception: You probably meant to install and run ta-lib
    ----------------------------------------
ERROR: Command errored out with exit status 1: 'c:usersm sanaconda3python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\Users\M S\AppData\Local\Temp\pip-install-chf6hp7j\talib_68b5a96fb6c24bf9bb216a856ab5c8f2\setup.py'"'"'; __file__='"'"'C:\Users\M S\AppData\Local\Temp\pip-install-chf6hp7j\talib_68b5a96fb6c24bf9bb216a856ab5c8f2\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'rn'"'"', '"'"'n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:UsersM SAppDataLocalTemppip-record-nl2y7qjqinstall-record.txt' --single-version-externally-managed --compile --install-headers 'c:usersm sanaconda3Includetalib' Check the logs for full command output.

C:WINDOWSsystem32>pip install ta-lib

Error:
Collecting ta-lib
  Using cached TA-Lib-0.4.19.tar.gz (267 kB)
Requirement already satisfied: numpy in c:usersm sanaconda3libsite-packages (from ta-lib) (1.18.5)
Building wheels for collected packages: ta-lib
  Building wheel for ta-lib (setup.py) ... error
  ERROR: Command errored out with exit status 1:
   command: 'c:usersm sanaconda3python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\Users\M S\AppData\Local\Temp\pip-install-0fhcistu\ta-lib_195c704785a44fab8ddfc0a4fb0a501a\setup.py'"'"'; __file__='"'"'C:\Users\M S\AppData\Local\Temp\pip-install-0fhcistu\ta-lib_195c704785a44fab8ddfc0a4fb0a501a\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'rn'"'"', '"'"'n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d 'C:UsersM SAppDataLocalTemppip-wheel-8lsv39uj'
       cwd: C:UsersM SAppDataLocalTemppip-install-0fhcistuta-lib_195c704785a44fab8ddfc0a4fb0a501a
  Complete output (27 lines):
  C:UsersM SAppDataLocalTemppip-install-0fhcistuta-lib_195c704785a44fab8ddfc0a4fb0a501asetup.py:71: UserWarning: Cannot find ta-lib library, installation may fail.
    warnings.warn('Cannot find ta-lib library, installation may fail.')
  running bdist_wheel
  running build
  running build_py
  creating build
  creating buildlib.win-amd64-3.8
  creating buildlib.win-amd64-3.8talib
  copying talibabstract.py -> buildlib.win-amd64-3.8talib
  copying talibdeprecated.py -> buildlib.win-amd64-3.8talib
  copying talibstream.py -> buildlib.win-amd64-3.8talib
  copying talibtest_abstract.py -> buildlib.win-amd64-3.8talib
  copying talibtest_data.py -> buildlib.win-amd64-3.8talib
  copying talibtest_func.py -> buildlib.win-amd64-3.8talib
  copying talibtest_pandas.py -> buildlib.win-amd64-3.8talib
  copying talibtest_stream.py -> buildlib.win-amd64-3.8talib
  copying talib__init__.py -> buildlib.win-amd64-3.8talib
  running build_ext
  skipping 'talib_ta_lib.c' Cython extension (up-to-date)
  building 'talib._ta_lib' extension
  creating buildtemp.win-amd64-3.8
  creating buildtemp.win-amd64-3.8Release
  creating buildtemp.win-amd64-3.8Releasetalib
  C:Program Files (x86)Microsoft Visual Studio2019CommunityVCToolsMSVC14.28.29333binHostX86x64cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ic:ta-libcinclude "-Ic:usersm sanaconda3libsite-packagesnumpycoreinclude" "-Ic:usersm sanaconda3include" "-Ic:usersm sanaconda3include" "-IC:Program Files (x86)Microsoft Visual Studio2019CommunityVCToolsMSVC14.28.29333ATLMFCinclude" "-IC:Program Files (x86)Microsoft Visual Studio2019CommunityVCToolsMSVC14.28.29333include" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0ucrt" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0shared" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0um" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0winrt" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0cppwinrt" /Tctalib_ta_lib.c /Fobuildtemp.win-amd64-3.8Releasetalib_ta_lib.obj
  _ta_lib.c
  talib_ta_lib.c(609): fatal error C1083: Cannot open include file: 'ta_libc.h': No such file or directory
  error: command 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.28.29333\bin\HostX86\x64\cl.exe' failed with exit status 2
  ----------------------------------------
  ERROR: Failed building wheel for ta-lib
  Running setup.py clean for ta-lib
Failed to build ta-lib
Installing collected packages: ta-lib
    Running setup.py install for ta-lib ... error
    ERROR: Command errored out with exit status 1:
     command: 'c:usersm sanaconda3python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\Users\M S\AppData\Local\Temp\pip-install-0fhcistu\ta-lib_195c704785a44fab8ddfc0a4fb0a501a\setup.py'"'"'; __file__='"'"'C:\Users\M S\AppData\Local\Temp\pip-install-0fhcistu\ta-lib_195c704785a44fab8ddfc0a4fb0a501a\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'rn'"'"', '"'"'n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:UsersM SAppDataLocalTemppip-record-f37b7we_install-record.txt' --single-version-externally-managed --compile --install-headers 'c:usersm sanaconda3Includeta-lib'
         cwd: C:UsersM SAppDataLocalTemppip-install-0fhcistuta-lib_195c704785a44fab8ddfc0a4fb0a501a
    Complete output (27 lines):
    C:UsersM SAppDataLocalTemppip-install-0fhcistuta-lib_195c704785a44fab8ddfc0a4fb0a501asetup.py:71: UserWarning: Cannot find ta-lib library, installation may fail.
      warnings.warn('Cannot find ta-lib library, installation may fail.')
    running install
    running build
    running build_py
    creating build
    creating buildlib.win-amd64-3.8
    creating buildlib.win-amd64-3.8talib
    copying talibabstract.py -> buildlib.win-amd64-3.8talib
    copying talibdeprecated.py -> buildlib.win-amd64-3.8talib
    copying talibstream.py -> buildlib.win-amd64-3.8talib
    copying talibtest_abstract.py -> buildlib.win-amd64-3.8talib
    copying talibtest_data.py -> buildlib.win-amd64-3.8talib
    copying talibtest_func.py -> buildlib.win-amd64-3.8talib
    copying talibtest_pandas.py -> buildlib.win-amd64-3.8talib
    copying talibtest_stream.py -> buildlib.win-amd64-3.8talib
    copying talib__init__.py -> buildlib.win-amd64-3.8talib
    running build_ext
    skipping 'talib_ta_lib.c' Cython extension (up-to-date)
    building 'talib._ta_lib' extension
    creating buildtemp.win-amd64-3.8
    creating buildtemp.win-amd64-3.8Release
    creating buildtemp.win-amd64-3.8Releasetalib
    C:Program Files (x86)Microsoft Visual Studio2019CommunityVCToolsMSVC14.28.29333binHostX86x64cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ic:ta-libcinclude "-Ic:usersm sanaconda3libsite-packagesnumpycoreinclude" "-Ic:usersm sanaconda3include" "-Ic:usersm sanaconda3include" "-IC:Program Files (x86)Microsoft Visual Studio2019CommunityVCToolsMSVC14.28.29333ATLMFCinclude" "-IC:Program Files (x86)Microsoft Visual Studio2019CommunityVCToolsMSVC14.28.29333include" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0ucrt" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0shared" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0um" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0winrt" "-IC:Program Files (x86)Windows Kits10include10.0.18362.0cppwinrt" /Tctalib_ta_lib.c /Fobuildtemp.win-amd64-3.8Releasetalib_ta_lib.obj
    _ta_lib.c
    talib_ta_lib.c(609): fatal error C1083: Cannot open include file: 'ta_libc.h': No such file or directory
    error: command 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.28.29333\bin\HostX86\x64\cl.exe' failed with exit status 2
    ----------------------------------------
ERROR: Command errored out with exit status 1: 'c:usersm sanaconda3python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\Users\M S\AppData\Local\Temp\pip-install-0fhcistu\ta-lib_195c704785a44fab8ddfc0a4fb0a501a\setup.py'"'"'; __file__='"'"'C:\Users\M S\AppData\Local\Temp\pip-install-0fhcistu\ta-lib_195c704785a44fab8ddfc0a4fb0a501a\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'rn'"'"', '"'"'n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:UsersM SAppDataLocalTemppip-record-f37b7we_install-record.txt' --single-version-externally-managed --compile --install-headers 'c:usersm sanaconda3Includeta-lib' Check the logs for full command output.

C:WINDOWSsystem32>pip install numpy
Requirement already satisfied: numpy in c:usersm sanaconda3libsite-packages (1.18.5)

Now, I have googled a few different things and then proceeded to download Windows Visual Community 2019 and then an older 2015 version, then also a MySQL developer package that all-in-all ended up being about 20gigs of random information that, for the life of me, I cannot understand why trying to use talib.SMA and other commands I would be forced to have on my system. My python paths are myinitialsdesktop , anaconda3scripts , anaconda3 and anaconda3Librarybin

It used to tell me that in the code

import numpy as np
import matplotlib.pyplot as plt
import yfinance as yf
import talib

No module talib exists or something very similar, now it’s telling me No module named yfinance.

How/where/what do I do to get any progress from here? Did I disable yfinance the module somehow, and why won’t freaking talib just import. I can’t explain how annoyed, frustrated and spread-apart the internet jury-rigged solutions are, why my hard drive has 20Gigs of what I consider irrelevant extra crab on it, and what I’m supposed to do next. I suppose I could reformat my whole drive, install Spyder and only Spyder without Jupyter notebook on it, or simply light the whole thing on fire but I am trying to put to use a course I’ve read and made plenty of screenshots through and while simple things work, others will Not function without talib commands. Thank you for any time, thoughts or comments on the matter.