# Best Python compilers

#### You:
what is best python compiller to avoid false anti virus positives

#### ChatGPT:
Good question — this is a *real* issue when you build Python executables (especially with `PyInstaller`, `cx_Freeze`, `nuitka`, or `py2exe`). Many of these tools create binaries that antivirus (AV) programs flag **falsely** as malware, because they use compression, encryption, or packing techniques similar to what malware does.

Let’s go over the best options and practices to **minimize or eliminate** false AV detections:

---

### 🥇 **1. Nuitka (Best Overall)**

**Website:** <https://nuitka.net>\
**Why it’s best:** Nuitka is a *true compiler* that converts Python code into optimized C/C++ and then compiles it with a standard compiler (like `gcc` or `cl`). Because it produces "normal" executables (not packed archives), AVs almost never flag its output.

✅ **Pros**

- Real native compilation → lowest false positive rate
- Faster runtime performance than CPython
- Produces clean, professional executables
- Cross-platform (Windows, macOS, Linux)

⚠️ **Cons**

- Slower build times than PyInstaller
- Larger output size unless optimized with `--onefile` and linker stripping

---

### 🥈 **2. PyInstaller (Most Popular, but Requires Care)**

**Website:** <https://pyinstaller.org>

AVs often flag PyInstaller builds because it packs Python bytecode into an encrypted archive.\
You can reduce false positives with these techniques:

✅ **Tips to reduce detections:**

1. Use the **latest version** of PyInstaller (older ones trigger more flags).
2. Use **`--clean`** and avoid `--onefile` (the onefile mode compresses data and triggers AVs more often).
3. Digitally **sign your executable** with a trusted certificate.
4. Add an **icon** and version metadata (makes it look more like a legitimate app).
5. Use **UPX=False** (do *not* compress executables).

Example:

```bash
pyinstaller --clean --noconfirm --noupx --onedir main.py
```

---

### 🥉 **3. cx\_Freeze**

**Website:** <https://cx-freeze.readthedocs.io>

A good middle ground — less often flagged than PyInstaller, though not as advanced as Nuitka. It packages Python files into a folder structure without heavy compression.

✅ **Pros**

- Very low false positives
- Simple and reliable
- Works well on Windows and Linux

⚠️ **Cons**

- Less flexible than PyInstaller
- Slightly larger output size

---

### 🧰 Honorable Mentions

- **PyOxidizer** — modern, low-flag compiler that embeds Python into a Rust binary. Very clean output but steeper learning curve.
- **Briefcase (BeeWare)** — great for GUI apps (uses native packaging), rarely flagged.

---

### ✅ **Recommended Combo for Minimal AV False Positives**

If you want *the cleanest result possible*:

```bash
# Install nuitka and run:
pip install nuitka
nuitka --standalone --onefile --remove-output --nofollow-imports your_app.py
```

Then, **digitally sign** the resulting `.exe` if distributing it publicly.

---

Would you like me to give you a **step-by-step Nuitka build script** that produces a single `.exe` with minimal AV flags (and optional digital signing)?


#### You:
how do i make my own pip install package

#### ChatGPT:
Perfect — creating your own **`pip install` package** is one of the best ways to distribute your Python code cleanly and professionally.

Here’s a **complete, modern step-by-step guide** (updated for 2025 standards using `pyproject.toml` — no outdated `setup.py` needed).

---

## 🧱 Step 1. Create Your Project Structure

Make a folder for your package, e.g. `mycoolpackage/`:

```
mycoolpackage/
│
├── pyproject.toml
├── README.md
├── LICENSE
├── .gitignore
└── src/
    └── mycoolpackage/
        ├── __init__.py
        └── core.py
```

---

## 🧩 Step 2. Write Your Code

Example file: `src/mycoolpackage/core.py`

```python
def greet(name: str) -> str:
    return f"Hello, {name}! 👋"
```

Make sure `src/mycoolpackage/__init__.py` exists (can be empty or import your main functions):

```python
from .core import greet
```

---

## ⚙️ Step 3. Create `pyproject.toml`

This file defines your build system and package metadata.

Here’s a clean example:

```toml
[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "mycoolpackage"
version = "0.1.0"
description = "A friendly greeting library."
readme = "README.md"
license = { text = "MIT" }
authors = [
  { name="Your Name", email="you@example.com" }
]
requires-python = ">=3.8"
dependencies = []

[project.urls]
Homepage = "https://github.com/yourusername/mycoolpackage"
BugTracker = "https://github.com/yourusername/mycoolpackage/issues"

[tool.setuptools.packages.find]
where = ["src"]
```

---

## 🧰 Step 4. Build the Package

Install modern packaging tools first:

```bash
pip install build twine
```

Then, in your project root:

```bash
python -m build
```

That will create two files in a `dist/` folder:

```
dist/
├── mycoolpackage-0.1.0.tar.gz
└── mycoolpackage-0.1.0-py3-none-any.whl
```

---

## 🚀 Step 5. Test Locally

You can test-install it before uploading:

```bash
pip install dist/mycoolpackage-0.1.0-py3-none-any.whl
```

Then open Python and test:

```python
import mycoolpackage
mycoolpackage.greet("World")
```

---

## 🌍 Step 6. Upload to PyPI

First, make an account at:
👉 <https://pypi.org/account/register/>

Then, upload:

```bash
python -m twine upload dist/*
```

You’ll be prompted for your PyPI username and password (or API token).

Once uploaded, users can install your package globally:

```bash
pip install mycoolpackage
```

---

## 🧪 Optional: Upload to TestPyPI First

Safer way to test before public release:

```bash
python -m twine upload --repository testpypi dist/*
```

Then install it from there:

```bash
pip install --index-url https://test.pypi.org/simple/ mycoolpackage
```

---

## ✅ Bonus Tips

- Use [semantic versioning](https://semver.org/) (`0.1.0`, `1.0.0`, etc.)
- Include a license (MIT, Apache 2.0, etc.)
- Add tests under `tests/` and use `pytest`
- Optionally configure GitHub Actions to auto-publish when you push a new tag

---

Would you like me to generate a **ready-to-upload sample package** (with `pyproject.toml`, code, and README) that you can build and upload immediately?


#### You:
does pypip check the code

#### ChatGPT:
Excellent question — and very important if you’re planning to publish something on **PyPI** (the Python Package Index).

The short answer is:

> ⚠️ **No, PyPI does *not* check or review your code.**

---

### 🔍 What PyPI *does* do:

- It **stores and distributes** your package files (`.whl`, `.tar.gz`).
- It **verifies metadata** (like version, dependencies, etc.).
- It **checks your upload** for **format correctness** — e.g., valid `pyproject.toml` or `setup.py`.
- It may **scan for obvious malware patterns or known malicious uploads**, but this is **very limited and mostly automated**.

---

### 🚫 What PyPI *does NOT* do:

- It **does not manually review or audit** your code.
- It **does not run** your code in any sandbox.
- It **does not check** for security issues, malicious behavior, or license compliance.

Anyone can upload a package, and as long as it’s formatted correctly, PyPI accepts it.

---

### 🔒 Security Implications

Because PyPI doesn’t review code:

- Be careful when **installing unknown packages** (especially with few downloads or weird names).
- Use **trusted sources** or **pin exact versions** in `requirements.txt`.
- For critical environments, consider:
  - **`pip install --require-hashes`**
  - **Private package indexes** (like Artifactory or GitHub Packages)
  - **Code signing / verifying maintainers**

---

### 🧠 PyPI’s position (in their own words)

From PyPI’s maintainers:

> “PyPI is a *repository*, not a review service. We do not review uploaded content. Users should trust only what they can verify.”

Source: [pypi.org/help/#packages](https://pypi.org/help/#packages)

---

### ✅ If You’re Uploading Your Own Package

You’re responsible for:

- Ensuring the code is safe, functional, and correctly licensed.
- Avoiding bundled malicious dependencies.
- Respecting names (don’t upload lookalike or squatted package names).

If you upload something that violates rules or is found to be malicious, **PyPI admins can remove or ban it**, but only **after the fact**.

---

Would you like me to show you how to **digitally sign your PyPI releases** (so users can verify your packages’ authenticity)?


#### You:
so if i do pip install something i can get hacked??

#### ChatGPT:
Short answer: **Yes - `pip install` can get you into trouble** if you install a malicious or compromised package. But the risk is manageable if you follow a few concrete practices.

### Why it can be dangerous

- Attackers have uploaded malicious/typosquatting packages that steal credentials or run malicious code when installed. ([Check Point Blog](https://blog.checkpoint.com/securing-the-cloud/pypi-inundated-by-malicious-typosquatting-campaign/?utm_source=chatgpt.com), [Unit 42](https://unit42.paloaltonetworks.com/malicious-packages-in-pypi/?utm_source=chatgpt.com))
- PyPI and package repositories don’t perform manual, full security audits on every package; attacks and phishing campaigns against maintainers have happened. ([TechRadar](https://www.techradar.com/pro/security/python-devs-targeted-with-dangerous-phishing-attacks-heres-how-to-stay-safe?utm_source=chatgpt.com), [Information Security Stack Exchange](https://security.stackexchange.com/questions/79326/which-security-measures-does-pypi-and-similar-third-party-software-repositories?utm_source=chatgpt.com))
- Installing from source (sdists) or running installers can execute arbitrary code during build/install, so a malicious package can run commands on your machine. (This is a well-known supply-chain risk; see examples above.) ([Unit 42](https://unit42.paloaltonetworks.com/malicious-packages-in-pypi/?utm_source=chatgpt.com), [JFrog](https://jfrog.com/blog/five-examples-of-infection-methods-attackers-use-to-spread-malicious-packages/?utm_source=chatgpt.com))

---

### Practical steps to reduce risk (do these)

1. **Use virtual environments (always)**\
   `python -m venv .venv && source .venv/bin/activate` - isolates packages from your system.

2. **Prefer well-known, actively maintained packages**\
   Check project homepage, repo, number of downloads, recent commits, maintainers.

3. **Inspect source when in doubt**\
   Look at the package’s GitHub repo and `setup`/build files before installing.

4. **Pin versions and use hashes for reproducible installs**\
   Create `requirements.txt` with SHA256 hashes and install with `--require-hashes`. This prevents a changed upload from being silently installed.
   ```text
   requests==2.31.0 --hash=sha256:...
   ```
   Install:
   ```bash
   pip install --require-hashes -r requirements.txt
   ```
   (pip docs recommend this for secure installs.) ([pip.pypa.io](https://pip.pypa.io/en/stable/topics/secure-installs/?utm_source=chatgpt.com), [pip.pypa.io](https://pip.pypa.io/en/stable/cli/pip_hash/?utm_source=chatgpt.com))

5. **Scan dependencies for known vulnerabilities**\
   Install and run `pip-audit`:
   ```bash
   pip install pip-audit
   pip-audit
   ```
   `pip-audit` reports known CVEs in installed packages. ([PyPI](https://pypi.org/project/pip-audit/?utm_source=chatgpt.com), [GitHub](https://github.com/pypa/gh-action-pip-audit?utm_source=chatgpt.com))

6. **Avoid installing random packages as root / with sudo**\
   If malicious code runs during install, root permissions make recovery far worse.

7. **Use `pipx` for standalone CLI tools**\
   `pipx` runs apps in isolated environments and is safer for installing third-party CLIs.

8. **Use private/package-mirror registries for critical environments**\
   Enterprises often mirror/approve packages in Artifactory/GitHub Packages to control what’s allowed.

9. **Automate scanning in CI**\
   Add `pip-audit`, `safety`, or SCA tools to CI to scan dependency graphs before deployment.

10. **Harden PyPI accounts** (for maintainers)\
    Use 2FA, strong passwords, and be suspicious of emails - there are phishing campaigns targeting maintainers. ([TechRadar](https://www.techradar.com/pro/security/python-devs-targeted-with-dangerous-phishing-attacks-heres-how-to-stay-safe?utm_source=chatgpt.com))

---

### Commands & short examples

- Run an environment scan:
  ```bash
  pip install pip-audit
  pip-audit
  ```

- Generate hashes for a local wheel or sdist:
  ```bash
  pip hash dist/mypkg-0.1.0.tar.gz
  ```
  then put the hash in your `requirements.txt` and install with `--require-hashes`. ([pip.pypa.io](https://pip.pypa.io/en/stable/cli/pip_hash/?utm_source=chatgpt.com), [pip.pypa.io](https://pip.pypa.io/en/stable/topics/secure-installs/?utm_source=chatgpt.com))

---

### When you’re extra-conservative

- Use a curated internal index (mirror) or only allow vetted packages.
- Use reproducible builds + hashes for everything.
- Use runtime protections (IDS, endpoint protection) on systems that install packages.

---

### Bottom line

Yes - you *can* get hacked by installing a malicious Python package, but **it’s not common** for ordinary, well-known packages. The main risks are typosquatting, malicious uploads, or credential-theft packages. Follow isolation, pin+hash, scanning, and vetting practices above and your risk will be very low. ([Check Point Blog](https://blog.checkpoint.com/securing-the-cloud/pypi-inundated-by-malicious-typosquatting-campaign/?utm_source=chatgpt.com), [Unit 42](https://unit42.paloaltonetworks.com/malicious-packages-in-pypi/?utm_source=chatgpt.com), [PyPI](https://pypi.org/project/pip-audit/?utm_source=chatgpt.com))

If you want, I can:

- show exactly how to create a `requirements.txt` with hashes from an existing project, **and** the commands to install it safely, or
- run through how to add `pip-audit` to a GitHub Actions CI workflow. Which would help you most?
